October 6, 2009           

Oxygen Safety: More Lessons from the UK

We’ve written several columns on issues related to oxygen therapy and many of the good recommendations have come from the UK. See our Patient Safety Tips of the Week for:

• April 8, 2008 “Oxygen as a Medication”
• June 10, 2008 “Monitoring the Postoperative COPD Patient”
• January 27, 2009 “Oxygen Therapy: Everything You Wanted to Know and More!”

Last week the UK National Patient Safety Agency (NPSA) issued a Rapid Response Report on Oxygen Safety in Hospitals. This is issued as the rapid response report itself and separate briefings for physicians and for nurses, midwives and allied health professionals. But the most useful document is the one with supporting information.

The NPSA alert followed reports of 281 incidents involving oxygen over a 5-year period, 9 of which caused patient deaths and another 35 of which may have contributed to patient deaths.

103 of the incidents involved equipment, including empty oxygen cylinders, missing or faulty equipment, inaccessibility of equipment, or user errors. A large number of these incidents occurred during patient transports or transfers. We’ve previously noted that some studies have shown over 50% of all inhospital transports have been complicated by oxygen supplies running out and encouraged use of tools such as Ticket to Ride to help avoid such events.

75 of the incidents involved prescribing or monitoring. Most involved inadequate monitoring of oxygen saturation but several also involved patients developing hypercapnia and respiratory acidosis.

In 54 of the incidents oxygen was not appropriately administered. This included cases where compressed air was mistakenly given to patients, cases where oxygen sources were disconnected, and cases where oxygen was given at incorrect flow rates. Again, some of these occurred during transport of patients within the hospital, often by nonclinical personnel.

Miscellaneous cases included events such as fires from patients smoking while connected to oxygen.

They also reviewed the literature and investigation reports done at the local hospital level. We have previously discussed the need to treat oxygen as a medication and stressed the use of the new British Thoracic Society Guidelines for Emergency Oxygen Use in Adult Patients. They cite multiple audits that have been done showing poor compliance with the prescribing and monitoring of oxygen use recommended by those guidelines. Oxygen was often given without an order from a physician and when it was, it was often provided without prescription of specific delivery mode and flow rate or target O2 saturation.

Oxygen should be used only for patients who are hypoxemic and then should be formally prescribed. The prescription should specify a mode of administration and a target oxygen saturation rather than a specific dose. Nursing or respiratory therapy should be able to change the oxygen flow rates to achieve and maintain the target oxygen saturations. Special care should be taken when administering oxygen to those patients at risk for hypercapnia (eg. those with COPD, sleep apnea, morbid obesity, severe kyphoscoliosis or certain neuromuscular disorders, etc.), where lower oxygen saturation targets should be used.

The NPSA Rapid Response Report makes multiple sound recommendations:

• All staff should be educated and oriented in the appropriate management of oxygen therapy.
• Use of oxygen cylinders should be minimized (piped oxygen is preferred in most scenarios).
• Where cylinders must be used, there should be robust systems in place reliable and adequate supplies.
• The risks of confusing oxygen with compressed air or other medical gases must be assessed.
• The BTS guidelines should be followed for all oxygen prescribing and monitoring.
• Pulse oximetry should be available and used to monitor oxygen saturation in all areas where oxygen is used.
• A “Medical Gas Committee” should be established to monitor and ensure safe and appropriate use of oxygen in all organizations. This should be a multidisciplinary group with representatives for all disciplines involved in oxygen use (including clinical personnel and respresentatives from pharmacy, patient transport, safety and risk management, biomedical engineering, supply, purchasing, and even a member of the Board). This group should be responsible for ensuring appropriate policies are in place and that adequate training be provided, monitor safety and availability of all oxygen equipment, audit the appropriateness of oxygen use and compliance with BTS guidelines, and review all incidents involving the use or misuse of oxygen.

They give many practical examples of how to avoid mixups between oxygen and other gases and how to avoid using cylinders that are empty or only partially filled. While they recommend appropriate labeling or color coding of wall gas outlets, it is interesting that they only briefly mention use of connectors that would make it impossible to connect oxygen to a source of gas other than oxygen. They stress separate storage for empty and full oxygen cylinders and good ways of labeling or otherwise identifying used or empty cylinders.

They provide a very good list of questions that staff should be able to answer after appropriate training. This includes very practical questions such as “Are staff checking the amount of oxygen in a cylinder before using it?” and they detail how staff would go about doing this.

One item we did not see in their otherwise extensive recommendations is the need to check all alarms on every ventilator prior to each use on patients. We previously described a case (see our March 5, 2007 Patient Safety Tip of the Week “Disabled Alarms”) in which an oxygen blender alarm on a ventilator failed to alert staff to disconnection of the oxygen source because a piece of tape had been placed over the blender alarm (probably during maintenance). The lesson learned in that case is that one should have a checklist-type routine for checking alarms immediately before a ventilator is used on a patient. And the checklist should be specific for the ventilator being used. It is not at all uncommon for a hospital to have multiple different models of ventilators and some may have alarms that others do not. Therefore, your protocol should include not only checking those alarms that are on all ventilators but also those that may be specific to the unit being used. Better yet, the design of new ventilators would automate such alarm checking prior to each use.

The Rapid Response Report also stresses the need for good planning when patients needing oxygen must be transported within hospitals or outside. In our Patient Safety Tips of the Week for April 8, 2008 “Oxygen as a Medication” and November 18, 2008 “Ticket to Ride: Checklist, Form, or Decision Scorecard?” we discussed in detail the risks involved with oxygen in patients during transports. The Ticket to Ride concept, in particular, is very useful in planning and implementing patient transports in a manner to ensure they don’t run out of oxygen and remain appropriately monitored throughout.

The Rapid Response Report also has links to good resources on use of pulse oximetry, fire and explosion hazards with oxygen, and tips on handling oxygen cylinders and their regulators. And, of course, the British Thoracic Society resource page on the guidelines for emergency oxygen use in adult patients provides a wealth of valuable resources, including sample policies, educational materials for staff, sample oxygen prescription forms, audit tools (for both the individual patient level and the medical unit level), and patient education materials.

All hospitals should have some initiative addressing high-risk medications in their organizations. If you consider oxygen as a medication, which you should be doing, it is one of the most high-risk medications you use in your organization. Making it a priority to monitor all aspects of oxygen usage and safety makes a lot of sense.

References:

National Patient Safety Agency (UK). Rapid Response Report. Oxygen safety in hospitals. September 29, 2009

http://www.nrls.npsa.nhs.uk/resources/?entryid45=62811

rapid response report

http://www.nrls.npsa.nhs.uk/EasySiteWeb/getresource.axd?AssetID=62806&type=full&servicetype=Attachment

supporting information

http://www.nrls.npsa.nhs.uk/EasySiteWeb/getresource.axd?AssetID=62808&type=full&servicetype=Attachment

briefing for doctors

http://www.nrls.npsa.nhs.uk/EasySiteWeb/getresource.axd?AssetID=62809&type=full&servicetype=Attachment

briefing for nurses, midwives, and allied health professionals

http://www.nrls.npsa.nhs.uk/EasySiteWeb/getresource.axd?AssetID=62810&type=full&servicetype=Attachment

British Thoracic Society. Guidelines for Emergency Oxygen Use in Adult Patients. Resource Page.

http://www.brit-thoracic.org.uk/ClinicalInformation/EmergencyOxygen/EmergencyOxygenuseinAdultPatients/tabid/327/Default.aspx

One Liners issue 67 - May 2009

http://www.mhra.gov.uk/Publications/Safetyguidance/OneLiners/CON046617

Oxygen cylinders and their regulators - top tips leaflet.

http://www.mhra.gov.uk/Publications/Postersandleaflets/CON014865

Take care with oxygen. Fire and explosion hazards in the use of oxygen

www.hse.gov.uk/pubns/hse8.pdf

General Practice Airways Group (GPIAG) opinion sheet on Pulse Oximetry in Primary Care.

www.gpiag.org/resources/pulseoximetry_final.pdf

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October 13, 2009           

Slipping Through the Cracks

Consider the following radiology report:

Doe, John                                             DOB: 03/18/48

MR# 555555                                       Date of report: July 7, 2009

Date of study: July 7, 2009

Study: Plain radiographs Chest, PA and lateral views

Clinical information: R/O pneumonia

Findings: PA and lateral views of the chest were of good quality with adequate inspiratory effort. There is no pulmonary infiltrate or evidence of pneumonia. There is no pleural effusion or thickening. There is a slight right perihilar fullness but no discrete mediastinal abnormality is seen. There is no deviation of the trachea. In the right upper lobe there is a poorly defined 0.5 centimeter density with rounded margins without calcification. The heart is of normal size and shape. No abnormalities of the great vessels are noted. No bony abnormalities are noted.

Impression: No evidence of pneumonia. Possible solitary nodule right upper lobe. Suggest further evaluation with CT scan of chest.

Report Dictated by: Joseph B. Smith, M.D.

Report signed electronically 7/7/09 JBS

Reports like this go out from radiology departments every day. The request could have come in from a med/surg inpatient unit, the emergency department, a physician’s office or the clinic. The limited clinical information is not uncommon. Physicians (and probably more importantly the systems we use for communicating) are notorious for failing to provide radiologists with adequate clinical information. Often the physician simply says “get a chest X-ray” and a secretary fills out the requisition. But that’s not the primary theme of this column. The issue is “What happens with this report?”.

We’ve talked about this issue in prior columns about results of significant clinical findings slipping through the cracks. We discussed these extensively in our May 1, 2007 Patient Safety Tip of the Week “The Missed Cancer” and our February 12, 2008 Patient Safety Tip of the Week “More on Tracking Test Results”. We talked about some of the solutions that various organizations and physicians have put in place to ensure reports like this don’t slip through the cracks. Remember, there should be two systems in place here: one in the radiology department to ensure this message gets to the person who needs to know and one with the ordering physician that ensures the physician always identifies results of tests ordered. We’ve talked about 2 types of system: paper and electronic. And some findings would require both. Actually, there should be a 3^rd system in place as well: one with the patients themselves. The educated patient should always ask the provider “when should I expect the result to be available?” and then contact the provider if they have not heard those results within a reasonable period of time.

This month an excellent paper (Singh et al 2009) studied the outcomes of an electronic alert system that conveyed such abnormal imaging results. It both quantified the magnitude of such alerts either not being acknowledged or not followed up on, and showed some very interesting findings. They looked at imaging studies done in a VA system. About 1% of all radiographs, CT scans, MRI scans, ultrasounds, and mammograms in that system generated electronic alerts because of abnormalities seen on the studies. The authors queried the electronic medical record to see if the alerts had been “acknowledged” by the ordering provider and examined patient records to see if any followup actions had been taken by 4 weeks after the alert had been issued. Phone calls were made to the ordering physician if no actions had taken place by 4 weeks.

18% of the alerts went unacknowledged and, overall, 7.7% of cases with alerts lacked timely follow-up at 4 weeks (after the initial phone call from the authors half of those patients had an appropriate action within a week). Their further analysis showed that housestaff were less likely to acknowledge the alerts than other physicians and physician assistants were more likely to acknowledge alerts. Dual alerts (i.e. alerts going out to more than one physician) were twice as likely to go unacknowledged.

There was no significant difference in lack of timely follow-up between those with acknowledged alerts and those with unacknowledged alerts. CT scans and MRI scans were more likely to have timely follow-up actions done. Timely follow-up actions were more likely when a verbal communication from a radiologist had taken place or if there was a hospitalization subsequent to the alert being issued and again twice as likely not to be done if there had been a dual alert.

When they looked at types of “near-misses” they found that chest imaging showing a nonspecific density (such as our example above) was more likely to be associated with lack of timely follow-up. Half of the test results lacking timely followup were abnormal chest X-rays. A possible new malignant neoplasm was one of the common near-misses. Of all the cases lacking timely follow-up, a quarter ultimately had testing leading to new diagnoses, often a new cancer.

Perhaps the scariest finding is that the likelihood of lack of timely follow-up was twice as likely in those cases where dual alerts were sent out. We typically do that thinking that we are adding a layer of safety, i.e. that if one person misses the alert another is likely to see it and respond to it. Obviously that is not the case. Does that surprise you? It really shouldn’t. We know statistically that, in many industries, there is a 10% chance that someone who is “supervising” or “double checking” someone else’s work will make an error. We’ve also often seen clinically that “co-managed” patients are likely to have gaps in their care. This is because both clinicians assume the other will follow-up and then neither follows up.

Also surprising in the Singh study was that some abnormal imaging results flagged as “critical” did not receive timely follow-up even when the alerts were acknowledged. Some of the issues may have had to do with the academic system in which the study was done (eg. housestaff may have only come to their “continuity” clinic once a week) but most of the issues raised can be applied to any healthcare setting.

In particular, imagine some settings where the result could be even worse. Think about the ER. It is not uncommon in many ER’s for the ER physician to do their own interpretation of the X-ray or receive only a “wet read” from the radiologist on-call (often nowdays a “night hawk” service). The official report comes back the next day. For instance, in the above example, the wet read might simply say “no pneumonia” and the report with the suspicious nodule does not appear until the following day. By that time, both the ER physician and the patient are long gone. Who looks at those reports? In a busy ER, it would be nearly impossible for one person to look at 100 or so radiology reports from the prior day to see which ones might have significant abnormal findings requiring follow-up. Some systems now include some form of electronic alert either on the EMR or the PACS system so that only the ones with significant or unexpected findings might be flagged.

The Singh group identified 5 important lessons for electronic alert systems:

1. Each organization must have a policy, well-publicized, stating who (PCP vs. ordering provider) is responsible for taking action on abnormal results.
2. Each electronic alert should remain on the EMR screen until it is acknowledged and electronically signed. The acknowledgement should include a statement of action as well.
3. To avoid alert fatigue, systems need to reduce the number of alerts generated and ensure that only the most important ones are transmitted.
4. The EMR system should be automated to track not just the acknowledgment of alerts but also the responses to those alerts.
5. A good audit system must be in place, with feedback to appropriate providers.

We have previously talked about radiology departments keeping their own log of significant abnormal findings. Some of these will require a direct phone call from the radiologist to the ordering provider. In others, a phone call may not be necessary but there must be some other system in place to see that there was an appropriate follow-up action taken on that patient. Choksi et al noted that the standard of care for radiologists is to notify the referring physician and document that communication in the radiology report whenever an unexpected finding such as a possible malignancy is noted. But they also found that such notification did not guarantee the patient would receive appropriate followup. So they devised a system in which every imaging report was assigned a code. For significant unexpected findings, such as possible malignancy, they assigned a code 8. A list of all code 8’s was given to a designated individual (in their system is was the tumor registrar) on a weekly basis. The latter individual then contacted the appropriate individuals to ensure that appropriate followup was done (or there was documentation as to why followup was not being done). In one year, they identified 395 code 8 cases. In 35 of the cases, no workup was documented at 2 weeks. In many, the finding had been acknowledged and workup initiated even though not documented. But eight cases would likely have been lost to followup if this safety net had not been in place. Five of those were ultimately diagnosed with malignancy.

We’d again like to stress that any provider who orders tests must have some sort of system, paper or electronic, to remind them to check on results of all tests they have ordered. Remember, the system in the Singh paper would not alert the provider to those cases where the test was never done! Failure to have the test done may be just as significant an issue. So your “tickler” system must say something like “if I haven’t heard Mrs. Smith’s CT scan result by Friday, I need to find out why not”.

And the patient, as above, should always ask the provider “When should I expect the result to be available?” and then contact the provider if they have not heard those results within a reasonable period of time. The patient should never assume that the test results were normal if they have not heard from the physician or other provider.

In our July 2009 What’s New in the Patient Safety World column “Failure to Inform Patients of Clinically Significant Outpatient Test Results” we noted a new study showing the frequency with which such failures to inform patients about clinically significant tests occur. Casalino et al reviewed charts from both community and academic primary care practices to find documentation of followup of abnormal results of 11 common blood tests and 3 common preventive tests. They found apparent failure to inform patients of such abnormal test results 7.1% of the time. Perhaps the most interesting finding is that those practices using a combination of paper and electronic records (so called “partial EMR”) had higher failure rates than those having either a full EMR or full paper-based systems. They found that very few practices had explicit rules or systems for managing test results and usually relied on the individual physician to devise his/her own system. Unfortunately, some were still telling patients to rely on the old “no news is good news” concept, which obviously is very flawed and unsafe.

A somewhat related topic appears in another new article this month (Leekha 2009) that looked at patient preferences for notification of test results and noted disparities between those preferences and how they were actually notified. A majority wanted notification via phone call from the physician or nurse practitioner but in reality the majority received notification either via a phone call from a nurse or by a return visit to the office. Use of more hi-tech methods (e-mail, automated answering mechanisms, etc.) were not highly regarded methods, though the average age of the population studied being 70 years may somewhat limit the generalizability of these conclusions. The authors discuss how misalignment of incentives can be a root cause for dissatisfaction (eg. patients dislike having to spend time and money for a followup office visit, whereas providers only get reimbursed for such visits and do not get reimbursed for phone calls).

How does your health system ensure that these cases don’t fall through the cracks?

References:

Singh H, Thomas EJ, Mani S, et al. Timely Follow-up of Abnormal Diagnostic Imaging Test Results in an Outpatient Setting. Arch Intern Med. 2009; 169(17): 1578-1586.

http://archinte.ama-assn.org/cgi/content/short/169/17/1578?home

Choksi VR, Marn CS, Bell Y, Carlos R. Efficiency of a Semiautomated Coding and Review Process for Notification of Critical Findings in Diagnostic Imaging. AJR 2006; 186: 933-936

http://www.ajronline.org/cgi/reprint/186/4/933

Casalino LP, Dunham D, Chin MH et al. Frequency of Failure to Inform Patients of Clinically Significant Outpatient Test Results. Arch Intern Med. 2009;169(12):1123-1129.

http://archinte.ama-assn.org/cgi/content/full/169/12/1123

Leekha S, Thomas KG, Chaudhry R, Thomas MR. Patient Preferences for and Satisfaction with Methods of Communicating Test Results in a Primary Care Practice. The Joint Commission Journal on Quality and Patient Safety 2009; 35(10): 497-501

http://www.ingentaconnect.com/content/jcaho/jcjqs/2009/00000035/00000010/art00002

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October 20, 2009           

Radiology Again...But This Time It's Really Radiology!

We’ve done multiple columns on the hazards of the radiology suite. But most of those have dealt with the errors and adverse events occurring in the radiology suite that are not related to radiology per se. Most of those have to do with things like medication errors, IV line mixups, running out of oxygen, and other events that are due to patients with complex medical problems being temporarily managed in “non-medical” areas of the hospital.

But this time we have a real issue directly related to radiology itself – the series of radiation overdoses occurring at Cedars-Sinai from CT brain perfusion imaging studies. On October 8, 2009 the FDA issued an alert about the issues involved. Over an 18-month period, 206 patients at Cedars-Sinai apparently received radiation doses eight times the expected level during brain CT perfusion imaging. The studies were being done in the acute diagnosis and management of patients with suspected stroke. The problem was only recognized after a patient complained of patchy hair loss after such a scan.

Though the FDA acknowledged this involved only one type of scan at one facility, the magnitude of the problem and the potential for occurrence at other facilities was so substantial that the alert was issued. The FDA encourages every facility performing CT to review its CT protocols and be aware of the dose indices that are displayed on the control panels. These indices should be checked for each protocol both before and after scanning and compared to the doses usually associated with that protocol.

Each type of CT study uses a protocol that is programmed into the system. Cedars-Sinai had apparently reprogrammed the protocol for only one type of scan, the brain perfusion scan, which is used for evaluation of patients with suspected acute stroke (LA Times October 14, 2009). That was done to enhance the ability of the radiologist to see cerebral blood flow changes. Apparently no other protocols were affected.

The radiation dose does apparently appear on the control display of most CT imaging studies. However, it is just one of a number of items appearing on those screens. The system in use, and apparently most CT systems, do not have any sort of flag (eg. display in a different color, audible alert, etc.) that alerts the CT technician or radiologist that the dose of radiation about to be administered is higher than the usual dose. Such flags should be “hard stops”, i.e. that the scan cannot proceed until the appropriate individual verifies that the higher dose is intended. This is analogous to having dose range limits programmed into a CPOE system that alerts physicians and/or pharmacists when a dose of a medication is higher (or lower) than most conventional doses.

Radiation doses also often appear with the images when the radiologist is reading the scans. But we bet that most radiologists probably never pay any attention to those numbers.

Cedars has apparently also instituted “double checks” when protocols are changed (ABC News October 13, 2009). The hospital has apparently created a chain of authority for making such reconfiguations and ensuring that they do not result in excessive radiation doses (LA Times October 16, 2009). They have also initiated further training for CT technicians.

Perhaps most bothersome is the fact that this went on for 18 months before it was detected. In the retrospective investigation, about 40% of affected patients had suffered patchy hair loss or skin redness or irritation (ABC News October 13, 2009).

To make matters worse, the issue of how and what the hospital told the affected patients has become an issue. Several patients who were contacted by personnel from the imaging department said they were asked multiple questions but never told that there had been an error nor told they had received excessive radiation doses (LA Times October 15, 2009). Candor and apology have become the accepted standards in patient safety. Sometimes early in an investigation you may be unaware that any error or adverse event has even occurred and you may need to contact patients as part of your investigation. However, once you have confirmed that the error or adverse event has taken place you should be very upfront and let the patient (or family in some cases) know what has happened and what you will be doing. In the current cases, since the average age of the patients was 70 years, there is less likelihood of long-term consequences of this radiation overdose. But for the younger patients affected, potential long-term consequences (eg. development of brain tumor) become more problematic. Such potential consequences should be explained clearly to the patient in all cases. See our June 16, 2009 Patient Safety Tip of the Week “Disclosing Errors That Affect Multiple Patients”.

The series of events also highlights more unintended consequences of technology. In highly computerized systems, a single error can be rapidly propogated to result in harm to multiple patients. The staff at Cedars may have thought the equipment defaulted back to the original standard protocol after each use. But the new (higher dose) protocol became the standard protocol that appeared each time a brain perfusion CT scan was done. Thus, the single change applied to the next 200+ patients receiving that type of scan.

The cases are also eerily similar to one described in what we think of as one of the first-ever patient safety books, Steven Casey’s “Set Phasers on Stun” (Casey 1993). That is a book about some of the adverse events related to design issues and the human-technology interface. In the lead case, a design flaw in the human-computer interface, plus several latent conditions, led to a cancer patient being inadvertently exposed to a fatal dose of radiation. The radiation machine had two output modes, a conventional one and a very high dose one, each activated by the technician entering a letter of the alphabet. However, when the technician entered the wrong letter, went back and edited to enter the desired letter, the machine did not recognize the sequence of keystrokes and delivered 25,000 rads to the patient. The computer screen then popped up an error code that led the technician to think no dose had been given so she actually delivered several more doses. Investigation in that case led to discovery of similar cases in at least 3 other cancer centers.

Design flaws are common in everything we interact with on a daily basis (see our prior columns on the work of Don Norman and John Grout and John Gosbee among others). But in medical equipment design we often fail to anticipate how humans will interact with the equipment, resulting in some very unintended consequences. In the above examples, the key question that should have been asked is “What is the worst thing this machine could do to a patient?”. Clearly the answer would be that it could deliver an unintentionally excessive dose of radiation. The design process should then do everything possible to prevent such an inadvertent consequence. That obviously should contain “hard stops” that would prevent a technician from delivering such a dose without getting approval for the override from some other authority. Simply putting the dose on the screen amongst numerous other parameters is not enough. A visual alarm (eg. color, flashing alert) or an audible alarm would be a start but is also not enough. The process should not be allowed to be overridden by a technician simply acknowledging that the warning was seen. After all, this is not Microsoft Word asking you if you want to save the changes you made to the document!!!! But the other key issue is that many (if not most) pieces of high tech equipment are designed away from actual user areas and the designers are often unaware of the ways in which healthcare workers are likely to interact with that equipment.

You should ask the question “Why should anyone be allowed to change the dose of radiation in the first place?”. Good question. Most of the recent changes in radiation doses have been in the downward direction. Protocols have been developed for certain types of imaging to allow lower doses yet allow adequate imaging of whatever is being imaged (see section below on cumulative radiation dose over a lifetime). That is a desirable goal. So there is a logical reason to allow users to change protocols. However, making it too easy to change a protocol can lead to the types of problems highlighted by the Cedars-Sinai events. Allowing the protocols to be changed should only take place under supervision of those who clearly understand all facets of the equipment (probably including the manufacturer).

The cases also again raise the issue of excessive use of imaging in our current healthcare system. As you can readily see, this has not only financial implications but clearly patient safety implications as well. The cumulative dose of radiation one gets over a lifetime from medical imaging studies now is considerably higher than for previous generations. We currently have no systems in place to track the cumulative dose of radiation patients receive. While one facility conceivably might keep track of the totals for studies done on a patient at their facility (but let us know if you actually find one!!!), patients typically have imaging studies done at multiple different facilities. Particularly as we move forward with electronic medical records, we should be able to begin to track lifetime cumulative radiation doses. Even if the exact radiation dose for each individual procedure is not captured in those EMR’s, it is pretty easy to set up a “counter” that would count the number of studies using radiation and multiply each by the “average” dose of radiation for that particular study. Just having a cumulative dose highlighted may defer someone from ordering another imaging study that may be of marginal necessity, particularly if a different diagnostic study not using radiation is available.

We hope you will be looking at all the sites in your organization that perform imaging studies and asking the key questions we’ve noted above. Don’t be surprised if you identify some vulnerabilities. The Cedars-Sinai events are ones that should make you all be asking “I wonder if that could happen here?”.

References:

Safety Investigation of CT Brain Perfusion Scans: Initial Notification

Date Issued: October 8, 2009

http://www.fda.gov/MedicalDevices/Safety/AlertsandNotices/ucm185898.htm

Doctors 'Shocked' by Radiation Overexposure at Cedars-Sinai

Medical Scans Continue Increasing Our Exposure to Radiation, Experts Say

By RADHA CHITALE
ABC News Medical Unit
Oct. 13, 2009

http://abcnews.go.com/Health/CancerPreventionAndTreatment/doctors-shocked-radiation-exposure/story?id=8818377

Cedars-Sinai head expresses regret for radiation overdoses

By Alan Zarembo

Los Angeles Times. October 16, 2009

http://www.latimes.com/news/local/la-me-cedars16-2009oct16,0,3559559.story?track=rss

4 patients say Cedars-Sinai did not tell them they had received a radiation overdose

By Alan Zarembo

Los Angeles Times. October 15, 2009

http://www.latimes.com/news/local/la-me-cedars15-2009oct15,0,2773125.story?track=rss

Cedars-Sinai radiation overdoses went unseen at several points

By Alan Zarembo

Los Angeles Times. October 14, 2009

http://www.latimes.com/news/local/la-me-cedars-sinai14-2009oct14,0,5065886.story

Casey S. Set Phasers on Stun and Other True Tales of Design, Technology, and Human Error. Santa Barbara California: Aegean Publishing Company, 1998 (first published in 1993).

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October 27, 2009           

Co-Managing Patients: The Good, The Bad, and The Ugly

Co-managing patients is an attractive concept: you draw upon the special knowledge, expertise and skill sets of more than one physician to provide the optimal care for your patients. Theoretically, such a synergistic approach should produce a result that is greater than sum of the parts – that two physicians are more likely to ensure the patient gets all the evidence-based care that is appropriate. But, in reality, is that what occurs? Sometimes co-management leads to a false sense of security that someone will remember all aspects of care.

On the outpatient side there are lots of examples where co-management by a primary care physician and a specialist results in less optimal care than that provided by either alone. We’ve seen the diabetic patient whose LDL elevation goes unaddressed because both the PCP and the endocrinologist assume the other is addressing it. Or the CHF patient whose blood pressure is still above target because the cardiologist and the PCP each assume the other is managing the blood pressure.

On the inpatient side, the co-management is most often done by a surgeon and a hospitalist or geriatrician. Nursing staff may be confused about whom to call for problems. The lab or radiology may not know whom to contact with critical or unexpected values. Patients and families frequently become confused about who their doctor really is and whom to go to when they have questions.

The hospitalist might be addressing medical issues such as glycemia management but might have a different glucose target than the surgeon who is concerned about surgical site infections. DVT prophylaxis approaches may differ between internists and surgeons but the rationales used by each need to be discussed with each other and then one should be assigned the responsibility of managing the DVT prophylaxis.

Whenever responsibility becomes “shared” we know there are certain dangers we may encounter. Two weeks ago, in our Patient Safety Tip of the Week “Slipping Through the Cracks”, we noted that appropriate timely follow-up to alerts about potentially significant radiology findings was twice as likely not to occur when dual alerts (i.e. alerts to more than one physician) were sent out.

Similarly, another point we have made over and over – double checks are very weak safety interventions. From all industries we know that the error rate when a supervisor checks someone else’s work may be 10% or higher. Note also that we don’t know what influence the double check has on the error rates of the original person. It is quite conceivable that the original person may make more errors if they feel that their errors will be intercepted by a second reviewer. In our May 2008 What’s New in the Patient Safety World column “UK NPSA Alert on Heparin Flushes” a study did acknowledge the controversy regarding double checks but notes that the literature supports a medication error reduction of about 30% when using a double check system.

Note that the second reviewer need not be a person. We have certainly seen in some technology solutions that staff become so confident in the computer’s ability to capture errors that their own vigilance may wane. There certainly have been numerous cases where a nurse administers too high a dose of a medication because the barcoding/bedside medication verification system “confirmed” that it was the correct patient, the correct medication, and the correct dose (i.e. the dose that had been ordered).

So there are lots of examples where dangers exist when two physicians are managing the same patient. But there are also lots of examples where co-management has been successful. A study from the University of Rochester in the most recent issue of Archives of Internal Medicine (Friedman et al 2009) looked at outcomes in a geriatric fracture center in a community teaching hospital where patients are co-managed by a geriatrician and an orthopedic surgeon. Compared with similar patients managed at a similar center without co-management, outcomes with co-management showed shorter times to surgery, fewer postoperative infections, fewer total complications and shorter lengths of stay. There were also fewer cases of delirium and restraint use in the co-managed group. Note that the co-managed model also relied heavily on care protocols and standardized order sets and focused heavily on measures to help avoid delirium or use of medications known to affect mental status. Involvement of geriatricians or hospitalists in orthopedic programs has also been of benefit in other studies done in the US (Pinzur et al 2009) and the UK (NHS 2009), including improvements not only in hospital efficiencies but also in patient satisfaction.

So co-management, if done correctly, does provide the opportunity to improve outcomes in many cases. Interestingly, whereas logic would predict the biggest impact of co-management would occur in patients with the most complex medical problems, some have anecdotally seen the biggest impact in those patients who were less sick (Butterfield 2009).

If you are going to co-manage patients, there are several recommendations we have for you:

• Make sure there is a true need for the “co-manager” (eg. if you just need someone to write orders while the surgeon is in the OR, a physician extender is a more logical choice but if you have a complicated patient with diabetes, CHF and chronic kidney disease the expertise of a hospitalist or geriatrician may be invaluable)
• Clearly define roles up front (who will manage what aspects of care)
• Define those roles in writing so the nursing staff (and others) know who to call for each problem
• Establish key goals (eg. glucose targets) to ensure you are all on the same page
• Clarify who will speak to family regarding what aspects of care
• Clarify who will communicate with those physicians who will be providing care after discharge
• Make sure your CPOE/clinical decision support system directs alerts to the appropriate physician and be very wary about “dual” alerts
• Make sure the lab (or radiology or other department) know whom to contact with critical values
• If you are co-managing perioperative patients, try to involve the hospitalist or geriatrician preoperatively, not just postoperatively
• Standardized order sets and standardized protocols are still valuable tools even for co-managed patients (eg. so both physicians don’t assume the other will write the order to discontinue the urinary catheter!)
• Co-management is particularly likely to be helpful in patients at risk for post-op delirium (see our Patient Safety Tips of the Week for October 21, 2008 “Preventing Delirium”, October 14, 2009 “Managing Delirium”, February 10, 2009 “Sedation in the ICU: The Dexmedetomidine Study”, and March 31, 2009 “Screening Patients for Risk of Delirium”)

Co-management can improve the quality of patient care and outcomes. But, like most other things in healthcare, it has the potential for unintended consequences. You need to be wary of these upfront and design your systems to help avoid them.

References:

Friedman SM, Mendelson DA, Bingham KW, Kates SL. Impact of a Comanaged Geriatric Fracture Center on Short-term Hip Fracture Outcomes. Arch Intern Med. 2009;169(18):1712-1717.

http://archinte.ama-assn.org/cgi/content/short/169/18/1712?home

Pinzur MS, Gurza E, Kristopaitis T, et al. Hospitalist–Orthopedic Co-management of High-risk Patients Undergoing Lower Extremity Reconstruction Surgery. ORTHOPEDICS 2009; 32: 495  July 2009

http://www.orthosupersite.com/print.asp?rID=41034

NHS Institute Orthopaedic Programme Improves Quality Of Care In 12 Weeks, UK

Medical News Today. 15 Oct 2009

http://www.medicalnewstoday.com/articles/167398.php

Butterfield S. Surgical comanagement done right. ACP Hospitalist 2009; March 2009

http://www.acphospitalist.org/archives/2009/03/cover.htm

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November 3, 2009           

Medication Safety:

Frontline to the Rescue Again!

Two great studies have been recently completed, again demonstrating that frontline nursing staff still play the most important role in medication safety.

Linda Flynn, R.N., Ph. D presented in an INQRI webinar "Examining the Impact of Nursing Structures and Processes on Medication Errors" work that she and her colleagues had done on how nurses help prevent medication errors. Seizing on the IOM statistic that 50% of medication errors are caught before they impact the patient and 87% of those are caught by nurses, they sought to find out what goes through nurses’ minds to catch those errors. So they interviewed 50 nurses at 10 hospitals and found 7 key things that nurses do to intercept such errors:

1. They independently evaluate and reconcile the MAR (medication administration record) with the original order, essentially performing an extra check.
2. They do a “full assessment” of the patient (what does the patient look like overall at this time?).
3. The question the rationale for the medication (what was it ordered for?).
4. They discuss with the physician or make rounds with the physician.
5. They educate the patient and family to enable them to become the last line of defense.
6. They advocate with pharmacy for timeliness of medications.
7. They ask the physician to rewrite the orders if there are handwriting legiblity issues or use of nonstandard abbreviations.

They then looked at barriers to accurate medication administration and found 2 that were most important. As you might anticipate, interruptions were one of those. They note that often the interruption is unnecessary (for example, the lab calls to see if the patient is back from radiology so they can come to draw blood samples) and the interrupting party could have obtained their information by other means. Second, the nursing/pharmacy interface was often poor. They provide, as an example, the scenario where pharmacy technicians daily switch out the medications in the patient’s “drawer”. If a patient is off the floor, pharmacy may take away a dose of a medication the patient was supposed to receive and the “new” drawer does not account for that dose. So nurses learn to hide the medication (actually physically hide the dose elsewhere so they can give it to the patient when he returns to the floor).

The second phase of their study evaluated factors in 14 hospitals that influence the medication administration process, looking at effects of nursing process, the practice environment, RN staffing, and technology. Of the 7 key things noted above, they found 4 that were statistically related to accurate medication administration: questioning the rationale for the medication, educating the patient/family to participate in safety, rewriting/clarifying orders, and independent reconciliation of the MAR and order. They then looked at various factors that predicted success of the medication administration process and found the following factors to be very favorable:

1. A good overall practice environment (supportive manager, good staffing, good relationships with physicians, participation in decisions, and foundations for quality)
2. RN hours per patient day
3. Presence of computerized physician order entry (CPOE)

In the third phase, they did an analysis of the costs of medication errors at both a community hospital and a university hospital and concluded that the attributable cost of such errors averages almost $7000 per error.

In the Q&A session following the presentation in that webinar, some very good questions were asked. One good question was whether the methodology just included surveys and medication error reporting or if it utilized “naïve observation” (where an observor observes all the aspects of the process without actually knowing anything about the particular medication). This study did not utilize naïve observation. The questioner noted the importance of interruptions and noted that not all interruptions are external. Sometimes the nurse is multitasking and the interruption is self-imposed (eg. talking to someone who happens to walk by). Not surprisingly, that questioner was one of the investigators of the second study

That second study was done by UCSF’s Integrated Nursing Leadership Program (INLP) and involved 9 San Francisco Bay area hospitals. They used the “naïve observor” methodology and tied overall medication administration accuracy to compliance with 6 process steps identified as “best practices” by CALNOC (the California Nursing Outcomes Coalition):

1. Compare medication to the medical record
2. Keep medication labeled until administration
3. Check two forms of patient identification
4. Immediately record medication administration in the chart
5. Explain the medication to the patient
6. Minimize distractions and interruptions

Accuracy of medication administration (i.e. all steps done without error) was 83.8% at baseline and improved to 96% after 36 months, an overall 88% reduction of medication error rate. The numbers for adherence to the 6 best practice had almost identical numbers (improving from 80% at baseline to 96% afer 36 months).

Avoiding distractions and interruptions played an important role and low-tech solutions played a huge role (see Colliver article). Such solutions included wearing brightly colored vests or sashes when administering medication, or physically announcing at key points, or creating quiet zones. Such low-tech solutions often led to dramatic reductions in interruptions.

This study fits very nicely with the observations in our August 25, 2009 Patient Safety Tip of the Week “Interruptions, Distractions, Inattention…Oops!”, in which we discussed the analogy with the “sterile cockpit” in aviation and numerous types of interruptions and distractions and interventions to minimize them.

The two studies here provide graphic evidence of the importance of frontline workers as the last step in preventing medication errors from reaching the patient and causing harm. Though there is little doubt that high-tech solutions such as barcoding/bedside medication verification (BMV) have also led to dramatic reductions in medication errors, we have also seen as an unintended consequence an over-reliance on those high-tech solutions. We have all seen cases where the computer said its okay to administer that drug which was ordered in error because “you have the right patient, the right medication, the right dose, the right time” and the nurse trusts that computer system so much that the medication is administered even though he/she might have questions. So implementing the great low-tech principles and processes in these two studies can serve to improve the accuracy and safety of medication administration even above and beyond that seen with BMV. And both make us keenly aware that we must invest heavily not just in technology but also in our people and systems. Congratulations to both groups for great contributions to patient safety!

References:

INQRI. Webinar "Examining the Impact of Nursing Structures and Processes on Medication Errors" Dr. Linda Flynn (link to both webinar and slides)

http://inqri.blogspot.com/2009/10/did-you-miss-yesterdays-webinar-watch.html

UCSF Program Achieves 88% Reduction in Medication Administration Error

Study Definitively Links Nursing “Best Practices” to Medication Administration Accuracy. Program Establishes Important Leadership Role for Front-Line Clinicians In Improving Healthcare Quality. Businesswire October 30, 2009 (study apparently to be published in the December 2009 issue of The Joint Commission Journal on Quality and Patient Safety)

http://www.businesswire.com/portal/site/home/permalink/?ndmViewId=news_view&newsId=20091030005861&newsLang=en

Integrated Nurse Leadership Program - Clinical Outcomes Fact Sheet

http://www.futurehealth.ucsf.edu/LinkClick.aspx?fileticket=ErsXd2JbgZY=&tabid=235

Colliver V. Prescription for success: Don’t bother nurses. SFGate.com. October 28, 2009

http://www.sfgate.com/cgi-bin/article.cgi?f=/c/a/2009/10/28/MNIM1AB9DB.DTL&type=health

The CALNOC Medication Administration Accuracy Measure: Understanding Medication Administration Processes and Outcomes.

http://www.socalpatientsafety.org/materials/docs/09-02-2009/Mary Foley.pdf

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November 10, 2009           

Conserving Resources…But Maintaining Patient Safety

In today’s economy and healthcare environment, most hospitals and other healthcare organizations are struggling to stay above water. All are cutting resource expenditures in one area or another. We are always concerned that such cuts may imperil patient safety. But there are numerous areas where such cuts can be undertaken while preserving patient safety and in the last few weeks there have been numerous examples.

One good example is after-hours ultrasound. Whether your organization is in an urban or a rural setting, you know that there is a shortage of ultrasound technicians. Hiring and retaining good ultrasound technicians is an uphill battle for many organizations. The biggest impediment to retaining them is the on-call schedule. Many balk at being called in at all hours of the night to do ultrasound scans, especially when such calls may take place 1-3 times each night at many hospitals. There is a very high rate of negative scans and many of those scans don’t have to be performed after-hours. In many cases, bridging therapy can be instituted overnight and the scan can be performed in the morning during usual working hours.

The University of Pittsburgh recently studied this issue (Chaer et al 2009). They developed a policy/guideline for after-hours performance of venous duplex ultrasound studies looking for DVT. A multidisciplinary group (surgery, internal medicine, emergency medicine) developed a structured algorithm using a modified Wells score and D-dimer testing. Patients who had a low probability of DVT (modified Wells score = 0 and D-dimer negative) were discharged and referred for outpatient followup the following day. Those at moderate risk (modified Wells score >1 or D-dimer positive) were treated with LMWH overnight and were scheduled for venous duplex ultrasound in the morning. For moderate- or high-risk patients in whom anticoagulation was contraindicated or declined for other reasons, the ultrasound tech was called in and the study performed. In the first year the number of after-hours ultrasound studies dropped from 59 per month to 19 per month without any clinically adverse events. There was also a substantial increase in the rate of positive after-hours studies. And job satisfaction for ultrasound techs improved significantly.

A second example is the use of daily chest x-rays, a practice commonly used in intubated, mechanically ventilated patients. A French study (Hejblum et al 2009) compared the routine daily chest x-ray strategy against an “on-demand” strategy (where chest x-rays are ordered based on clinical questions). They found that the on-demand strategy resulted in 32% fewer x-rays being done with no obvious adverse clinical consequences. Fewer x-rays should translate to lower costs, fewer x-rays of limited clinical utility, lower radiation exposure, and theoretically even less exposure to microbial pathogens on the portable x-ray equipment. Fewer portable x-rays also translates to more technician time available for imaging studies on outpatients. So hospitals really should look at their current policies (whether truly policy or just traditional practice) and see whether the on-demand approach better suits them. The authors and the accompanying editorialist appropriately note that local factors will weigh heavily into such decisions. Changes in workflow (eg. the on-demand strategy really requires early rounding daily to see whether chest x-rays are needed that day) may be necessary.

A third example is use of clinical “rules” that help guide the decisions whether to pursue imaging or not in patients seen in the emergency department. For years, we have used the Ottawa knee and ankle rules in our ED’s and seen the number of knee and ankle x-rays diminish without adversely affecting patient care. Similarly, there are several “rules” that aid the decision about performing CT scans of the head in patients with minor head trauma. Use of such rules not only saves costs but it also streamlines ED throughput and helps avoid lengthy waits by patients.

The Canadian C-spine rule was developed almost 10 years ago and during validation studies demonstrated a sensitivity for significant spinal injury of 99%. It was postulated that implementation of this clinical rule could reduce unnecessary cervical spine films by almost 50%. Now, the results of a well-done randomized trial at Canadian hospitals has been published (Stiell et al 2009). The study showed that cervical spine imaging at the intervention hospitals had a relative decrease of 12.8% whereas there was a relative increase of 12.5% at the control hospitals. The relative reduction in imaging rates was greater in community hospitals than teaching hospitals. Using fairly sophisticated methods to detect any significant missed injuries, they found no missed fractures nor adverse clinical outcomes at the intervention hospitals. Note that rates of imaging at all hospitals were considerably lower than at typical US hospitals, suggesting that many physicians in Canada may have already begun adopting the rule even before this study. Implementation of the rule was fairly simple. A one hour educational session and distribution of pocket guides, posters, and the supporting literature were used. In addition, there was the requirement that physicians complete the rule at the time the imaging requisition was submitted. (Our note: As hospitals implement computerized physician order entry or CPOE, one can easily incorporate the rule into the order entry process and provide help at ensuring the rule is interpreted correctly). Though the degree of benefit in the Canadian hospitals was modest, the opportunity in US is much higher, given the higher baseline cervical spine imaging rates in the US. Perhaps the litiginous nature of the US legal system may be preventing adoption of the Canadian C-spine rule in the US. However, if it becomes the “standard of care” there should be fewer concerns about lawsuits and less studies ordered “defensively”. Again – without compromising patient safety the opportunity from reducing unnecessary cervical spine imaging impacts not only costs but also reduces radiation dose, frees up radiology resources for other endeavors, and improves wait times in the ED.

And we still see other practices that are both costly and potentially threaten patient safety. Many hospitals still do not have automatic review of all oxygen orders (see our Patient Safety Tips of the Week for April 8, 2008 “Oxygen as a Medication” and January 27, 2009 “Oxygen Therapy: Everything You Wanted to Know and More!”. How often have you made rounds and seen patients with their oxygen face mask or nasal prongs hanging down around their neck? If they don’t need or use the oxygen, why would you put them (and the institution) at risk for adverse events such as fires. Most hospitals have now incorporated protocols in which respiratory therapy or nursing have the ability to discontinue oxygen if parameters like degree of oxygen saturation are met. But at a minimum you should have protocols and reminders that force the question be asked about continued need for oxygen at least every few days.

But there are other examples where you do not want to cut and where investment in resources may save money in the long run. Housekeeping is one of those areas. We have seen hospitals faced with budget deficits cut housekeeping staff, only to encounter increased nosocomial infection rates. Note that two of the articles in our November 2009 What’s New in the Patient Safety World column (“Ten Ways to Prevent Healthcare-Associated Infections” and “BMA: Tackling healthcare associated infections through effective policy action”) mention the need for increased attention to cleaning “near-patient high-touch” sites (eg. bed rails, bedside lockers, infusion pumps, door handles, switches, etc.). Well, another study from the UK (Dancer et al 2009) suggests that hiring an additional cleaner who focuses on these sites has the potential to save a hospital £30,000 to £70,000 ($50,000 to $116,000 US) annually even after accounting for the salary for the extra cleaner. In this study, the hospital hired an extra cleaner to perform “enhanced” cleaning (focusing on the near-patient high-touch sites) 5 days a week. Two wards were compared in a crossover design. They demonstrated a 33% reduction in microbial contamination at the hand-touch sites and a 26.6% reduction in new MRSA infections on the wards receiving the enhanced cleaning. When the enhanced cleaner crossed over to the other ward, the reduction was seen on the new ward. And both wards had clusters of new MRSA infections 2 to 4 weeks after the enhanced cleaner left both wards. Though the study makes some assumptions and has some other limitations, our guess is that there is real savings to be had with this approach.

The bottom line: in hard times think your decisions about resource reallocation through wisely. Do those that you can do without diminishing patient safety. And sometimes spending a little extra in some areas can improve both patient safety and your budget.

References:

Chaer RA, Myers J, Pirt D, et al. The Impact of a Systemwide Policy for Emergent Off-Hours Venous Duplex Ultrasound Studies. Annals of Vascular Surgery 2009; Corrected Proof, 11 September 2009
DOI: 10.1016/j.avsg.2009.06.013

http://www.annalsofvascularsurgery.com/article/S0890-5096(09)00139-3/abstract

Hejblum G, Chalumeau-Lemoine L, Ioos V, et al. Comparison of routine and on-demand prescription of chest radiographs in mechanically ventilated adults: a multicentre, cluster-randomised, two-period crossover study. The Lancet 2009; Early Online Publication, 5 November 2009

doi:10.1016/S0140-6736(09)61459-8

http://www.thelancet.com/journals/lancet/article/PIIS0140-6736(09)61459-8/abstract

Stiell IG, Clement CM, Grimshaw J, et al. Implementation of the Canadian C-Spine Rule: prospective 12 centre cluster randomised trial. BMJ  2009;339:b4146 (Published )

http://www.bmj.com/cgi/content/abstract/339/oct29_4/b4146

Dancer SJ, White LF, Lamb J, Girvan EK, Robertson C. Measuring the effect of enhanced cleaning in a UK hospital: a prospective cross-over study. BMC Medicine 2009, 7:28  doi:10.1186/1741-7015-7-28

http://www.biomedcentral.com/1741-7015/7/28

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November 17, 2009           

Switched Babies

Here’s a topic where we really are asking our readers for their input and opinions. Mercy Medical Center in Williston, North Dakota had an incident this past September in which the wrong baby was given to a mother at discharge. The error was recognized within hours and both babies were reunited with their correct mothers promptly. Last week Mercy Medical held a press conference in which they transparently disclosed the details of the incident (maintaining patient confidentiality, of course) and the results of the subsequent root cause analysis (RCA). We applaud Mercy Medical for their actions. Not only do their actions bring credibility to themselves but they also raise the issue for all other hospitals to address. We challenge each and every hospital to honestly answer the question “Could that have happened here?”. Most will probably say “I really don’t know. Certainly the human error element could happen here. But I’m not sure if our safety net and safety systems would prevent the actual adverse outcome.”

Sending a baby home with the wrong parents is the worst case scenario but in-hospital baby mixups, which are probably more common, can be just as traumatic. Not only are they psychologically devastating for many parents but the issue of potential infection transmission is raised when babies are breastfed by the wrong mothers.

Mercy Medical’s actions after their root cause analysis include reenforcement of some current policies and simplification of others. They also developed a tracking log in which the hospital staff logs each baby's movement after the child is taken from a bassinet for changing and feeding. And the discharge process was changed so that babies are not allowed to leave the hospital until a wristband is double-checked against paperwork.

Statistics on the frequency with which such misidentification errors result in actual baby switches are not readily available. From time to time one hears a story about adults who find out they were switched as babies many years earlier. But there are few stories about such baby switches at the time they actually occur. In 2008 there was such an occurrence at a southern Illinois hospital. In that incident the mixup apparently occurred when two babies were sent to the OR for circumcisions. We are unaware of publication of the root cause analysis from that hospital or from The Joint Commission, which investigated the incident, but a subsequent lawsuit alleged that the personal identification materials had been removed for the surgery and the mixup apparently occurred when they were reapplied.

After an incident in Queensland (Australia), which requires reporting of such events regardless of ultimate outcome, was made public it was revealed that there had been 57 cases in which at least one identification tag of an infant was missing or contained the wrong name in 2008, and 55 cases in 2007, though no infants went home with the wrong family. But there were cases where the wrong infant was breastfed by the wrong mother, necessitating testing for hepatitis and HIV. Even then, we know that even in mandatory incident reporting systems there is significant underreporting.

If you google using enough search terms, you can find about a case a year that appears in newspapers worldwide.

For at least the last 10 years, most hospitals have had fairly sophisticated systems in place to avoid infant abductions and to respond prompty if one occurs. The Joint Commission issued a Sentinel Event Alert in 1999 identified root causes in cases of infant abductions from hospitals and made numerous recommendations for steps to prevent such. All hospitals have developed infant abduction policies (often called “Code Pink” policies). Among those recommendations were attaching secure identically numbered identification bands to the baby (wrist and ankle bands), mother, and father or significant other immediately after birth. In addition, the footprint of the infant and a color photograph of the infant are recommended. Some hospitals also use a fingerprint of the mother in the identification process. Prompt recording of the physical examination of the infant is also useful in the identification process (eg. recording of birthmarks may be very helpful in correct identification). Code Pink policies also include conspicuous identification badges for all staff members, good security/surveillance of all access and exit sites, and high tech infant security tags and alarm systems. Note also that you may wish to modify your “Code Pink” policy to also include patients who have eloped or are otherwise missing (see our July 28, 2009 Patient Safety Tip of the Week “Wandering, Elopements, and Missing Patients”). So many elements of your Code Pink policy should also be helpful in preventing baby mixups.

Education of both staff and the family are important in preventing infant abductions but should also be extended to help prevent incorrect identification of infants. When providing such education to mothers and family, it is important to assess their level of understanding. It may actually be wise to do that education twice with the mother, once in the days or weeks just prior to anticipated delivery and then again immediately after delivery when the ID tags are being placed. You need to keep in mind that the mother’s cognition may be impaired by drugs used during labor and delivery and she may not fully comprehend what she is being told at that time. In any case, the identification process should be reinforced on every interaction between mother and baby and staff.

The following may be contributing factors in some cases of baby mixups:

• Understaffing/excess workloads
• Change of shift or change of personnel
• Babies often born about the same time
• Babies may often go for feeding about the same time
• Babies may often go to the OR for circumcision about the same time
• Preparing more than one patient identification tag at a time
• Mother is not yet familiar with the baby (may have only seen him/her once!)
• Similar names

Some contributing factors gleaned from the scant literature on baby mixups appear to be understaffing or excessive workload and also change of shift. Several of the events have occurred when the person applying the identification tags is different from the  individual immediately responsible for the infant at delivery.

Maternal recognition of the baby is an issue. We’ve heard people say “How could that happen? Couldn’t the mother recognize she had the wrong baby when she left the hospital?”. Well, think about that. The time of greatest risk for such misidentification is when the ID tags are first being affixed. The mother probably only sees the baby briefly at delivery and could not be expected to recognize that baby based on that sole exposure (particularly if drugs had to be used during labor and delivery). When the baby is later brought back for breastfeeding or just bonding, the mother then begins to recognize that baby as her baby (and the mixup may have already occurred!).

The use of two identification bands on the baby, however, is also not an infallible method of identification. In a baby mixup in a Hong Kong hospital this year, two babies had different identification bracelets on their wrists and ankles. Each was breastfed by the wrong mother for several days before the mixup was correctly sorted out using birthweights, footprints, blood typing, and eventually DNA identification.

The root cause analysis of the Hong Kong incident is very instructive and confirms some of the factors that increase the risk of such infant misidentifications. That incident was only recognized when the mother of one baby let the nursing staff know that the wrist band of her baby was missing but there was a wrist band bearing the name of another mother in her baby’s cot (subsequent DNA testing confirmed the mixup).

That hospital had what sounded like good policies and protocols in place for proper identification of newborns. But one nurse prepared the ankle bracelets for two babies at the same time and asked a ward assistant to affix them to the ankles of the respective babies. That assistant checked the information on the ankle bracelets with that on the head of the cots but not against the babies’ wrist bracelets. And the nurse did not verify with the mothers the baby identification at time of first feeding. There were other system issues as well, such as inadequate systems to ensure staff at all levels were apprised of updates to policies and procedures and lack of a good system for monitoring compliance with key elements of the policies.

We have previously identified that doing things on two (or more) patients at the same time raises significant patient safety issues. See our Patient Safety Tips of the Week for June 19, 2007 “Unintended Consequences of Technological Solutions” in which we described inadvertent transposition of remote telemetry units when 2 units were prepared at the same time and April 23, 2007 “Predictable Errors” in which we describe the “two in a box” type of error. Multitasking may be good for some things but, frankly, it is dangerous for most things we do in healthcare.

Similar names is always an issue when it comes to wrong patient events. In our May 20, 2008 Patient Safety Tip of the Week “CPOE Unintended Consequences – Are Wrong Patient Errors More Common?” we noted you would be surprised to see how often patients with the same or very similar names may be hospitalized at the same time. Shojania (2003) described a near-miss related to patients having the same last name and noted that a survey on his medical service over a 3-month period showed patients with the same last names on 28% of the days. The problem is even more significant on neonatal units, where multiple births often lead to many patients with the same last name being hospitalized at the same time and medical record numbers being similar except for one digit. Gray et al (2006) found multiple patients with the same last names on 34% of all NICU days during a full calendar year, and similar sounding names on 9.7% of days. When similar-appearing medical records numbers were also included, not a single day occurred where there was no risk for patient misidentification. Both these studies were on relatively small services so one can anticipate that the risks of similar names is much higher when the entire hospitalized patient population is in the database.

In addition to mothers directly breastfeeding the wrong baby, there is the risk of babies being fed expressed breast milk from the wrong mother. The Pennsylvania Patient Safety Authority issued a Patient Safety Advisory on Mismanagement of Expressed Breast Milk in 2007. The Pennsylvania Patient Safety Reporting System (PA-PSRS) had received 20 reports of infants being fed another mother’s expressed breast milk. They identified risk factors that involved not only identification issues but also labeling issues, and problems with verification, storage and dispensing. The Advisory has good recommendations on risk reduction strategies and an excellent section on how to respond and manage patients when such exposures do occur, particularly managing the risk for infectious disease transmission. All those recommendations obviously would also apply in cases where infants were directly exposed to breasfeeding by the wrong mother.

Certainly, a number of patient safety tools are available that might reduce the chance of baby mixups. These include both high tech and low tech tools. Barcoding is an obvious tool, given that so many hospitals have now moved to barcoding systems to improve medication safety. The design of the identification bracelets for babies and parents are beyond the scope of this column but the issues can get quite complex. Barcoding can be either linear or 2-dimensional and the number of elements staff want to display on barcoded identification bracelets can get quite cumbersome. Design of the bracelets and labels for the infant is also tricky, given the small wrists and ankles the babies have and the problem that the resulting curvature makes scanning more difficult. The actual unique identification code that appears on both the baby’s and mother’s bracelet needs to be something other than the medical record number. Otherwise you would increase the risk of administering a drug to the mother instead of the baby or vice versa. And, though barcoding is a great tool, it doesn’t help if the bracelets/labels were already mixed up and it can often give rise to a false sense of security.

So back to low tech! The timeout is a logical tool to use. Just as in the OR we use a timeout to verify the correct patient (and many other things) you could use a timeout to verify the correct baby/mother combination or identify the correct baby going for any other procedure. Use of checklists could also be very valuable. We haven’t seen the tracking log that Mercy Medical described in its corrective actions but a tracking log could easily be designed in a checklist format that would include appropriate reminders for patient identification and baby/mother verification. We’ll be some obstetrical units or nurseries or NICU’s could get creative and develop a Ticket to Ride type tool (see our November 18, 2008 Patient Safety Tip of the Week “Ticket to Ride: Checklist, Form, or Decision Scorecard?”).

What about double checks? A point we have made over and over is that double checks are very weak safety interventions. From all industries we know that the error rate when a supervisor checks someone else’s work may be 10% or higher. And we don’t know what influence the double check has on the error rates of the original person. It is quite conceivable that the original person may make more errors if they feel that their errors will be intercepted by a second reviewer. We have certainly seen in some technology solutions that staff become so confident in the computer’s ability to capture errors that their own vigilance may wane. Nevertheless, the literature supports a medication error reduction of about 30% when using a double check system. So one might anticipate some potential benefit if double checks, such as at discharge, were applied to the baby/mother identification verification process.

And, importantly, we feel that you must have some way of auditing your processes to ensure compliance with your well-intentioned policies. The best policies in the world will not help if no one adheres to them. Plus auditing helps you identify when workarounds are being used. Workarounds are almost always indicative of a flaw in your policy or procedure and should tip you off that you need to fix the underlying system. The audits could be random spot audits or “secret shopper” type audits.

It also seems to us that the complexity of the identification process and some of the reduncancies built into it may actually be contributing factors to some cases of misidentification. Having 3 identification tags (wrist band, ankle bracelet, and bassinette tag) rather than 2 increases the mathematical possibility there will be mismatches of tags. We understand that the tags often fall off babies or may become illegible due to moisture, etc. so we understand the rationale for using 2 tags on the babies. But if (as seen in the Hong Kong case RCA) everyone focuses on only one of the tags and largely ignores the  other, are we just adding to the complexity?

So how do you prevent such mixups from happening at your facility? Are you at risk? This is another great topic for your organization to perform a FMEA (failure mode and effects analysis) on. We’d be interested in hearing what you find!

References:

Smith N. Mercy officials explain switched babies. Officials say human error was the reason for the mistake.
Williston Herald. November 11, 2009

http://www.willistonherald.com/articles/2009/11/11/news/doc4afaecbc51cae698705308.txt

Families sue over infant switch.

John D. Homan, TheSouthern.com April 11, 2008

http://thesouthern.com/news/article_233f7eae-df10-558e-813e-99c91d725663.html

Queensland hospital errors lead to newborn mix-ups

Patrick Lion

couriermail.com.au  April 17, 2009

http://www.news.com.au/couriermail/story/0,23739,25348095-952,00.html

The Joint Commission. Sentinel Event Alert. Infant Abductions: Preventing Future Occurrences. Issue 9 April 9, 1999

http://www.jointcommission.org/SentinelEvents/SentinelEventAlert/sea_9.htm

Breast-feeding error adds to mix-up moms' miseries.
Two registered nurses and a health assistant have been sent for retraining and placed under supervision following a mix-up in which two mothers breast-fed each other's baby for at least 36 hours.
Patsy Moy and Andrea Chan
The Standard (China) Tuesday, August 18, 2009

http://www.thestandard.com.hk/news_detail.asp?pp_cat=30&art_id=86508&sid=24978364&con_type=1

Investigation Report of the Incident with Misidentification of Two Babies in Queen Elizabeth Hospital

http://www3.ha.org.hk/qeh/pdf/full090918en.pdf

Shojania KG. AHRQ Web M&M Case and Commentary. Patient Mix-Up. February 2003. http://www.webmm.ahrq.gov/case.aspx?caseID=1&searchStr=shojania

Gray JE, Suresh G, Ursprung R, Edwards WH, Nickerson J, Shiono PH, Plsek P, Goldmann DA, Horbar J. Patient Misidentification in the Neonatal Intensive Care Unit: Quantification of Risk. Pediatrics 2006;117;e43-e47

http://pediatrics.aappublications.org/cgi/reprint/117/1/e43

Mismanagement of Expressed Breast Milk

PA PSRS Patient Saf Advis 2007 Jun;4(2):46-50

http://patientsafetyauthority.org/ADVISORIES/AdvisoryLibrary/2007/jun4(2)/Pages/46.aspx

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November 24, 2009           

Another Rough Month for Healthcare IT

Our October 2009 What’s New in the Patient Safety World column “A Cautious View on CPOE” noted a new systematic review (Reckmann 2009) that concluded evidence showing a reduction in medication errors by CPOE, particularly serious medication errors, is scant. The few studies that did demonstrate positive results either had very focused outcomes (i.e. only certain types of medication errors in select populations were studied) or the study populations were very small or there were methodological problems. This month another study (van Doormaal 2009) adds to the uncertainty. This study, performed in the Netherlands, used times series analysis to get around some of the thorny methodological issues seen in before/after studies. It evaluated the effect of computerized physician order entry (CPOE), primarily medication order entry with rudimentary clinical decision support (CDSS), on both medication errors and preventable adverse drug events (those with harm). It showed that the percentage of orders with at least one medication error dropped from 55% pre-implementation to 17% post-implementation. The number of preventable adverse drug events also decreased post-implementation if one looked at just the conventional before/after design. However, there had been a significant downward trend prior to the CPOE/CDSS implementation. When the time series analysis was applied, that difference was no longer significant. That is, the number of preventable adverse drug events (those with harm) was not reduced after CPOE/CDSS.

Then this past week two other studies were released that conclude the cost savings from healthcare IT is negligible. One new study from researchers at the Harvard School of Public Health showed marginal differences in quality (as measured by CMS core measures) and costs (as measured by LOS) among hospitals with full-featured electronic medical records (EMR’s), partial EMR’s, and no EMR’s. The second study (Himmelstein 2009) looked at over 4000 hospitals and concluded that computerization was associated with modest improvement in process measures of quality but not with administrative or overall costs. Both studies, of course, cast doubt on the savings to the healthcare system projected to occur over the next decade.

So where does that leave us? Should we abandon our endeavors to use healthcare IT to improve quality and control costs? Of course not. However, we readily agree that we have yet to demonstrate that the theoretical benefits of healthcare IT actually translate into “hard” benefits, either in patient outcomes or efficiencies and costs. So what is wrong with the above studies? First of all, they probably looked at the wrong things. All hospitals have been working on improving the CMS core measures whether they were computerized or not. And the CMS core measures are primarily process measures, not true patient outcome measures. Similarly, all hospitals have worked hard to reduce LOS (length of stay) independently of their efforts to computerize. So it is no surprise that there should be little difference between the groups on these measures. The Himmelstein data on overall cost and administrative cost are more convincing. They offer 3 potential explanations for the lack of an impact of computerization on cost: (1) that the cost of computerization cancels out any efficiency savings or (2) the cost savings may come n the future or (3) that computerization actually has resulted in hospitals being able to increase their billings. Actually, there is probably a bit of truth in all three of those explanations.

What about the findings in the van Doormaal study? It may be that the degree of sophistication of the clinical decision support systems may have been inadequate to substantially reduce the number of medication errors leading to harm. The alerts generated were primarily related to dosing ranges, allergies, and some drug-drug interactions. They apparently did not include more complex clinical decision supports such as help with dosing based on renal function.

There are two common approaches to CPOE. One is to focus on reminding people to do those common evidence-based things you might forget to do (eg. DVT prophylaxis, remove or avoid altogether a Foley catheter, use beta blockers in post-MI patients, etc.). This is the approach many hospitals take when they first implement CPOE, alert systems, and standardized order sets. But there are other less hi-tech ways to do those things (patient safety rounds, clinical pharmacists rounding with clinical teams, paper order sets, etc.). The other approach is to focus on those things that go beyond the typical “computing” capability of the human brain. We know very few nephrologists, let alone non-nephrologists, who can appropriately dose medications just by looking at the GFR. On the other hand, computers are quite good at this. Similarly, most experienced clinicians are used to managing heparin and coumadin but if they have to use a less familiar anticoagulant drug like argotroban in a patient with heparin-induced thrombocytopenia they make errors. So developing computerized tools to help deal with these unfamiliar scenarios may be productive.

Perhaps lost in these papers is the fact that the biggest savings for our healthcare system in hospitals costs is actually in preventing hospitalization in the first place. The greatest potential, therefore, may be on the outpatient side, where computerization lags far behind the inpatient side. But we have also been unable to clearly demonstrate that those hypothetical savings from computerization in ambulatory care will actually translate to hard savings.

But the onus is still on us to show that computerization improves not just error rates but that it actually prevents those errors from reaching the patient and causing harm. Bedside medication verification (barcoding systems), a technology we love because it significantly reduces medication errors, still will not prevent a nurse from administering an inappropriate dose to a patient if that incorrect dose were originally ordered by a physician in error. So we desperately need to show that computerization actually prevents patient harm. In every other aspect of medicine today we demand evidence-based care so we should be no less demanding when it comes to IT as an intervention.

We still strongly believe that computerization will play a key role in both patient safety and improving the inefficiencies in our healthcare system. But make sure you don’t spend all our time and money developing a complex computerized solution where the classic paper checklist will produced the desired outcome.

References:

Reckmann MH, Westbrook JI, Koh Y, Lo C, Day RO. Does Computerized Provider Order Entry Reduce Prescribing Errors for Hospital Inpatients? A Systematic Review.
 J Am Med Inform Assoc 2009; 16: 613-623

http://www.jamia.org/cgi/content/abstract/16/5/613

van Doormaal JE, van den Bemt PMLA, Zaal RJ, et al. The Influence that Electronic Prescribing Has on Medication Errors and Preventable Adverse Drug Events: an Interrupted Time-series Study. J Am Med Inform Assoc 2009; 16: 816-825

http://www.jamia.org/cgi/content/abstract/16/6/816

Lohr S. Little Benefit Seen, So Far, in Electronic Patient Records. New York Times November 15, 2009

http://www.nytimes.com/2009/11/16/business/16records.html?_r=1&scp=1&sq=electronic patient records&st=cse

Himmelstein DU, Wright A, Woolhandler S. Hospital Computing and the Costs and Quality of Care: A National Study.

The American Journal of Medicine (2009) xx, xxx

http://www.amjmed.com/webfiles/images/journals/ajm/AJM10662S200.pdf

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December 1, 2009           

Patient Safety Doesn't

End at Discharge

Have you ever heard this response when you are discussing DVT prophylaxis with one of your physicians: “He had those same risk factors for DVT before he came into the hospital and we didn’t have him on DVT prophylaxis at home.”? That physician, of course, has a very valid argument.

Admittedly, hospitalization has additional risk factors (eg. relative immobility, factors related to acute infection, etc.) that further increase the risk for DVT.  But many of those patients had been relatively immobile at home. And when we discharge many of those patients, we know they will continue to be relatively immobile at home and their other risk factors for DVT will persist as well. The problem is nobody knows how long we should continue DVT pharmacoprophlaxis and whether it impacts clinically important patient outcomes (like mortality, rehospitalization, etc.). With few exceptions, the evidence base is simply lacking. There have been studies on the continued DVT risk after certain orthopedic injuries or procedures and those have resulted in some guidelines for duration of prophylaxis after discharge for those procedures.

Now, oncologists are beginning to ask the same question. A recent consensus statement (Khorana et al 2009) from multiple oncology organizations on the use of DVT prophylaxis in cancer patients was published in the Journal of Clinical Oncology. While it notes that prophylaxis in ambulatory cancer patients is not currently recommended (with certain specific exceptions such as patients receiving thalidomide or lenalidomide therapy), it issues a call to action encouraging research to determine the role of prophylaxis in ambulatory patients and to study its impact on mortality. However, they also noted that the prophylaxis recommendations for ambulatory patients may change with use of the thrombosis risk assessment tool developed at the University of Rochester School of Medicine and Dentistry (Khorana et al 2008).

That tool was derived from a large database of cancer patients undergoing chemotherapy and then validated on an independent group of cancer patients. It utilized the primary site of cancer, platelet count, leukocyte count, hemoglobin level, use of erythropoiesis-stimulatingagents, and body mass index as predictive factors. Patients whom they were able to classify as being in the highest risk group had almost a 7% risk of symptomatic thrombotic events. Most of those thrombotic events occurred during the first 1-2 cycles of chemotherapy. They have suggested use of this tool in selecting patients in studies looking at ambulatory prophylaxis. Obviously, such studies will need to weigh the risks as well as benefits and consider other key questions such as impact on ultimate survival and cost. We fully expect that in the next year or so we will see emerging guidelines on identification of patient populations for whom ambulatory prophylaxis will be recommended.

But let’s extend the same basic question to some other patient safety interventions we do on inpatients and ask “why don’t we continue these after discharge?”. Think of all the interventions you currently do on inpatients. You do assessments and interventions for fall risk, decubitus risk, delirium risk, hypercapnia risk, high-alert medications, and probably several other conditions.

Let’s consider fall risk. Falls, by the way, used to be one of the commonest causes for readmissions after hospitalizations (Mahoney et al 1994). We don’t have any current statistics on that but would not be surprised if they still rank high on the list. Pretty much every hospital has a program for fall risk assessment and then uses interventions based upon the results of that assessment. Some of those interventions are generic ones applied to patients who score at high risk levels (see our comments in our August 4 2009 Patient Safety Tip of the Week “Faulty Fall Risk Assessments?”). Others are more targeted interventions to address the specific risk items for the individual patient.

Since many in-hospital falls occur during toileting activities, one of the key things you likely do is attend to the toileting needs of the fall-prone patient. You probably make sure he/she uses the toilet shortly before he goes to sleep each night and probably try to time doses of any diuretics so they are less likely to cause nocturia. But how many of you really go over those same interventions carefully with the patient and their family/caregiver at the time of discharge. We find that such important interventions are easily overlooked once the patient returns home.

Similarly, medications are usually one of the prime contributing factors to falls. Drugs in the following classes have been linked to increased risk of falls, particularly in the elderly: sedative/hypnotics, antidepressants (particularly tricyclics), benzodiazepines (particularly long-acting ones), anticonvulsants, antipsychotics/neuroleptics, and drugs that cause orthostatic hypotension. Many of these drugs are on Beer’s list (see our January 15, 2008 Patient Safety Tip of the Week  “Managing Dangerous Medications in the Elderly ” and June 2008 What’s New in the Patient Safety World “Potentially Inappropriate Medication Use in Elderly Hospitalized Patients”) and should generally be avoided in the elderly.

Discontinuation of these drugs makes sense, though there really are no randomized controlled trials out there documenting that this strategy successfully reduces falls (Ferreri et al 2008). Nevertheless, we often discontinue drugs in these categories while the patient is an inpatient. However, we often fail to convey to the patients’ other physicians the reasons we discontinued them, only to see the drugs restarted once the patient has been discharged. Ironically, a hospital admission offers the ideal opportunity to get patients off these drugs that may increase their fall risk. Firstly, some may need to be tapered while the patient is under observation, because withdrawal syndromes may be seen. More important is a phenomenon we have often mentioned in the past. Physicians, when informed that their patient is on one of the Beer’s List drugs, will almost never discontinue those drugs. They may reduce their new prescriptions for those drugs in other patients but they almost never go back and take patients off the drugs they are already taking. So our ability to discontinue these drugs while the patient is hospitalized often gets the patient back to a state where the outside physicians do not have to take a patient off the drugs. So again, discharge ought to be the ideal opportunity to discuss the reasons for drug discontinuation not only with the patient, but also with the family/caregiver and the primary care physician (or other physicians rendering ambulatory care). But how many of you really take the time to do that?

At any rate, if you considered the patient to be at high risk for falls while hospitalized, you can bet that he/she remains at high risk after discharge. In fact, recent hospitalization is often listed as a risk factor for falls in the community-dwellling elderly. Addressing that risk is an important part of the discharge process.

So our basic premise is simple: if you do a patient safety risk assessment and intervention on the inpatient side, you must ask yourself if you (or someone else) should also be doing it after discharge. Patient safety doesn’t end at discharge.

References:

Khorana AA, Streiff MB, Farge D, et al. Venous Thromboembolism Prophylaxis and Treatment in Cancer: A Consensus Statement of Major Guidelines Panels and Call to Action. Journal of Clinical Oncology 2009; 27: 4919-4926

http://jco.ascopubs.org/cgi/content/abstract/27/29/4919

Khorana AA, Kuderer NM, Culakova E, Lyman GH, Francis CW. Development and validation of a predictive model for chemotherapy-associated thrombosis. Blood 2008; 111: 4902 – 4907

http://bloodjournal.hematologylibrary.org/cgi/reprint/111/10/4902?maxtoshow=&HITS=10&hits=10&RESULTFORMAT=&fulltext=khorana&searchid=1&FIRSTINDEX=0&sortspec=relevance&resourcetype=HWCIT

Mahoney J, Sager M, Dunham NC, Johnson J: Risk of falls after hospital discharge.

J Am Geriatr Soc 1994, 42(3):269-274

http://www.ncbi.nlm.nih.gov/pubmed/8120311?dopt=AbstractPlus&holding=f1000,f1000m,isrctn

Ferreri S, Roth MT, Casteel C, Demby KB, Blalock SJ. Methodology of an Ongoing, Randomized Controlled Trial to Prevent Falls Through Enhanced Pharmaceutical Care. Am J Geriatr Pharmacother 2008; 6: 61-81

http://ajgeripharmacother.com/articles/061_fer.pdf

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December 8, 2009           

Prescribing Errors

The EQUIP study done in the UK provides some interesting insights into prescribing errors. Though originally established to look at prescribing errors made by first year residents, the study demonstrated that prescribing errors were both common and made by physicians at all levels. Looking at over 100,000 medication orders across 20 hospital sites, they found an average error rate of 8.9 errors per 100 medication orders. The error rate for first year residents, responsible for about half the orders, was 8.4% - actually lower than that for the entire group. All physician levels, including attendings, made prescribing errors. The highest rate (10.3%) was actually seen for second year residents. Interestingly, nurses and pharmacists who were allowed to order medications, had much lower error rates.

Potentially serious errors occurred in about 5% of cases and potentially lethal errors in about 2%. The good news, however, is that almost all errors were caught by pharmacists before they could affect patients. Errors were made most often at the time of admission. In fact, orders at admission were 70% more likely to contain an error. Analgesics, antibacterials, bronchodilators, antianginals and corticosteroids were the classes of medication most frequently involved.

Of the error types, the commonest was omission of a drug on admission, accounting for almost 30% of the errors. Wrong dose or missing dose accounted for almost another 30% of the errors. Other errors involved times, routes of administration, formulations, duplications, clinical contraindications, and a variety of others.

Medications that were order via electronic order entry were 12% less likely to contain errors than those in handwriting.

They also performed a systematic review of the literature. In that review, overall error rate was slightly lower (median 7%) but occurred in over 50% of hospital admissions and, again, most errors were intercepted before harm came to patients. Errors were commonest with antimicrobials and were more common in adults than children. The most common type of error was incorrect dosage.

The most important part of the study, however, was to capture insight into factors contributing to prescribing errors. They did both a systematic review of the literature and interviewed residents and medical school curriculum directors to get further insight.

In the interviews with residents, one of the most striking features was that residents often did not remember making errors (though they did suspect they made more errors than they knew about), nor did they seem overly anxious about them. Interviewees often distinguished between “silly” errors and more serious ones. An example of a “silly” error might be ordering a medication at the wrong time of the day.

They grouped errors according to Reason’s model of accident causation (active failures, error-provoking conditions, and latent conditions). Active failures were identified and classified as either knowledge-based errors, rule-based errors or skill-based memory lapses and slips. Of 85 errors analyzed, 18 were mainly due to a knowledge-based mistake, 34 to a rule-based mistake, and 23 were mainly due to slips or lapses and three were direct violations. Seven others were related to receipt of incorrect information and therefore were not the active failure of the respondent but of another individual. They provide a nice diagram and verbatim comments from the respondents illustrating how slips interacted with contributing factors such as workload or time pressures to result in errors. They provide a similar diagram and verbatim comments for skill-based memory errors. Examples such as forgetting the dates or times for medications often elicited comments about inadequate design of the prescription “chart” or the electronic order entry screens. Both slips and memory lapses were types of errors often captured by the “safety net” (nurses and pharmacists) and seldom resulted in patient harm.

A similar diagram is used to illustrate 34 rules-based mistakes. Here, lack of expertise comes into play. That is often lack of expertise in framing the clinical situation and, as a result, applying the wrong rules. One issue raised here and elsewhere is that the residents felt so comfortable with the “safety net” that they expected a nurse or pharmacist would identify any errors.

The same process was applied for knowledge-based mistakes and for communication errors. Often in knowledge-based incidents residents did not seek out help (due to a variety of factors such as workload, time pressures, fear that others would look upon the lack of knowledge as a weakness, etc.). Some of the comments, however, showed that they felt better once they realized it was okay to have to look something up. Especially seeing one of their more senior physicians look up a dose was reinforcing in that respect. Regarding communication errors, the most salient finding may be showing how easily some errors may get perpetuated throughout the healthcare system.

The section on violations is excellent. Examples are given where computer-generated alerts are willfully ignored or where intentional violations are done just to “get the job done”.

They did find some overarching themes in prescribing errors:

• Busyness/rushing
• Time pressures
• Lack of support from senior colleagues
• Working on-call
• Being asked to do multiple things at the same time
• Influence of nurses
• Different standards or expectations on different units
• Following orders of a more senior colleague unquestioningly
• Poor design of the drug charts
• Poor design of the electronic order entry system
• Overreliance on the safety net (i.e. that someone else would notice and correct the error)

A section with extensive comments about prior educational experiences of residents is included, as well as those about transitioning from medical school to the first year of residency. Perhaps the most significant comments relate to the difference between pharmacology and prescribing. The former is well taught in medical schools, the latter poorly covered. Thus, there is a big gap between the theoretical and the practical. During the first year of residency, training in prescribing was appreciated but most wanted more. Lack of feedback about prescribing errors was also noted as a system problem.

They also performed a systematic review of those studies which reported causative or contributing factors for medication prescribing errors and grouped them according to Reason’s model of accident causation (active failures, error-provoking conditions, and latent conditions). The most common active failure was a mistake due to inadequate knowledge of the drug or the patient but skills-based slips and memory lapses were also common. Error-provoking conditions included lack of training or experience, fatigue, stress, high workload, inadequate communication, etc. Latent conditions included reluctance to question senior colleagues and inadequate provision of training.

Just as we typically see when we do root cause analyses of adverse events, prescribing errors are often multifactorial, with several active failures and error-provoking conditions often acting together (the error cascade) to result in the ultimate outcome. Because of that, the authors caution that solutions addressing a single cause are likely to have only limited benefit and that multifactorial interventions will likely be necessary. In particular, the authors suggest that education, in the traditional sense, is not likely to significantly impact prescribing errors. If education is to play a significant role, it would have to be more along the lines of “just in time” education.

Amongst their recommendations are:

• Standardization of the drug “chart”
• More use of electronic prescribing (but watch for unintended consequences)
• Making information and references more readily available
• Ensuring more senior staff understand their roles as supervisors and role models
• Optimize working conditions
• Add more practical experiences to the medical school curriculum
• More and better “just-in-time” training on prescribing
• More senior members should also get prescribing training
• More teamwork training and team-based education
• More effective feedback
• Encourage help-seeking activities

This document is 215 pages long but it is fairly easy reading. It is also an excellent introduction to the Reason model of accident causation for those who need some introduction into the science of “human factors”. It also has some excellent diagrams that illustrate both the complexities and interactions of numerous contributory factors. And it has a great bibliography and review of the literature on prescribing errors. Read it – you’ll see that all the contributing factors in play are also in play at your facility whether you are a teaching hospital or not.

Reference:

Dornan T, Ashcroft D, Heathfield H et al. An in depth investigation into causes of prescribing errors by foundation trainees in relation to their medical education. EQUIP study. December 2009

http://www.gmc-uk.org/FINAL_report__the_prevalence_and_incidence_of_prescribing_errors.pdf_snapshot.pdf

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December 15, 2009           

The Weekend Effect

We have discussed in several columns the increased incidence of adverse events and poor outcomes in the hospital at night and on weekends (see our February 26, 2008 Patient Safety Tip of the Week “Nightmares….The Hospital at Night” and our What’s New in the Patient Safety World columns for October 2008 “Hospital at Night Project” and September 2009 “After-Hours Surgery – Is There a Downside?”).

We discussed the presentation “The Hospital at Night Program: Reducing Risks at Our Most Vulnerable Time of the Day” by David Gozzard and Carol Haraden given at an IHI annual meeting. This described a redesign of hospital structure and processes in anticipation of a significant limitation of work hours imposed by the European Union (the European Working Time Directive). They collected data on the tasks performed off-hours and found that many tasks performed by doctors at night could be redistributed to nonmedical staff and that many tasks could be performed during daytime hours. For instance, leaving space in the OR schedule for emergencies reduced delays in regularly scheduled cases and reduced the likelihood of doing overflow cases at night. They also focused on communication and handoffs and made greater use of SBAR and written reports that were discussed verbally. And they made better use of the MEWS (Modified Early Warning System) to identify patients at risk of deterioration. Preliminary, largely anecdotal, experiences with the program were positive. However, the first report of outcomes of this project, available at the Hospital at Night project website, showed outcomes to have been modest.

In the September 2009 “After-Hours Surgery – Is There a Downside?” we noted that some surgical outcomes are worse or more adverse events may be seen when cases are done “after-hours”. We pointed out that the operating team after-hours is likely different from your daytime team. All members of that team (physicians, nurses, anesthesiologists, techs, etc.) may not have the same level of expertise as your regular daytime team and the team dynamics between members is likely to be different. The post-surgery recovery unit is likely to be staffed much differently after-hours as well. The staff may be more likely to be unfamiliar with things like location of equipment. And some of the other hospital support services (eg. radiology) may have lesser staffing after-hours. Just as importantly, many or all of the “on-call” staff that make up the after-hours surgical team have likely worked a full daytime shift that day so fatigue enters as a potential contributory factor.

Interestingly, our focus in the above columns was always on the professional staff. But some recent research has given us an “aha!” moment. Nursing researcher Patti Hamilton recently talked about her research at INQRI’s annual meeting and pointed out what should have been obvious to us: there are fewer non-nursing staff on the weekends. That means fewer support staff to answer phones, handle administrative tasks, or retrieve necessary medical supplies. So who ends up doing these tasks? Yes – nurses! And all those extra tasks and responsibilities take them away from direct patient care.

Hamilton noted “What we’re finding is that many, many small troubles pile up during off-peak shifts. There is rarely one big crisis situation. It’s usually an accumulation of little barriers that keep nurses from doing their jobs as effectively as during peak times.”.  Sometimes the nurses end up doing tasks such as transporting patients or even mopping floors. There is also less dietary and nutrition support, pharmacy and imaging services, physical therapy, patient teaching, and social services. She also points out that they may spend more time on the phone trying to track down doctors on weekends. So nurses end up doing many more tasks that they do not normally perform during regular “day” hours and they do not have as much time to do patient care and bedside nursing.

The net result is that reported nurse staffing ratios may give us a very misleading sense of security at certain times of the day or week. Many studies have demonstrated better patient outcomes and fewer adverse events when nurse:patient ratios are more favorable. But it is clear from the above that the same nurse:patient ratio is really very different at night and on weekends than on the day shift.

And what do we usually do in the C-suite when facing a budget crunch? We, of course, all say “We can’t cut clinical staff! Our cuts will have to come from non-clinical staff.” So we cut those non-clinical positions and the tasks they used to perform still have to be done. Only now we are asking our higher-cost clinical personnel to carry out those functions – all at the cost of taking them away from patient care. We often shoot ourselves in the foot when we make these decisions. (As an aside, we also remember a story about a new CEO attempting to do a hospital turnaround. That CEO reduced the housekeeping staff as part of the budget cuts. Infection rates increased, with resulting increased lengths of stay and increased pharmacy costs.)

The moral of the story: every person who works in a hospital provides some function that is vital to patient outcomes – even those people you think of as “non-clinical”. Your non-clinical people can contribute greatly to your quality improvement and patient safety programs. Every time we have done a root cause analysis at a hospital regarding long turnaround times for radiology reports, the person most likely to know the root causes (and consequently the solutions) – the unit secretary! And we use our medical records staff to help us identify practices that put our patients at risk. And our housekeeping staff can help us save lives and dollars (see our November 10, 2009 Patient Safety Tip of the Week “Conserving Resources…But Maintaining Patient Safety”).

It is only when you do the kind of research that Patti Hamilton does – talking to frontline staff and observing people doing tasks at different times of the day – that you get a real feel for how a hospital runs! That’s a great lesson. When you do your Patient Safety Walkrounds or your Executive Walkrounds, make sure you don’t just do them on the day shift. You’ll learn a lot more if you do them at night or on a weekend. And your staff will have a totally different impression of you when they see you out there on a weekend!

Reference:

Robert Wood Johnson Foundation. INQRI Researcher Patti Hamilton Explores Why the "Weekend Effect" is Putting Patients at Risk. Robert Wood Johnson Foundation. Publications and Research. September 30, 2009

http://www.rwjf.org/pr/product.jsp?id=49139

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December 22, 2009           

Falls on Toileting Activities

Almost half of falls in the hospital occur during activities related in some way to toileting (see our January 1, 2008 Patient Safety Tip of the Week “Fall Prevention” and our October 7, 2008 Patient Safety Tip of the Week “Lessons from Falls....from Rehab Medicine”). Despite this fact, surprisingly little research has been done on this phenomenon.

Now a new study (Tzeng 2010) focused on falls related to toileting. Tzeng did a literature review on this topic and an analysis of 547 falls that took place on medical, surgical or mixed medical/surgical units in a community hospital. Toileting activities included not just those that occurred in the bathroom but any in which the intent to toilet was present prior to the fall. 45.2% of the falls in the Tzeng study occurred on activities related to toileting. Only 6% of the falls actually occurred while getting on or off the toilet but most of the falls occurred when attempting to go from bed or chair to the bathroom or returning from the bathroom.

Interestingly, the maximum time period for falls in the Tzeng study was between 11 PM and 3 AM and over 60% of the falls occurred between 7 PM and 7 AM. That is different from the daytime preponderance of falls noted in rehab medicine patients. So you really need to analyze the falls data at your own facility to see what time of day your patients are most likely to fall. A study of falls in a multiple hospital system (Krauss 2007) showed that there are differences in risk factors for both falls and serious injury based on the type of hospital. Another study from the same group (Fischer et al 2005) showed substantial differences in fall rates and rate of fall-related injuries by type of service the patient was on. However, the Tzeng study was from a general community hospital so the times of falling are likely representative of many hospitals. In addition to the staffing issues noted below, the timing of falls has implications for lighting in patient rooms. Tzeng recommends use of night lights or motion-sensor lights in or near patient bathrooms.

But here is the most bothersome finding in the Tzeng study: almost all the falls occurred in patients who had already been classified as high risk for falls and were on fall risk precautions. Tzeng makes a case for better auditing and surveillance of our fall prevention programs. It is simply not good enough to identify patients as being high risk for falls if our interventions are inadequate or, worse yet, ignored. Particularly when nursing is understaffed or otherwise overworked, there is a tendency to skip some of the pre-emptive activities to help avoid patients falling when getting out of bed at night. A previous study (Krauss et al 2008) showed poor staff compliance with toileting schedules, even during a period of a targeted intervention. Given that the period of greatest risk for falls in the Tzeng study was between 11 PM and 3 AM, it is worth remembering the point of last week’s Tip of the Week “The Weekend Effect” in which we noted all the other nonclinical things nurses get stuck doing after-hours. These clearly take away from bedside nursing activities. Perhaps the toileting needs of our patients are better met by aides or staff other than nursing. Perhaps a specially-trained aide or team could work from 10 PM to midnight or 9 PM to 11 PM and just focus on ensuring all patients at high risk for falls get appropriate assistance toileting before they go to sleep. Keep in mind that such attention to toileting is also important in the patient at risk for delirium. Note that we have also mentioned the gender issue on several occasions. Many studies have identified male sex as a risk factor for falls. We don’t know if that is due to macho vs. modesty. If it is the latter, then male patients may be hesitant to ask a female nurse to help them to the bathroom. So consider having some male aides on your “team” to assist male patients with toileting as well.

The Krauss paper (Krauss et al 2008) also had another lesson not unfamiliar to those involved in performance improvement projects: many good projects are not sustainable. In that study, a focused intervention to prevent falls was quite successful over the first 5 months but by 9 months the results were no longer statistically better compared to the control group.

Tzeng stresses something we have frequently noted is sorely lacking: good analysis of after a fall has occurred. The typical medical responder after a patient fall does a good job looking to see if the patient was injured but seldom does a good analysis as to why the patient fell. We recommend you do an on-the-spot fall investigation for every fall. That is the only way you are likely to identify the specific fall risk factors for that patient. We have discussed previously that most of the general fall risk assessment tools simply identify patients as being at risk for falls (and still miss a significant number who will fall) but do not lead to interventions that would address specific risk factors in the individual patient (see our August 4, 2009 Patient Safety Tip of the Week “Faulty Fall Risk Assessments?”).

Though not yet directly related to falls, another interesting paper appeared last week (Kraft et al. 2009) on “lying obliquely”. They found that patients who lie obliquely in bed (i.e. at an angle to the longitudinal axis of the bed rather than aligned straight with that axis) have a substantial likelihood of cognitive impairment. Lying obliquely is really a sign of visuospatial impairment. One might expect that this clinical sign might be a good predictor of falls as well. In fact, this very sign has been described long ago in patients prone to falling (Tobis et al 1981). So don’t be surprised in about 2 years when the “lying oblique” sign pops up on your fall risk assessment!

To summarize the lessons from these papers:

• Toileting activities are a significant risk factor for falls in all hospitals
• Such falls are more likely to occur at night
• Fall-prevention interventions related to toileting activities are poorly complied with
• Consider teams of staff other than nurses to address the toileting interventions
• Audit compliance with all your fall-prevention strategies

References:

Tzeng H-M. Understanding the Prevalence of Inpatient Falls Associated With Toileting in Adult Acute Care Settings. Journal of Nursing Care Quality 2010; 25(1):22-30

http://journals.lww.com/jncqjournal/Abstract/2010/01000/Understanding_the_Prevalence_of_Inpatient_Falls.5.aspx

Krauss MJ, Nguyen SL, Dunagan WC, et al. Circumstances of Patient Falls and Injuries In 9 Hospitals In a Midwestern Healthcare System. Infection Control and Hospital Epidemiology 2007; 28: 544–550

http://www.journals.uchicago.edu/doi/pdf/10.1086/513725

Fischer ID, Krauss MJ, Dunagan WC, et al. Patterns and Predictors of Inpatient Falls and Fall-Related Injuries in a Large Academic Hospital. Infection Control and Hospital Epidemiology 2005; 26: 822–827

http://www.journals.uchicago.edu/doi/pdf/10.1086/502500

Krauss MJ, Tutlam M, Costantinou E, et al. Intervention to Prevent Falls on the Medical Service in a Teaching Hospital. Infection Control and Hospital Epidemiology. Volume 29, Issue 6, Page 539–545, Jun 2008

http://www.journals.uchicago.edu/doi/pdf/10.1086/588222

Kraft P, Gadeholt O, Wieser MJ, Jennings J, Classen J. Lying obliquely—a clinical sign of cognitive impairment: cross sectional observational study. BMJ 2009; 339: b5273 (Published 16 December 2009)

http://www.bmj.com/cgi/content/abstract/339/dec16_3/b5273?maxtoshow=&HITS=10&hits=10&RESULTFORMAT=&fulltext=lying+obliquely&searchid=1&FIRSTINDEX=0&sortspec=date&resourcetype=HWCIT

Tobis JS, Nayak L, Hoehler F. TitleVisual perception of verticality and horizontality among elderly fallers. Archives of Physical Medicine & Rehabilitation 1981. 62(12):619-22
http://www.ncbi.nlm.nih.gov/pubmed/7316723

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December 29, 2009           

Recognizing Deteriorating Patients

“Failure to rescue” is becoming one of the recurrent themes we see in patient safety evaluations in acute care settings (and some more chronic settings, too). We’ve previously done several columns on responses to clinical deterioration and use of rapid response teams (see our What’s New in the Patient Safety World columns for August 2007  “Responding to Patients with Clinical Deterioration”, December 2008 “Rapid Response Teams Don’t Live Up to Expectations”, and April 2009 “Early Emergency Team Calls Reduce Serious Adverse Events” plus our November 27, 2007 Patient Safety Tip of the Week “More on Rapid Response Teams”). The impact of rapid response teams on actual outcomes has shown mixed results.

Whether or not you believe that rapid response teams have a significant impact on patient safety, there is one unmistakable fact: we need to do a better job of recognizing earlier the patient who is deteriorating and initiating appropriate responses. When you do your root cause analyses on serious events, it is not uncommon to identify cases in which earlier recognition and action on a deteriorating patient might have prevented an adverse outcome. Also, those organizations that have done detailed reviews of all patients undergoing cardiopulmonary arrests or patients requiring transfer to ICU’s typically find that more subtle deterioration had preceded the formal event in the majority of cases.

In our April 2009 What’s New in the Patient Safety World column “Early Emergency Team Calls Reduce Serious Adverse Events” we noted that reanalysis of the data from the MERIT study (Medical Emergency Response Intervention and Therapy) found evidence to support the concept of the early emergency call (Chen et al 2009). They found that early calls were associated with reductions in the rate of cardiac arrests and unexpected deaths. For every 10% increase in early calls, there was a 2.2 per 100,000 reduction in cardiac arrests and a 0.94 per 100,000 reduction in unexpected deaths.

The National Patient Safety Agency (UK) had reported in 2007 that 11% of deaths analyzed in one year were the result of deterioration not recognized or acted upon. Some incidents involved cases where no vital sign observations were made for prolonged periods but more frequently vital sign observations were made but the significance of the trends were not appreciated. And in yet others, the significance was recognized but there was a delay in the medical response.

One of the UK’s Patient Safety First campaign’s projects “Reducing Harm from Deterioration” is based on that 2007 report and the 2007 NICE (National Institute for Health and Clinical Excellence) clinical guideline “Acutely ill patients in hospital. Recognition of and response to acute illness in adults in the hospital”.

The intervention used in “Reducing Harm from Deterioration” consists of 6 key elements:

1. Physiological observations should be recorded on all patients
2. These observations should be recorded by staff trained to understand their clinical relevance and act upon them
3. Physiological track and trigger systems should be used
4. You should have a graded response strategy
5. An escalation protocol should be in place
6. A good communication tool should be utilized

Most of you will say “of course we record physiological observations on all our patients”. And you undoubtedly do. However, if you do chart audits you will often find things like respiratory rate missing. Worse yet, when you see 8 straight recordings of respiratory rate as “20” you can probably guess that there has not been accurate recording of the respiratory rate!

One of the problems we are seeing now is an unintended consequence of computerization. In the past, when nurses recorded vital signs they did so on a flow chart where trends were readily discernible. Today, they are often entering those vital signs into an isolated computer screen and the flow chart may not be readily visible. Say, for instance, that the respiratory rate is 24. In isolation, that respiratory rate might not raise concern. But if you saw a trend where the respiratory rate began at 16 and increased by 2 breaths per minute each hour, then the rate of 24 should definitely raise concerns. Today’s hospital electronic medical records often do not mimic the old vital sign graphic chart. Yes, you may be able to get to some sort of representation of vital signs that allows trends to be seen but that often takes several clicks to get to and it’s often not even a graphic representation. More importantly, it is often lacking when the nurse is at the patient’s bedside. Result: an opportunity to detect patient deterioration early is missed. Therefore, it is critical that you build into your EMR the capability of displaying the vital sign trends while new data are being input. Alternatively (or in addition) you may develop computer algorhithms that are designed to detect such trends and alert accountable individuals.

Making sure that the physiological observations are recorded by staff trained to understand and act upon them is not as easy as it sounds. Many facilities today have vital signs recorded by someone other than RN’s (or they may even be recorded mechanically). In such cases, it is crucial that a nurse be available to promptly review those results.

There are a variety of track and trigger tools but the best known is probably MEWS (modified early warning score). That is a system that utilizes physiological parameters to calculate a “score” that helps identify patients with subtle signs of deterioration. But you need to keep in mind that MEWS was developed as a general tool and may not be applicable to an individual patient. For example, you may need to take into account that one of the individual patient’s baseline parameters is not “normal”. If a patient’s baseline blood pressure is 160/100, a new blood pressure measurement of 140/80 could be an easily missed sign of early deterioration.

Some facilities color code the MEWS scores. For instance, they may use green to indicate that the score is in the “normal” range, yellow for scores moving outside the normal range, and red for scores clearly in the abnormal range. Some facilities even use these colors (or some other sort of alert icon) on the computerized status boards or on whiteboards in the nursing stations.

There is an excellent article on MEWS in this month’s Joint Commission Journal on Quality and Patient Safety (Maupin et al 2009). The Mercy Hospital system in Cincinnati had noted failure to rescue as a common theme in many of their root cause analyses. They then did a chart review on a year’s worth of Code Blues and found that in 60% of the cases application of MEWS could have led to earlier recognition of patient deterioration (by an average of 6.6 hours prior to the code). The article goes on to describe how they went about piloting and implementing MEWS in their system and the dramatic improvements they achieved (substantial reduction in number of Code Blues and increase in the number of calls to the rapid response teams). Implementing the MEWS, which was facilitated by their IT system, required very little additional time on the part of nurses. Their project was so successful that they are now implementing “outbound” MEWS, i.e. applying MEWS to patients as they leave the ER for an admission to the floor or as they leave ICU! Definitely a good read. Also nice description of the MEWS tool and good quality improvement project management.

The previously mentioned NICE guideline also discusses several scoring systems for identification of patients clinically deteriorating, including the MET (single parameter), MEWS (aggregate scoring system) and ASSIST (assessment score for sick patient identification and step-up in treatment – aggregate scoring system) systems.

Note also that your tracking and trigger tool may be customized for different areas of care. For instance, you might have different versions for obstetrical patients, pediatric patients, and adult medical/surgical patients.

The graded response strategy and escalation protocol typically consists of differing responses based upon the scoring of whatever track and trigger system you are using. For example, for those cases that hit your threshold for a response, the early response may simply be increasing the frequency of observation and notifying the charge nurse. The next level threshold might involve urgently notifying the medical team with primary responsibility for the patient. And the highest threshold would trigger a call to your rapid response team.

A good communication tool should be used to escalate concern between team members. Most such tools utilize the SBAR format but alternatives exist (eg. RSVP: Reason-Story-Vital Signs-Plan). The “How to Guide’ for Reducing Harm from Deterioration provides nice examples of both SBAR and RSVP format tools and a sample audit tool for evaluating your use of an SBAR tool.

The Patient Safety First campaign website contains multiple resources for addressing the issue of early recognition and intervention for clinical deterioration. In addition to the “How to Guide” for Reducing Harm from Deterioration there are several clinical case studies from UK hospitals that have implemented successful systems. One of the most interesting lessons from the case studies was that one hospital went back to the bedside sphygmomanometer for taking blood pressures manually (rather than using more automated systems for blood pressure recording). They found that this required face-to-face contact with the patient, facilitating use of other cues to more rapidly identify signs of deterioration. The “How to Guide’ for Reducing Harm from Deterioration also discusses measurements to determine the impact of your programs.

References:

Chen J, Bellomo R, Flabouris A, Hillman K, Finfer S; MERIT Study Investigators for the Simpson Centre; ANZICS Clinical Trials Group. The relationship between early emergency team calls and serious adverse events. Crit Care Med. 2009 Jan;37(1):148-53

http://www.ncbi.nlm.nih.gov/pubmed/19050625?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum

National Patient Safety Agency (UK). Safer care for the acutely ill patient: learning from serious incidents. 2007

http://www.nrls.npsa.nhs.uk/EasySiteWeb/getresource.axd?AssetID=60141&type=full&servicetype=Attachment

NICE (National Institute for Health and Clinical Excellence). Acutely ill patients in hospital. Recognition of and response to acute illness in adults in hospital. July 2007

http://www.nice.org.uk/guidance/CG50

Patient Safety First (UK). Interventions. Deterioration.

http://www.patientsafetyfirst.nhs.uk/Content.aspx?path=/interventions/Deterioration/

Patient Safety First (UK). The “How To Guide” For Reducing Harm From Deterioration.

http://www.patientsafetyfirst.nhs.uk/ashx/Asset.ashx?path=/How-to-guides-2008-09-19/Deterioration 1.1_17Sept08.pdf

Maupin JM, Roth DJ. Krapes JM. Use of the Modified Early Warning Score Decreases Code Blue Events. Joint Commission Journal on Quality and Patient Safety 2009; 35(12): 598-603

http://www.ingentaconnect.com/content/jcaho/jcjqs/2009/00000035/00000012/art00006

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