What’s New in the Patient Safety World

January 2013

 

 

·        Silver-Coated Urinary Catheters Don’t Reduce CAUTI’s

·        Bed Alarms Fail the Test

·        How Frequent are Surgical Never Events?

·        More IT Unintended Consequences

·        More on the Downside of Contact Isolation

 

 

 

 

Silver-Coated Urinary Catheters Don’t Reduce CAUTI’s

 

 

For many years antibiotic-coated or silver-coated catheters have been touted as potentially reducing CAUTI’s. Such recommendations were based mostly on studies in relatively small populations or studies using methodologies other than randomized controlled trials (eg. Liedberg 1990). Saint et al. in a meta-analysis noted discrepant results among trials of silver-coated urinary catheters and noted that silver alloy catheters are significantly more effective in preventing urinary tract infections than are silver oxide catheters (Saint 1998).  Karchmer et al. (Karchmer 2000) found that the risk of infection declined by 32% among patients in whom silver-coated catheters were used on the wards and that use of the more expensive silver-coated catheter appeared to offer cost savings by preventing excess hospital costs from nosocomial UTI associated with catheter use. Rupp et al. found that a silver alloy, hydrogel-coated urinary catheter was associated with a significant decline in nosocomial UTI and cost savings over the range of cost estimates (Rupp 2004).

 

But despite those studies, there has remained considerable controversy and doubt as to whether silver-coated (or antimicrobial-coated) catheters reduce CAUTI rates. In our March 2010 What’s New in the Patient Safety World column “IDSA CAUTI Guidelines” we discussed the Infectious Diseases Society of America guidelines on CAUTI’s “Diagnosis, Prevention, and Treatment of Catheter-Associated Urinary Tract Infection in Adults: 2009 International Clinical Practice Guidelines from the Infectious Diseases Society of America” (Hooton 2010). The guidelines were developed in collaboration with multiple other specialty societies. In those guidelines they concluded that evidence was insufficient to make a recommendation as to whether silver-coated or antibiotic-coated urinary catheters were effective in reducing catheter-related bacteruria or CAUTI’s.

 

Now a new large randomized controlled trial hopefully puts the issue to rest (Pickard 2012). Patients requiring short-term urinary catheterization were randomly allocated 1:1:1 to receive a silver alloy-coated catheter, a nitrofural-impregnated catheter, or a PTFE-coated catheter (control group).  Compared with 271 (12·6%) of 2144 participants in the control group, 263 (12·5%) of 2097 participants allocated a silver alloy catheter developed a symptomatic CAUTI by 6 weeks, as did 228 (10·6%) of 2153 participants allocated a nitrofural catheter. They concluded that silver alloy-coated catheters were not effective for reduction of incidence of symptomatic CAUTI and that the reduction in CAUTI associated with nitrofural-impregnated catheters was less than that regarded as clinically important. Routine use of antimicrobial-impregnated catheters is not supported by this trial.

 

 

 

Our other columns on urinary catheter-associated UTI’s:

 

 

 

 

 

References:

 

 

Liedberg H, Lundeberg T. Silver Alloy Coated Catheters Reduce Catheter-associated Bacteriuria. British Journal of Urology 1990; 65(4): 379–381

http://onlinelibrary.wiley.com/doi/10.1111/j.1464-410X.1990.tb14760.x/abstract

 

 

Saint S, Elmore JG, Sullivan SD, Emerson SS, Koepsell TD. The efficacy of silver alloy-coated urinary catheters in preventing urinary tract infection: a meta-analysis. Am J Med 1998; 105(3): 236-41

http://www.amjmed.com/article/S0002-9343%2898%2900240-X/abstract

 

 

Karchmer TB, Giannetta ET, Muto CA, et al. A Randomized Crossover Study of Silver-Coated Urinary Catheters in Hospitalized Patients. Arch Intern Med. 2000; 160(21): 3294-3298

http://archinte.jamanetwork.com/article.aspx?articleid=485555

(Karchmer 2000)

 

 

Rupp ME, Fitzgerald T, Marion N, et al. Effect of silver-coated urinary catheters: efficacy, cost-effectiveness, and antimicrobial resistance. American Journal of Infection Control 2004; 32(8): 445-450

http://europepmc.org/abstract/MED/15573050/reload=0;jsessionid=iw2CF0dN1E2U8qDb2wdU.12

 

 

Hooton TM, Bradley SF, Cardenas DD, et al. Diagnosis, Prevention, and Treatment of Catheter-Associated Urinary Tract Infection in Adults: 2009 International Clinical Practice Guidelines from the Infectious Diseases Society of America. Clinical Infectious Diseases 2010; 50: 625-663

http://www.journals.uchicago.edu/doi/pdf/10.1086/650482

 

 

Pickard R, Lam T, MacLennan G, et al. Antimicrobial catheters for reduction of symptomatic urinary tract infection in adults requiring short-term catheterisation in hospital: a multicentre randomised controlled trial. Lancet 2012; 380(9857): 1927-1935

http://www.thelancet.com/journals/lancet/article/PIIS0140-6736%2812%2961380-4/abstract#

 

 

 

 

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Bed Alarms Fail the Test

 

 

Many hospitals have invested in bed alarm system to help reduce patient falls. The theory behind them is simple: a sensor responds to the weight of the patient in the bed. If the patient attempts to get out of the bed, the sensor detects the reduction in weight/pressure and alarms in the nursing station. But, much to our surprise, such bed alarm systems had never been studied using well-designed scientific methodology to determine whether they truly reduced falls or injuries.

 

Now a study has demonstrated that an intervention designed to increase bed alarm use in an urban community hospital increased alarm use but had no statistically or clinically significant effect on fall rates, fall-related events or physical restraint use (Shorr 2012). Using a cluster randomized methodology the “intervention” nursing units received education, training and technical support on use of the bed alarm system. The “control” units did have bed alarms but received no training or support on their use. The study population included over 27,000 inpatients in general medical, surgical, and specialty units. Prevalence of alarm use was 64.41 days per 1000 patient-days on intervention units and 1.79 days per 1000 patient-days on control units. But there was no difference in change in fall rates per 1000 patient-days or in the number of patients who fell, injurious fall rates, or the number of patients physically restrained on intervention units compared with control units.

 

Our only prior column that mentioned bed alarms (June 19, 2007 Patient Safety Tip of the Week “Unintended Consequences of Technological Solutions”) noted a case when a hospital purchased a new alarm system that would send an alarm when the patient got out of bed. It turned out that on some units there were not enough electrical outlets for both the new bed alarms and the nurse call buttons. So a decision was made in some cases to swap out these two devices. You can guess what happened: nursing staff responded to the “out-of-bed” alarm only to find the patient lying on the floor with an injury because he tried to get out of bed after no one responded when he pushed the nurse call button!

 

Like so many other things in medicine, what sounds good often turns out not to be so good. Unfortunately, because we often adopt interventions without appropriate scrutiny we end up spending much time, money and other resources without reaping the expected benefits.

 

 

 

References:

 

 

Shorr RI, Chandler AM, Mion LC, et al. Effects of an Intervention to Increase Bed Alarm Use to Prevent Falls in Hospitalized Patients: A Cluster Randomized Trial. Ann Intern Med 2012; 157(10): 692-699

http://annals.org/article.aspx?articleid=1392191

 

 

 

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How Frequent are Surgical Never Events?

 

 

Surgical “never events” continue to occur despite a variety of patient safety interventions designed to prevent them. These include retained surgical items (RSI’s) and a variety of events we classify under the term “wrong site surgery”.

 

This month we learned from researchers at Johns Hopkins that over 4000 surgical never events occur annually in the US (Mehtsun 2012). The researchers reviewed malpractice claims and settlements reported in the National Practitioner Data Bank (NPDB) and identified cases of retained foreign bodies, wrong-site, wrong-patient, and wrong-procedure surgery. They identified a total of 9,744 paid malpractice settlements and judgments for surgical never events occurring between 1990 and 2010. But these only identify those cases in which there was actually a paid malpractice settlement or award so these are likely an underestimate of the actual occurrence of such surgical never events. Based on literature rates of surgical adverse events resulting in paid malpractice claims, they estimated that 4,082 surgical never event claims occur each year in the United States.

 

Importantly, the authors identified some of the demographic variables in such cases. They found that 12.4% of physicians named in a surgical never event claim were later named in at least 1 future surgical never event claim. Also 62% of the physicians were named in other malpractice claims. Surgeons in the 50-59 age bracket were more likely to be named in multiple claims than surgeons less than 40 years old. Surgeons in the age 40-49 age bracket accounted for about a third of the events overall.

 

In terms of patient outcomes death occurred in 6.6% of patients, permanent injury in 32.9%, and temporary injury in 59.2%. The patient age group most often affected was the 40-49 years old group.

 

It’s pretty clear we still have a long way to go to reduce the occurrence of these surgical never events. The November 2012 issue of the Pennsylvania Patient Safety Advisory has two good articles identifying barriers to implementation of the Pennsylvania Patient Safety Authority’s proposed recommendations to prevent wrong-site surgery (Clarke 2012a, Clarke 2012b). We’ve discussed retained surgical items in the past (see our June 12, 2012 Patient Safety Tip of the Week “Lessons Learned from the CDPH: Retained Foreign Bodies” and November 2012 What’s New in the Patient Safety World column “More on Retained Surgical Items”) and we will have another discussion upcoming soon.

 

 

 

References:

 

 

Mehtsun WT, Ibrahim AM, Diener-West M, Pronovost PJ, Makary MA. Surgical never events in the United States. Surgery 2012; published online ahead of print 18 December 2012

http://www.surgjournal.com/article/S0039-6060%2812%2900623-X/abstract

 

 

Clarke J. What Keeps Facilities from Implementing Best Practices to Prevent Wrong-Site Surgeries? Barriers and Strategies for Overcoming Them. Pa Patient Saf Advis 2012; 9(Suppl 1): 1-15

http://patientsafetyauthority.org/ADVISORIES/AdvisoryLibrary/2012/nov20_9%28suppl%201%29/Pages/01.aspx

 

 

Clarke J. Comments from Pennsylvania Medical Professional Societies on the Pennsylvania Patient Safety Authority’s Potential Recommendations to Prevent Wrong-Site Surgery and the Authority’s Responses. Pa Patient Saf Advis 2012; 9(Suppl 1): 16-20

http://patientsafetyauthority.org/ADVISORIES/AdvisoryLibrary/2012/nov20_9%28suppl%201%29/Pages/16.aspx

 

 

 

 

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More IT Unintended Consequences

 

 

Health IT has provided many tools that have been helpful in improving patient safety. Yet the technology has also give rise to some unintended and unwanted consequences that have been detrimental to patient care (see list of our many prior columns on this at the end of today’s column).

 

The Pennsylvania Patient Safety Authority recently reviewed its adverse events database for events related to healthcare IT (Spannon 2012). They identified over 3000 reports over an 8-year period in which IT errors were considered root causes of untoward events. Errors related to medications and lab tests dominated. In almost 90% of cases the IT error was not reported to be associated with patient harm and in most of the rest the error created unsafe conditions but no actual harm. But there were cases in which harm did occur. An example was a patient who was allergic to penicillin developing anaphylaxis after being given ampicillin. The information about the allergy had been entered into part of the EHR that was not linked to the allergy portion of the pharmacy computer system that would have triggered an alert if the allergy had been recognized.

 

The PPSA developed a taxonomy for IT errors that modified and expanded the taxonomy developed previously by Magrabi et al. (Magrabi 2012). Examples were given for input errors. These included transposition and transcription errors, entry of wrong physician names, entry of incorrect patient parameters that trigger calculations, entry using wrong units (eg. pounds rather than kilograms), and data entered into wrong fields. There were frequent problems with default values. Such might be related to a clinician failing to change default values when they should be changed or to the system reverting to default values. The latter often happens with start times for an order. For example, we might write an order for a medication we want started now but the computer may default that order to the next “standard” time of medication administration resulting in a delay or omission of an important dose. Another category of error included failure to update data. An example might be failure to enter a new lab value that was important for calculation of a medication dose.

 

Especially bothersome are situations where paper-based computer-based systems are being used at the same time. An example might be a patient admitted via the emergency department where a medication given in the ED does not get documented in the inpatient HER so the patient gets a second dose upon arrival to the inpatient unit.

 

One of the concerns identified is that errors in IT systems tend to get propagated far more easily than did errors in the paper chart. That’s because the IT systems are interconnected to so many other systems.

 

The timely PPSA review highlights the need for systems to IT-related adverse events and near-misses. You’ll recall that a year ago the Institute of Medicine issued a report recognizing that the benefits of health information technology are accompanied by unwanted consequences and risks to patient safety (IOM 2011). That report called for greater oversight by the public and private sectors and recommended the secretary of the U.S. Department of Health and Human Services should publish a plan within 12 months to minimize patient safety risks associated with health IT and report annually on the progress. Moreover, it called for the FDA to exercise its authority to regulate these technologies. Specifically, it recommended HHS should establish a mechanism for both technology vendors and users to report health IT-related deaths, injuries, or unsafe conditions. Moreover, it suggested Congress establish an independent federal entity to investigate patient deaths, injuries, or potential unsafe conditions associated with health IT. 

 

The IOM report noted serious errors involving these technologies resulting in patient deaths and injuries. Examples given included medication dosing errors, failure to detect fatal illnesses, and treatment delays due to poor human-computer interactions or loss of data.  It also recommended better design to avoid alert fatigue and the need for computer interfaces need to be more intuitive for users.

 

It recommended development of criteria and methods for assessing and monitoring safety and measuring impacts of health IT on safety. It also recommended better information sharing about unintended consequences and panned the nondisclosure agreements and "hold harmless" clauses in many IT vendor contracts that shift the liability of unsafe health IT features to care providers. 

 

Well, it’s a year later and the ONC (Office of the National Coordinator for Health IT) has just released its proposed its Health IT Patient Safety Action and Surveillance Plan for public comment through Feb. 4, 2013 (ONC 2012). It is designed to help provide necessary data through reporting adverse event for developers, providers, researchers and policymakers to improve the safety of health IT and make care safer. ONC will work closely with the Centers for Medicare & Medicaid Services (CMS) to align its health and safety standards and guidance for providers and suppliers. CMS will also develop training for surveyors that enhances their ability to identify safe and unsafe practices associated with health IT. The Health IT Safety Plan’s goal is to “Inspire Confidence and Trust in Health IT and Health Information Exchange,” by taking steps to:

1. Use health IT to make care safer

2. Continuously improve the safety of health IT

 

The new plan will take advantage of the Agency for Healthcare Research and Quality’s (AHRQ) Common Formats with common definitions and reporting formats to improve how adverse event data is gathered, reviewed and reported. AHRQ will also encourage reporting to Patient Safety Organizations (PSOs) and increase health care provider adoption of the formats. The appendices included in the plan include a cross-walk between recommendations in the IOM report and actions in the ONC plan.

 

Two unintended consequences of healthcare IT made ECRI Institute’s 2013 Top 10 Health Technology Hazards (ECRI 2012). The first involves patient/data mismatches, which can result from either human error (eg. data input) or from system errors, poor user interfaces, design or workflow issues, software flaws, etc. Especially vulnerable are times when data is transferred from one system to another. They provide multiple examples and recommendations on ways to minimize the risks involved. The second involves interoperability failures between Health IT systems and medical devices. They discuss failures of communication between physiologic monitoring devices and a variety of other devices. They also note that errors may be detected in one system and manually corrected in that system but that no one recognizes the error is now in the Health IT system and has not been corrected there. As usual, ECRI’s annual Top Technology Hazards issue is timely and very useful and available for free download.

 

Speaking of user interfaces, another interesting phenomenon was recently reported at the American Society of Nephrology annual meeting. The problem of “cognitive drift” was reported as potentially giving rise to medical errors in those using the EHR (Onuigbo 2012). This refers to what happens when there is a delay between a mouse click and what appears on the computer screen in response to that click. In a survey of ICU physicians, the authors noted that most doctors begin to lose focus if that delay is greater than 10 seconds. Virtually all of the ICU physicians who responded to the survey reported experiencing such “cognitive drift” several times a day and cited this as a source of significant frustration, stress and possible burnout.

 

 

Healthcare IT also has been in the news recently for another unwanted reason: its cost. A huge part of the projected savings in the Affordable Care Act comes from anticipated savings resulting from widespread adoption of EHR’s by hospitals and physicians. Such savings is anticipated because EHR’s, in theory, should improve quality, reduce adverse events, foster better preventive care, reduce duplication, and improve continuity of care across all levels of the continuum. However, the empiric data to date does not confirm such savings. In fact, the early data suggests the oppostite. The OIG’s report (Levinson 2012) suggests that hospitals and physicians substantially increased their billings to Medicare in 2010 compared to prior years. Specifically, there has been a shift in physician billing for higher E&M (evaluation and management) codes and it is suspected that EHR’s make it easier to justify the higher coding. They found that approximately 1700 physicians who consistently billed the top 2 level E&M codes in 2010 accounted for about $108 million in Medicare costs.

 

Another surprising finding also has cost implictions. Part of achieving meaningful use for EHR’s requires providing patients access to a variety of computerized resources. It has always been presumed that patients having access to their EHR and ability to communicate with their physicians via means other than face-to-face visits would improve efficiencies and quality and ultimately lead to lower utilization and lower healthcare costs. But a recent study done at Kaiser Permanente Colorado (Palen 2012) unexpectedly showed that patients having online access to their medical records and clinicians was associated with significantly increased utilization of services. Of course, that study does not prove causality. Rather it may be that patients who need more services were more likely to get and use the enhanced IT access. Nevertheless, this association certainly raises the possibility of another unintended consequence.

 

 

We are still strong believers that ultimately healthcare IT will deliver on the quality and patient safety side and has the potential to reduce healthcare costs. However any cost savings, if it is to occur at all, is not likely in the immediate or near future.

 

 

See some of our other Patient Safety Tip of the Week columns dealing with unintended consequences of technology and other healthcare IT issues:

 

 

 

References:

 

 

Institute of Medicine (IOM). Health IT and Patient Safety: Building Safer Systems for Better Care. November 8, 2011

http://www.iom.edu/Reports/2011/Health-IT-and-Patient-Safety-Building-Safer-Systems-for-Better-Care.aspx

 

 

Spannon E, Marella WM. The Role of Electronic Health Record in Patient Safety Events. Pa Patient Saf Advis 2012; 9(4): 113-121

http://patientsafetyauthority.org/ADVISORIES/AdvisoryLibrary/2012/Dec;9%284%29/Pages/113.aspx

 

 

Magrabi F, Ong MS, Runciman W, et al. Using FDA reports to inform a classification for health information technology safety problems. J Am Med Inform Assoc 2012; 19(1): 45-53

http://jamia.bmj.com/content/19/1/45.abstract

 

 

ECRI Institute. 2013 Top 10 Health Technology Hazards. 2012

https://www.ecri.org/Forms/Pages/ECRI-Institute-2013-Top-10-Hazards.aspx

 

 

Office of the National Coordinator for Health Information Technology (ONC). Health IT Patient Safety Action and Surveillance Plan. December 21, 2012

http://www.healthit.gov/policy-researchers-implementers/health-it-and-patient-safety

 

 

AHRQ (Agency for Healthcare Research and Quality). Common Formats.

http://www.pso.ahrq.gov/formats/commonfmt.htm

 

 

Onuigbo MA, Onuigbo NT. Cognitive Drift in the Electronic Medical Record System: An Unrecognized Source of Physician Stress and a Silent Cause of Medication Errors: Results of a Small Physician Survey. Kidney Week 2012: American Society of Nephrology 45th Annual Meeting. Abstract FR-PO070. Presented November 2, 2012

http://www.asn-online.org/education/kidneyweek/archives/

As reported in Medscape by Keller DM. EHR System Lags Increase Error Risk. November 16, 2012

http://www.medscape.com/viewarticle/774650

 

 

Palen TE, Ross C, Powers JD, Xu S. Association of Online Patient Access to Clinicians and Medical Records With Use of Clinical Services. JAMA. 2012; 308(19): 2012-2019

http://jama.jamanetwork.com/article.aspx?articleid=1392562

 

 

Levinson DR. Coding Trends of Medicare Evaluation and Management Services. Department of Health and Human Services. Office of the Inspector General. May 2012

https://oig.hhs.gov/oei/reports/oei-04-10-00180.pdf

(Levinson 2012)

 

 

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More on the Downside of Contact Isolation

 

 

We’ve discussed some of the unintended consequences of contact isolation in prior Patient Safety Tips of the Week (January 17, 2012 “Delirium and Contact Isolation” and March 25, 2008 “More on MRSA”). Kirkland and Weinstein (Kirkland 1999) found that healthcare workers who treated patients in contact isolation entered their rooms less frequently and had significantly less direct contact with them. Saint et al. (2003) found that attending physicians in two teaching hospitals were about half as likely to examine patients in contact isolation. Another study (Stelfox et al. 2003) showed that isolated patients are twice as the likely as control patients to suffer an adverse event during hospitalization. The difference was primarily due to preventable adverse events and included event such as falls, decubiti, and fluid/electrolyte disorders. In fact, the latter events were 8 times more likely in isolated patients. They also had a cohort of congestive heart failure patients in isolation and these patients were much less likely to have certain interventions and evidence-based care than a control group of congestive heart failure patients. And we have all seen that patients in contact isolation often do not get services such as active rehabilitation that they might get were they not in isolation. A review of the literature (Morgan 2009) found 15 studies relating to adverse outcomes of contact isolation and identified these in four main themes: less patient-healthcare worker contact, changes in systems of care that produce delays and more noninfectious adverse events, increased symptoms of depression and anxiety, and decreased patient satisfaction with care. The University of Maryland group (Morgan 2011) had also previously poor adherence to core measures for patients on contact isolation. And another study from the University of Maryland (Day 2012) found that delirium was 75% more common in patients who are put into contact isolation during admission (as opposed to those placed in contact isolation at the time of admission).

 

 

Now another new study from the researchers at the University of Maryland (Morgan 2013) further quantifies some of the impact of contact precautions on patient care. They used a “secret shopper” methodology to observe and monitor certain aspects of care in patients on contact precautions compared to those not on such precautions. The patient population included both ICU patients and patients on general med/surg units. Patients on contact precautions had 36.4% fewer hourly visits by healthcare workers (HCW’s) than patients not on contact precautions (2.78 vs 4.37 visits per hour). They also had 17.7% less direct patient contact time with HCWs (13.98 vs 16.98 minutes per hour). The latter difference, however, was largely accounted for by patients who were not in ICU’s (those in ICU’s did not have a significant difference in contact time with HCW’s). Those on contact precautions also had 23.6% fewer visitors.

 

On the positive side, hand hygiene on exiting rooms was higher in those on contact precautions (but there was no difference in hand hygiene on entering patient rooms).

 

This observational study did not assess outcomes of patient care nor did it look at adverse events. Nevertheless, it does reinforce the observation that patients in contact isolation (particularly those in non-ICU settings) have considerably reduced contacts and contact time with both providers and visitors, likely increasing the potential for more adverse events.

 

Make your decisions wisely about who and when to use contact isolation. But make sure that your care plan includes appropriate interventions and monitoring to ensure that patients on contact isolation get all their medical and psychological needs met.

 

 

References:

 

 

Kirkland KB, Weinstein JM. Adverse effects of contact isolation. The Lancet 1999; 354: 1177-1178 http://www.thelancet.com/journals/lancet/article/PIIS0140673699041963/abstract

 

 

Saint S, Higgins LA, Nallamothu BK, Chenoweth C. Do physicians examine patients in contact isolation less frequently? A brief report. Am J Infect Control 2003; 31: 354-356 http://www.ajicjournal.org/article/S0196-6553(02)48250-8/abstract

 

 

Stelfox HT, Bates DW, Redelmeier DA. Safety of Patients Isolated for Infection Control. JAMA. 2003;290:1899-1905

http://jama.ama-assn.org/cgi/content/abstract/290/14/1899 (abstract)

http://jama.ama-assn.org/cgi/reprint/290/14/1899 (pdf)

 

 

Morgan DJ, Diekema DJ, Sepkowitz K, Perencevich EN. Adverse outcomes associated with contact precautions: A review of the literature. Am J Infect Control 2009; 37(2): 85–93

http://www.ajicjournal.org/article/S0196-6553%2808%2900685-8/abstract

 

 

Morgan DJ, Day HR, Harris AD, et al. The Impact of Contact Isolation on the Quality of Inpatient Hospital Care. PLoS One. 2011; 6(7): e22190

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141007/

 

 

Day HR, Perencevich EN, Harris AD, et al. Association Between Contact Precautions and Delirium at a Tertiary Care Center. Infection Control and Hospital Epidemiology 2012; 33(1): 34-39

http://www.jstor.org/pss/10.1086/663340

 

 

Morgan DJ, Pineles L, Shardell M, et al. The Effect of Contact Precautions on Healthcare Worker Activity in Acute Care Hospitals. Infection Control and Hospital Epidemiology 2013; 34(1): 69-73

http://www.jstor.org/discover/10.1086/668775?uid=3739832&uid=2134&uid=2&uid=70&uid=4&uid=3739256&sid=21101503744301

 

 

 

 

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