Patient Safety Tip
of the Week
March 6, 2018 Nurse Workload and Mortality
There have been numerous studies linking poor nurse:patient ratios with adverse patient outcomes. A study by Aiken and colleagues found that each additional patient per nurse was associated with a 7% increase in the likelihood of dying within 30 days of admission and a 7% increase in the odds of failure-to-rescue (Aiken 2002).
California was the
first state to mandate nurse:patient ratios and
multiple other states have also already mandated or are considering mandating nurse:patient ratios. But the issue is more complex than
simple nurse:patient ratios. Those ratios do not take
into account actual nurse workload nor do they take into account the fatigue
factor that may accompany long work shifts or forced overtime. One factor that
comes into play in those conditions is the concept of “missed nursing care” or
“care left undone” (see our Patient Safety Tips of the Week for November 26,
2013 “Missed
Care: New Opportunities?” and May 9, 2017 “Missed
Nursing Care and Mortality Risk”).
In our July 11, 2017
Patient Safety Tip of the Week “The
12-Hour Shift Takes More Hits”
we discussed a study by Ball and colleagues (Ball
2017a), using survey data from the RN4CAST
study to correlate measures of nurse-reported quality with shift duration. They
found the rate of “care left undone” was 1.13 times higher for nurses working ≥12 hours.
A previous study by Ball (Ball
2017b) showed that a 10% increase in the amount of care left undone by
nurses was associated with a 16% increase in mortality.
The two studies by
Ball and colleagues focus on nurse staffing levels and fatigue as big issues
leading to care left undone and its potential effects on patient care. But
another issue that we have discussed, primarily in our columns on “the weekend
effect”, has to do with nurse workload. We often see circumstances where a nurse:patient ratio is reasonable, yet the workload placed
on nurses leads to care left undone.
Patient acuity and
case mix, of course, are primary factors contributing to nurse workload. There
are a number of tools used to factor patient acuity into nurse workload
estimates. These have been used primarily in intensive care unit settings. But
factors other than patient acuity also contribute to nurse workload.
A recent retrospective analysis of adult patients admitted to two multi-disciplinary Intensive Care Units in Hong Kong showed that exposing critically ill patients to high workload/staffing ratios is associated with a substantial reduction in the odds of survival (Lee 2017). Data required to calculate TISS-76 (Therapeutic Intervention Scoring System), Acute Physiology and Chronic Health Evaluation III (APACHE III) and the average number of bedside nurses working on each day were collected on almost 900 patients over a 5-month period. TISS-76 uses 76 possible interventions to quantify nursing workload
They found that
survival to hospital discharge was more likely to occur when the maximum
workload-to-nurse ratio was low and that death was more likely to occur when
the ratio was high. Moreover, exposure to as little as one day of high
workload/staffing ratios was associated with a substantially increased risk of
death in critically ill patients.
Results of the Lee study suggest that staffing should be based on workload, not just patient numbers, and that “making do” with fewer nurses even for a short time or temporary increases in ICU capacity without a corresponding increase in staffing may adversely affect patient outcome.
Of course, extrapolation of the ICU experience described by Lee et al. to other settings is not possible. The measures of nurse workload in the TISS-76 may not be applicable to the med/surg or pediatric wards, ob/gyn or rehab settings, etc. And it’s not known whether the type of additional activities we’ve described in “the weekend effect” that increase nurse workload would have the same impact as those in an ICU.
But the overall implication is clearcut: nurse staffing considerations must take into account not only the nurse:patient ratio but also a measure of nurse workload.
In our many previous columns on the weekend effect or after-hours effect we have pointed out how hospitals differ during these more vulnerable times. Staffing patterns (both in terms of volume and experience) are the most obvious difference but there are many others as well. We’ve often said the use of the simple nurse:patient staffing ratio on weekends may be misleading. That is because there is often a significant difference in nurse workload on weekends. We’ve described the tremendous increase in nurse responsibilities on weekends due to lack of other staff (no clerical staff, delayed imaging, physicians not on site) that add additional responsibilities to their jobs. Our December 15, 2009 Patient Safety Tip of the Week “The Weekend Effect” discussed how adding non-clinical administrative tasks to already overburdened nursing staff on weekends may be detrimental to patient care. Just do rounds on one of your med/surg floors or ICU’s on a weekend. You’ll see nurses answering phones all day long, causing interruptions in some attention-critical nursing activities. Calls from radiology and the lab that might go directly to physicians now often go first to the nurse on the floor, who then has to try to track down the physician. They end up filing lab and radiology reports or faxing medication orders down to pharmacy, activities often done by clerical staff during daytime hours. Even in those facilities that have CPOE, nurses off-hours often end up entering those orders into the computer because the physicians are off-site and are phoning in verbal orders. You’ll also see nurses giving directions to the increased numbers of visitors typically seen on weekends. They may even end up doing some housekeeping chores and delivering food trays. All of these interruptions and distractions obviously interfere with nurses’ ability to attend to their clinically important tasks (see our Patient Safety Tips of the Week for August 25, 2009 “Interruptions, Distractions, Inattention…Oops!” and May 4, 2010 “More on the Impact of Interruptions”). We thus think that simply addressing nurse:patient staffing ratios without addressing nurse workload issues may be short-sighted.
Few attempts to predict nurse workload have taken into account factors beyond patient acuity. One study in Singapore (Hoi 2010) did take into account other factors and developed a nursing workload intensity measurement system (WIMS). In addition to patient diagnoses, WIMS incorporated nursing diagnoses and nursing time spent on direct patient care and time spend on indirect patient care. They found that patient dependency measurements were not correlated with nursing time. The authors concluded that workload predictions should de-link patient dependency with acuity status as both do not correlate, as evidenced by this study.
A protocol for more accurately measuring nurse workload has been proposed in the Netherlands (van den Oetelaar 2016). The researchers expanded upon a framework for nurse workload management that had been developed in the Netherlands, called the NZi methodology, which consisted of the following items:
- A checklist of nine patient characteristics that lead to a classification of light, moderate, heavy and intensive care;
- Time study of nurses' activities, registering time spent on direct and indirect patient care, unit-related tasks and other tasks;
- Estimate of allocated nursing resources;
- Questionnaire of perceived workload and perceived quality of work.
These data are combined to estimate and validate the workload of nurses.
But several disadvantages of that methodology led to modification by the new researchers. The proposal uses a new list of patient characteristics expected to influence care time. It also more specifically determines the required nurse resources, differentiating for levels of education and experience. Finally, it also uses a validated questionnaire to determine nurses' perceived workload. They choose to measure five dimensions of perceived workload: work pace (time pressure), amount of work, emotional load, physical load and mental load, as experienced by nurses.
Identifying relevant
patient characteristics
Rather than classifying patients in categories of intensity of care, the researchers sought to directly predict care time of patient characteristics. Focus will be on finding patient characteristics that are expected to cause additional care time, on top of “baseline” care time that all patients get.
Time study nursing
staff
A random sample of the activities of nurses is a useful and cost-effective methodology to explore work-related activities and provide broad insight into the way nurses spend their working hours, and to what extent their work is directly patient-related. The time study would utilize trained observers but might incorporate some self-reporting when certain activities (such as cognitive activities) cannot be directly observed. From the time study, time spent on non-patient-related activities can also be estimated.
Estimating required
care time
Results of the patient characteristic checklist will be combined with work sampling results. Data will be analyzed from the perspective of the nurse (How do they spend their time?) and the perspective of the patient (How much time is spent on caring for patients?). This is designed to answer questions such as: Does care time increase when certain characteristics apply? Also, what is the baseline care time for a patient when none of the characteristics apply?
Estimating allocated
care time
Allocated care time can be calculated by simply counting the number of nurses in a shift and multiplying this amount by the shift hours. However, that ignores staff skill and experience mix. Therefore, it is necessary to introduce nurse education levels and level of expertise into the workload equation.
Estimating nurses'
workload
An estimate of nurses' workload can be made by dividing the estimate of allocated care time by the estimate of required care time. Patient type profiles for all admitted patients in a shift can be added up to get to the total required care time for patient-related activities for that shift and added to an estimate for time spent on non-patient-related activities per shift to determine the total estimated required nursing time. Allocated nursing time is then determined by counting the number of nurses on duty and multiplying this by the shift time. This will be performed for each type of nurse on duty (registered, student, etc).
Measuring perceived
nurses' workload
Job demands and resources will be assessed with shortened
scales of the validated Questionnaire on the Experience and Evaluation of Work
(QEEW).
Validation
The workload management method will be validated by comparing the estimated nurses' workload to the workload as it was perceived by the nurses on duty.
There are a host of factors that contribute to nursing care left undone and ultimately to adverse patient outcomes. Nurse:patient ratio is a major factor, but nurse fatigue contributes and nurse workload is likely a major factor. Workload is not simply a function of patient acuity and we need to take into account all the other factors that impact a nurse’s time. We are pleased to see that ongoing studies are beginning to look at those factors so we can appropriately address ways to ensure our nurses are able to safely address the needs of our patients.
Some of our other columns on missed nursing care/care
left undone:
November 26, 2013 “Missed
Care: New Opportunities?”
May 9, 2017 “Missed Nursing Care and Mortality Risk”).
Some of our other columns on the role of fatigue in
Patient Safety:
November 9, 2010 “12-Hour
Nursing Shifts and Patient Safety”
April 26, 2011 “Sleeping
Air Traffic Controllers: What About Healthcare?”
February 2011 “Update on 12-hour Nursing Shifts”
September 2011 “Shiftwork
and Patient Safety
November 2011 “Restricted
Housestaff Work Hours and Patient Handoffs”
January 2012 “Joint
Commission Sentinel Event Alert: Healthcare Worker Fatigue and Patient Safety
January 3, 2012 “Unintended
Consequences of Restricted Housestaff Hours”
June 2012 “June
2012 Surgeon Fatigue”
November 2012 “The
Mid-Day Nap”
November 13, 2012 “The
12-Hour Nursing Shift: More Downsides”
July 29, 2014 “The
12-Hour Nursing Shift: Debate Continues”
October 2014 “Another
Rap on the 12-Hour Nursing Shift”
December 2, 2014 “ANA
Position Statement on Nurse Fatigue”
August 2015 “Surgical
Resident Duty Reform and Postoperative Outcomes”
September 2015 “Surgery
Previous Night Does Not Impact Attending Surgeon Next Day”
September 29, 2015 “More
on the 12-Hour Nursing Shift”
September 6, 2016 “Napping
Debate Rekindled”
April 18, 2017 “Alarm
Response and Nurse Shift Duration”
July 11, 2017 “The
12-Hour Shift Takes More Hits”
Our previous columns on the 12-hour nursing shift:
November 9, 2010 “12-Hour Nursing Shifts and Patient Safety”
February 2011 “Update on 12-hour Nursing Shifts”
November 13, 2012 “The
12-Hour Nursing Shift: More Downsides”
July 29, 2014 “The
12-Hour Nursing Shift: Debate Continues”
October 2014 “Another
Rap on the 12-Hour Nursing Shift”
December 2, 2014 “ANA
Position Statement on Nurse Fatigue”
September 29, 2015 “More
on the 12-Hour Nursing Shift”
July 11, 2017 “The
12-Hour Shift Takes More Hits”
References:
Aiken LH, Clarke SP, Sloane DM, et al. Hospital Nurse Staffing and Patient Mortality, Nurse Burnout, and Job Dissatisfaction. JAMA 2002; 288(16): 1987-1993
https://jamanetwork.com/journals/jama/fullarticle/195438
Ball J, Day T, Murrells T, et al. Cross-sectional
examination of the association between shift length and hospital nurses job
satisfaction and nurse reported quality measures. BMC Nursing 2017; 16: 26
https://bmcnurs.biomedcentral.com/articles/10.1186/s12912-017-0221-7#CR25
Ball JE. Nurse
Staffing Levels, Care Left Undone, & Patient Mortality in Acute Hospitals.
Karolinska Institutet; Stockholm 2017
Lee A, Cheung YSL, Joynt GM, et al. Are high nurse workload/staffing ratios associated with decreased survival in critically ill patients? A cohort study. Ann Intensive Care 2017; 7: 46
https://annalsofintensivecare.springeropen.com/articles/10.1186/s13613-017-0269-2
Hoi SY, Ismail N, Ong LC, Kang J. Determining nurse staffing needs: the workload intensity measurement system. J Nurs Manag 2010; 18(1): 44-53
http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2834.2009.01045.x/full
van den Oetelaar WFJM, van Stel HF, van Rhenen W, et al. Balancing nurses' workload in hospital wards: study protocol of developing a method to manage workload. BMJ Open 2016; 6: e012148
http://bmjopen.bmj.com/content/6/11/e012148
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