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October 16, 2018
Burnout
We just did a column on physician burnout and its impact on medical errors (see our August 2018 What's New in the Patient Safety World column “Burnout and Medical Errors”). We’ve also talked about nurse burnout in multiple columns on nurse workload and long nursing shifts. But since August there has been a deluge of publications on burnout, so here we go again.
Burnout, of course, occurs in all careers, not just healthcare ones. And we all know healthcare workers who show signs of burnout. But why are we talking about burnout in a patient safety column? The answer is simple: burnout affects patient care and patient safety.
That August 2018 What's New in the Patient Safety World column “Burnout and Medical Errors” highlighted a study (Tawfik 2018) which showed that physicians reporting symptoms of burnout were more than twice as likely to have reported a major medical error in the prior 3 months.
In addition to that study, there have been two recent systematic reviews and meta-analyses showing an association between physician burnout and patient safety issues. And physician burnout also made Becker’s Hospital Review’s “10 Top Patient Safety Issues for 2018” (Vaidya 2018).
The first systematic review (Panagioti 2018) analyzed 47 studies that met their inclusion criteria, accounting for over 42,000 physicians. Physician burnout was associated with an increased risk of patient safety incidents (OR, 1.96), poorer quality of care due to low professionalism (OR, 2.31), and reduced patient satisfaction (OR, 2.28). The links between burnout and low professionalism were larger in residents and early-career (≤5 years post residency) physicians compared with middle- and late-career physicians. Particularly in residents and early career physicians (≤5 years post residency), burnout was associated with close to four times increased risk for unprofessional behaviors. Overall, the depersonalization dimension had the most adverse association with quality and safety of patient care and patient satisfaction.
The second systematic review that focused on patient safety (Mossburg 2018) found that, of 22 studies meeting inclusion criteria, ten studies showed a relationship between both safety culture and clinical errors with burnout. Two of 3 studies reported an association between burnout and patient outcomes.
Remember also that the relationship between burnout and medical errors is bidirectional. Those physicians or nurses who have been involved in a serious incident, the “second victims”, are at greater risk of burnout (see our August 9, 2016 Patient Safety Tip of the Week “More on the Second Victim”).
A number of the studies on physician burnout point to the electronic health record (EHR) as a significant factor contributing to burnout. Alexander and colleagues (Alexander 2018) discuss the 3 main features of burnout: lack of enthusiasm, lack of accomplishment, and cynicism/depersonalization. Then, in attempt to find reason for a significant increase in burnout prevalence between 2011 and 2014, they analyzed 5 major transformational medical practice events that occurred between 2011 and 2014 (pervasive hospital purchases of medical groups, rising drug prices, the Affordable Care Act, pay for performance, and mandated electronic health records). Analyzing those events for the 3 main burnout features, they concluded that only the HER met all 3 attributes of physician burnout.
A survey last year showed that 60% of neurologists have at least one symptom of burnout (Busis 2017). Bernat and Busis (Bernat 2018), in describing factors contributing to that high burnout rate, also point to the role of the EHR as a major detrimental factor. They state “Completion of EHR data entry during office visits disturbs the patient–physician relationship by diverting physician eye contact and attention away from the patient. Completion of the EHR outside of the visit markedly adds clerical time to already overburdened physicians, further aggravating work–life imbalance. Physicians’ awareness that the usurpation of patient visit time by mandated but unproductive EHR documentation compounds their sense that work is meaningless and increases their dissatisfaction with practice. Patients ultimately become harmed as a result. EHRs were mainly designed for primary care physicians. Successfully practicing neurology depends on a more thorough history and physical examination than many other specialties. It is difficult to enter a complete and accurate neurologic history and examination into an EHR and to review electronic records from colleagues.”
We found these comments from neurologist Steven Sergay (Sergay 2018) about how physician burnout leads to patient burnout particularly compelling:
“Our patients are becoming disillusioned about their caregivers and have dampened expectations for the care they receive. Their doctor no longer seems personally involved. Many patients feel helpless and bear a sense of defeat and resignation. Why, they ask, do we have to cope with both illness and care quality anxiety? My patients often recognize pursuit of efficiency over effectiveness. They complain their doctor is harried, their care hurried, mechanical, and lacking in humanity. They miss eye contact with their doctor, literally and figuratively. Their caregiver does not take the necessary time to know them as a person with an illness rather than as “a disease,” to understand their experiences, anxieties, and preconceptions, all of which may dictate their receptivity to care approaches and methods. They decry the absence of discussion and explanation. They perceive the increased risk of their diagnosis being missed or delayed by regimented care delivery and that this often leads to unnecessary testing and its product: increased cost. They see their caregiver being sidetracked by recordkeeping and administrative requirements. They fear their hospital care may be suboptimal without an advocate.”
A systematic review and meta-analysis of the literature (Rotenstein 2018) showed wide variability of reported rates of burnout or individual burnout symptoms. They note that the prevalence of burnout ranged from 0% to over 80%. They found marked variation in burnout definitions, assessment methods, and study quality. These findings preclude definitive conclusions about the prevalence of burnout and highlight the importance of developing a consensus definition of burnout and of standardizing measurement tools. Most of the published studies on burnout have used the Maslach Burnout Inventory (MBI) as a tool to assess burnout. It measures three main dimensions of burnout: emotional exhaustion, depersonalization and diminished personal accomplishment. In an accompanying editorial (Schwenk 2018) Schwenk and Gold point out the MBI was originally developed for assessing burnout in social service professionals. They question whether it has the same applicability in physicians.
Burnout may begin very early in one’s medical career. Among US resident physicians, symptoms of burnout and career choice regret were prevalent, but varied substantially by clinical specialty (Dyrbye 2018). Training in urology, neurology, emergency medicine, and general surgery were associated with higher relative risks of reported symptoms of burnout relative to training in internal medicine. Another study of residents (Williford 2018) showed that 75% of general surgery residents met criteria for burnout (measured by the MBI), and 39% met criteria for depression (measured by the PHQ-9). Of those with burnout, 48% were at elevated risk of depression. Attendings and residents underestimated the prevalence of these conditions. The top 3 barriers to seeking care for burnout were: inability to take time off to seek treatment, avoidance or denial of the problem, and negative stigma toward those seeking care.
The overall message remains clear: burnout is a real problem and it contributes to medical errors and untoward patient outcomes. We, thus, need better ways to recognize physician burnout and interventions to offer support when we recognize it. Other industries have recognized job burnout and developed approaches to address it. We need to borrow from those industries and apply their approaches to healthcare. An excellent review on physician burnout also recently appeared in the Mayo Clinic Proceedings (Olson 2017).
So where do we start? In a commentary, Linzer (Linzer 2018) notes some factors contributing to burnout (eg. the EHR, chaotic workplaces, regulatory environment). We’re not going to cure the inefficiencies brought on by the EHR and insurance/regulatory climates in today’s column. Linzer also notes that stress and dissatisfaction in their role models and mentors may play a role in trainee’s high rates of burnout. He does note that workflow redesign has been shown to have a positive impact on burnout.
A recent article (Cheyney 2018) showed how workflow optimization addresses physician burnout in physician practices affiliated with Virginia Mason Medical Center, They note that workflow optimization usually targets 3 categories :lack of set up, mismatch of supply and demand, and poor skill-task alignment so they focused primarily on three workflow optimization tactics that foster team work: spreading the work burden among physicians, adoption of standardized work roles, and colocation of team members when feasible. That included having more patients seen by caregivers other than the physicians, including clinical pharmacists, care managers, RN’s, physician assistants, and nurse practitioners. Care managers have a greater role in helping manage patients with diabetes or other chronic diseases. And they make use of clinical pharmacists, who may deal with patients taking antihypertensives, antidepressants, and chronic opioids, and help with medication reconciliation in patients recently discharged from the hospital. They also developed standards that allow staff other than physicians to handle some of the phone calls. They note that having such team members co-located on-site with the rest of the team is very valuable.
Another excellent paper from the National Academy of Medicine (Smith 2018) discusses how implementing optimal team-based care to reduce clinician burnout. Successful teams have the capacity to improve patient outcomes, the efficiency of care, and the satisfaction and well-being of health care clinicians.
And recall that our February 27, 2018 Patient Safety Tip of the Week “Update on Patient Safety Walk Rounds” noted a study in multiple settings in the Michigan Keystone collaborative to determine the impact of Walk Rounds (WR) on domains such as safety culture, employee engagement, burnout and work-life balance. Focus was on the importance of feedback (Sexton 2017). The researchers found that both personal burnout and burnout climate were lowest in work settings that had the highest rates of WR with feedback.
Lastly, we must get a better understanding of the factors related to high burnout rates among residents. We already noted that reducing burnout in attending physicians may help reduce burnout in residents. Some academic practices have implemented innovative programs for developing four “emotional intelligence” skills: self-awareness; self-management; social awareness; and social skills that may improve stress management skills, promote wellness, and prevent burnout in resident physicians (Shahid 2018).
Burnout is real. It’s contagious. It’s bad for physicians, nurses, and all healthcare workers. It’s bad for our future generations of healthcare professionals. And, most of all, it’s bad for our patients. All too long burnout has been treated as a nebulous concept and, as such, there has been little focus on solutions in healthcare. The time has come to focus on mitigating those environmental factors that take the fun and reward out of the practice of medicine.
References:
Tawfik DS, Profit J, Morgenthaler TI, et al. Physician Burnout, Well-being, and Work Unit Safety Grades in Relationship to Reported Medical Errors. Mayo Clinic Proceedings 2018; Published online: July 9, 2018
https://www.mayoclinicproceedings.org/article/S0025-6196(18)30372-0/fulltext
Vaidya A, Zimmerman B, Bean M. 10 top patient safety issues for 2018. Becker’s Hospital Review 2018; January 09, 2018
https://www.beckershospitalreview.com/10-top-patient-safety-issues-for-2018.html
Panagioti M, Geraghty K, Johnson J, et al. Association Between Physician Burnout and Patient Safety, Professionalism, and Patient SatisfactionA Systematic Review and Meta-analysis. JAMA Intern Med 2018; 178(10): 1317-1330
Mossburg SE, Dennison Himmelfarb C. The association between professional burnout and engagement with patient safety culture and outcomes: a systematic review. J Patient Saf 2018; Epub ahead of print June 2018.
Alexander AG, Ballou KA, Work–Life Balance, Burnout, and the Electronic Health Record. Amer J Med 2018; 131(8): 857-858
https://www.amjmed.com/article/S0002-9343(18)30286-9/fulltext
Busis NA, Shanafelt TD, Keran CM, et al. Burnout, career satisfaction, and well-being among US neurologists in 2016. Neurology 2017; 88: 1-12
http://n.neurology.org/content/neurology/early/2017/01/25/WNL.0000000000003640.full.pdf
Bernat JL, Busis NA. Patients are harmed by physician burnout. Neurol Clin Pract 2018 8: 279-280; published ahead of print June 18, 2018
http://cp.neurology.org/content/8/4/279?etoc=
Sergay SM. The burnout patient. Neurol Clin Pract 2018 8: 346-348; published ahead of print June 18, 2018
http://cp.neurology.org/content/8/4/346?etoc=
Rotenstein LS, Torre M, Ramos MA, et al. Prevalence of Burnout Among Physicians. A Systematic Review. JAMA 2018; 320(11): 1131-1150
Schwenk TL, Gold KJ. Physician Burnout—A Serious Symptom, But of What? (editorial). JAMA 2018; 320(11) :1109-1110
https://jamanetwork.com/journals/jama/article-abstract/2702852
Dyrbye LN, Burke SE, Hardeman RR, et al. Association of Clinical Specialty With Symptoms of Burnout and Career Choice Regret Among US Resident Physicians. JAMA 2018; 320(11): 1114-1130
https://jamanetwork.com/journals/jama/article-abstract/2702870
Williford ML, Scarlet S, Meyers MO, et al. Multiple-Institution Comparison of Resident and Faculty Perceptions of Burnout and Depression During Surgical Training. JAMA Surg 2018; 153(8): 705-711
Olson KD. Physician Burnout—A Leading Indicator of Health System Performance? Mayo Clinic Procedings 2017; 92(11): 1608-1611
https://www.mayoclinicproceedings.org/article/S0025-6196(17)30690-0/fulltext
Linzer M. Clinician Burnout and the Quality of Care. JAMA Intern Med 2018; 178(10): 1331-1332
https://jamanetwork.com/journals/jamainternalmedicine/article-abstract/2698140
Cheney C. How Workflow Optimization Addresses Physician Burnout. HealthLeaders 2018; August 22, 2018
Smith CD, Balatbat C, Corbridge S. et al. Implementing Optimal Team-Based Care to Reduce Clinician Burnout. Discussion Paper. National Academy of Medicine 2017; September 17, 2018
https://nam.edu/implementing-optimal-team-based-care-to-reduce-clinician-burnout/
Sexton JB, Adair KC, Leonard MW, et al Providing feedback following Leadership WalkRounds is associated with better patient safety culture, higher employee engagement and lower burnout. BMJ Qual Saf 2017; Published Online First: 09 October 2017
http://qualitysafety.bmj.com/content/early/2017/10/09/bmjqs-2016-006399
Shahid R, Stirling J, Adams W. Promoting wellness and stress management in residents through emotional intelligence training. Advances in Medical Education and Practice 2018; 9: 681-686
https://www.dovepress.com/articles.php?article_id=40739
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October 2018
We’ve done several columns on the devastating events related to various tubing misconnections. Reported cases have involved almost any catheter you can think of (substances intended for feeding tubes being given intravenously or via dialysis catheter, intravenous medications being given intrathecally, hypertonic intravenous contrast agents being given intrathecally for myelography, bladder irrigation solutions being given intravenously, intramuscular medications like Bicillin being given intravascularly, IV fluid being injected into a tracheostomy cuff, blood pressure cuffs being hooked up to IV lines, and many more examples).
In our September 2014 What's New in the Patient Safety World column “New Tubing Connections” we discussed a variety of contributing factors but noted that the most salient root cause is design of the systems that allows 2 things to be connected that were never intended to be connected. That led to multiple groups collaborating to come up with new design solutions to prevent such inadvertent misconnections.
The FDA recently sent a letter (Maisel 2018) to healthcare providers, hospitals, and manufacturers of enteral feeding devices to encourage use of enteral device connectors that reduce risk of misconnection. The letter notes there are currently marketed enteral connectors that meet the ISO 80369-3 standard, many of which are identified by the tradename ENFit.
The FDA letter recommends healthcare professionals:
It also recommends that hospital purchasing departments purchase enteral devices that comply with the new ISO 80369-1 or ISO 80369-3 series standards to reduce the risk of misconnection.
ECRI Institute last year put out an excellent guidance for implementing the ENFit initiative for preventing enteral tubing misconnections (ECRI 2017). We encourage our readers follow the excellent recommendations in that guidance.
ISMP (ISMP 2018) also recently reported on a misconnection between intravenous (IV) tubing and a tracheostomy pilot balloon port (cuff inflation port) that led to a young patient’s cardiac arrest. A nurse removed an IV bag from a triple lumen IV catheter port, intending to administer an antibiotic via that catheter port. But, by accident, the nurse grabbed the nearby tracheostomy pilot balloon port and connected the antibiotic tubing. Because the luer connector on the balloon port looked different than usual, the nurse interposed another connector that allowed a connection to be made. The subsequent fluid infusion caused the balloon to inflate and ultimately burst, releasing the fluid into the patient’s lungs. The patient arrested but was resuscitated. The ISMP report discusses factors contributing to the error and has excellent recommendations for avoiding this kind of mistake.
Catheter misconnections remain a serious threat to patient safety. The new ENFit connectors go a long way toward minimizing the risk of such events. Hospitals and healthcare providers should heed the recommendations in the FDA, ECRI, and ISMP resources mentioned above.
Some of our previous columns on tubing/catheter misconnections:
July 10, 2007 “Catheter Connection Errors/Wrong Route Errors”
November 2007 “More Patient Deaths from Luer Misconnections”
August 2009 “Catheter Misconnections Continue to Occur”
March 30, 2010 “Publicly Released RCA’s: Everyone Learns from Them”
April 2010 “RCA: Epidural Solution Infused Intravenously”
August 2010 “ISMP Advice on Catheter Misconnections”
August 23, 2011 “Catheter Misconnections Back in the News”
April 2012 “Tubing Misconnections”
September 2014 “New Tubing Connections”
References:
Maisel WH. The FDA Encourages Use of Enteral Device Connectors that Reduce Risk of Misconnection and Patient Injury. FDA 2018; September 7, 2018
ECRI Institute. Implementing the ENFit Initiative for Preventing Enteral Tubing Misconnections. Published 3/29/2017
ISMP (Institute for Safe Medication Practices). Ongoing Risk: Misconnections of Tracheostomy Pilot Balloon Ports with IV Infusions Can Result in Fatal Outcomes. ISMP Medication Safety Alert! Acute Care Edition 2019; September 20, 2018
Print “October 2018 FDA/ECRI/ISMP on Tube Misconnections
In addition to Beers’ List, we have described the START and STOPP tools for avoiding prescribing potentially inappropriate medications. Now we also have STRIP (Systematic Tool to Reduce Inappropriate Prescribing).
The STRIP combines both implicit and explicit prescribing tools (Drenth-van Maanen 2018). Explicit prescribing tools are usually developed on the basis of literature reviews, expert opinion, and consensus. These often include lists of drugs or drug classes to be avoided in older people because these drugs have an increased risk of negative outcomes or potential adverse consequences in this population. Beers’ criteria and the START and STOPP tools are examples of explicit criteria.
On the other hand, implicit criteria use the knowledge or expertise a clinician or pharmacist can apply to any prescription. For example, they may take into account such patient-related factors like comorbidities, patient preferences, or previously unsuccessful treatment approaches.
STRIP has actually been around for some time now and has been shown to effective in helping final‐year medical students improve their prescribing skills (Keijsers 2014). Another showed that physicians were able to significantly improve medication optimization for polypharmacy patients with the online STRIP Assistant tool (Meulendijk 2015). Appropriate decisions increased from 58% without the STRIP Assistant to 76% with it, and inappropriate decisions decreased from 42% without the STRIP Assistant to 24% with it. However, that came at a time expense. More time was spent optimizing medication with the STRIP Assistant (24 min.) than without it (13 min.), perhaps accounting for a marginal user satisfaction rating.
The STRIP consists of 5 steps:
The medication history/assessment consists of 10 topics:
The second step is the pharmacotherapy review. Here the patient's current morbidities
and symptoms should be matched with the medications used by the patient. Additional
information, such as blood pressure, weight, estimated glomerular filtration rate, and HbA1c are taken into consideration. Once therapeutic aims have been formulated, the medication list is checked for underprescribing, ineffective prescribing, overprescribing, side effects, contraindications, and drug‐drug and drug‐disease interactions, incorrect dosages/dosing frequencies, and practical intake issues. This is also where the START and STOPP criteria are implemented.
The third step is the pharmaceutical care plan, which sets:
The fourth step, shared decision-making, takes into account patient preferences and addresses other problems that might interfere with the patient’s ability to comply with the treatment plan.
The fifth step, followup and monitoring, is very important and one that often gets neglected. Note that you specified in Step 3 how, when, and by whom the interventions will be evaluated.
And note that we did not call the fifth step the last step. That’s because the whole process is a cycle and one moves from Step 5 back to Step 1 and we start all over again.
The ongoing OPERAM study in Europe is investigating the effect of STRIP use on clinical and economic outcomes. A video demonstration of the online STRIP Assistant tool is available online (make sure you click the full screen icon so you can see details).
Another recently published study did not use the STRIP tool but did use two explicit criteria, the START and STOPP tools, to study the impact of prescribing at hospital discharge (Counter 2018). Counter and colleagues showed that the presence of potentially inappropriate medications (PIMs) and potential prescribing omissions (PPOs) in older adults discharged from hospital is significantly associated with repeated hospital admissions and mortality, respectively. Prescription of more than five medications was significantly associated with PIMs and PPOs. Presence of a PIM was associated with three or more readmissions (odds ratio 2.43) and PPO’s were associated with mortality (OR 1.88). This, of course, was a retrospective study. It would be interesting to see how something, like the STRIP tool, applied proactively would impact readmissions and mortality.
Inappropriate prescribing, particularly in the elderly, remains a significant patient safety issue. Add the STRIP tool to our armamentarium to combat such inappropriate prescribing.
Of course, the other very important part of medication management in all patients, not just the elderly, is medication reconciliation performed at all transitions of care. Regarding medication reconciliation, there is some recent disappointing news. Five hospitals implemented a standardized approach to admission and discharge medication reconciliation using an evidence-based toolkit with longitudinal mentorship from the study investigators (Schnipper 2018). Each study site used a pharmacist and a hospitalist to implement the toolkit with 11 intervention components. Unfortunately, though there was a reduction in total medication discrepancies, overall potentially harmful discrepancies did not decrease over time beyond baseline temporal trends. But there were significant differences between the study sites. Sites that successfully implemented the recommended interventions were more likely to achieve reductions in harmful medication discrepancies. Interestingly, sites that had installed new EHR’s did not fare as well. Another study (Horsky 2018) compared 2 different medication reconciliation tools integrated into electronic health record systems (EHRs) and found the manner of presentation may have an important influence. Significantly fewer errors were made with the EHR that presented lists in a side-by-side view, automatically grouped medications by therapeutic class and more effectively identified duplicates. Participants favored that design and indicated that they routinely used several workarounds in the other EHR. Yet another study last year (Stockton 2017) found medication errors were common after the implementation of electronically prepopulated medication reconciliation forms. The authors recommended that prospective research examine the impact of prepopulated medication reconciliation forms and ensure they do not facilitate errors of commission. We actually highlighted problems with prepopulated medication lists a decade ago (see our December 30, 2008 Patient Safety Tip of the Week “Unintended Consequences: Is Medication Reconciliation Next?”). Bottom line: we still have a long way to go for optimal medication reconciliation.
Some of our past columns on Beers’ List and Inappropriate Prescribing in the Elderly:
Some of our past columns on deprescribing:
References:
Drenth-van Maanen AC, Leendertse AJ, Jansen PA, et al. The Systematic Tool to Reduce Inappropriate Prescribing (STRIP): Combining implicit and explicit prescribing tools to improve appropriate prescribing. Journal of Evaluation in Clinical Practice 2018; 24(2): 317-322 First published: 04 August 2017
https://onlinelibrary.wiley.com/doi/abs/10.1111/jep.12787
Keijsers CJPW, van Doorn ABD, van Kalles A, et al. Structured Pharmaceutical Analysis of the Systematic Tool to Reduce Inappropriate Prescribing Is an Effective Method for Final‐Year Medical Students to Improve Polypharmacy Skills: A Randomized Controlled Trial. J Amer Geriatr Soc 2014; 62(7): 1353-1359
https://onlinelibrary.wiley.com/doi/abs/10.1111/jgs.12884
Meulendijk MC1, Spruit MR, Drenth-van Maanen AC, et al. Computerized Decision Support Improves Medication Review Effectiveness: An Experiment Evaluating the STRIP Assistant's Usability. Drugs Aging 2015; 32(6): 495-503
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4469772/
STRIP Assistant (STRIPA) for OPERAM. Video demonstration.
http://videodemo.stripa.eu/english/
Counter D, Millar JWT, McLay JS. Hospital readmissions, mortality and potentially inappropriate prescribing: a retrospective study of older adults discharged from hospital. British Journal of Clinical Pharmacology 2018; 84(8): 1757-1763
https://bpspubs.onlinelibrary.wiley.com/doi/10.1111/bcp.13607
Schnipper JL, Mixon A, Stein J, et al. Effects of a multifaceted medication reconciliation quality improvement intervention on patient safety: final results of the MARQUIS study. BMJ Qual Saf 2018; Published Online First: 20 August 2018
https://qualitysafety.bmj.com/content/early/2018/08/20/bmjqs-2018-008233
Horsky J, Drucker EA, Ramelson HZ. Higher accuracy of complex medication reconciliation through improved design of electronic tools . Journal of the American Medical Informatics Association 2018; 25(5): 465-475
https://academic.oup.com/jamia/article-abstract/25/5/465/4601882?redirectedFrom=fulltext
Stockton KR, Wickham ME, Lai S, et al. Incidence of clinically relevant medication errors in the era of electronically prepopulated medication reconciliation forms: a retrospective chart review. CMAJ Open 2017; 5: E345-E353
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5498425/
Print “October 2018 STOPP/START/STRIP”
Delirium goes unrecognized or undiagnosed in up to 72% of cases in hospitalized patients (Collins 2010). One of the reasons may be that commonly used screening tests for delirium may not be brief enough or may require specific training for administration. While traditional validated tools like the CAM and CAM-ICU remain key components of any programs addressing delirium, we wholeheartedly support the exploration of tools that can be administered briefly and by those without extensive training. Such tools could likely greatly increase the detection of delirium so that appropriate management strategies can be put in place.
We have discussed such rapid screening tools in prior columns (our What’s New in the Patient Safety World columns for August 2014 “A New Rapid Screen for Delirium in the Elderly” and July 2016 “New Simple Test for Delirium”)
Since that last column there have been a few more studies on rapid screening tools for delirium. One study evaluated the brief Confusion Assessment Method (bCAM) in a German emergency department setting and administered during the daily work routine (Baten 2018). The bCAM showed 93.8% specificity but only moderate (65.2%) sensitivity. Positive and negative likelihood ratios were 10.5 and 0.37, respectively, But delirium was missed in 10 of 16 cases, since the bCAM did not indicate altered levels of consciousness and disorganized thinking. Nevertheless, the authors felt that application of the bCAM most likely improves the delirium detection rate. However, they cautioned it should only be applied by trained physicians to maximize diagnostic accuracy and hence improve the bCAM's sensitivity.
Another study reviewed the literature on attention, arousal and other rapid bedside screening instruments for delirium in older patients (Quispel-Aggenbach 2018). The authors found wide variability in specificity and sensitivity. Two arousal assessment tools - the Observational Scale of Level of Arousal (OSLA) and Richmond Agitation and Sedation Scale (RASS) had sensitivity and specificity >80%. Both those tools can be easily administered by nurses during daily interaction with patients.
We hope you’ll go back to our What’s New in the Patient Safety World columns for August 2014 “A New Rapid Screen for Delirium in the Elderly” and July 2016 “New Simple Test for Delirium” for discussions on the other tools that have been used for rapid screening for delirium. But the two new studies demonstrate we still have a need for better screening tools that can be rapidly and easily administered during routine care.
Some of our prior columns on delirium assessment and management:
References:
Collins N, Blanchard MR, Tookman A, Sampson EL. Detection of delirium in the acute hospital. Age Ageing 2010; 39 (1): 131-135
http://ageing.oxfordjournals.org/content/39/1/131.full.pdf+html
Baten V, Busch J-J, Busche C, et al. Validation of the Brief Confusion Assessment Method for Screening Delirium in Elderly Medical Patients in a German Emergency Department. Academic Medicine 2018; First Published: 08 May 2018
https://onlinelibrary.wiley.com/doi/abs/10.1111/acem.13449
Quispel-Aggenbach DWP, Holtman GA, Zwartjes HAHT, et al. Attention, Arousal and Other Rapid Bedside Screening Instruments for Delirium in Older Patients. A Systematic Review of Test Accuracy Studies. Age Ageing 2018; 47(5): 644-653
https://academic.oup.com/ageing/article/47/5/644/4985481?searchresult=1
Print “October 2018 Rapid Screening for Delirium”
In our March 6, 2018 Patient Safety Tip of the Week “Nurse Workload and Mortality” we noted 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.
A seminal 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).
We fully support legislation that raises nurse:patient staffing 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”).
We discussed the issue of nursing workload in detail in our Patient Safety Tips of the Week for March 6, 2018 “Nurse Workload and Mortality” and May 29, 2018 “More on Nursing Workload and Patient Safety”.
In the upcoming (November) election in Massachusetts one of the items to be voted upon is Question 1, which would mandate nurse staffing ratios at all hospitals. Nurse:patient ratios would take into account the type of unit and some measure of intensity.
The battle lines are drawn. The Massachusetts Nurses Association, which strongly supports the proposed legislation, has estimated the total cost of such a mandate would be $47 million. But other groups have estimated that the cost would be $74.8 million dollars per year just for the four state-run hospitals in Massachusetts (Coalition 2018). The Massachusetts Health Policy Commission, an independent state agency, says that “mandating of nurse-to-patient staffing ratios in Massachusetts could have a significant impact on health care costs, quality and access in the state” (Salsberg 2018). The opposition to Question 1, led by the Coalition to Protect Patient Safety, has received more than $11 million in campaign contributions while the support, led by the Committee to Ensure Safe Patient Care, has banked almost $6 million, according to the latest reports from the Massachusetts Office of Campaign and Political Finance (Cohan 2018).
Massachusetts had already passed a law, effective as of 2016, requiring a 1:1 or 2:1 patient-to-nurse staffing ratio in intensive care units (ICU) in the state, and guided by a tool that accounts for patient acuity and anticipated care intensity. Just published was an analysis of the impact of this legislation on patient outcomes (Law 2018). The researchers compared staffing levels and mortality and certain patient complications between Massachusetts ICU’s and out-of-state ICU’s. There actually were only modest increases in ICU nurse staffing ratios in Massachusetts (from 1.38 patients per nurse before implementation to 1.28 patients per nurse after) and those staffing increases were largely mirrored in other states that did not have the mandate. Massachusetts ICU nurse staffing regulations were not associated with changes in hospital mortality within Massachusetts or when compared with changes in hospital mortality in other states. Complications and DNR orders also remained unchanged relative to secular trends. The authors conclude that the law had little impact on either staffing levels or patient outcomes.
We’re not quite sure what to make of the results after passage of the previous Massachusetts legislation. We might have predicted that, because ICU’s are already staffed at high levels, we would not see much change. But the proposed new legislation is aimed at all hospital units, not just ICU’s, and that is where we are most likely to see a substantial impact on patient outcomes.
We believe the prior research that shows staffing levels do influence patient outcomes. But as we’ve discussed in so many prior columns, there needs to be a match between staffing levels and nursing workload. Patient acuity is only one potential component of workload. In our prior columns we noted several tools that have been used as better measures of nursing workload.
The proposed Massachusetts legislation is a political hot potato. It pits hospitals vs. nurses’ unions. Both should be interested in the most important outcome: what happens to our patients. We are concerned that the uncertain costs of implementing this legislation may lead to it being voted down and that a potentially useful strategy for improving patient care will be lost. We believe it would have been more politically expedient for Massachusetts to have funded a semi-controlled study in which the state would select a representative sample of different types of hospital (academic, community, rural, etc.) and foot the cost of any upgraded staffing there (CMS and other third party payers could also have contributed to such funding) and then compare patient outcomes against all the other hospitals.
Come November we’ll find out how the electorate of Massachusetts feels.
Some of our other columns on nursing workload and missed nursing care/care left undone:
November 26, 2013 “Missed Care: New Opportunities?”
May 9, 2017 “Missed Nursing Care and Mortality Risk”
March 6, 2018 “Nurse Workload and Mortality”
May 29, 2018 “More on Nursing Workload and Patient Safety”
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
Coalition to Protect Patient Safety (Press Release). Official Massachusetts Voter Guide Estimates Question 1 Will Cost State At Least $67.8 Million. September 28, 2018
Salsberg B. Backers of nurse staffing proposal object to agency's study. The Hour 2018; September 29, 2018
https://www.thehour.com/news/article/Backers-of-nurse-staffing-proposal-object-to-13268413.php
Cohan A. Fight over nurse workload. Hospitals battle unions in Nov. ballot question. Boston Herald 2018; September 30, 2018
http://www.bostonherald.com/business/business_markets/2018/09/fight_over_nurse_workload
Law AC, Stevens JP, Hohmann S, et al. Patient Outcomes After the Introduction of Statewide ICU Nurse Staffing Regulations. Critical Care Medicine 2018; 46(10): 1563-1569
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