Krein, et al (Patient-Reported Complications Related to Peripherally Inserted Central Catheters: A Multicenter Prospective Cohort Study; Feb 2019) should be commended for sharing the results of this very interesting study. After reading it a few times, I am compelled to share the following concerns with you and the research team. The knowledge regarding PICC-related complications is indeed incomplete, but I am not sure if the main outcome(s) of your study are clearly represented to the reader.
The word “possible” is critical to correctly interpreting the results of this study. The term “complication” implies a medical diagnosis or medical confirmation – which your study attempted to do by conducting the chart reviews to confirm the presence or absence of a PICC complication, with limited success. Terms such as signs, symptoms, issues, adverse effects, and complications are used interchangeably throughout the paper to describe the patients’ self-reported experience, but without the benefit of operational definitions. These are not synonyms. Definitions help us to have a common understanding of a word or topic; they help us get on the same page when reading about an issue.
The word “possible” seems appropriate in the main outcome(s) statement, but is curiously missing from the report title. The phrase “medical complications” is used in the title of Table 2 – which clearly reports predominantly patient self-reported symptoms. The same bias is exhibited...
Krein, et al (Patient-Reported Complications Related to Peripherally Inserted Central Catheters: A Multicenter Prospective Cohort Study; Feb 2019) should be commended for sharing the results of this very interesting study. After reading it a few times, I am compelled to share the following concerns with you and the research team. The knowledge regarding PICC-related complications is indeed incomplete, but I am not sure if the main outcome(s) of your study are clearly represented to the reader.
The word “possible” is critical to correctly interpreting the results of this study. The term “complication” implies a medical diagnosis or medical confirmation – which your study attempted to do by conducting the chart reviews to confirm the presence or absence of a PICC complication, with limited success. Terms such as signs, symptoms, issues, adverse effects, and complications are used interchangeably throughout the paper to describe the patients’ self-reported experience, but without the benefit of operational definitions. These are not synonyms. Definitions help us to have a common understanding of a word or topic; they help us get on the same page when reading about an issue.
The word “possible” seems appropriate in the main outcome(s) statement, but is curiously missing from the report title. The phrase “medical complications” is used in the title of Table 2 – which clearly reports predominantly patient self-reported symptoms. The same bias is exhibited in the paragraph titled “Change in patient-reported complications over time”. The study limitations clearly note that the signs and symptoms reported could not be interpreted within the context of comorbidities, nor could the complications be confirmed without evidence in the medical record.
Study titles and terms will influence the readers – who in this case are clinicians and patients. It seems irresponsible to use the term “complication” without the qualifying word “possible” to accurately represent the findings and import of this study.
Krein et al have the best of intentions as they try to develop the body of knowledge around vascular access devices. However, an analysis of self-reported symptoms should not be represented as a complication rate.
O’Reilly-Shah et al. present a novel approach to quality improvement in anaesthesia by attempting to elicit change in practice using ‘nudge theory’ derived from the field of behavioural economics [1]. Translating new research evidence into common clinical practice is an important quality issue and cheap and effective strategies to achieve this are of interest. O’Reilly-Shah et al. hypothesised that using ‘nudge-type’ interventions, an audit-feedback dashboard as well as changes to mechanical ventilator default settings, might improve anaesthesia provider compliance with this ‘lung protective’ ventilation strategy in the general operating theatre environment.
I disagree with the conclusion that the authors have drawn, that these interventions might improve clinical and financial outcomes. My disagreement stems from the clinical rationale of the intervention, which overlaps onto the assumptions built into the ‘nudge theory’ of behavioural economics itself.
Sunstein & Thaler, who have influenced large scale policy making in several countries, describe nudge theory as a form of choice architecture that “alters people’s behaviour in a predictable way without forbidding any options or significantly changing their economic incentives” [2, 3]. Their philosophy is described as “libertarian paternalism”, as it influences choices that make people better off as judged by themselves, while preserving their freedom to choose otherwise. This is presumably what the interve...
O’Reilly-Shah et al. present a novel approach to quality improvement in anaesthesia by attempting to elicit change in practice using ‘nudge theory’ derived from the field of behavioural economics [1]. Translating new research evidence into common clinical practice is an important quality issue and cheap and effective strategies to achieve this are of interest. O’Reilly-Shah et al. hypothesised that using ‘nudge-type’ interventions, an audit-feedback dashboard as well as changes to mechanical ventilator default settings, might improve anaesthesia provider compliance with this ‘lung protective’ ventilation strategy in the general operating theatre environment.
I disagree with the conclusion that the authors have drawn, that these interventions might improve clinical and financial outcomes. My disagreement stems from the clinical rationale of the intervention, which overlaps onto the assumptions built into the ‘nudge theory’ of behavioural economics itself.
Sunstein & Thaler, who have influenced large scale policy making in several countries, describe nudge theory as a form of choice architecture that “alters people’s behaviour in a predictable way without forbidding any options or significantly changing their economic incentives” [2, 3]. Their philosophy is described as “libertarian paternalism”, as it influences choices that make people better off as judged by themselves, while preserving their freedom to choose otherwise. This is presumably what the interventions chosen by O’Reilly-Shah et al. were based on, that changing ventilator defaults did not force anaesthetists to select a certain tidal volume, and audit-feedback dashboards might foster change through an increase in awareness of peer group behaviour.
Assessing preferences and costs may not be straightforward, as described in a critique of nudge theory by Berg & Davidson [3]. They argue that many choice decisions implicitly have a trade-off, and it is difficult to predict in advance which direction the balance tips. Furthermore, selecting a particular tidal volume (a continuous variable) for a particular patient during an operation might be a complex decision and not a binary option, which makes the cost or indeed the opportunity cost, of a particular choice difficult to ascertain, in economic parlance.
A study much vaunted by the New York Times Magazine demonstrating improvement in hand hygiene rates amongst clinicians after the introduction of screen savers depicting bacterial cultures from physicians’ hands, failed to be replicated in another study using a similar methodology, which suggests that audit-feedback dashboard techniques may not be robust [4, 5]. O’Reilly-Shah et al. state that most practitioners accepted the target ventilation strategy without debate but they also admit that there is equipoise in the anaesthetic literature regarding the benefit of a low-tidal volume strategy for elective surgical patients [1]. As such, the increased compliance rate might not have reflected the provider’s ‘better preference’ per se, but a trend towards the default lower tidal volume as it may not have been an important factor either way.
A better example using the authors’ approach might be the default setting of ‘pressure-controlled’ ventilation as opposed to ‘volume-controlled’ ventilation in paediatric patients undergoing general anaesthesia, to avoid the danger of delivering overtly dangerous large tidal volumes. This is sensible practice in paediatric, but in hospitals with mixed adult and paediatric populations, this may not always be appropriate. It would then represent a binary decision and the benefit would be more obvious.
References
1. O'Reilly-Shah VN, Easton GS, Jabaley CS, Lynde GC. Variable effectiveness of stepwise implementation of nudge-type interventions to improveprovider compliance with intraoperative low tidal volume ventilation. BMJ Qual Saf. 2018 May 18
2. Thaler RH, Sunstein CR. Nudge: Improving Decisions About Health, Wealth, And Happiness. New Haven : Yale University Press, 2008, p5-6.
3. Berg C, Davidson S. Nudging, calculation, and utopia, Journal of Behavioral Economics for Policy, Vol. 1, Special Issue, 49-52, 2017
4. Dubner SJ, Levitt SD. Selling soap. The New York Times Magazine, September 24, 2006.
5. Charters M, Cheng AL, Esaki RK, Kuo AS, Neal J, Thawani JP, Chenoweth C. The impact of a screensaver in promoting hand hygiene. Am J Infect Control. 2009 Dec;37(10):867-8
I read this paper1 first published on 5 March 2018 in your journal with great interest.
The great pace of health information technology (health IT) advancement in recent decades held promise in improving patient safety and quality of care, but unfortunately there has since been inadvertent consequences and carry-over effects of technology-related safety concerns in its use and implementation.2 This paper has further fuelled the boon or bane debate of health IT.3
Ironically, the implementation of a national, multifaceted, quality improvement (QI) programme of ‘de-implementing’ electronic health record (EHR) notifications to primary care physicians (PCPs) has shown some benefit.1 This has, in some way, proven that being too reliant on technology in healthcare may yet rear its ugly head.
The paper has shown that high volume of EHR notifications can overwhelm PCPs;1 the proposed measure of breaking these down into “low-value” and “high-value”, and enforcing certain mandatory ones, may merely be an intermediate stopgap technique. Determining which is which, by its nature, is difficult to do and standardise.
Further, implementing a nationwide programme such as this poses certain challenges that the authors have not considered – will there be a difference between urban and rural healthcare facilities in its implementation, given resource limitations?4 Will technology have improved or changed by the time this programme is fully implemented nationwide?...
I read this paper1 first published on 5 March 2018 in your journal with great interest.
The great pace of health information technology (health IT) advancement in recent decades held promise in improving patient safety and quality of care, but unfortunately there has since been inadvertent consequences and carry-over effects of technology-related safety concerns in its use and implementation.2 This paper has further fuelled the boon or bane debate of health IT.3
Ironically, the implementation of a national, multifaceted, quality improvement (QI) programme of ‘de-implementing’ electronic health record (EHR) notifications to primary care physicians (PCPs) has shown some benefit.1 This has, in some way, proven that being too reliant on technology in healthcare may yet rear its ugly head.
The paper has shown that high volume of EHR notifications can overwhelm PCPs;1 the proposed measure of breaking these down into “low-value” and “high-value”, and enforcing certain mandatory ones, may merely be an intermediate stopgap technique. Determining which is which, by its nature, is difficult to do and standardise.
Further, implementing a nationwide programme such as this poses certain challenges that the authors have not considered – will there be a difference between urban and rural healthcare facilities in its implementation, given resource limitations?4 Will technology have improved or changed by the time this programme is fully implemented nationwide? If so, the costs of constantly chasing our technological tails will be great, especially if applied to larger countries, or ones with sprawling rural/regional areas like in Australia.
National programmes pose other barriers as well: would measurements be commensurate with other driving factors like local differences in practice and accessibility? The authors assumed that reduced notifications is a positive outcome, but if a regional facility has limited access to certain diagnostic tools or treatment capacity, the EHR notifications for these things will inevitably be less. Does that truly mean that the medicine practised in these areas are optimal and evidence-based, as espoused by the article?
But the paper has also shown that technological de-implementation of a health IT system is a double-edged sword. The results have indicated that there are PCPs and facilities enabling higher notifications post-intervention.1 Perhaps the real issue here isn’t using one form of technology to counter another’s pitfalls: we’re so focussed on technology alone where we’ve become so used to ordering diagnostic tests and monitoring because of its availability, at the expense of proper clinical practice and reasons, that we need to be constantly reminded of what we’ve ordered. Perhaps we should aim to integrate technology into a healthcare culture where principles of safety and quality are emphasised instead.5
(430 words)
References:
1. Shah T, Patel-Teague S, Kroupa L, et al. Impact of a national QI programme on reducing electronic health record notifications to clinicians. BMJ quality & safety 2018 doi: 10.1136/bmjqs-2017-007447
2. Magrabi F, Aarts J, Nohr C, et al. A comparative review of patient safety initiatives for national health information technology. International journal of medical informatics 2013;82(5):e139-48. doi: 10.1016/j.ijmedinf.2012.11.014 [published Online First: 2012/12/26]
3. Jacobson J. Health information technology: bane or boon? The American journal of nursing 2014;114(12):18-9. doi: 10.1097/01.Naj.0000457401.30598.69 [published Online First: 2014/11/26]
4. Chipp CL, Johnson ME, Brems C, et al. Adaptations to Health Care Barriers as Reported by Rural and Urban Providers. Journal of health care for the poor and underserved 2008;19(2):532-49. doi: 10.1353/hpu.0.0002
5. Thimbleby H. Technology and the Future of Healthcare. Journal of Public Health Research 2013;2(3):e28. doi: 10.4081/jphr.2013.e28
Hemming et al. (“Ethical Implications of Excessive Cluster Sizes in Cluster Randomized Trials,” 20 February 2018) cite the FIRST Trial as an example of a “higher risk” cluster-randomized trial in which large cluster sizes pose unjustifiable excess risk. The authors state, “[t]he obvious way to reduce the cluster size in this study is to reduce the duration of the trial…”
We believe this to be an inappropriate recommendation stemming from an inaccurate appraisal of the FIRST Trial.
The FIRST Trial was designed to inform a potential policy change in U.S. resident duty hours. In the Statistical Analysis Plan, which was made available at www.nejm.org, we clearly and prospectively stated that “[t]his study is a trial-based evaluation of potential policy effects on patient safety and resident wellbeing... this study is intended to inform real-world policy decision-making with respect to resident duty hours regulation.”[1] The SAP and Supplemental Appendix (www.nejm.org) also provides all assumptions for our power calculations and cluster sizes, which were not large in the case of resident outcomes.[2]
As such, it was important that the trial closely resemble real-world conditions in which residency training occurs and duty hour policies are implemented. A shorter study would pose risks owing to non-standard, multiple policy shifts and would increase administrative/organizational bu...
Hemming et al. (“Ethical Implications of Excessive Cluster Sizes in Cluster Randomized Trials,” 20 February 2018) cite the FIRST Trial as an example of a “higher risk” cluster-randomized trial in which large cluster sizes pose unjustifiable excess risk. The authors state, “[t]he obvious way to reduce the cluster size in this study is to reduce the duration of the trial…”
We believe this to be an inappropriate recommendation stemming from an inaccurate appraisal of the FIRST Trial.
The FIRST Trial was designed to inform a potential policy change in U.S. resident duty hours. In the Statistical Analysis Plan, which was made available at www.nejm.org, we clearly and prospectively stated that “[t]his study is a trial-based evaluation of potential policy effects on patient safety and resident wellbeing... this study is intended to inform real-world policy decision-making with respect to resident duty hours regulation.”[1] The SAP and Supplemental Appendix (www.nejm.org) also provides all assumptions for our power calculations and cluster sizes, which were not large in the case of resident outcomes.[2]
As such, it was important that the trial closely resemble real-world conditions in which residency training occurs and duty hour policies are implemented. A shorter study would pose risks owing to non-standard, multiple policy shifts and would increase administrative/organizational burdens of staff workflow coordination. Moreover, a shorter period would threaten external validity, rendering evidence from the study potentially uninformative for policy decisions that could affect the lives of millions. Thus, a shorter study would be of little social benefit while imposing unjustifiable risks and burden. A planned interim analysis was independently reviewed by a Data Safety Monitoring Board out of consideration for patient safety, but termination was unwarranted.[3]
If the policy intervention is ethically unacceptable, the study should not be done under any time frame. Yet, the debate over U.S. resident duty hours is marked by equipoise: it is not at all clear that flexible duty hours pose greater risk than duty hour regulations that interrupt critical patient care (e.g., leaving during an operation) or lead to more patient care hand offs.[4] Considerable literature demonstrates adverse effects on patient outcomes of excessive care transitions [5,6] along with residents’ concerns that training may suffer with reductions in duty hours.[7-10]
Hemming et al. are well-intentioned in articulating ethical concerns arising from gratuitously large clusters. However, in trials designed to inform policy, the importance of external validity may justify ostensibly “large” cluster sizes.
Respectfully yours,
Karl Y. Bilimoria, M.D., M.S.
Jeanette W. Chung, Ph.D.
Larry V. Hedges, Ph.D.
[4] Philibert I, Nasca T, Brigham T, Shapiro J. Duty-hour limits and patient care and resident outcomes: can high-quality studies offer insight into complex relationships? Ann Rev Med. 2013;64:467-483
[5] Denson JL, Jensen A, Saag HS, et al. Association between end-of-rotation resident transition in care and mortality among hospitalized patients. JAMA. 2016;316(21):2204-2213
[6] Denson JL, McCarty M, Fang Y, et al. Increased mortality rates during resident handoff periods and the effect of ACGME duty hour regulations. Am J Med. 2015;128(9):994-1000
[7] Ahmed N, Devitt KS, Kshet I, et al. A systematic review of the effects of resident duty hour restrictions in surgery: impact on resident wellness, training, and patient outcomes. Ann Surg. 2014;259(6):1041-1053
[8] Drolet BC, Spalluto LB, Fischer SB. Residents’ perspectives on ACGME regulation of supervision and duty horus – a national survey. N Engl J Med. 2010;363:e34
[9] Drolet BC, Christopher DA, Fischer SA. Residents’ response to duty-hour regulations – a follow-up national survey. N Engl J Med. 2012;366:e35
[10] Fargen KM, Chakraborty A, Friedman WA. Results of a national neurosurgery resident survey on duty hour regulations. Neurosurgery. 2011;69(6):1162-1170
Conventional statistical process control (SPC) has limitations when used with hospital averse event (AE) data. Much data, especially hospital infections like bacteraemias, arise in complex systems.1 These differ from the simple or complicated industrial systems that produce data that are analysed with such success with conventional SPC. AE data arising in complex systems are often nonlinear. Expected values are often unknown. There is often delay in obtaining the AE data e.g. with bacteraemia data – the patient has symptoms, a blood sample is obtained, it is sent to pathology for culture, analysis and reporting and is finally placed in a suitable database then analysed (one of the benefits of conventional SPC is in providing rapid feedback so an industrial process that is going out of control is promptly identified). Most hospital AEs are relatively uncommon and alert staff such as those in Infection Management will frequently detect a change well before a statistical analysis. However, analysis using a time-series chart is still desirable. It can add confirmation to the observations of Infection Management and Quality Improvement staff. A hospital department can summarise its performance with a chart. Management and the public can be informed. A problem is devising control limits about an often non-existent expected value using a linear mean value that may be atypical of much of the data.
How may this dilemma be overcome? The often changing predicted mean value can...
Conventional statistical process control (SPC) has limitations when used with hospital averse event (AE) data. Much data, especially hospital infections like bacteraemias, arise in complex systems.1 These differ from the simple or complicated industrial systems that produce data that are analysed with such success with conventional SPC. AE data arising in complex systems are often nonlinear. Expected values are often unknown. There is often delay in obtaining the AE data e.g. with bacteraemia data – the patient has symptoms, a blood sample is obtained, it is sent to pathology for culture, analysis and reporting and is finally placed in a suitable database then analysed (one of the benefits of conventional SPC is in providing rapid feedback so an industrial process that is going out of control is promptly identified). Most hospital AEs are relatively uncommon and alert staff such as those in Infection Management will frequently detect a change well before a statistical analysis. However, analysis using a time-series chart is still desirable. It can add confirmation to the observations of Infection Management and Quality Improvement staff. A hospital department can summarise its performance with a chart. Management and the public can be informed. A problem is devising control limits about an often non-existent expected value using a linear mean value that may be atypical of much of the data.
How may this dilemma be overcome? The often changing predicted mean value can be shown well using a generalised additive model (GAM). Its confidence limits can be useful as they delimit the range of the predicted mean supported by the GAM analysis. Trends and change-points may be identified. However, this fails to address potentially outlying individual observations such as large monthly counts and rates. It is suggested that the supported ranges identified by the confidence intervals about the individual monthly values can help identify outliers. Finally, a seasonal trend test can help identify the trends and change-points that frequently accompany determined efforts to improve or that complicate a deteriorating process. Admittedly, these observations apply chiefly to rate data such as bacteraemias and new isolates of antibiotic-resistant organisms. However, there are also binary data to which they apply.
Reference
1. Morton, A., Whitby, M., Tierney, N., Sibanda, N. and Mengersen, K. 2016. Statistical Methods for Hospital Monitoring. Wiley StatsRef: Statistics Reference Online. 1–8.
[This is a revision of a submission from earlier today that contains references.]
To the editor:
We read Weenink, et al.’s review of remediation and rehabilitation programs for healthcare professionals with interest.1 It is among the most systematic and certainly the most internationally focused reviews to date. The article noted, “the aim of these programs is two-fold: to help professionals with problems and to protect patients from professionals who are unable to perform adequately.” This important point is in direct alignment with the Federation of State Physician Health Program’s (FSPHP) philosophy of supporting our member programs in their mission of early detection of potentially impairing illness. As members of the leadership of the Federation of State Physician Health Programs (FSPHP), we laud this review and believe additional commentary is worthwhile.
In the U.S. and Canada, each Physician Health Program (PHP) is unique in its scope of services, funding and the types of healthcare professionals served.2 In the U.S., we trace our roots back to a seminal paper that appeared in the Journal of the American Medical Association (AMA) in 1973.3 As Weenink, et al. noted, all programs provide services for professionals with substance use disorders and other mental health conditions. PHPs do not provide treatment, rather, we provide care coordination and monitoring for health professionals with impairing illness. The FSPHP brings together PHPs in the U....
[This is a revision of a submission from earlier today that contains references.]
To the editor:
We read Weenink, et al.’s review of remediation and rehabilitation programs for healthcare professionals with interest.1 It is among the most systematic and certainly the most internationally focused reviews to date. The article noted, “the aim of these programs is two-fold: to help professionals with problems and to protect patients from professionals who are unable to perform adequately.” This important point is in direct alignment with the Federation of State Physician Health Program’s (FSPHP) philosophy of supporting our member programs in their mission of early detection of potentially impairing illness. As members of the leadership of the Federation of State Physician Health Programs (FSPHP), we laud this review and believe additional commentary is worthwhile.
In the U.S. and Canada, each Physician Health Program (PHP) is unique in its scope of services, funding and the types of healthcare professionals served.2 In the U.S., we trace our roots back to a seminal paper that appeared in the Journal of the American Medical Association (AMA) in 1973.3 As Weenink, et al. noted, all programs provide services for professionals with substance use disorders and other mental health conditions. PHPs do not provide treatment, rather, we provide care coordination and monitoring for health professionals with impairing illness. The FSPHP brings together PHPs in the U.S. and Canada. We are working to expand and improve services we provide to healthcare workers.
As noted, multiple studies confirm the PHP model’s remarkable remission rates from substance use disorders. The combination of sufficient initial treatment, often amongst a cohort of peers, with chronic disease management (comprised of frequent random substance screening, ongoing support group attendance and needed adjuvant pharmacotherapy, psychotherapy and psychiatric care) results in a five-year remission rate of approximately 80 percent. Remarkably this chronic disease management model shows exactly the same efficacy in opioid use disorders as other substance problems.4 This stands in sharp contrast to the suboptimal outcomes seen in the general population as we struggle to find solutions to the international problem of opioid use disorders. The outcomes achieved by PHPs have led to assertions this model of treatment should be considered for all addiction disorders, including opioid use disorders.5
Outcomes for other behavioral health conditions have been less clear, with few papers addressing outcomes in this area.6 We believe this is partly due to the lack of a uniform systematic disease management model for treating depressive illnesses, stress and burnout among physicians and other healthcare workers. The FSPHP is the North American forum of evolving concepts in in the management of chronic mental health conditions.
PHPs in the U.S. and Canada are less directly involved with medical skill dyscompetence per se, except in cases where the dyscompetence arises from, or is exacerbated by, interpersonal difficulties, behavioral or medical illness. In North America, such problems are more often addressed through credentialing bodies and medical boards (US) and colleges (Canada). A network of evaluators assess physician competency and assist PHPs, medical boards and medical colleges in determining individual needs and remediation strategies.
Maintaining a healthy and competent healthcare workforce requires a collaborative effort by organized medicine inclusive of the multiple stakeholders that oversee and/or represent health professionals. We see Weenink, et al.’s fine paper as a call to action to do more. The FSPHP is eager to answer this call by sharing our efforts collaboratively with our international partners to enhance, expand and explore current and future pathways to a safe healthcare workforce around the world. Surely, we owe all those we serve in the day to day practice of medicine the “globalization” of effective models of remediation and rehabilitation for healthcare professionals.
Paul H. Earley, M.D., DFASAM
Brad Hall, M.D., DABAM, DFASAM, MROCC, AAMRO
Chris Bundy, MD, MPH
References
1. J.-W. Weenink, R. B. Kool, R. H. Bartels, and G. P. Westert. "Getting Back on Track: A Systematic Review of the Outcomes of Remediation and Rehabilitation Programmes for Healthcare Professionals with Performance Concerns." British Medical Journal Quality & Safety 26, no. 12 (2017): 1004.
2. R. DuPont, A. McLellan, G. Carr, M. Gendel, and G. Skipper. "How Are Addicted Physicians Treated? A National Survey of Physician Health Programs." J Subst Abuse Treat 37, no. 1 (2009): 1-7.
3. AMA Council on Mental Health. "The Sick Physician: Impairment by Psychiatric Disorders, Including Alcoholism and Drug Dependence." JAMA 223, no. 6 (1973): 684-87.
4. K. Domino, T. F. Hornbein, N. L. Polissar, G. Renner, J. Johnson, S. Alberti, and L. Hankes. "Risk Factors for Relapse in Health Care Professionals with Substance Use Disorders." JAMA 293, no. 12 (2005): 1453-60.
5. R. L. DuPont, W. M. Compton, and A. T. McLellan. "Five-Year Recovery: A New Standard for Assessing Effectiveness of Substance Use Disorder Treatment." J Subst Abuse Treat 58 (2015): 1-5.
6. J. R. Knight, L. T. Sanchez, L. Sherritt, L. R. Bresnahan, and J. A. Fromson. "Outcomes of a Monitoring Program for Physicians with Mental and Behavioral Health Problems." J Psychiatr Pract 13, no. 1 (2007): 25-32.
The authors should be commended for highlighting some of the groundbreaking work on behavioral economics and touching on the potential for nudging in the clinical setting.1 Recently, others have advocated for the broad incorporation or nudge units within health systems.2 While the authors focus on physician-oriented nudges, for patient-directed nudges in particular, reflecting on the ethical implications of the nudge, and deciding to what degree patient autonomy is compromised, may be particularly important for physicians embarking on incorporating choice architecture into practice.
There is an important distinction between engaging in what the original proponents of nudging termed “libertarian paternalism” (e.g., encouraging smoking cessation),3 and self-serving nudging (e.g., encouraging patients to choose a particular procedure or treatment, which may also benefit the physician or health care system).4 Indeed, concerns abound regarding the ethics of nudging the informed consent process, and pharmaceutical companies’ reliance on similar heuristics to improve sales is well established.5,6
It is also worth highlighting that nudges are often experimental; as such, it is not always clear that they will have the desired effect, further stressing the need for an ethical pause. While these concerns are implicitly acknowledged by the authors, given the potential impact of nudges, and the lack of patient-facing transparency in developing choice architecture—a defini...
The authors should be commended for highlighting some of the groundbreaking work on behavioral economics and touching on the potential for nudging in the clinical setting.1 Recently, others have advocated for the broad incorporation or nudge units within health systems.2 While the authors focus on physician-oriented nudges, for patient-directed nudges in particular, reflecting on the ethical implications of the nudge, and deciding to what degree patient autonomy is compromised, may be particularly important for physicians embarking on incorporating choice architecture into practice.
There is an important distinction between engaging in what the original proponents of nudging termed “libertarian paternalism” (e.g., encouraging smoking cessation),3 and self-serving nudging (e.g., encouraging patients to choose a particular procedure or treatment, which may also benefit the physician or health care system).4 Indeed, concerns abound regarding the ethics of nudging the informed consent process, and pharmaceutical companies’ reliance on similar heuristics to improve sales is well established.5,6
It is also worth highlighting that nudges are often experimental; as such, it is not always clear that they will have the desired effect, further stressing the need for an ethical pause. While these concerns are implicitly acknowledged by the authors, given the potential impact of nudges, and the lack of patient-facing transparency in developing choice architecture—a defining feature of a nudge—it may be prudent to explicitly incorporate careful ethical debate as an early step in the deployment process.
References
1. Vaughn VM, Linder JA. Thoughtless design of the electronic health record drives overuse, but purposeful design can nudge improved patient care. BMJ Qual Saf 2018.
2. Patel MS, Volpp KG, Asch DA. Nudge Units to Improve the Delivery of Health Care. N Engl J Med 2018;378:214-6.
3. Thaler RHS, C.R. Nudge: Improving Decisions About Health, Wealth, and Happiness. New York: Penguin Books; 2009.
4. Simkulet W. Nudging, informed consent and bullshit. J Med Ethics 2017.
5. Brooks T. Should we nudge informed consent? Am J Bioeth 2013;13:22-3.
6. Ploug T, Holm S. Pharmaceutical "nudging"--reinterpreting the ethics of evaluative conditioning. Am J Bioeth 2013;13:25-7.
Gagliardi and her Canadian colleagues must be commended for calling a spade a spade: “there may be little point in solely educating or incentivising individual physicians to report adverse medical device events unless environmental conditions are conducive to doing so”.(1) “Environmental conditions” being “healthcare system capacity and industry responsiveness”.(1) The French state of affairs illustrates the latter is not about unresponsiveness but deliberate obstructions.
First, in March 2017, after serial warning letters, the French regulatory agency required withdrawal of YSY Medical’s medical devices within a 6 months delay as devices have been marketed without CE marking (Conformité Européenne _European Conformity, in 1985 France was a leader in the Union_ which is about basic safety standards (eg. no explosion, no electrocution …). YSY Medical challenged the decision before a regional administrative court which: a) considered the topic was in its jurisdiction; b) issued an emergency ruling to suspend the Agency’s decision. The Conseil d’Etat, France’s highest court, confirmed the ruling in 2018.(2)
Second, after a suit by the Snitem (National Union of Medical Technologies Industries) and Medtech (an association of 40 companies), the Conseil d’Etat just cancelled a decree (#1716. 13 Dec 2016) requiring a summary of product characteristics for class III and implantable devices.
However, France is improving. In 2009, the Agency’s director wrote “...
Gagliardi and her Canadian colleagues must be commended for calling a spade a spade: “there may be little point in solely educating or incentivising individual physicians to report adverse medical device events unless environmental conditions are conducive to doing so”.(1) “Environmental conditions” being “healthcare system capacity and industry responsiveness”.(1) The French state of affairs illustrates the latter is not about unresponsiveness but deliberate obstructions.
First, in March 2017, after serial warning letters, the French regulatory agency required withdrawal of YSY Medical’s medical devices within a 6 months delay as devices have been marketed without CE marking (Conformité Européenne _European Conformity, in 1985 France was a leader in the Union_ which is about basic safety standards (eg. no explosion, no electrocution …). YSY Medical challenged the decision before a regional administrative court which: a) considered the topic was in its jurisdiction; b) issued an emergency ruling to suspend the Agency’s decision. The Conseil d’Etat, France’s highest court, confirmed the ruling in 2018.(2)
Second, after a suit by the Snitem (National Union of Medical Technologies Industries) and Medtech (an association of 40 companies), the Conseil d’Etat just cancelled a decree (#1716. 13 Dec 2016) requiring a summary of product characteristics for class III and implantable devices.
However, France is improving. In 2009, the Agency’s director wrote “rapid obsolescene of the products ... is hardly compatible with the delay necessary for clinical trials, particularly morbidity-mortality data.” and recommended “predictive equivalence, the check of the results of the specific test Bench”.(3)
The weak regulation of medical devices, for both efficacy and safety, is an exception in the healthcare system. Exceptions in health never benefit to patients.
1 Gagliardi AR, Ducey A, Lehoux P et al. Factors influencing the reporting of adverse medical device events: qualitative interviews with physicians about higher risk implantable devices. BMJ Qual Saf 2018;27:190-198.
2 Braillon A. Assessment of medical devices: the Emperor's new clothes. Br J Radiol 2018. Online April 24. doi: 10.1259/bjr.20180242
3 Braillon A. Medical devices and the approval processes: United States vs France. Arch Intern Med. 2010;170:2040-1.
The population with intellectual disabilities have multiple morbidities and greater health needs compared with the general population. This population experiences health and healthcare inequities and inequalities. To reduce the health inequality gap people with intellectual disabilities should be involved as partners in their healthcare. This will require access to relevant information and the development of tools that support collaboration, such as tailored patient decision aids (PDA) (1).
The population with intellectual disabilities is rarely considered or involved (2)at the guideline development stage. The consequent failure of clinical guidelines to adequately address the health needs of people with intellectual disabilities exacerbates already poor access to health and healthcare. An examination of clinical guidelines from seven countries(3) found that most clinical guidelines failed to address people with intellectual disabilities as being at high risk for particular conditions when appropriate.
Guidelines and PDAs developed with the general population in mind may not reflect the complexity and multi-morbidity of individual patients with intellectual disabilities and their ‘real world’ lives. Many people with intellectual disabilities have visual, hearing, mobility, memory and dexterity difficulties. Clinicians and guidelines developers may not be aware of the complexity of the task their ask their patients with intellectual disabilities and their...
The population with intellectual disabilities have multiple morbidities and greater health needs compared with the general population. This population experiences health and healthcare inequities and inequalities. To reduce the health inequality gap people with intellectual disabilities should be involved as partners in their healthcare. This will require access to relevant information and the development of tools that support collaboration, such as tailored patient decision aids (PDA) (1).
The population with intellectual disabilities is rarely considered or involved (2)at the guideline development stage. The consequent failure of clinical guidelines to adequately address the health needs of people with intellectual disabilities exacerbates already poor access to health and healthcare. An examination of clinical guidelines from seven countries(3) found that most clinical guidelines failed to address people with intellectual disabilities as being at high risk for particular conditions when appropriate.
Guidelines and PDAs developed with the general population in mind may not reflect the complexity and multi-morbidity of individual patients with intellectual disabilities and their ‘real world’ lives. Many people with intellectual disabilities have visual, hearing, mobility, memory and dexterity difficulties. Clinicians and guidelines developers may not be aware of the complexity of the task their ask their patients with intellectual disabilities and their carers to undertake e.g. blood glucose monitoring, sliding scale insulin administration, inhaler use, administration of epilepsy rescue medication etc..
Significant gaps in the reporting of evaluations of PDAs have been identified (4). The SUNDAE Checklist (Standards for UNiversal reporting of patient Decision Aid Evaluations) should facilitate evaluation of any PDA, in ‘hard to reach’ population groups, such as the population with intellectual disabilities.
Before applying a guideline or using PDAs with a person with an intellectual disability the following questions could be asked
• Does this person with an intellectual disability understand the connection between the illness and some consequent intervention e.g. diet/exercise, prescribed medication, blood testing?
• What level of health literacy has the person with intellectual disability and/or their carer?
• Do the outcomes measured matter to this person with intellectual disability?
• Is this person with intellectual disability very different from the people studied?
• Are the treatments practical in the ‘real world’ living environment of this person with intellectual disability?
• Do treatment comparisons reflect the circumstances of the person with intellectual disability?
• How certain can the evidence be applied to a person with intellectual disability?
• Do the advantages outweigh the disadvantages for this person with intellectual disability?
1. BMJ 2017; editorial Shehan, Strydom, Hassiotis 358 doi: https://doi.org/10.1136/bmj.j3896
2. Mizen LAM, Maclie ML, Cooper S-A, Melville CA. Clinical guidelines contribute to the health inequities experienced by individuals with intellectual disabilities. Implementation Science. 2012;7(42):1–9.
3. Mizen LAM, Maclie ML, Cooper S-A, Melville CA. Clinical guidelines contribute to the health inequities experienced by individuals with intellectual disabilities. Implementation Science. 2012;7(42):1–9
4. Sepucha KR, Abhyankar P, Hoffman AS, et al. Standards for UNiversal reporting of patient Decision Aid Evaluation studies: the development of SUNDAE Checklist. BMJ Qual Saf Published Online First: 21 December 2017. doi: 10.1136/bmjqs-2017-006986
We read with great interest the original research done by Stagg et al where rates of unnecessary antibiotic use for asymptomatic bacteriuria (ASB) were decreased by implementing a two-step urine culture algorithm in the emergency department (ED). [1] We want to congratulate the authors for their successful research, and hope that algorithms such as the two-step ordering process will be implemented as widespread protocol to help decrease the overutilization of antibiotics for ASB.
We have presented the findings of our own retrospective observational IRB-approved study performed at a 695-bed academic medical center to discern the downstream impact of routine urinalysis and urine cultures ordered from the ED on antibiotic prescribing. We hope these results will add to the growing body of evidence for stricter protocol regarding urine testing and subsequent treatment. The primary objective of our study was to evaluate the incidence of antibiotic treatment based on urinalysis and urine culture results with or without associated urinary symptoms. Secondary objectives included: incidence of symptoms documented in the medical record for patients who were ordered a urinalysis with or without urine culture, incidence of antibiotic treatment of ASB, and quantification of mean antibiotic dose given to patients with clinically defined ASB.
Adult patients who had urinalysis with or without a urine culture performed in the ED were identified and randomized by reports genera...
We read with great interest the original research done by Stagg et al where rates of unnecessary antibiotic use for asymptomatic bacteriuria (ASB) were decreased by implementing a two-step urine culture algorithm in the emergency department (ED). [1] We want to congratulate the authors for their successful research, and hope that algorithms such as the two-step ordering process will be implemented as widespread protocol to help decrease the overutilization of antibiotics for ASB.
We have presented the findings of our own retrospective observational IRB-approved study performed at a 695-bed academic medical center to discern the downstream impact of routine urinalysis and urine cultures ordered from the ED on antibiotic prescribing. We hope these results will add to the growing body of evidence for stricter protocol regarding urine testing and subsequent treatment. The primary objective of our study was to evaluate the incidence of antibiotic treatment based on urinalysis and urine culture results with or without associated urinary symptoms. Secondary objectives included: incidence of symptoms documented in the medical record for patients who were ordered a urinalysis with or without urine culture, incidence of antibiotic treatment of ASB, and quantification of mean antibiotic dose given to patients with clinically defined ASB.
Adult patients who had urinalysis with or without a urine culture performed in the ED were identified and randomized by reports generated through the quality department from 2016. Patients were excluded if they were incarcerated, had other indications of antibiotics on admission, had a planned urological procedure within 48 hours, pregnant, or had charts containing incomplete data. The final convenience sample size of 432 included patients were analyzed.
In general, patients were more likely not to have classical urinary symptoms (symptomatic: n=65, 15%; asymptomatic: n=367, 85%). Urine cultures were ordered in 151 patients (symptomatic: n=33, 51%; asymptomatic: n=118, 32%; p=0.004); of which, 53 (35%) had a positive culture result. Most of these patients (n=38, 72%) were asymptomatic; yet, they received inappropriate antibiotics for treatment of ASB (n=25, 66%). Typically, patients received third-generation cephalosporins (n=16, 64%) or a fluoroquinolone (n=4, 16%) and were treated for an average of 3 days. This correlates with our previously published data showing a 62% inappropriate treatment rate of ASB at our institution five years prior to this cohort. Previously, we decreased this rate to 26% following an education period. [2]
Lab ordering algorithms, such as the one used by Stagg et al, would address the issues found in our institution. We educated prescribers on the overtreatment of ASB, but demonstrated that educational initiatives at academic hospitals lose effectiveness over time. Antimicrobial stewardship programs (ASPs) can leverage electronic medical record prescribing to educate clinicians on appropriate ordering of urine tests when patients lack classical and non-classical urinary symptoms. Two-step urine culture ordering, combined with additional rationale for urine culture processing (documentation of urinary symptoms in the processing order), would allow for additional stop measures to ensure appropriate urine culture ordering, provide documentation for clinicians to retrospectively audit the process, and promote lab stewardship on the front lines. Inappropriate management of patients with ASB has been a substantial challenge for ASPs over the past ten years that has brought unfortunate burdens on the healthcare system that we as clinicians have the power to stop.
REFERENCES:
1 Stagg A, Lutz H, Kirpalaney S, et al. Impact of two-step urine culture ordering in the emergency department: a time series analysis. BMJ Qual Saf. 2018;2:140-147.
2 Kelley D, Aaronson P, Poon E, et al. Evaluation of an antimicrobial stewardship approach to minimize overuse of antibiotics in patients with asymptomatic bacteriuria. Infect Control Hosp Epidemiol. 2014;2:193-5.
Krein, et al (Patient-Reported Complications Related to Peripherally Inserted Central Catheters: A Multicenter Prospective Cohort Study; Feb 2019) should be commended for sharing the results of this very interesting study. After reading it a few times, I am compelled to share the following concerns with you and the research team. The knowledge regarding PICC-related complications is indeed incomplete, but I am not sure if the main outcome(s) of your study are clearly represented to the reader.
The word “possible” is critical to correctly interpreting the results of this study. The term “complication” implies a medical diagnosis or medical confirmation – which your study attempted to do by conducting the chart reviews to confirm the presence or absence of a PICC complication, with limited success. Terms such as signs, symptoms, issues, adverse effects, and complications are used interchangeably throughout the paper to describe the patients’ self-reported experience, but without the benefit of operational definitions. These are not synonyms. Definitions help us to have a common understanding of a word or topic; they help us get on the same page when reading about an issue.
The word “possible” seems appropriate in the main outcome(s) statement, but is curiously missing from the report title. The phrase “medical complications” is used in the title of Table 2 – which clearly reports predominantly patient self-reported symptoms. The same bias is exhibited...
Show MoreO’Reilly-Shah et al. present a novel approach to quality improvement in anaesthesia by attempting to elicit change in practice using ‘nudge theory’ derived from the field of behavioural economics [1]. Translating new research evidence into common clinical practice is an important quality issue and cheap and effective strategies to achieve this are of interest. O’Reilly-Shah et al. hypothesised that using ‘nudge-type’ interventions, an audit-feedback dashboard as well as changes to mechanical ventilator default settings, might improve anaesthesia provider compliance with this ‘lung protective’ ventilation strategy in the general operating theatre environment.
Show MoreI disagree with the conclusion that the authors have drawn, that these interventions might improve clinical and financial outcomes. My disagreement stems from the clinical rationale of the intervention, which overlaps onto the assumptions built into the ‘nudge theory’ of behavioural economics itself.
Sunstein & Thaler, who have influenced large scale policy making in several countries, describe nudge theory as a form of choice architecture that “alters people’s behaviour in a predictable way without forbidding any options or significantly changing their economic incentives” [2, 3]. Their philosophy is described as “libertarian paternalism”, as it influences choices that make people better off as judged by themselves, while preserving their freedom to choose otherwise. This is presumably what the interve...
I read this paper1 first published on 5 March 2018 in your journal with great interest.
The great pace of health information technology (health IT) advancement in recent decades held promise in improving patient safety and quality of care, but unfortunately there has since been inadvertent consequences and carry-over effects of technology-related safety concerns in its use and implementation.2 This paper has further fuelled the boon or bane debate of health IT.3
Ironically, the implementation of a national, multifaceted, quality improvement (QI) programme of ‘de-implementing’ electronic health record (EHR) notifications to primary care physicians (PCPs) has shown some benefit.1 This has, in some way, proven that being too reliant on technology in healthcare may yet rear its ugly head.
The paper has shown that high volume of EHR notifications can overwhelm PCPs;1 the proposed measure of breaking these down into “low-value” and “high-value”, and enforcing certain mandatory ones, may merely be an intermediate stopgap technique. Determining which is which, by its nature, is difficult to do and standardise.
Further, implementing a nationwide programme such as this poses certain challenges that the authors have not considered – will there be a difference between urban and rural healthcare facilities in its implementation, given resource limitations?4 Will technology have improved or changed by the time this programme is fully implemented nationwide?...
Show MoreHemming et al. (“Ethical Implications of Excessive Cluster Sizes in Cluster Randomized Trials,” 20 February 2018) cite the FIRST Trial as an example of a “higher risk” cluster-randomized trial in which large cluster sizes pose unjustifiable excess risk. The authors state, “[t]he obvious way to reduce the cluster size in this study is to reduce the duration of the trial…”
We believe this to be an inappropriate recommendation stemming from an inaccurate appraisal of the FIRST Trial.
The FIRST Trial was designed to inform a potential policy change in U.S. resident duty hours. In the Statistical Analysis Plan, which was made available at www.nejm.org, we clearly and prospectively stated that “[t]his study is a trial-based evaluation of potential policy effects on patient safety and resident wellbeing... this study is intended to inform real-world policy decision-making with respect to resident duty hours regulation.”[1] The SAP and Supplemental Appendix (www.nejm.org) also provides all assumptions for our power calculations and cluster sizes, which were not large in the case of resident outcomes.[2]
As such, it was important that the trial closely resemble real-world conditions in which residency training occurs and duty hour policies are implemented. A shorter study would pose risks owing to non-standard, multiple policy shifts and would increase administrative/organizational bu...
Show MoreConventional statistical process control (SPC) has limitations when used with hospital averse event (AE) data. Much data, especially hospital infections like bacteraemias, arise in complex systems.1 These differ from the simple or complicated industrial systems that produce data that are analysed with such success with conventional SPC. AE data arising in complex systems are often nonlinear. Expected values are often unknown. There is often delay in obtaining the AE data e.g. with bacteraemia data – the patient has symptoms, a blood sample is obtained, it is sent to pathology for culture, analysis and reporting and is finally placed in a suitable database then analysed (one of the benefits of conventional SPC is in providing rapid feedback so an industrial process that is going out of control is promptly identified). Most hospital AEs are relatively uncommon and alert staff such as those in Infection Management will frequently detect a change well before a statistical analysis. However, analysis using a time-series chart is still desirable. It can add confirmation to the observations of Infection Management and Quality Improvement staff. A hospital department can summarise its performance with a chart. Management and the public can be informed. A problem is devising control limits about an often non-existent expected value using a linear mean value that may be atypical of much of the data.
How may this dilemma be overcome? The often changing predicted mean value can...
Show More[This is a revision of a submission from earlier today that contains references.]
To the editor:
Show MoreWe read Weenink, et al.’s review of remediation and rehabilitation programs for healthcare professionals with interest.1 It is among the most systematic and certainly the most internationally focused reviews to date. The article noted, “the aim of these programs is two-fold: to help professionals with problems and to protect patients from professionals who are unable to perform adequately.” This important point is in direct alignment with the Federation of State Physician Health Program’s (FSPHP) philosophy of supporting our member programs in their mission of early detection of potentially impairing illness. As members of the leadership of the Federation of State Physician Health Programs (FSPHP), we laud this review and believe additional commentary is worthwhile.
In the U.S. and Canada, each Physician Health Program (PHP) is unique in its scope of services, funding and the types of healthcare professionals served.2 In the U.S., we trace our roots back to a seminal paper that appeared in the Journal of the American Medical Association (AMA) in 1973.3 As Weenink, et al. noted, all programs provide services for professionals with substance use disorders and other mental health conditions. PHPs do not provide treatment, rather, we provide care coordination and monitoring for health professionals with impairing illness. The FSPHP brings together PHPs in the U....
The authors should be commended for highlighting some of the groundbreaking work on behavioral economics and touching on the potential for nudging in the clinical setting.1 Recently, others have advocated for the broad incorporation or nudge units within health systems.2 While the authors focus on physician-oriented nudges, for patient-directed nudges in particular, reflecting on the ethical implications of the nudge, and deciding to what degree patient autonomy is compromised, may be particularly important for physicians embarking on incorporating choice architecture into practice.
There is an important distinction between engaging in what the original proponents of nudging termed “libertarian paternalism” (e.g., encouraging smoking cessation),3 and self-serving nudging (e.g., encouraging patients to choose a particular procedure or treatment, which may also benefit the physician or health care system).4 Indeed, concerns abound regarding the ethics of nudging the informed consent process, and pharmaceutical companies’ reliance on similar heuristics to improve sales is well established.5,6
It is also worth highlighting that nudges are often experimental; as such, it is not always clear that they will have the desired effect, further stressing the need for an ethical pause. While these concerns are implicitly acknowledged by the authors, given the potential impact of nudges, and the lack of patient-facing transparency in developing choice architecture—a defini...
Show MoreGagliardi and her Canadian colleagues must be commended for calling a spade a spade: “there may be little point in solely educating or incentivising individual physicians to report adverse medical device events unless environmental conditions are conducive to doing so”.(1) “Environmental conditions” being “healthcare system capacity and industry responsiveness”.(1) The French state of affairs illustrates the latter is not about unresponsiveness but deliberate obstructions.
First, in March 2017, after serial warning letters, the French regulatory agency required withdrawal of YSY Medical’s medical devices within a 6 months delay as devices have been marketed without CE marking (Conformité Européenne _European Conformity, in 1985 France was a leader in the Union_ which is about basic safety standards (eg. no explosion, no electrocution …). YSY Medical challenged the decision before a regional administrative court which: a) considered the topic was in its jurisdiction; b) issued an emergency ruling to suspend the Agency’s decision. The Conseil d’Etat, France’s highest court, confirmed the ruling in 2018.(2)
Second, after a suit by the Snitem (National Union of Medical Technologies Industries) and Medtech (an association of 40 companies), the Conseil d’Etat just cancelled a decree (#1716. 13 Dec 2016) requiring a summary of product characteristics for class III and implantable devices.
However, France is improving. In 2009, the Agency’s director wrote “...
Show MoreThe population with intellectual disabilities have multiple morbidities and greater health needs compared with the general population. This population experiences health and healthcare inequities and inequalities. To reduce the health inequality gap people with intellectual disabilities should be involved as partners in their healthcare. This will require access to relevant information and the development of tools that support collaboration, such as tailored patient decision aids (PDA) (1).
Show MoreThe population with intellectual disabilities is rarely considered or involved (2)at the guideline development stage. The consequent failure of clinical guidelines to adequately address the health needs of people with intellectual disabilities exacerbates already poor access to health and healthcare. An examination of clinical guidelines from seven countries(3) found that most clinical guidelines failed to address people with intellectual disabilities as being at high risk for particular conditions when appropriate.
Guidelines and PDAs developed with the general population in mind may not reflect the complexity and multi-morbidity of individual patients with intellectual disabilities and their ‘real world’ lives. Many people with intellectual disabilities have visual, hearing, mobility, memory and dexterity difficulties. Clinicians and guidelines developers may not be aware of the complexity of the task their ask their patients with intellectual disabilities and their...
We read with great interest the original research done by Stagg et al where rates of unnecessary antibiotic use for asymptomatic bacteriuria (ASB) were decreased by implementing a two-step urine culture algorithm in the emergency department (ED). [1] We want to congratulate the authors for their successful research, and hope that algorithms such as the two-step ordering process will be implemented as widespread protocol to help decrease the overutilization of antibiotics for ASB.
We have presented the findings of our own retrospective observational IRB-approved study performed at a 695-bed academic medical center to discern the downstream impact of routine urinalysis and urine cultures ordered from the ED on antibiotic prescribing. We hope these results will add to the growing body of evidence for stricter protocol regarding urine testing and subsequent treatment. The primary objective of our study was to evaluate the incidence of antibiotic treatment based on urinalysis and urine culture results with or without associated urinary symptoms. Secondary objectives included: incidence of symptoms documented in the medical record for patients who were ordered a urinalysis with or without urine culture, incidence of antibiotic treatment of ASB, and quantification of mean antibiotic dose given to patients with clinically defined ASB.
Adult patients who had urinalysis with or without a urine culture performed in the ED were identified and randomized by reports genera...
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