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.
Pressure injuries are a largely avoidable adverse patient safety event, which are the focus of considerable global quality improvement efforts. Recent papers by Padula and Pronovost (1) and Squitieri et al. (2) highlight some of the challenges that exist with regards to efforts prevent and reduce the extent of patient harm arising from pressure injuries. These challenges include inconsistent reporting of the extent of pressure injury related harm as evinced by differences in the pressure injury related documentation from different care settings (1, 2) which are thought to be due to financial penalties for nosocomial pressure injuries (1). Padula and Pronovost (1) highlight the fact that the majority of the measurement and reporting of pressure injuries as well as the financial penalties for pressure injuries focus on hospital settings when pressure injury can arise at any point during a patient’s care trajectory. A number of possible solutions are put forward by Padula and Pronovost (1) to avoid underreporting the true extent of pressure injuries and to generate more accurate data that can be used to prevent and reduce the number of patients with pressure injuries in hospitals and other care settings. However, it is worth reflecting on the challenges of measurement and reporting for quality improvement and to considering what other routinely collected pressure injury related data can be used to inform improvement efforts.
Establishing systems in which patient harm i...
Pressure injuries are a largely avoidable adverse patient safety event, which are the focus of considerable global quality improvement efforts. Recent papers by Padula and Pronovost (1) and Squitieri et al. (2) highlight some of the challenges that exist with regards to efforts prevent and reduce the extent of patient harm arising from pressure injuries. These challenges include inconsistent reporting of the extent of pressure injury related harm as evinced by differences in the pressure injury related documentation from different care settings (1, 2) which are thought to be due to financial penalties for nosocomial pressure injuries (1). Padula and Pronovost (1) highlight the fact that the majority of the measurement and reporting of pressure injuries as well as the financial penalties for pressure injuries focus on hospital settings when pressure injury can arise at any point during a patient’s care trajectory. A number of possible solutions are put forward by Padula and Pronovost (1) to avoid underreporting the true extent of pressure injuries and to generate more accurate data that can be used to prevent and reduce the number of patients with pressure injuries in hospitals and other care settings. However, it is worth reflecting on the challenges of measurement and reporting for quality improvement and to considering what other routinely collected pressure injury related data can be used to inform improvement efforts.
Establishing systems in which patient harm is measured and reported in a manner that underpins improvement in healthcare is challenging for a number of reasons. Firstly, many of the measurement instruments have their limitations with regards to utility and ease of use (3). Many of the harms that are subject to measurement are believed to be preventable but it is often challenging to establish the extent to a specific harm can be prevented (3). Pressure injuries are the quintessence of how challenging it can be to ascertain the preventability of a specific harm as they can be arise through the complex interplay of different factors at any point in the patient’s care continuum. The measurement of harm in healthcare is a social practice that is undertaken in complex adaptive system in which a number of organisational contextual, organisational and human factors are at play. The impact of these factors is epitomised by the fact that a focus on measuring harm can have unintended consequences such as gaming and effort substitution (3, 4) which undermine improvement efforts. In addition, measurement systems are often calibrated to report past harms and so provide a limited but important insight into contemporary patient safety (3).
In light of the challenges of measurement, it is important to consider what other sources of routinely collected data can be used to underpin pressure injury related quality improvement efforts. For example, pressure injury related patient safety incident reports often contain ‘soft data’ which helps to identify the human, causative and contributory factors give result in adverse events (5). Therefore, patient safety incident reports provide valuable soft data into aspects of harm that can exist beyond of formal measurement systems and may constitute fugitive knowledge. The analysis of patient safety incident reports has been shown (5) to be an effective way of informing national and population level improvement efforts because patient safety incident reports provide unique insights into the factors that give rise to adverse event which are often overlooked at a local level. It may astute to combine the ‘soft data’ and soft intelligence that can be obtained from pressure injury related patient safety incident reports and other sources with the hard data obtained through formal measures of harm to inform quality improvement interventions.
References
1. Padula WV, Pronovost PJ. Addressing the multisectoral impact of pressure injuries in the USA, UK and abroad. BMJ Quality & Safety. 2018;27(3):171-3.
2. Squitieri L, Ganz DA, Mangione CM, Needleman J, Romano PS, Saliba D, et al. Consistency of pressure injury documentation across interfacility transfers. BMJ Qual Saf. 2018;27(3):182-9.
3. Dixon-Woods M. Measuring what matters: how can we know we are delivering prudent healthcare? Saving 1000 Lives Wales; Cardiff: Saving 1000 Lives Wales Available from: http://www.1000livesplus.wales.nhs.uk/sitesplus/documents/1011/marydixon... 2014.
4. Kelman S, Friedman JN. Performance Improvement and Performance Dysfunction: An Empirical Examination of Distortionary Impacts of the Emergency Room Wait-Time Target in the English National Health Service. Journal of Public Administration Research and Theory. 2009;19(4):917-46.
5. Samuriwo R, Williams H, Cooper J, Carson-Stevens A. Improving skin care through data: a pitch for patient safety incident reporting. Journal of Wound Care. 2016;25(12):691
Sexton et al describe an observed association between leadership WalkRounds (WR) with feedback and improved levels of safety culture within healthcare settings.1 This work builds on previous data from this group evaluating WR in building a safety culture.2 These encouraging findings spur the need for understanding the robustness of evidence that the WR concept is built on in order to evaluate if continuation and expansion of the WR concept should be promulgated.
The research data that WR are based on are largely observational sets or pre and post studies without control groups or objective outcome measures.3 This is fertile ground for bias and confounding that will undermine the probity of the findings. Sources of bias relate to institutional incentives around WR programs succeeding and the want held by individuals to be seen to be implementing initiatives that improve quality. In the present study described by Sexton et al, the cross sectional observational nature of the data collection is exposed to confounding with clinicians involved in a WR program potentially working in an environment with a superior safety culture regardless of the presence of regular WR (with or without feedback).1 Self-selection bias will also be at play as it is with any voluntary survey method as will be recall bias with culturally high achieving environments and poorly functioning settings over and under estimating their performance respectively, and perhaps ascribi...
Sexton et al describe an observed association between leadership WalkRounds (WR) with feedback and improved levels of safety culture within healthcare settings.1 This work builds on previous data from this group evaluating WR in building a safety culture.2 These encouraging findings spur the need for understanding the robustness of evidence that the WR concept is built on in order to evaluate if continuation and expansion of the WR concept should be promulgated.
The research data that WR are based on are largely observational sets or pre and post studies without control groups or objective outcome measures.3 This is fertile ground for bias and confounding that will undermine the probity of the findings. Sources of bias relate to institutional incentives around WR programs succeeding and the want held by individuals to be seen to be implementing initiatives that improve quality. In the present study described by Sexton et al, the cross sectional observational nature of the data collection is exposed to confounding with clinicians involved in a WR program potentially working in an environment with a superior safety culture regardless of the presence of regular WR (with or without feedback).1 Self-selection bias will also be at play as it is with any voluntary survey method as will be recall bias with culturally high achieving environments and poorly functioning settings over and under estimating their performance respectively, and perhaps ascribing this to the presence or absence of WR (with or without feedback). The limited data in this field using a pure WR intervention (outside a bundled intervention) with control groups have reported mixed findings and possibly a detrimental effect of WR in some settings.3,4
Another potential concern may be that the outcome data point most assessed and focused on in the WR area is safety culture or other relatively subjective outcomes that are used as a surrogate for clinical outcomes relying on linked evidence outside of the WR studies.5 Data linking an intervention to improve safety culture with a corresponding recorded enhancement in clinical outcome measures appear to be lacking. As is the case in much of the quality and safety space, studies that employ an empirical randomised controlled trial (RCT) approach with objective clinical endpoints are absent from the literature.
Overall, it might be argued that within the quality and safety field RCTs are not only needed but are perhaps mandatory if the area is to move forward meaningfully. It may seem to some that explanations positioning the area as somehow different or unique when compared with other health spheres is likely to be met with growing cynicism and perhaps the time to turn the corner has arrived.
References:
1. Sexton JB, Adair KC, Leonard MW, Frankel TC, Proulx J, Watson SR, Magnus B, Bogan B, Jamal M, Schwendimann R, Frankel AS. Providing feedback following Leadership WalkRounds is associated with better patient safety culture, higher employee engagement and lower burnout. BMJ Quality & Safety. 2018 Apr;27(4)261-270.
2. Frankel A, Graydon-Baker E, Neppl C, Simmonds T, Gustafson M, Gandhi TK. Patient safety leadership WalkRounds™. Joint Commission Journal on Quality and Patient Safety. 2003 Jan;29(1):16-26.
3. Singer SJ, Tucker AL. The evolving literature on safety WalkRounds: emerging themes and practical messages. BMJ Quality & Safety. 2014 Oct;23(10):789.
4. Singer SJ, Rivard PE, Hayes JE, Shokeen P, Gaba D, Rosen A. Improving patient care through leadership engagement with frontline staff: A Department of Veterans Affairs case study. Joint Commission Journal on Quality and Patient Safety. 2013 Aug;39(8):349-60.
5. DiCuccio MH. The Relationship Between Patient Safety Culture and Patient Outcomes: A Systematic Review. Journal of Patient Safety. 2015 Sep;11(3):135-42.
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...
Show MorePressure injuries are a largely avoidable adverse patient safety event, which are the focus of considerable global quality improvement efforts. Recent papers by Padula and Pronovost (1) and Squitieri et al. (2) highlight some of the challenges that exist with regards to efforts prevent and reduce the extent of patient harm arising from pressure injuries. These challenges include inconsistent reporting of the extent of pressure injury related harm as evinced by differences in the pressure injury related documentation from different care settings (1, 2) which are thought to be due to financial penalties for nosocomial pressure injuries (1). Padula and Pronovost (1) highlight the fact that the majority of the measurement and reporting of pressure injuries as well as the financial penalties for pressure injuries focus on hospital settings when pressure injury can arise at any point during a patient’s care trajectory. A number of possible solutions are put forward by Padula and Pronovost (1) to avoid underreporting the true extent of pressure injuries and to generate more accurate data that can be used to prevent and reduce the number of patients with pressure injuries in hospitals and other care settings. However, it is worth reflecting on the challenges of measurement and reporting for quality improvement and to considering what other routinely collected pressure injury related data can be used to inform improvement efforts.
Show MoreEstablishing systems in which patient harm i...
To the editor,
Sexton et al describe an observed association between leadership WalkRounds (WR) with feedback and improved levels of safety culture within healthcare settings.1 This work builds on previous data from this group evaluating WR in building a safety culture.2 These encouraging findings spur the need for understanding the robustness of evidence that the WR concept is built on in order to evaluate if continuation and expansion of the WR concept should be promulgated.
The research data that WR are based on are largely observational sets or pre and post studies without control groups or objective outcome measures.3 This is fertile ground for bias and confounding that will undermine the probity of the findings. Sources of bias relate to institutional incentives around WR programs succeeding and the want held by individuals to be seen to be implementing initiatives that improve quality. In the present study described by Sexton et al, the cross sectional observational nature of the data collection is exposed to confounding with clinicians involved in a WR program potentially working in an environment with a superior safety culture regardless of the presence of regular WR (with or without feedback).1 Self-selection bias will also be at play as it is with any voluntary survey method as will be recall bias with culturally high achieving environments and poorly functioning settings over and under estimating their performance respectively, and perhaps ascribi...
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