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.
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
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.
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
Authors do not acknowledge some of the most common criticisms of these studies:
(1) Physician health program (PHP) data may be suspect because PHPs benefit from presenting a rosy picture of their effectiveness.
(2) Self-reports from those being evaluated by PHPs, which have much to lose from responding to surveys in ways that criticize these programs, may not be reliable.
(3) There are considerable reasons to doubt that "programme completion," "return to practice," and "no relapse/recurrence" reflect treatment efficacy. Unwarranted referrals may also result in coerced treatment for physicians who do not have a substance use disorder or problematic performance, making "graduation" not meaningful for the purposes of drawing conclusions about PHP treatment effectiveness.
Other concerns with this research will be addressed in forthcoming publications by the commentator.
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 MoreI 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 MoreTo 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...
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...
Authors do not acknowledge some of the most common criticisms of these studies:
(1) Physician health program (PHP) data may be suspect because PHPs benefit from presenting a rosy picture of their effectiveness.
(2) Self-reports from those being evaluated by PHPs, which have much to lose from responding to surveys in ways that criticize these programs, may not be reliable.
(3) There are considerable reasons to doubt that "programme completion," "return to practice," and "no relapse/recurrence" reflect treatment efficacy. Unwarranted referrals may also result in coerced treatment for physicians who do not have a substance use disorder or problematic performance, making "graduation" not meaningful for the purposes of drawing conclusions about PHP treatment effectiveness.
Other concerns with this research will be addressed in forthcoming publications by the commentator.
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