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Acquired immunodeficiency syndrome (Update 2000)

https://policybase.cma.ca/en/permalink/policy165
Last Reviewed
2020-02-29
Date
2000-12-09
Topics
Health care and patient safety
  1 document  
Policy Type
Policy document
Last Reviewed
2020-02-29
Date
2000-12-09
Replaces
Acquired immunodeficiency syndrome (1989)
Topics
Health care and patient safety
Text
Acquired immunodeficiency syndrome (UPDATE 2000) The Canadian Medical Association has developed the following general principles to serve as guidelines for various bodies, health care professionals and the general public. Specific aspects of infection with human immunodeficiency virus (HIV) and acquired immunodeficency syndrome (AIDS) that relate to physicians' ethical responsibilities as well as society's moral obligations are discussed. Such matters include: the need for education, research and treatment resources; the patient's right to investigation and treatment and to refuse either; the need to obtain the patient's informed consent; the right to privacy and confidentiality; the importance of infection control; and the right to financial compensation in the case of occupational exposure to HIV. Education Physicians should keep their knowledge of AIDS and HIV infection up to date. Physicians should educate patients and the general public in the prevention of AIDS by informing them of means available to protect against the risk of HIV infection and to avoid further transmission of the virus. Health authorities should maintain an active public education program on AIDS that includes the school population and such initiatives as public service announcements by the media. Resources All levels of government should provide resources for adequate information and education of health care professionals and the public on HIV-related diseases; research into the prevention and treatment of HIV infection and AIDS; and the availability and accessibility of proper diagnosis and care for all patients with HIV infection. HIV antibody testing Physicians have an ethical responsibility to recommend appropriate testing for HIV antibody and to care for their patients with AIDS or refer them to where treatment is available. Physicians should provide counselling to patients before and after HIV antibody testing. Because of the potential psychologic, social and economic consequences attached to a positive HIV test result, informed consent must, with rare exceptions, be obtained from a patient before testing. However, the CMA endorses informed mandatory testing for HIV infection in cases involving the donation of blood, body fluids or organs. The CMA recognizes that people who have doubts about their serologic status may avoid being tested for fear of indiscretion and therefore supports voluntary non-nominal testing of potential HIV carriers on request. The CMA supports the Canadian Blood Service and Hema-Québec in their programs of testing and screening blood donations and blood products. Confidentiality in reporting and contact tracing The CMA supports the position that cases of HIV infection should be reported non-nominally with enough information to be epidemiologically useful. In addition, each confirmed case of AIDS should be reported non-nominally to a designated authority for epidemiologic purposes. The CMA encourages attending physicians to assist public health authorities to trace and counsel confidentially all contacts of patients with HIV infection. Contact tracing should be carried out with the cooperation and participation of the patient to provide maximum flexibility and effectiveness in alerting and counselling as many potentially infected people as possible. In some jurisdictions physicians may be compelled to provide detailed information to public health authorities. In such circumstances, the CMA urges those involved to maintain confidentiality to the greatest extent possible and to take all reasonable steps to inform the patient that their information is being disclosed. The CMA Code of Ethics (article 22) advises physicians that disclosure of a patient’s HIV status to a spouse or current sexual partner may not be unethical and, indeed, may be indicated when physicians are confronted with an HIV-infected patient who is unwilling to inform the person at risk. Such disclosure may be justified when all of the following conditions are met: the partner is at risk of infection with HIV and has no other reasonable means of knowing of the risk; the patient has refused to inform his or her sexual partner; the patient has refused an offer of assistance by the physician to do so on the patient's behalf; and the physician has informed the patient of his or her intention to disclose the information to the partner. The CMA stresses the need to respect the confidentiality of patients with HIV infection and consequently recommends that legal and regulatory safeguards to protect such confidentiality be established and maintained. Infection control Health care institutions and professionals should ensure that adequate infection-control measures in the handling of blood and body fluids are in place and that the rights of professionals directly involved in patient care to be informed of and protected from the risks of HIV infection are safeguarded. The CMA does not recommend routine testing of hospitalized patients. The CMA urges appropriate funding agencies to assess the explicit and implicit costs of infection control measures and to ensure that additional funds are provided to cover these extraordinary costs. Occupational exposure and the health care professional Health care workers should receive adequate financial compensation in the case of HIV infection acquired as a result of accidental occupational exposure. Physicians and other health care providers with HIV infection have the same rights as others to be protected from wrongful discrimination in the workplace and to be eligible for financial compensation for work-related infection. Physicians with HIV infection should consult appropriate colleagues to determine the nature and extent of the risk related to their continued involvement in the care of patients.
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Appropriateness in health care

https://policybase.cma.ca/en/permalink/policy11516
Last Reviewed
2020-02-29
Date
2014-12-06
Topics
Health care and patient safety
  1 document  
Policy Type
Policy document
Last Reviewed
2020-02-29
Date
2014-12-06
Topics
Health care and patient safety
Text
CMA POLICY Appropriateness in Health Care Summary This paper discusses the concept of appropriateness in health care and advances the following definition: The Canadian Medical Association adopts the following definition for appropriateness in health care: It is the right care, provided by the right providers, to the right patient, in the right place, at the right time, resulting in optimal quality care. Building on that definition it makes the following policy recommendations: * Provinces and territories should work with providers to develop a comprehensive framework by which to assess the appropriateness of health care. * Provinces and territories should work with providers to develop robust educational products on appropriateness in health care and to disseminate evidence-informed strategies for necessary changes in care processes. * Provinces and territories should work with providers to put in place incentives to decrease the provision of marginally useful or unnecessary care. Introduction As health systems struggle with the issue of sustainability and evidence that the quality of care is often sub-optimal, increasing attention is focused on the concept of appropriateness. A World Health Organization study published in 2000 described appropriateness as "a complex, fuzzy issue"1. Yet if the term is to be applied with benefit to health care systems, it demands definitional clarity. This policy document presents the Canadian Medical Association definition of appropriateness which addresses both quality and value. The roots of the definition are anchored in the evolution of Canadian health care over the last two decades. The document then considers the many issues confronting the operationalization of the term. It concludes that appropriateness can play a central role in positive health system transformation. Definition At the Canadian Medical Association General Council in 2013 the following resolution was adopted: The Canadian Medical Association adopts the following definition for appropriateness in health care: It is the right care, provided by the right providers, to the right patient, in the right place, at the right time, resulting in optimal quality care. This definition has five key components: * right care is based on evidence for effectiveness and efficacy in the clinical literature and covers not only use but failure to use; * right provider is based on ensuring the provider's scope of practice adequately meets but does not far exceed the skills and knowledge to deliver the care; * right patient acknowledges that care choices must be matched to individual patient characteristics and preferences and must recognize the potential challenge of reconciling patient and practitioner perceptions; * right venue emphasizes that some settings are better suited in terms of safety and efficiency to delivering a specific type of care than others; * right time indicates care is delivered in a timely manner consistent with agreed upon bench marks. It is essential to appreciate that the "right cost" is a consequence of providing the right care, that it is an outcome rather than an input. In other words, if all five components above are present, high quality care will have been delivered with the appropriate use of resources, that is, at the right cost. Equally, however, it should be cautioned that right cost may not necessarily be the affordable cost. For example, a new drug or imaging technology may offer small but demonstrable advantages over older practices, but at an enormous increase in cost. Some might argue that right care includes the use of the newer drug or technology, while others would contend the excessive opportunity costs must be taken into consideration such that the older practices remain the right care. An Evolving Canadian Perspective from 1996 to 2013 In a pioneering paper from 1996 Lavis and Anderson wrote: ...there are two distinct types of appropriateness: appropriateness of a service and appropriateness of the setting in which care is provided. The differences between the two parallel the differences between two other concepts in health care: effectiveness and cost-containment...An appropriate service is one that is expected to do more good than harm for a patient with a given indication...The appropriateness of the setting in which care is provided is related to cost effectiveness2. This very serviceable definition moved beyond a narrow clinical conception based solely on the therapeutic impact of an intervention on a patient, to broader contextual consideration focused on venue. Thus, for example, the care provided appropriately in a home-care setting might not be at all appropriate if given in a tertiary care hospital. Significantly, the authors added this important observation: "Setting is a proxy measure of the resources used to provide care"2. This sentence is an invitation to expand the original Lavis and Anderson definition to encompass other resources and inputs identified over the ensuing decades. Three elements are especially important. Timeliness became an issue in Canadian health care just as the Lavis and Anderson paper appeared. In 1997 almost two-thirds of polled Canadians felt surgical wait times were excessive, up from just over half of respondents a year earlier3. By 2004 concern with wait times was sufficiently pervasive that when the federal government and the provinces concluded the First Ministers' Agreement, it included obligations to provide timely access to cancer care, cardiac care, diagnostic imaging, joint replacement and sight restoration4. These rapid developments indicate that timeliness was now considered an essential element in determining the appropriateness of care. A second theme that became prominent in health care over the last two decades was the concept of patient-centredness. When the Canadian Medical Association released its widely endorsed Health Care Transformation in Canada in 2010, the first principle for reform was building a culture of patient-centred care. Succinctly put, this meant that "health care services are provided in a manner that works best for patients"5. To begin the process of operationalizing this concept CMA proposed a Charter for Patient-centred Care. Organized across seven domains, it included the importance of: allowing patients to participate fully in decisions about their care; respecting confidentiality of health records; and ensuring care provided is safe and appropriate. This sweeping vision underscores the fact that care which is not matched to the individual patient cannot be considered appropriate care. A third significant development over the last two decades was heightened awareness of the importance of scopes of practice. This awareness arose in part from the emphasis placed on a team approach in newer models of primary care6, but also from the emergence of new professions such as physician assistants, and the expansion of scopes of practice for other professionals such as pharmacists7. As the same health care activity could increasingly be done by a wider range of health professionals, ensuring the best match between competence required and the service provided became an essential element to consider when defining appropriateness. Under-qualified practitioners could not deliver quality care, while overly-qualified providers were a poor use of scarce resources. To summarize, as a recent scoping review suggested, for a complete conceptualization of appropriateness in 2013 it is necessary to add the right time, right patient and right provider to the previously articulated right care and right setting8. Why Appropriateness Matters The most frequent argument used to justify policy attention to appropriateness is health system cost. There is a wealth of evidence that inappropriate care - avoidable hospitalizations, for example, or alternative level of care patients in acute care beds - is wide spread in Canada9; eliminating this waste is critical to system sustainability. In Saskatchewan, for example, Regina and Saskatoon contracted in 2011 with private clinics to provide a list of 34 surgical procedures. Not only were wait times reduced, but costs were 26% lower in the surgical clinics than in hospitals for doing the same procedures10. There is, however, an equally important issue pointing to the importance of ensuring appropriate care: sub-optimal health care quality. In the United States, for example, a study evaluated performance on 439 quality indicators for 30 acute and chronic conditions. Patients received 54.9% of recommended care, ranging from a high of 78.7% for senile cataracts to 10.5% for alcohol dependence11. A more recent Australian study used 522 quality indicators to assess care for 22 common conditions. Patients received clinically appropriate care in 57% of encounters, with a range from 90% for coronary artery disease to 13% for alcohol dependence12. While no comparable comprehensive data exist for Canada, it is unlikely the practices in our system depart significantly from peer nations. Focusing on appropriateness of care, then, is justified by both fiscal and quality concerns. Methodology: the Challenge of Identifying Appropriateness While there is a clear need to address appropriateness - in all its dimensions - the methods by which to assess the appropriateness of care are limited and, to date, have largely focused on the clinical aspect. The most frequently used approach is the Rand/University of California Los Angeles (Rand) method. It provides panels of experts with relevant literature about a particular practice and facilitates iterative discussion and ranking of the possible indications for using the practice. Practices are labeled appropriate, equivocal or inappropriate13. A systematic review in 2012 found that for use on surgical procedures the method had good test-retest reliability, interpanel reliability and construct validity14. However, the method has been criticized for other short-comings: panels in different countries may reach different conclusions when reviewing the same evidence; validity can only be tested against instruments such as clinical practice guidelines that themselves may have a large expert opinion component2; Rand appropriateness ratings apply to an "average" patient, which cannot account for differences across individuals; and, finally, Rand ratings focus on appropriateness when a service is provided but does not encompass underuse, that is, failure to provide a service that would have been appropriate9. The Rand method, while not perfect, is the most rigorous approach to determining clinical appropriateness yet devised. It has recently been suggested that a method based on extensive literature review can identify potentially ineffective or harmful practices; when applied to almost 6000 items in the Australian Medical Benefits Schedule, 156 were identified that may be inappropriate15. This method also presents challenges. For example, the authors of a study using Cochrane reviews to identify low-value practices note that the low-value label resulted mainly from a lack of randomized evidence for effectiveness16. Assessing the appropriateness of care setting has focused almost exclusively on hospitals. Some diagnoses are known to be manageable in a community setting by primary care or specialty clinics. The rate of admissions for these ambulatory care sensitive conditions (ACSCs) - which fell from 459 per 100,000 population in 2001-02 to 320 per 100,00 in 2008-09 - is one way of gauging the appropriateness of the hospital as a care venue9. A second measure is the number of hospital patients who do not require either initial or prolonged treatment in an acute care setting. Proprietorial instruments such as the Appropriateness Evaluation Protocol (AEP)17or the InterQual Intensity of Service, Severity of Illness and Discharge Screen for Acute Care (ISD-AC)18 have been used to assess the appropriateness of hospital care for individual patients. While these instruments have been applied to Canadian hospital data19,20, there is a lack of consensus in the literature as to the reliability and utility of such tools21-23. Benchmarks exist for appropriate wait times for some types of care in Canada through the work of the Wait Time Alliance4. These include: chronic pain, cancer care, cardiac care, digestive health care, emergency rooms, joint replacement, nuclear medicine, radiology, obstetrics and gynecology, pediatric surgery, plastic surgery, psychiatric illness, and sight restoration. The recommendations are based on evidence-informed expert opinion. The other two domains of appropriateness - right patient, right provider - as yet have no objective tools by which to assess appropriateness. Barriers Determining appropriateness demands a complex and time-consuming approach, and its operationalization faces a number of barriers. The availability of some health care services may be subject to political influence which will over-ride appropriateness criteria. For example, recommendations to close smaller hospitals deemed to be redundant or inefficient may not be implemented for political reasons. Patient expectations can challenge evidence-based appropriateness criteria. In a primary care setting, for instance, it may be difficult to persuade a patient with an ankle sprain that an x-ray is unlikely to be helpful. The insistence by the patient is compounded by an awareness of potential legal liability in the event that clinical judgment subsequently proves incorrect. Choosing Wisely Canada recommends physicians and patients become comfortable with evidence-informed conversations about potentially necessary care24. Traditional clinical roles are difficult to revise in order to ensure that care is provided by the most appropriate health professional. This is especially true if existing funding silos are not realigned to reflect the desired change in practice patterns. Finally, and perhaps most importantly, even if agreed upon appropriateness criteria are developed, holding practitioners accountable for their application in clinical practice is extremely difficult due to data issues25. Chart audits could be conducted to determine whether appropriateness criteria were met when specific practices were deployed, but this is not feasible on a large scale. Rates of use of some practices could be compared among peers from administrative data; however, variation in practice population might legitimately sustain practice variation. For diagnostic procedures it has been suggested that the percentage of negative results is an indicator of inappropriate use; however, most administrative claim databases would not include positive or negative test result data26. This data deficit must be addressed with health departments and regional health authorities. Important Caveats There are several additional constraints on the use of the concept by health system managers. First, the vast majority of practices have never been subject to the Rand or any other appropriateness assessment. Even for surgical procedures clinical appropriateness criteria exist for only 10 of the top 25 most common inpatient procedures and for 6 of the top 15 ambulatory procedures in the United States. Most studies are more than 5 years old27. Second, while the notion is perhaps appealing to policy makers, it is incorrect to assume that high use of a practice equates with misuse: when high-use areas are compared to low use areas, the proportion of inappropriate use has consistently been shown to be no greater in the high-use regions28,29. Finally, it is uncertain how large a saving can be realized from eliminating problematic clinical care. For example, a US study modeling the implementation of recommendations for primary care found that while a switch to preferentially prescribing generic drugs would save considerable resources, most of the other items on the list of questionable activities "are not major contributors to health care costs"30. What is important to emphasize is that even if dollars are not saved, by reducing inappropriate care better value will be realized for each dollar spent. Policy Recommendations These methodological and other challenges31 notwithstanding, the Canadian Medical Association puts forward the following recommendations for operationalizing the concept of appropriateness and of clinical practice. 1. Provinces and territories should work with providers to develop a comprehensive framework by which to assess the appropriateness of health care. Jurisdictions should develop a framework32 for identifying potentially inappropriate care, including under-use. This involves selecting criteria by which to identify and prioritize candidates for assessment; developing and applying a robust assessment methodology; and creating mechanisms to disseminate and apply the results. Frameworks must also include meaningful consideration of care venue, timeliness, patient preferences and provider scope of practice. International examples exist for some aspects of this exercise and should be adapted to jurisdictional circumstances. Necessarily, a framework will demand the collection of supporting data in a manner consistent with the following 2013 General Council resolution: The Canadian Medical Association supports the development of data on health care delivery and patient outcomes to help the medical profession develop an appropriateness framework and associated accountability standards provided that patient and physician confidentiality is maintained. 2. Provinces and territories should work with providers to develop robust educational products on appropriateness in health care and to disseminate evidence-informed strategies for necessary changes in care processes. Both trainees and practicing physicians should have access to education and guidance on the topic of appropriateness and on practices that are misused, under-used, or over-used. Appropriately designed continuing education has been shown to alter physician practice. Point of care guidance via the electronic medical record offers a further opportunity to alert clinicians to practices that should or should not be done in the course of a patient encounter33. An initiative co-led by the Canadian Medical Association that is designed to educate the profession about the inappropriate over use of diagnostic and therapeutic interventions is Choosing Wisely Canada. The goal is to enhance quality of care and only secondarily to reduce unnecessary expenditures. It is an initiative consistent with the intent of two resolutions from the 2013 General Council: The Canadian Medical Association will form a collaborative working group to develop specialty-specific lists of clinical tests/interventions and procedures for which benefits have generally not been shown to exceed the risks. The Canadian Medical Association believes that fiscal benefits and cost savings of exercises in accountability and appropriateness in clinical care are a by-product rather than the primary focus of these exercises. 3. Provinces and territories should work with providers to put in place incentives to decrease the provision of marginally useful or unnecessary care. Practitioners should be provided with incentives to eliminate inappropriate care. These incentives may be financial - delisting marginal activities or providing bonuses for achieving utilization targets for appropriate but under-used care. Any notional savings could also be flagged for reinvestment in the health system, for example, to enhance access. Giving physicians the capacity to participate in audit and feedback on their use of marginal practices in comparison to peers generally creates a personal incentive to avoid outlier status. Public reporting by group or institution may also move practice towards the mean30. In any such undertakings to address quality or costs through changes in practice behaviour it is essential that the medical profession play a key role. This critical point was captured in a 2013 General Council resolution: The Canadian Medical Association will advocate for adequate physician input in the selection of evidence used to address costs and quality related to clinical practice variation. Conclusion When appropriateness is defined solely in terms of assessing the clinical benefit of care activities it can provide a plausible rational for "disinvestment in" or "delisting of" individual diagnostic or therapeutic interventions. However, such a narrow conceptualization of appropriateness cannot ensure that high quality care is provided with the optimal use of resources. To be truly useful in promoting quality and value appropriateness must be understood to mean the right care, provided by the right provider, to the right patient, in the right venue, at the right time. Achieving these five components of health care will not be without significant challenges, beginning with definitions and moving on to complex discussions on methods of measurement. Indeed, it may prove an aspirational goal rather than a completely attainable reality. But if every encounter in the health system - a hospitalization, a visit to a primary care provider, an admission to home care - attempted to meet or approximate each of the five criteria for appropriateness, a major step towards optimal care and value will have been achieved across the continuum. Viewed in this way, appropriateness has the capacity to become an extraordinarily useful organizing concept for positive health care transformation in Canada. Approved by CMA Board on December 06, 2014 References 1. World Health Organization. Appropriateness in Health Care Services, Report on a WHO Workshop. Copenhagen: WHO; 2000. 2. Lavis JN, Anderson GM. Appropriateness in health care delivery: definitions, measurement and policy implications. CMAJ. 1996;154(3):321-8. 3. Sanmartin C, Shortt SE, Barer ML, Sheps S, Lewis S, McDonald PW. Waiting for medical services in Canada: lots of heat, but little light. CMAJ. 2000;162(9):1305-10. 4. Wait Time Alliance. Working to Improve Wait Times Across Canada. Toronto: Wait Time Alliance; 2014. Available: http://www.waittimealliance.ca. (accessed April 18, 2013) 5. Canadian Medical Association. Health Care Transformation in Canada. Ottawa: Canadian Medical Association; 2010. 6. Canadian Medical Association. CMA Policy: Achieving Patient-centred Collaborative Care. Ottawa: Canadian Medical Association; 2008. 7. Maxwell-Alleyne A, Farber A. Pharmacists' expanded scope of practice: Professional obligations for physicians and pharmacists working collaboratively. Ont Med Rev. 2013;80(4):17-9. 8. Sanmartin C, Murphy K, Choptain N, et al. Appropriateness of healthcare interventions: concepts and scoping of the published literature. Int J Technol Assess Health Care. 2008;24(3)342-9. 9. Canadian Institute for Health Information. Health Care in Canada 2010. Ottawa: CIHI; 2010. 10. MacKinnon J. Health Care Reform from the Cradle of Medicare. Ottawa: Macdonald-Laurier Institute; 2013. 11. McGlynn EA, Asch SM, Adams J, et al. The quality of health care delivered to adults in the United States. NEJM. 2003;348(26):2635-45. 12. Runciman WB, Hunt TD, Hannaford NA, et al. CareTrack: assessing the appropriateness of health care delivery in Australia. Med J Aust. 2012;197(2):100-5. 13. Brook RH, Chassin MR, Fink A, Solomon DH, Kosecoff J, Park RE. A method for the detailed assessment of the appropriateness of medical technologies. Int J Technol Assess Health Care. 1986;2(1):53-63. 14. Lawson EH, Gibbons MM, Ko CY, Shekelle PG. The appropriateness method has acceptable reliability and validity for assessing overuse and underuse of surgical procedures. J Clin Epidemiol. 2012;65(11):1133-43. 15. Elshaug AG, Watt AM, Mundy L, Willis CD. Over 150 potentially low-value health care practices: an Australian study. Med J Aust. 2012;197(10):556-60. 16. Garner S, Docherty M, Somner J, et al. Reducing ineffective practice: challenges in identifying low-value health care using Cochrane systematic reviews. J Health Serv Res Policy. 2013;18(1):6-12. 17. Gertman PM, Restuccia JD. The appropriateness evaluation protocol: a technique for assessing unnecessary days of hospital care. Med Care. 1981;19(8):855-71. 18. Mitus AJ. The birth of InterQual: evidence-based decision support criteria that helped change healthcare. Prof Case Manag. 2008;13(4):228-33. 19. DeCoster C, Roos NP, Carriere KC, Peterson S. Inappropriate hospital use by patients receiving care for medical conditions: targeting utilization review. CMAJ. 1997;157(7):889-96. 20. Flintoft VF, Williams JI, Williams RC, Basinski AS, Blackstien-Hirsch P, Naylor CD. The need for acute, subacute and nonacute care at 105 general hospital sites in Ontario. Joint Policy and Planning Committee Non-Acute Hospitalization Project Working Group. CMAJ . 1998;158(10):1289-96. 21. Kalant N, Berlinguet M, Diodati JG, Dragatakis L, Marcotte F. How valid are utilization review tools in assessing appropriate use of acute care beds? CMAJ. 2000;162(13):1809-13. 22. McDonagh MS, Smith DH, Goddard M. Measuring appropriate use of acute beds. A systematic review of methods and results. Health policy. 2000;53(3):157-84. 23. Vetter N. Inappropriately delayed discharge from hospital: what do we know? BMJ. 2003;326(7395):927-8. 24. Choosing Wisely Canada. Recent News. Ottawa: Choosing Wisely Canada; 2015. Available: www.choosingwiselycanada.org. (accessed Dec 2014) 25. Garner S, Littlejohns P. Disinvestment from low value clinical interventions: NICEly done? BMJ. 2011;343:d4519. 26. Baker DW, Qaseem A, Reynolds PP, Gardner LA, Schneider EC. Design and use of performance measures to decrease low-value services and achieve cost-conscious care. Ann Intern Med. 2013;158(1):55-9. 27. Lawson EH, Gibbons MM, Ingraham AM, Shekelle PG, Ko CY. Appropriateness criteria to assess variations in surgical procedure use in the United States. Arch Surg. 2011;146(12):1433-40. 28. Chassin MR, Kosecoff J, Park RE, et al. Does inappropriate use explain geographic variations in the use of health care services? A study of three procedures. JAMA. 1987;258(18):2533-7. 29. Keyhani S, Falk R, Bishop T, Howell E, Korenstein D. The relationship between geographic variations and overuse of healthcare services: a systematic review. Med care. 2012;50(3):257-61. 30. Kale MS, Bishop TF, Federman AD, Keyhani S. "Top 5" lists top $5 billion. Arch Intern Med. 2011;171(20):1856-8. 31. Elshaug AG, Hiller JE, Tunis SR, Moss JR. Challenges in Australian policy processes for disinvestment from existing, ineffective health care practices. Aust New Zealand Health Policy. 2007;4:23. 32. Elshaug AG, Moss JR, Littlejohns P, Karnon J, Merlin TL, Hiller JE. Identifying existing health care services that do not provide value for money. Med J Aust. 2009;190(5):269-73. 33. Shortt S GM, Gorbet S. Making medical practice safer: the role of public policy. Int J Risk Saf Med. 2010;22(3):159-68.
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Guiding principles for the optimal use of data analytics by physicians at the point of care

https://policybase.cma.ca/en/permalink/policy11812
Last Reviewed
2020-02-29
Date
2016-02-27
Topics
Health information and e-health
  1 document  
Policy Type
Policy document
Last Reviewed
2020-02-29
Date
2016-02-27
Topics
Health information and e-health
Text
Electronic tools are now being used more widely in medicine than ever before. A majority of physicians in Canada have adopted electronic medical records (EMRs)-75% of physicians use EMRs to enter or retrieve clinical patient notes, and 80% use electronic tools to access laboratory/diagnostic test results. The increased use of point-of-care tools and information repositories has resulted in the mass digitization and storage of clinical information, which provides opportunities for the use of big data analytics. Big data analytics may come to be understood as the process of examining clinical data in EMRs cross-referenced with other administrative, demographic and behavioural data sources to reveal determinants of patient health and patterns in clinical practice. Its increased use may provide opportunities to develop and enhance clinical practice tools and to improve health outcomes at both point-of-care and population levels. However, given the nature of EMR use in Canada, these opportunities may be restricted to primary care practice at this time. Physicians play a central role in finding the right balance between leveraging the advantages of big data analytics and protecting patient privacy. Guiding Principles for the Optimal Use of Data Analytics by Physicians at the Point of Care outlines basic considerations for the use of big data analytics services and highlights key considerations when responding to requests for access to EMR data, including the following: * Why will data analytics be used? Will the safety and effectiveness of patient care be enhanced? Will the results be used to inform public health measures? * What are the responsibilities of physicians to respect and protect patient and physician information, provide appropriate information during consent conversations, and review data sharing agreements and consult with EMR vendors to understand how data will be used? As physicians will encounter big data analytics in a number of ways, this document also outlines the characteristics one should be looking for when assessing the safety and effectiveness of big data analytics services: * protection of privacy * clear and detailed data sharing agreement * physician-owned and -led data collaboratives * endorsement by a professional or recognized association, medical society or health care organization * scope of services and functionality/appropriateness of data While this guidance is not a standalone document-it should be used as a supplemental reference to provincial privacy legislation-it is hoped that it can aid physicians to identify suitable big data analytics services and derive benefits from them. Introduction This document outlines basic considerations for the use of big data analytics services at the point of care or for research approved by a research ethics board. This includes considerations when responding to requests for access to data in electronic medical records (EMRs). These guiding principles build on the policies of the Canadian Medical Association (CMA) on Data Sharing Agreements: Principles for Electronic Medical Records/Electronic Health Records,1 Principles Concerning Physician Information2 and Principles for the Protection of Patients' Personal Health Information,3 the 2011 clinical vignettes Disclosing Personal Health Information to Third Parties4 and Need to Know and Circle of Care,5 and the Canadian Medical Protective Association's The Impact of Big Data on Healthcare and Medical Practice.6 These guiding principles are for information and reference only and should not be construed as legal or financial advice, nor is this document a substitute for legal or other professional advice. Physicians must always comply with all legislation that applies to big data analytics, including privacy legislation. Big data analytics in the clinical context involves the collection, use and potential disclosure of patient and physician information, both of which could be considered sensitive personal information under privacy legislation. Big data analytics has the potential to improve health outcomes, both at the point of care and at a population level. Doctors have a key role to play in finding the right balance between leveraging the advantages of big data (enhanced care, service delivery and resource management) and protecting patient privacy.7 Background A majority of physicians in Canada have adopted EMRs in their practice. The percentage of physicians using EMRs to enter or retrieve clinical patient notes increased from 26% in 2007 to 75% in 2014. Eighty percent of physicians used electronic tools to access laboratory/diagnostic test results in 2014, up from 38% in 2010.8 The increasingly broad collection of information by physicians at the point of care, combined with the growth of information repositories developed by various governmental and intergovernmental bodies, has resulted in the mass digitization and storage of clinical information. Big data is the term for data sets so large and complex that it is difficult to process them using traditional relational database management systems, desktop statistics and visualization software. What is considered "big" depends on the infrastructure and capabilities of the organization managing the data.9 Analytics is the discovery and communication of meaningful patterns in data. Analytics relies on the simultaneous application of statistics, computer programming and operations research. Analytics often favours data visualization to communicate insight, and insights from data are used to guide decision-making.10 For physicians, big data analytics may come to be understood as the process of examining the clinical data in EMRs cross-referenced with other administrative, demographic and behavioural data sources to reveal determinants of patient health and patterns in clinical practice. This information can be used to assist clinical decision-making or for research approved by a research ethics board. There are four types of big data analytics physicians may encounter in the provision of patient care. They are generally performed in the following sequence, in a continuous cycle11,12,13,14: 1. Population health analytics: Health trends are identified in the aggregate within a community, a region or a national population. The data can be derived from biomedical and/or administrative data. 2. Risk-based cost analysis: Populations are segmented into groups according to the level of risk to the patient's health and/or cost to the health system. 3. Care management: Clinicians are enabled to manage patient care according to defined care pathways and clinical protocols informed by population health analytics and risk-based cost analysis. Care management includes the following: o Clinical decision support: Outcomes are predicted and/or alternative treatments are recommended to clinicians and patients at the point of care. o Personalized/precision care: Personalized data sets, such as genomic DNA sequences for at-risk patients, are leveraged to highlight best practice treatments for patients and practitioners. These solutions may offer early detection and diagnosis before a patient develops disease symptoms. o Clinical operations: Workflow management is performed, such as wait-times management, mining historical and unstructured data for patterns to predict events that may affect care. o Continuing education and professional development: Longitudinal performance data are combined across institutions, classes, cohorts or programs with correlating patient outcomes to assess models of education and/or develop new programs. 4. Performance analytics: Metrics for quality and efficiency of patient care are cross-referenced with clinical decision-making and performance data to assess clinical performance. This cycle is also sometimes understood as a component of "meaningful" or "enhanced" use of EMRs. How might physicians encounter big data analytics? Many EMRs run analytics both visibly (e.g., as a function that can be activated at appropriate junctures in the care pathway) and invisibly (e.g., as tools that run seamlessly in the background of an EMR). Physicians may or may not be aware when data are being collected, analyzed, tailored or presented by big data analytics services. However, many jurisdictions are strengthening their laws and standards, and best practices are gradually emerging.15 Physicians may have entered into a data sharing agreement with their EMR vendor when they procured an EMR for their practice. Such agreements may include provisions to share de-identified (i.e., anonymized) and/or aggregate data with the EMR vendor for specified or unspecified purposes. Physicians may also receive requests from third parties to share their EMR data. These requests may come from various sources: * provincial governments * intergovernmental agencies * national and provincial associations, including medical associations * non-profit organizations * independent researchers * EMR vendors, service providers and other private corporations National Physician Survey results indicate that in 2014, 10% of physicians had shared data from their EMRs for the purposes of research, 10% for chronic disease surveillance and 8% for care improvement. Family physicians were more likely than other specialists to share with public health agencies (22% v. 11%) and electronic record vendors (13% v. 2%). Specialists were more likely than family physicians to share with researchers (59% v. 37%), hospital departments (47% v. 20%) and university departments (28% v. 15%). There is significant variability across the provinces with regard to what proportion of physicians are sharing information from their EMRs, which is affected by the presence of research initiatives, research objectives defined by the approval of a research ethics board, the adoption rates of EMRs among physicians in the province and the functionality of those EMRs.16 For example, there are family practitioners across Canada who provide data to the Canadian Primary Care Sentinel Surveillance Network (CPCSSN). The CPCSSN is a multi-disease EMR surveillance and research system that allows family physicians, epidemiologists and researchers to understand and manage chronic care conditions for patients. Health information is collected from EMRs in the offices of participating family physicians, specifically information about Canadians suffering from chronic and mental health conditions and three neurologic conditions, including Alzheimer's and related dementias.17 In another example, the Canadian Partnership Against Cancer's Surgical Synoptic Reporting Initiative captures standardized information about surgery at the point of care and transmits the surgical report to other health care personnel. Surgeons can use the captured information, which gives them the ability to assess adherence to the clinical evidence and safety procedures embedded in the reporting templates, to track their own practices and those of their community.18 The concept of synoptic reporting-whereby a physician provides anonymized data about their practice in return for an aggregate report summarizing the practice of others -can be expanded to any area in which an appropriate number of physicians are willing to participate. Guiding principles for the use of big data analytics These guiding principles are designed to give physicians a starting point as they consider the use of big data analytics in their practices: * The objective of using big data analytics must be to enhance the safety and/or effectiveness of patient care or for the purpose of health promotion. * Should a physician use big data analytics, it is the responsibility of the physician to do so in a way that adheres to their legislative, regulatory and/or professional obligations. * Physicians are responsible for the privacy of their individual patients. Physicians may wish to refer to the CMA's policy on Principles for the Protection of Patients' Personal Health Information.19 * Physicians are responsible for respecting and protecting the privacy of other physicians' information. Physicians may wish to refer to the CMA's policy on Principles Concerning Physician Information.20 * When physicians enter into and document a broad consent discussion with their patient, which can include the electronic management of health information, this agreement should convey information to cover the elements common to big data analytics services. * Physicians may also wish to consider the potential for big data analytics to inform public health measures and enhance health system efficiency and take this into account when responding to requests for access to data in an EMR. * Many EMR vendors provide cloud-based storage to their clients, so information entered into an EMR may be available to the EMR vendor in a de-identified and/or aggregate state. Physicians should carefully read their data sharing agreement with their EMR vendor to understand how and why the data that is entered into an EMR is used, and/or they should refer to the CMA's policy on the matter, Data Sharing Agreements: Principles for Electronic Medical Records/Electronic Health Records.21 * Given the dynamic nature of this emerging tool, physicians are encouraged to share information about their experiences with big data analytics and its applications with colleagues. Characteristics of safe and effective big data analytics services 1. Protection of privacy Privacy and security concerns present a challenge in linking big data in EMRs. As data are linked, it becomes increasingly difficult to de-identify individual patients.22 As care is increasingly provided in interconnected, digital environments, physicians are having to take on the role of data stewardship. To that end, physicians may wish to employ conservative risk assessment practices-"should we" as opposed to "can we" when linking data sources-and obtain express patient consent, employing a "permission-based" approach to the collection and stewardship of data. 2. A clear and detailed data sharing agreement Physicians entering into a contract with an EMR vendor or other third party for provision of services should understand how and when they are contributing to the collection of data for the purposes of big data analytics services. There are template data sharing agreements available, which include the basic components of safe and effective data sharing, such as the model provided by the Information and Privacy Commissioner of Ontario.23 Data sharing agreements may include general use and project-specific use, both of which physicians should assess before entering into the agreement. When EMR access is being provided to a ministry of health and/or regional health authority, the data sharing agreement should distinguish between access to administrative data and access to clinical data. Physicians may wish to refer to the CMA's policy on Data Sharing Agreements: Principles for Electronic Medical Records/Electronic Health Records.24 3. Physician-owned and -led data collaboratives In some provinces there may exist opportunities to share clinical data in physician-owned and -led networks to reflect on and improve patient care. One example is the Physicians Data Collaborative in British Columbia, a not-for-profit organization open to divisions of family practice.25 Collaboratives such as this one are governed by physicians and driven by a desire to protect the privacy and safety of patients while producing meaningful results for physicians in daily practice. Participation in physician-owned data collaboratives may ensure that patient data continue to be managed by physicians, which may lead to an appropriate prioritization of physicians' obligations to balance patient-centred care and patient privacy. 4. Endorsement by a professional or other recognized association or medical society or health care organization When considering use of big data analytics services, it is best to select services created or endorsed by a professional or other recognized association or medical society. Some health care organizations, such as hospitals, may also develop or endorse services for use in their clinical environments. Without such endorsement, physicians are advised to proceed with additional caution. 5. Scope of services and functionality/appropriateness of data Physicians may wish to seek out information from EMR vendors and service providers about how big data analytics services complement the process of diagnosis and about the range of data sources from which these services draw. While big data analytics promises insight into population health and practice trends, if it is not drawing from an appropriate level of cross-referenced sources it may present a skewed picture of both.26 Ultimately, the physician must decide if the sources are appropriately diverse. Physicians should expect EMR vendors and service providers to make clear how and why they draw the information they do in the provision of analytics services. Ideally, analytics services should integrate population health analytics, risk-based cost analysis, care management services (such as point-of-care decision support tools) and performance analytics. Physicians should expect EMR vendors to allocate sufficient health informatics resources to information management, technical infrastructure, data protection and response to breaches in privacy, and data extraction and analysis.27,28 Physicians may also wish to consider the appropriateness of data analytics services in the context of their practices. Not all data will be useful for some medical specialties, such as those treating conditions that are relatively rare in the overall population. The potential for new or enhanced clinical practice tools informed by big data analytics may be restricted to primary care practice at this time.29 Finally, predictive analytics often make treatment recommendations that are designed to improve the health outcomes in a population, and these recommendations may conflict with physicians' ethical obligations to act in the best interests of individual patients and respect patients' autonomous decision-making).30 References 1 Canadian Medical Association. Data sharing agreements: principles for electronic medical records/electronic health records [CMA policy]. Ottawa: The Association; 2009. Available: http://policybase.cma.ca/dbtw-wpd/Policypdf/PD09-01.pdf 2 Canadian Medical Association. Principles concerning physician information [CMA policy]. CMAJ 2002 167(4):393-4. Available: http://policybase.cma.ca/dbtw-wpd/PolicyPDF/PD02-09.pdf 3 Canadian Medical Association. Principles for the protection of patients' personal health information [CMA policy]. Ottawa: The Association; 2010. Available: http://policybase.cma.ca/dbtw-wpd/Policypdf/PD11-03.pdf 4 Canadian Medical Association. Disclosing personal health information to third parties. Ottawa: The Association; 2011. Available: www.cma.ca/Assets/assets-library/document/en/advocacy/CMA_Disclosure_third_parties-e.pdf 5 Canadian Medical Association. Need to know and circle of care. Ottawa: The Association; 2011. Available: www.cma.ca/Assets/assets-library/document/en/advocacy/CMA_Need_to_know_circle_care-e.pdf 6 Canadian Medical Protective Association. The impact of big data on healthcare and medical practice. Ottawa: The Association; no date. Available: https://oplfrpd5.cmpa-acpm.ca/documents/10179/301372750/com_14_big_data_design-e.pdf 7 Kayyali B, Knott D, Van Kuiken S. The 'big data' revolution in US health care: accelerating value and innovation. New York: McKinsey & Company; 2013. p. 1. 8 College of Family Physicians of Canada, Canadian Medical Association, Royal College of Physicians and Surgeons of Canada. National physician survey, 2014. National results by FP/GP or other specialist, sex, age and all physicians. Q7. Ottawa: The Colleges and Association; 2014. Available: http://nationalphysiciansurvey.ca/wp-content/uploads/2014/08/2014-National-EN-Q7.pdf 9 Anonymous. Data, data everywhere. The Economist 2010 Feb 27. Available: www.economist.com/node/15557443 10 Anonymous. Data, data everywhere. The Economist 2010 Feb 27. Available: www.economist.com/node/15557443 11 Canada Health Infoway. Big data analytics in health. Toronto: Canada Health Infoway; 2013. Available: www.infoway-inforoute.ca/index.php/resources/technical-documents/emerging-technology/doc_download/1419-big-data-analytics-in-health-white-paper-full-report (accessed 2014 May 16). 12 Ellaway RH, Pusic MV, Galbraith RM, Cameron T. 2014 Developing the role of big data and analytics in health professional education. Med Teach 2014;36(3):216-222. 13 Marino DJ. Using business intelligence to reduce the cost of care. Healthc Financ Manage 2014;68(3):42-44, 46. 14 Porter ME, Lee TH. The strategy that will fix health care. Harv Bus Rev 2013;91(10):50-70. 15 Baggaley C. Data protection in a world of big data: Canadian Medical Protective Association information session [presentation]. 2014 Aug 20. Available: https://oplfrpd5.cmpa-acpm.ca/documents/10179/301372750/com_2014_carmen_baggaley-e.pdf 16 College of Family Physicians of Canada, Canadian Medical Association, Royal College of Physicians and Surgeons of Canada. National physician survey, 2014. National results by FP/GP or other specialist, sex, age and all physicians. Q10. Ottawa: The Colleges and Association; 2014. Available: http://nationalphysiciansurvey.ca/wp-content/uploads/2014/08/2014-National-EN-Q10.pdf 17 Canadian Primary Care Sentinel Surveillance Network. Available: http://cpcssn.ca/ (accessed 2014 Nov 15). 18 Canadian Partnership Against Cancer. Sustaining action toward a shared vision: 2012-2017 strategic plan. Toronto: The Partnership; no date. Available: www.partnershipagainstcancer.ca/wp-content/uploads/sites/5/2015/03/Sustaining-Action-Toward-a-Shared-Vision_accessible.pdf 19 Canadian Medical Association. Principles for the protection of patients' personal health information [CMA policy]. Ottawa: The Association; 2011. Available: http://policybase.cma.ca/dbtw-wpd/Policypdf/PD11-03.pdf 20 Canadian Medical Association. Principles for the protection of patients' personal health information [CMA policy]. Ottawa: The Association; 2011. Available: http://policybase.cma.ca/dbtw-wpd/Policypdf/PD11-03.pdf 21 Canadian Medical Association. Data sharing agreements: principles for electronic medical records/electronic health records [CMA policy]. Ottawa: The Association; 2009. Available: http://policybase.cma.ca/dbtw-wpd/Policypdf/PD09-01.pdf 22 Weber G, Mandl KD, Kohane IS. Finding the missing link for big biomedical data . JAMA 2014;311(24):2479-2480. doi:10.1001/jama.2014.4228. 23 Information and Privacy Commissioner of Ontario. Model data sharing agreement. Toronto: The Commissioner; 1995. Available: www.ipc.on.ca/images/Resources/model-data-ag.pdf 24 Canadian Medical Association. Data sharing agreements: principles for electronic medical records/electronic health records [CMA policy]. Ottawa: The Association; 2009. Available: http://policybase.cma.ca/dbtw-wpd/Policypdf/PD09-01.pdf 25 Physicians Data Collaborative. Overview. Available: www.divisionsbc.ca/datacollaborative/home 26 Cohen IG, Amarasingham R, Shah A, Xie B, Lo B. The legal and ethical concerns that arise from using complex predictive analytics in health care. Health Aff 2014;33(7):1139-1147. 27 Rhoads J, Ferrara L. Transforming healthcare through better use of data. Electron Healthc 2012;11(1):e27. 28 Canadian Medical Protective Association. The impact of big data and healthcare and medical practice. Ottawa: The Association; no date. Available: https://oplfrpd5.cmpa-acpm.ca/documents/10179/301372750/com_14_big_data_design-e.pdf 29 Genta RM, Sonnenberg A. Big data in gastroenterology research. Nat Rev Gastroenterol Hepatol 2014;11(6):386-390. 30 Cohen IG, Amarasingham R, Shah A, Xie B, Lo B. The legal and ethical concerns that arise from using complex predictive analytics in health care. Health Aff 2014;33(7):1139-1147.
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Framework for Ethical Decision Making During the Coronavirus Pandemic

https://policybase.cma.ca/en/permalink/policy14133
Date
2020-04-01
Topics
Ethics and medical professionalism
Health care and patient safety
  1 document  
Policy Type
Policy document
Date
2020-04-01
Topics
Ethics and medical professionalism
Health care and patient safety
Text
The current global pandemic caused by the novel coronavirus has presented the international medical community with unprecedented ethical challenges. The most difficult of these has involved making decisions about access to scarce resources when demand outweighs capacity. In Canada, it is well accepted that everyone should have an equal opportunity to access and receive medical treatment. This is possible when there are sufficient resources. But in contexts of resource scarcity, when there are insufficient resources, difficult decisions have to be made about who receives critical care (e.g., ICU beds, ventilators) by triaging patients. Triage is a process for determining which patients receive treatment and/or which level of care under what circumstances in contexts of resource scarcity. Priority-setting for resource allocation becomes more ethically complex during catastrophic times or in public health emergencies, such as today’s COVID-19 pandemic, when there is a need to manage a potential surge of patients. Physicians from China to Italy to Spain to the United States have found themselves in the unfathomable position of having to triage their most seriously ill patients and decide which ones should have access to ventilators and which should not, and which allocation criteria should be used to make these decisions. While the Canadian Medical Association hopes that Canadian physicians will not be faced with these agonizing choices, it is our intent, through this framework, to provide them with guidance in case they do and enable them to make ethically justifiable informed decisions in the face of difficult ethical dilemmas. Invoking this framework to ground decisions about who has access to critical care and who does not should only be made as a last resort. As always, physicians should carefully document their clinical and ethical decisions and the reasoning behind them. Generally, the CMA would spend many months in deliberations and consultations with numerous stakeholders, including patients and the public, before producing a document such as this one. The current situation, unfortunately, did not allow for such a process. We have turned instead to documents, reports and policies produced by our Italian colleagues and ethicists and physicians from Canada and around the world, as well as provincial level documents and frameworks. The CMA is endorsing and recommending that Canadian physicians use the guidance provided by Emmanuel and colleagues in the New England Journal of Medicine article dated from March 23rd, as outlined below. We believe these recommendations represent the best current approach to this situation, produced using the highest current standard of evidence by a panel of internationally recognized experts. We also recognize that the situation is changing constantly, and these guidelines may need to be updated as required. The CMA will continue to advocate for access to personal protective equipment, ventilators and ICU equipment and resources. We also encourage physicians to make themselves aware of any relevant provincial or local documents, and to seek advice from their regulatory body or liability protection provider. It should be noted that some provinces and indeed individual health care facilities will have their own protocols or frameworks in place. At the time of its publication, this document was broadly consistent with those protocols that we were given an opportunity to review. The CMA recognizes that physicians may experience moral distress when making these decisions. We encourage physicians to seek peer support and practice self-care. In addition, the CMA recommends that triage teams or committees be convened where feasible in order to help separate clinical decision making from resource allocation, thereby lessening the moral burden being placed on the individual physician. The CMA recommends that physicians receive legal protection to ensure that they can continue providing needed care to patients with confidence and support and without fear of civil or criminal liability or professional discipline. In this time of uncertainty, physicians should be reassured that their good faith efforts to provide care during such a crisis will not put them at increased medical-legal risk. Providing such reassurance is needed so that physicians have the confidence to continue to provide care to their patients. Recommendations: Recommendation 1: In the context of a pandemic, the value of maximizing benefits is most important. This value reflects the importance of responsible stewardship of resources: it is difficult to justify asking health care workers and the public to take risks and make sacrifices if the promise that their efforts will save and lengthen lives is illusory. Priority for limited resources should aim both at saving the most lives and at maximizing improvements in individuals’ post-treatment length of life. Saving more lives and more years of life is a consensus value across expert reports. It is consistent both with utilitarian ethical perspectives that emphasize population outcomes and with nonutilitarian views that emphasize the paramount value of each human life. There are many reasonable ways of balancing saving more lives against saving more years of life; whatever balance between lives and life-years is chosen must be applied consistently. Limited time and information in a Covid-19 pandemic make it justifiable to give priority to maximizing the number of patients that survive treatment with a reasonable life expectancy and to regard maximizing improvements in length of life as a subordinate aim. The latter becomes relevant only in comparing patients whose likelihood of survival is similar. Limited time and information during an emergency also counsel against incorporating patients’ future quality of life, and quality-adjusted life-years, into benefit maximization. Doing so would require time-consuming collection of information and would present ethical and legal problems. However, encouraging all patients, especially those facing the prospect of intensive care, to document in an advance care directive what future quality of life they would regard as acceptable and when they would refuse ventilators or other life-sustaining interventions can be appropriate. Operationalizing the value of maximizing benefits means that people who are sick but could recover if treated are given priority over those who are unlikely to recover even if treated and those who are likely to recover without treatment. Because young, severely ill patients will often comprise many of those who are sick but could recover with treatment, this operationalization also has the effect of giving priority to those who are worst off in the sense of being at risk of dying young and not having a full life. Because maximizing benefits is paramount in a pandemic, we believe that removing a patient from a ventilator or an ICU bed to provide it to others in need is also justifiable and that patients should be made aware of this possibility at admission. Undoubtedly, withdrawing ventilators or ICU support from patients who arrived earlier to save those with better prognosis will be extremely psychologically traumatic for clinicians — and some clinicians might refuse to do so. However, many guidelines agree that the decision to withdraw a scarce resource to save others is not an act of killing and does not require the patient’s consent. We agree with these guidelines that it is the ethical thing to do. Initially allocating beds and ventilators according to the value of maximizing benefits could help reduce the need for withdrawal. Recommendation 2: Irrespective of Recommendation 1, Critical Covid-19 interventions — testing, PPE, ICU beds, ventilators, therapeutics, and vaccines — should go first to front-line health care workers and others who care for ill patients and who keep critical infrastructure operating, particularly workers who face a high risk of infection and whose training makes them difficult to replace. These workers should be given priority not because they are somehow more worthy, but because of their instrumental value: they are essential to pandemic response. If physicians and nurses and RTs are incapacitated, all patients — not just those with Covid-19 — will suffer greater mortality and years of life lost. Whether health workers who need ventilators will be able to return to work is uncertain but giving them priority for ventilators recognizes their assumption of the high-risk work of saving others. Priority for critical workers must not be abused by prioritizing wealthy or famous persons or the politically powerful above first responders and medical staff — as has already happened for testing. Such abuses will undermine trust in the allocation framework. Recommendation 3: For patients with similar prognoses, equality should be invoked and operationalized through random allocation, such as a lottery, rather than a first-come, first-served allocation process. First-come, first-served is used for such resources as transplantable kidneys, where scarcity is long-standing, and patients can survive without the scarce resource. Conversely, treatments for coronavirus address urgent need, meaning that a first-come, first-served approach would unfairly benefit patients living nearer to health facilities. And first-come, first-served medication or vaccine distribution would encourage crowding and even violence during a period when social distancing is paramount. Finally, first-come, first-served approaches mean that people who happen to get sick later on, perhaps because of their strict adherence to recommended public health measures, are excluded from treatment, worsening outcomes without improving fairness. In the face of time pressure and limited information, random selection is also preferable to trying to make finer-grained prognostic judgments within a group of roughly similar patients. Recommendation 4: Prioritization guidelines should differ by intervention and should respond to changing scientific evidence. For instance, younger patients should not be prioritized for Covid-19 vaccines, which prevent disease rather than cure it, or for experimental post- or pre-exposure prophylaxis. Covid-19 outcomes have been significantly worse in older persons and those with chronic conditions. Invoking the value of maximizing saving lives justifies giving older persons priority for vaccines immediately after health care workers and first responders. If the vaccine supply is insufficient for patients in the highest risk categories — those over 60 years of age or with coexisting conditions — then equality supports using random selection, such as a lottery, for vaccine allocation. Invoking instrumental value justifies prioritizing younger patients for vaccines only if epidemiologic modeling shows that this would be the best way to reduce viral spread and the risk to others. Epidemiologic modeling is even more relevant in setting priorities for coronavirus testing. Federal guidance currently gives priority to health care workers and older patients but reserving some tests for public health surveillance could improve knowledge about Covid-19 transmission and help researchers target other treatments to maximize benefits. Conversely, ICU beds and ventilators are curative rather than preventive. Patients who need them face life-threatening conditions. Maximizing benefits requires consideration of prognosis — how long the patient is likely to live if treated — which may mean giving priority to younger patients and those with fewer coexisting conditions. This is consistent with the Italian guidelines that potentially assign a higher priority for intensive care access to younger patients with severe illness than to elderly patients. Determining the benefit-maximizing allocation of antivirals and other experimental treatments, which are likely to be most effective in patients who are seriously but not critically ill, will depend on scientific evidence. These treatments may produce the most benefit if preferentially allocated to patients who would fare badly on ventilation. Recommendation 5: People who participate in research to prove the safety and effectiveness of vaccines and therapeutics should receive some priority for Covid-19 interventions. Their assumption of risk during their participation in research helps future patients, and they should be rewarded for that contribution. These rewards will also encourage other patients to participate in clinical trials. Research participation, however, should serve only as a tiebreaker among patients with similar prognoses. Recommendation 6: There should be no difference in allocating scarce resources between patients with Covid-19 and those with other medical conditions. If the Covid-19 pandemic leads to absolute scarcity, that scarcity will affect all patients, including those with heart failure, cancer, and other serious and life-threatening conditions requiring prompt medical attention. Fair allocation of resources that prioritizes the value of maximizing benefits applies across all patients who need resources. For example, a doctor with an allergy who goes into anaphylactic shock and needs life-saving intubation and ventilator support should receive priority over Covid-19 patients who are not frontline health care workers. Approved by the CMA Board of Directors April 2020
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CMA Statement on Racism

https://policybase.cma.ca/en/permalink/policy14245
Date
2020-06-02
Topics
Ethics and medical professionalism
Health care and patient safety
  1 document  
Policy Type
Policy document
Date
2020-06-02
Topics
Ethics and medical professionalism
Health care and patient safety
Text
Racism is a structural determinant of health and drives health and social inequities. The recent incidents of anti-Black violence, racism and discrimination in the US and Canada also shed light on the structural inequities and racism that exist within the medical profession and the health system. The profession of medicine is grounded in respect for all people. This commitment recognizes that everyone has equal and inherent worth, the right to be valued and respected, and the right to be treated with dignity. It’s critical that our medical culture – and society more broadly – upholds these values. But today, we’re reminded that there’s much more to do as a profession, and as a global community, to get us there. Earlier this year, we launched our first-ever policy on equity and diversity in medicine Opens in a new window to help break down the many broad and systemic barriers that remain, to reduce discrimination and bias within our profession, and to create physically and psychologically safe environments for ourselves, our colleagues and our patients. Alongside this policy comes a commitment to holding ourselves accountable to recognizing and challenging behaviours, practices and conditions that hinder equity and diversity, including racism. Instances of racism, intolerance, exclusion, violence and discrimination have no place in medicine, and no place in our society. The Canadian Medical Association condemns racism in all its forms. Today, we stand alongside all those who have been affected by these appalling and inexcusable actions and beliefs. Dr. Sandy Buchman President, Canadian Medical Association
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