A representative from the “Not on My Watch Prevention Campaign” contacted me and asked me to look at their organization's media release related to healthcare-acquired infections (HAI). I am not affiliated with Kimberly-Clark, nor do I have any interests in their company, but it is great to see that there is a business case for quality.
Their media release summarizes some of the CDC's statistical reports related to HAI. In 2002, they estimate that almost 100,000 Americans died of healthcare-associated infections. The most striking finding in one of the CDC reports is that a basic and simple human behavior is likely the largest contributing factor—many providers find themselves too busy to wash their hands.
Many cultural patterns are complex, but hand washing is fairly simple. We know that healthcare providers are busy, and numerous factors make their lives chaotic, but it seems like it is time to slow down and do the simple task hand washing.
Thursday, October 22, 2009
Sunday, September 20, 2009
Using Internet-Based Medical Decision Aids To Improve Clinical Practice
“Our culture is embedded with a strong belief that more is better and that physicians know best.” John Wennberg, MD
Clinical practice varies across regions of the United States. The variation is not explained by patient illness or preferences; the supply (or oversupply) of medical treatments impacts quality (or failure) of our health system. The United States has focused on medical errors and associated performance measures to reduce practice variation. Although important, it is misleading to solely measure the quality of how medicine is administered without also considering if medical treatments should have been administered in the first place. In the book, “Overtreated: Why Too Much Medicine is Making Us Sicker and Poorer,” Shannon Brownlee tells the non-obvious story of how more medical care often does not result in better outcomes. As a result, our health system compared to other developed countries is forty percent more expensive, yet it is in the bottom quartile for most quality indicators (Brook et al., 2000; Institute of Medicine, 2001).
In this article, I first discuss the exciting interdisciplinary field of medical decision making. Second, I describe how improving the medical decision making process (driven partly by empowering patients) can shift geographic patterns associated with over-treatment. Finally, I argue that the US healthcare system could be improved if patients and physicians use internet-based decision aids to guide the complex and often difficult decisions involving medical treatments.
Doing the Right Things Right
Clinical Evidence BMJ evaluated 2,500 medical treatments and found that only half of these were governed by clear evidence-based guidelines (How Much Do We Know?, 2006). Acknowledging this finding, O'Connor et al. (2007) defined "effective" and "preference-sensitive" treatments. Both have some scientific knowledge about outcomes, yet for effective treatments there is enough information that benefits outweigh harms. In contrast, for preference-sensitive treatments, we are less certain that potential harms are justified. Given the evidence that medical counseling is often inadequate, and that the use of preference-sensitive treatments can vary two to fivefold across practice regions, the authors posit that it is important to improve the medical decision process. Wennberg (2004) provides a good example by showing that the rate of exposure to coronary bypass surgery and the case fatality rate of bypass surgery patients is about the same. This be explained by the finding that a substantial percentage (between 0-25%) of CABG procedures are inappropriately performed in the first place (Summaries for Patients, 2001). If patients received medical treatments only when needed, it would make sense to only look at the quality of treatments. However, with varying appropriateness of treatments being performed, we need to improve the medical decision making process. Doing a treatment effectively is not enough; clinicians need to do the right things right (Chassin et al., 1987; Blumenthal, 2004; Wennberg, 2004).
The current focus of the healthcare quality movement is to measure medical errors. It is necessary, however, to measure both how well treatments are administered, and the quality of the decision making process (Sirovich et al., 2008; Wennberg, 2004). Although there are many possible tools to improve medical decision making, the focus here is on internet-based decision aids. Once patients think more clearly about their goals, values, and risk/benefits preferences, they may be able to help their doctors make better decisions for themselves and society.
Medical Decision Making
An excellent book titled, “Medical Decision Making: A Physicians Guide” bridges the gap between decades of decision science research and the actual use of effective decision methods among clinicians and patients (Schwartz and Bergus, 2008). The authors first discuss the importance of helping patients define their goals with respect to their health and medical treatments. Patients have diverse demographic traits and social situations, and these will shape how medical treatments can fulfill their near and distant objectives. Next, there is a large volume of research about how people rate their current health, and using these methodologies, it is possible to have a patient “trade-off” the length and quality of their life. For example, it is possible to estimate “quality-adjusted life expectancy” after obtaining information about health states, life expectancy of the patient, and a discounting factor for future health. This information can be used to construct decision models that can then be used for specific cases in which patients can decide if an extended life is preferable to treatment-induced disabilities. Although some people without question seek a longer life, others are not willing to give up a standard quality of life, and will choose more or less aggressive treatment options. These methods allow patients' values to be an important part of the medical decision making process.
The third section of the book stresses that physicians and patients need to have the tools to embrace uncertainty. The authors start by introducing the concept of risk. Risk, unlike uncertainty, allows one to assign a probability of the likely outcome based on data from a large sample of observations. For example, it is possible to assign a probability of death for a population of patients if we have quality outcome data for a population with similar age and clinical characteristics . Of course, assigning an individual patient an exact probability of the outcome is impossible; we have to accept that some individuals are different than the population in unknown ways, and thus predicting at the individual level is problematic. Information about risk at the population level, however, can still be very useful to patients if it is presented in a clear way. Gigerenzer (2002) provides a good example. He finds that people are better able to understand raw frequencies in contrast to probabilities. Thus, when presenting people with information about the risk of harm that they might experience from a medical procedure, it is better to show them graphical representations of numerators and denominators rather than rates and associated probabilities. Finally, the book provides an overview of the concept of expected value in which patients can evaluate expected events by summing up the value of an outcome multiplied by its probability of occurrence.
Although there is much more to learn about the medical decision making process, researchers have generated an impressive amount of knowledge that could help patients and physicians make better decisions. Much of this science is applied in nature and very applicable to the design of effective decision aids.
Patient Decision Aids Are Effective
High quality patient decision aids are based on knowledge from medical decision science. The tools help patients document their values and goals, and then help them to evaluate associated risks and benefits of their treatment options. To construct quality decision aids, evidence-based clinical guidelines and other clinical knowledge has to be summarized for each medical condition or treatment of interest. These should then be tested with a pilot group of patients to ensure that the tool is easily understood by patients. Since decision aids are often involve a tree structure or a set of questions to evaluate, they can be administered in-person, pencil-and-paper or through an internet application. Given the interest in provider websites and personal health records, it is likely that web-based applications will become an increasingly effective way to administer decision aids.
O'Connor et al. (2007) state that decision aids lead to informed judgments by providing patients with personalized information about the tradeoffs of their various treatment options. Following decision theory, they write that decision aids: (1) state treatment options, outcomes, and probabilities, (2) help patients' evaluate which outcomes are the most important to them and (3) provide clear steps for patients to make choices and then communicate these ideas to their physician.
Key points from O'Connor (2007, p.176) have been copied below to highlight the likely benefits of decision aids.
• “Patient decision aids prepare patients to discuss "grey zone" treatment options and to clarify
which benefits and harms matter most to them”
• “They differ from educational aids by not only providing option information but also tailoring it to the patient's clinical risk profile and guiding patients to express their personal values”
• “They promote informed values-based decisions and improve patient participation and comfort
levels in decision-making”
• “They prevent the overuse of "grey zone" options that informed patients do not value (e.g.,
aggressive discretionary surgery such as hysterectomy, prostatectomy and back surgery)”
• “They will be used routinely at the point of clinical care only if they are made easy for clinicians to use and become something patients expect as part of high-quality care”
Is there any strong scientific evidence that decision aids work? A recent meta-analysis published by the Cochrane Collaboration evaluates fifty-five studies of decision aids that used the gold standard randomized control trail (O'Connor et al., 2009). The authors found that decision aids were better than treatment as usual options. Specifically they found that patients using decision aids had: (1) more knowledge about the treatment (2) less decisional conflict and (3) were less likely to be passive in the decision-making process. There was some additional evidence that decision aids resulted in fewer treatments as compared to the control group. Overall, the analysis of the large number of high-quality studies does provide evidence that decision aids can improve patient outcomes (for some specific examples for maternal patients see: Farnworth et al, 2008; Montgomery et al, 2007).
Decision Aids are Available on the Internet
There are many organizations that have implemented decision aids on the internet. Ottawa Health Decision Centre at the Ottawa Hospital Research Institute, however, brings together an extensive set of decision aids produced by a variety of organizations. This group is led by Dr. Annette O'Connor, a leading researcher in this field. Their organization's website has an "A to Z inventory" of decision aids that cover a wide variety of medical topics. To list only a few, there are extensive decision aids related to breast cancer, diabetes, headaches, acne, obesity. Patients can search an area of interest to them, and then learn more about how particular decision aids might help them with their understand their medical problem. Most of the aids posted on this site were developed by HealthWise and Health Dialog, but there are also aids developed by universities and health systems such as the Mayo Clinic. Decision aids are only posted if they meet the standards outlined by the Cochrane Collaboration. They must have development guided by expert review, have an update policy, be supported by scientific evidence, and disclose funding sources and conflicts of interest.
The Future of Internet-Based Decision Aids
There is a clear need to improve the medical decision making process, and knowledge from decision making research can be used to create evidence-based decision aids. There are, however, numerous road blocks for widespread adoption of decision aids. First, O'Connor et al. (2007) argue that many physicians do not perceive the value of decision aids. To increase adoption it will be important for medical students and practicing physicians to receive training about how decision aids might better improve their patient encounters (Holmes-Rovner et al, 2007). This will likely involve a large cultural shift in American medicine (Starr, 1982). Next, the legal system in the United States presents barriers to the use of decision aids. State laws vary however, and there are some areas that might serve as examples for states to follow. Third, payment strategies in the United States often do not provide incentives for improving patient health; capitation of payment, and possibly pay for performance strategies might encourage greater adoption of internet based decision aids. Finally, it will be important to develop and evaluate decision aids for the large number of preference-sensitive treatments in which few tools are currently available.
Although the barriers to diffusion of internet-based decision aids are real, the future for these tools seems bright. With the current debate about health reform raging, there is a slow, yet growing awareness among patients that more medicine is not always better, and physicians do not always know more than the patient. The use of the internet is also expanding, and it is encouraging, for example, that older patients at Northern California Kaiser are using online tools to manage their health (Jermy Wong, personal communication; see Cambell and Nolfi, 2005 for contrary view). Given this social environment, it is possible that patients will become more interested in using decision aids on the internet. Over the course of the next decade, they might put pressure on physicians, lawyers, and health administrations to remove barriers for use of decision aids, and enable a new generation of patient-centered care. In this new world, every healthcare organization could point their patients to decision aid web links for thousands of conditions and treatments, and counsel them to come to their appointments prepared to share with their physician personal preferences, values, and other output from these tools. Of course, with their years of training and expertise, physicians will be respected for their advice, yet they will be expected to listen carefully to what the patient has learned from the decision aid. Most importantly, physicians will be trained to understand decision science and how to help their patients value and understand decision aids. Internet-based decision aids will likely only be a small part of a reformed medical system, yet these tools will likely contribute to a health system that provides Americans equal access to a sustainable and efficient health system that does not over-treat (and harm) its people.
References
Blumenthal, D. (2004). Decisions, decisions: why the quality of medical decisions matters. Health Aff (Millwood), Suppl Web Exclusives, VAR124-127.
Brook, R. H., McGlynn, E. A., & Shekelle, P. G. (2000). Defining and measuring quality of care: a perspective from US researchers. Int J Qual Health Care, 12(4), 281-295.
Brownlee, S. (2007). Overtreated: why too much medicine is making us sicker and poorer (1st U.S. ed.). New York, NY: Bloomsbury.
Campbell, R. J., & Nolfi, D. A. (2005). Teaching elderly adults to use the Internet to access health care information: before-after study. J Med Internet Res, 7(2), e19.
Chassin, M. R., Kosecoff, J., Park, R. E., Winslow, C. M., Kahn, K. L., Merrick, N. J., et al. (1987). Does inappropriate use explain geographic variations in the use of health care services? A study of three procedures. Jama, 258(18), 2533-2537.
Farnworth, A., Robson, S. C., Thomson, R. G., Watson, D. B., & Murtagh, M. J. (2008). Decision support for women choosing mode of delivery after a previous caesarean section: a developmental study. Patient Educ Couns, 71(1), 116-124.
Gigerenzer, G. (2002). Calculated risks : how to know when numbers deceive you. New York: Simon & Schuster.
Holmes-Rovner, M., Nelson, W. L., Pignone, M., Elwyn, G., Rovner, D. R., O'Connor, A. M., et al. (2007). Are patient decision aids the best way to improve clinical decision making? Report of the IPDAS Symposium. Med Decis Making, 27(5), 599-608.
“How much do we know?” BMJ Clinical Evidence, 2006, http://clinicalevidence.bmj.com/ceweb/about/knowledge.jsp (accessed 16 September 2009)
Institute of Medicine (U.S.). Committee on Quality of Health Care in America. (2001). Crossing the quality chasm : a new health system for the 21st century. Washington, D.C.: National Academy Press.
Lauer, J. A., & Betran, A. P. (2007). Decision aids for women with a previous caesarean section. Bmj, 334(7607), 1281-1282.
Montgomery, A. A., Emmett, C. L., Fahey, T., Jones, C., Ricketts, I., Patel, R. R., et al. (2007). Two decision aids for mode of delivery among women with previous caesarean section: randomised controlled trial. Bmj, 334(7607), 1305.
O'Connor, A. M. (2007). Using decision aids to help patients navigate the "grey zone" of medical decision-making. CMAJ, 176(11), 1597-1598.
O'Connor, A. M., Bennett, C. L., Stacey, D., Barry, M., Col, N. F., Eden, K. B., et al. (2009). Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev(3), CD001431.
O'Connor, A. M., Wennberg, J. E., Legare, F., Llewellyn-Thomas, H. A., Moulton, B. W., Sepucha, K. R., et al. (2007). Toward the 'tipping point': decision aids and informed patient choice. Health Aff (Millwood), 26(3), 716-725.
Schwartz, A., & Bergus, G. (2008). Medical decision making : a physician's guide. Cambridge, UK ; New York: Cambridge University Press.
Sirovich, B., Gallagher, P. M., Wennberg, D. E., & Fisher, E. S. (2008). Discretionary decision making by primary care physicians and the cost of U.S. Health care. Health Aff (Millwood), 27(3), 813-823.
Starr, P. (1982). The social transformation of American medicine. New York: Basic Books.
Summaries for patients. Overuse of coronary artery bypass graft surgery and percutaneous transluminal coronary angioplasty. (2001). Ann Intern Med, 135(5), S-35.
Wennberg, J. E. (2004). Practice variations and health care reform: connecting the dots. Health Aff (Millwood), Suppl Web Exclusives, VAR140-144.
Clinical practice varies across regions of the United States. The variation is not explained by patient illness or preferences; the supply (or oversupply) of medical treatments impacts quality (or failure) of our health system. The United States has focused on medical errors and associated performance measures to reduce practice variation. Although important, it is misleading to solely measure the quality of how medicine is administered without also considering if medical treatments should have been administered in the first place. In the book, “Overtreated: Why Too Much Medicine is Making Us Sicker and Poorer,” Shannon Brownlee tells the non-obvious story of how more medical care often does not result in better outcomes. As a result, our health system compared to other developed countries is forty percent more expensive, yet it is in the bottom quartile for most quality indicators (Brook et al., 2000; Institute of Medicine, 2001).
In this article, I first discuss the exciting interdisciplinary field of medical decision making. Second, I describe how improving the medical decision making process (driven partly by empowering patients) can shift geographic patterns associated with over-treatment. Finally, I argue that the US healthcare system could be improved if patients and physicians use internet-based decision aids to guide the complex and often difficult decisions involving medical treatments.
Doing the Right Things Right
Clinical Evidence BMJ evaluated 2,500 medical treatments and found that only half of these were governed by clear evidence-based guidelines (How Much Do We Know?, 2006). Acknowledging this finding, O'Connor et al. (2007) defined "effective" and "preference-sensitive" treatments. Both have some scientific knowledge about outcomes, yet for effective treatments there is enough information that benefits outweigh harms. In contrast, for preference-sensitive treatments, we are less certain that potential harms are justified. Given the evidence that medical counseling is often inadequate, and that the use of preference-sensitive treatments can vary two to fivefold across practice regions, the authors posit that it is important to improve the medical decision process. Wennberg (2004) provides a good example by showing that the rate of exposure to coronary bypass surgery and the case fatality rate of bypass surgery patients is about the same. This be explained by the finding that a substantial percentage (between 0-25%) of CABG procedures are inappropriately performed in the first place (Summaries for Patients, 2001). If patients received medical treatments only when needed, it would make sense to only look at the quality of treatments. However, with varying appropriateness of treatments being performed, we need to improve the medical decision making process. Doing a treatment effectively is not enough; clinicians need to do the right things right (Chassin et al., 1987; Blumenthal, 2004; Wennberg, 2004).
The current focus of the healthcare quality movement is to measure medical errors. It is necessary, however, to measure both how well treatments are administered, and the quality of the decision making process (Sirovich et al., 2008; Wennberg, 2004). Although there are many possible tools to improve medical decision making, the focus here is on internet-based decision aids. Once patients think more clearly about their goals, values, and risk/benefits preferences, they may be able to help their doctors make better decisions for themselves and society.
Medical Decision Making
An excellent book titled, “Medical Decision Making: A Physicians Guide” bridges the gap between decades of decision science research and the actual use of effective decision methods among clinicians and patients (Schwartz and Bergus, 2008). The authors first discuss the importance of helping patients define their goals with respect to their health and medical treatments. Patients have diverse demographic traits and social situations, and these will shape how medical treatments can fulfill their near and distant objectives. Next, there is a large volume of research about how people rate their current health, and using these methodologies, it is possible to have a patient “trade-off” the length and quality of their life. For example, it is possible to estimate “quality-adjusted life expectancy” after obtaining information about health states, life expectancy of the patient, and a discounting factor for future health. This information can be used to construct decision models that can then be used for specific cases in which patients can decide if an extended life is preferable to treatment-induced disabilities. Although some people without question seek a longer life, others are not willing to give up a standard quality of life, and will choose more or less aggressive treatment options. These methods allow patients' values to be an important part of the medical decision making process.
The third section of the book stresses that physicians and patients need to have the tools to embrace uncertainty. The authors start by introducing the concept of risk. Risk, unlike uncertainty, allows one to assign a probability of the likely outcome based on data from a large sample of observations. For example, it is possible to assign a probability of death for a population of patients if we have quality outcome data for a population with similar age and clinical characteristics . Of course, assigning an individual patient an exact probability of the outcome is impossible; we have to accept that some individuals are different than the population in unknown ways, and thus predicting at the individual level is problematic. Information about risk at the population level, however, can still be very useful to patients if it is presented in a clear way. Gigerenzer (2002) provides a good example. He finds that people are better able to understand raw frequencies in contrast to probabilities. Thus, when presenting people with information about the risk of harm that they might experience from a medical procedure, it is better to show them graphical representations of numerators and denominators rather than rates and associated probabilities. Finally, the book provides an overview of the concept of expected value in which patients can evaluate expected events by summing up the value of an outcome multiplied by its probability of occurrence.
Although there is much more to learn about the medical decision making process, researchers have generated an impressive amount of knowledge that could help patients and physicians make better decisions. Much of this science is applied in nature and very applicable to the design of effective decision aids.
Patient Decision Aids Are Effective
High quality patient decision aids are based on knowledge from medical decision science. The tools help patients document their values and goals, and then help them to evaluate associated risks and benefits of their treatment options. To construct quality decision aids, evidence-based clinical guidelines and other clinical knowledge has to be summarized for each medical condition or treatment of interest. These should then be tested with a pilot group of patients to ensure that the tool is easily understood by patients. Since decision aids are often involve a tree structure or a set of questions to evaluate, they can be administered in-person, pencil-and-paper or through an internet application. Given the interest in provider websites and personal health records, it is likely that web-based applications will become an increasingly effective way to administer decision aids.
O'Connor et al. (2007) state that decision aids lead to informed judgments by providing patients with personalized information about the tradeoffs of their various treatment options. Following decision theory, they write that decision aids: (1) state treatment options, outcomes, and probabilities, (2) help patients' evaluate which outcomes are the most important to them and (3) provide clear steps for patients to make choices and then communicate these ideas to their physician.
Key points from O'Connor (2007, p.176) have been copied below to highlight the likely benefits of decision aids.
• “Patient decision aids prepare patients to discuss "grey zone" treatment options and to clarify
which benefits and harms matter most to them”
• “They differ from educational aids by not only providing option information but also tailoring it to the patient's clinical risk profile and guiding patients to express their personal values”
• “They promote informed values-based decisions and improve patient participation and comfort
levels in decision-making”
• “They prevent the overuse of "grey zone" options that informed patients do not value (e.g.,
aggressive discretionary surgery such as hysterectomy, prostatectomy and back surgery)”
• “They will be used routinely at the point of clinical care only if they are made easy for clinicians to use and become something patients expect as part of high-quality care”
Is there any strong scientific evidence that decision aids work? A recent meta-analysis published by the Cochrane Collaboration evaluates fifty-five studies of decision aids that used the gold standard randomized control trail (O'Connor et al., 2009). The authors found that decision aids were better than treatment as usual options. Specifically they found that patients using decision aids had: (1) more knowledge about the treatment (2) less decisional conflict and (3) were less likely to be passive in the decision-making process. There was some additional evidence that decision aids resulted in fewer treatments as compared to the control group. Overall, the analysis of the large number of high-quality studies does provide evidence that decision aids can improve patient outcomes (for some specific examples for maternal patients see: Farnworth et al, 2008; Montgomery et al, 2007).
Decision Aids are Available on the Internet
There are many organizations that have implemented decision aids on the internet. Ottawa Health Decision Centre at the Ottawa Hospital Research Institute, however, brings together an extensive set of decision aids produced by a variety of organizations. This group is led by Dr. Annette O'Connor, a leading researcher in this field. Their organization's website has an "A to Z inventory" of decision aids that cover a wide variety of medical topics. To list only a few, there are extensive decision aids related to breast cancer, diabetes, headaches, acne, obesity. Patients can search an area of interest to them, and then learn more about how particular decision aids might help them with their understand their medical problem. Most of the aids posted on this site were developed by HealthWise and Health Dialog, but there are also aids developed by universities and health systems such as the Mayo Clinic. Decision aids are only posted if they meet the standards outlined by the Cochrane Collaboration. They must have development guided by expert review, have an update policy, be supported by scientific evidence, and disclose funding sources and conflicts of interest.
The Future of Internet-Based Decision Aids
There is a clear need to improve the medical decision making process, and knowledge from decision making research can be used to create evidence-based decision aids. There are, however, numerous road blocks for widespread adoption of decision aids. First, O'Connor et al. (2007) argue that many physicians do not perceive the value of decision aids. To increase adoption it will be important for medical students and practicing physicians to receive training about how decision aids might better improve their patient encounters (Holmes-Rovner et al, 2007). This will likely involve a large cultural shift in American medicine (Starr, 1982). Next, the legal system in the United States presents barriers to the use of decision aids. State laws vary however, and there are some areas that might serve as examples for states to follow. Third, payment strategies in the United States often do not provide incentives for improving patient health; capitation of payment, and possibly pay for performance strategies might encourage greater adoption of internet based decision aids. Finally, it will be important to develop and evaluate decision aids for the large number of preference-sensitive treatments in which few tools are currently available.
Although the barriers to diffusion of internet-based decision aids are real, the future for these tools seems bright. With the current debate about health reform raging, there is a slow, yet growing awareness among patients that more medicine is not always better, and physicians do not always know more than the patient. The use of the internet is also expanding, and it is encouraging, for example, that older patients at Northern California Kaiser are using online tools to manage their health (Jermy Wong, personal communication; see Cambell and Nolfi, 2005 for contrary view). Given this social environment, it is possible that patients will become more interested in using decision aids on the internet. Over the course of the next decade, they might put pressure on physicians, lawyers, and health administrations to remove barriers for use of decision aids, and enable a new generation of patient-centered care. In this new world, every healthcare organization could point their patients to decision aid web links for thousands of conditions and treatments, and counsel them to come to their appointments prepared to share with their physician personal preferences, values, and other output from these tools. Of course, with their years of training and expertise, physicians will be respected for their advice, yet they will be expected to listen carefully to what the patient has learned from the decision aid. Most importantly, physicians will be trained to understand decision science and how to help their patients value and understand decision aids. Internet-based decision aids will likely only be a small part of a reformed medical system, yet these tools will likely contribute to a health system that provides Americans equal access to a sustainable and efficient health system that does not over-treat (and harm) its people.
References
Blumenthal, D. (2004). Decisions, decisions: why the quality of medical decisions matters. Health Aff (Millwood), Suppl Web Exclusives, VAR124-127.
Brook, R. H., McGlynn, E. A., & Shekelle, P. G. (2000). Defining and measuring quality of care: a perspective from US researchers. Int J Qual Health Care, 12(4), 281-295.
Brownlee, S. (2007). Overtreated: why too much medicine is making us sicker and poorer (1st U.S. ed.). New York, NY: Bloomsbury.
Campbell, R. J., & Nolfi, D. A. (2005). Teaching elderly adults to use the Internet to access health care information: before-after study. J Med Internet Res, 7(2), e19.
Chassin, M. R., Kosecoff, J., Park, R. E., Winslow, C. M., Kahn, K. L., Merrick, N. J., et al. (1987). Does inappropriate use explain geographic variations in the use of health care services? A study of three procedures. Jama, 258(18), 2533-2537.
Farnworth, A., Robson, S. C., Thomson, R. G., Watson, D. B., & Murtagh, M. J. (2008). Decision support for women choosing mode of delivery after a previous caesarean section: a developmental study. Patient Educ Couns, 71(1), 116-124.
Gigerenzer, G. (2002). Calculated risks : how to know when numbers deceive you. New York: Simon & Schuster.
Holmes-Rovner, M., Nelson, W. L., Pignone, M., Elwyn, G., Rovner, D. R., O'Connor, A. M., et al. (2007). Are patient decision aids the best way to improve clinical decision making? Report of the IPDAS Symposium. Med Decis Making, 27(5), 599-608.
“How much do we know?” BMJ Clinical Evidence, 2006, http://clinicalevidence.bmj.com/ceweb/about/knowledge.jsp (accessed 16 September 2009)
Institute of Medicine (U.S.). Committee on Quality of Health Care in America. (2001). Crossing the quality chasm : a new health system for the 21st century. Washington, D.C.: National Academy Press.
Lauer, J. A., & Betran, A. P. (2007). Decision aids for women with a previous caesarean section. Bmj, 334(7607), 1281-1282.
Montgomery, A. A., Emmett, C. L., Fahey, T., Jones, C., Ricketts, I., Patel, R. R., et al. (2007). Two decision aids for mode of delivery among women with previous caesarean section: randomised controlled trial. Bmj, 334(7607), 1305.
O'Connor, A. M. (2007). Using decision aids to help patients navigate the "grey zone" of medical decision-making. CMAJ, 176(11), 1597-1598.
O'Connor, A. M., Bennett, C. L., Stacey, D., Barry, M., Col, N. F., Eden, K. B., et al. (2009). Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev(3), CD001431.
O'Connor, A. M., Wennberg, J. E., Legare, F., Llewellyn-Thomas, H. A., Moulton, B. W., Sepucha, K. R., et al. (2007). Toward the 'tipping point': decision aids and informed patient choice. Health Aff (Millwood), 26(3), 716-725.
Schwartz, A., & Bergus, G. (2008). Medical decision making : a physician's guide. Cambridge, UK ; New York: Cambridge University Press.
Sirovich, B., Gallagher, P. M., Wennberg, D. E., & Fisher, E. S. (2008). Discretionary decision making by primary care physicians and the cost of U.S. Health care. Health Aff (Millwood), 27(3), 813-823.
Starr, P. (1982). The social transformation of American medicine. New York: Basic Books.
Summaries for patients. Overuse of coronary artery bypass graft surgery and percutaneous transluminal coronary angioplasty. (2001). Ann Intern Med, 135(5), S-35.
Wennberg, J. E. (2004). Practice variations and health care reform: connecting the dots. Health Aff (Millwood), Suppl Web Exclusives, VAR140-144.
Sunday, September 6, 2009
Using Second Life to Help Medical Students Understand the Value of Organized (Cooperative) Medicine
I recently attended a meeting at the California state capital in which three prestigious speakers discussed how to improve healthcare quality through evidence-based medicine. I became increasingly agitated by a number of physicians in the room, whom after the talks, commented about how all or most physicians believe in and practice evidence-based medicine. They blamed insurance companies and others for any lack of high quality care. In response, I loudly voiced how astonished I was that we had all just heard strong scientific evidence that many physicians in the US do not practice scientific medicine, and that indeed there is a great deal of practice variation. I lamented that Paul Starr's book, “The Social Transformation of American Medicine” remains the story of 2009; many physicians desire autonomy in their practice, and this prevents any real chance of quality medical care. In my opinion, the most important component of health reform is to provide medical students (and practicing physicians) with an opportunity to choose an organizational “culture” that will allow them to really practice evidence-based medicine (EBM).
In this article, I will first briefly discuss important elements of medical culture relevant EBM. Next, I will argue the only specific types of medical organizations support EBM. Finally, I will discuss how Second Life could be used as a tool to help medical students understand that if they really want to practice EMB, they might have to sacrifice some autonomy and work within larger (or more social connected) medical organizations.
The Culture of EMB
Culture is composed of rules, ideas, procedures, or beliefs that influence behavior. Given this broad definition, almost all of human behavior is at some level guided by culture. Our personal beliefs are shaped by how people around us frame complex topics, and our behavior is often constrained by cultural rules and norms. Lets make the discussion more concrete by thinking about the cultural elements that embody the broad idea of EBM. First, most people know the cultural blueprint sometimes called the “scientific method.” This cultural pattern has evolved over thousands of years, and although the methods vary somewhat, the basic pattern is to identify a problem of interest, define some hypotheses, and then collect observations to make claims that hypotheses can be accepted or rejected. Second, once scientific studies have been debated and looked at together, knowledge can be generated. In medicine, clinical trails tend to be our favorite sources of information that can create prescriptions about how to treat patients. The next step is for physicians to consider using scientific knowledge when treating their patients. Here again, we need to think about cultural patterns. For example, what do physicians believe is quality clinical knowledge, and how will they access this information when they treat patients. Will they have the knowledge at the point of care (e.g., embedding in a clinical support system) or will they read medical journals in the evening and use the information the next day? Even more, are there rules or policies that clinical staff should meet to discuss scientific evidence? The list could go on and on. The point is to see that the culture of evidence based medicine is much more than scientific papers. What really matters is how (or if) information is used to improve the outcomes of patient care.
The Social Organization of EMB
As mentioned early in this blog, there is evidence that medical culture varies from place to place and from provider to provider. More specifically, the use of EBM among different medical groups, hospitals, and other types of medical organizations will vary as a result of the culture defining medical knowledge and how it should be used to improve patient care. A good way to think about this is to compare a large complex bureaucratic medical organization such as Kaiser with small independent practices. Large medical organizations such as Kaiser have people who operate in clearly defined and often specialized roles. For example, Kaiser employs research scientists in narrow fields, and very specific types of IT personal such as database experts and EMR systems designers. In contrast, independent practices with a few physicians and some support staff are forced to fulfill all the specialized duties themselves (if possible). Small groups are required to do their own library research, and install their own IT systems. Consultants can help, but this can also be challenging process. None of this should be surprising to anybody, but it is useful to remind ourselves about the benefits of large organizations; specialization of labor can lead to efficiencies and outcomes that small groups cannot easily accomplish.
I have been reading numerous scholarly publications by researchers such as Stephen Shortell (UC Berkeley Public Health), David Lawrence (former Kaiser CEO) and researchers from the Dartmouth medical school (Wennberg, Fisher). The consensus of this research is that US medical care is fragmented, inefficient, and often likely to produce too much or too little care. Other problems include having too many specialists in one area who fail to work as a team. But the common denominator of all this work is that the desire for physician autonomy keeps the system fragmented, and prevents the teamwork required for the practice of scientific or evidence-based medicine. In short, I will make a strong statement that I believe is supported by a large amount of scientific evidence from a variety of scientific disciplines; evidence-based medicine is extremely difficult to achieve among small independent physician practices that do not have real social connections with larger organizational entities.
Giving New Medical Students a Choice: Second Life as a Tool
I suspect that the majority of aspiring young physicians are drawn to the field to help people. Moreover, most see the value of science, and want to improve health outcomes using data, information, and knowledge effectively. Sadly, I think many American medical schools do not adhere to my statement about the importance of organizational elements to fulfill EBM. Thus, it is possible that medical students are given the false illusion that they can practice EBM as independent physicians. Of course, the reality is that a few talented and motivated physicians can pull it off. One of my health informatics classmates can do it I bet (Jonathan Ware). However, assuming that I am generally correct in what I have outlined above, would it be possible to use Second Life as a way to clearly illustrate my points? Once medical students had more information about the benefits of organized medicine, would this motivate more of them to work for such medical groups?
If I worked for a medical school, I would build multiple Second Life “islands” that represent the varying geography and human ecology of medicine. To make it evidence-based, I would employ ethnographic observers to spend time in a variety of medical settings. To start with, I might send teams to the Mayo Clinic and Northern California Kaiser to build examples of organized medicine. As a comparison, I would choose a few independent medical practices that have only a few physicians and small staff. Within Second Life it would be possible to build clinics that were similar to these real organizations, and then put in the importance “objects” such as record files, computers (with and with EMRs), and possibly some simple medical equipment. It might even be possible to embed examples of real EMRs systems such as Epic, so that the medical students would have a chance to actually try out a variety of IT systems. I suspect that it might be resource intensive, yet possible, to recreate the physical structures of medical organizations. However, how would it be possible to effectively demonstrate the subtle yet important cultural elements of these organizations?
To start, it might be possible to employ pre-medical undergraduate students to act as nurses, support staff, and patients within the Second Life environment. They could be trained to follow predefined scripts that embody the real procedures and subtle behaviors that were found in the ethnographic studies. For example, in the Kaiser setting, there would be multiple support staff that act in very defined roles. To address issues of procedure utilization, it might be neat to present the medical students with clinical situations that require difficult decisions about which treatments to select. In the Kaiser example, there would be a decision support system and some electronic guidelines that pop up as they enter data about the patient into the EMR. In contrast, there might be fewer of these IT structures in place for one of the independent practice settings. It might even be possible to re-create the daily clinical functions in paper-based system.
I have yet to become familiar enough with Second Life to fully evaluate if a virtual environment could provide enough human “context” to allow users to understand different cultures that exist among American medical groups. I suspect that the best way to fully understand other people is to travel and spend time with them within their organizations. However, the ultimate goal of this project might not be to fully give students an appreciation of the diverse ways of doing medicine, but give them the opportunity to think about what evidence-based medicine is, and how it can be truly achieved. Second Life might then provide enough interest to get students thinking about such diversity and make them curious enough to more fully explore their career options.
Wednesday, August 19, 2009
How Patients Use the Internet to Find Quality Healthcare Providers
The United States spends more per capita on healthcare than any other country, yet ranks low on quality metrics. Healthcare costs and quality also vary among states. Finally, as discussed earlier, the Dartmouth Atlas of Healthcare shows dramatic sub-state variation based on healthcare referral regions. Although these macro-level studies are important for policy makers, consumers face the immediate problem of choosing high quality providers in their local area (or choosing to travel for healthcare). There are two important ways that people find information on the Internet about the reputation of their healthcare providers—organizational report cards and word-of-mouth. Although government agencies and other organizations publish quality information about physicians, plans, and hospitals, many consumers seem to prefer word-of-mouth (or Internet blogs) to select providers.
First, lets consider report cards that are produced by many government and non-government organizations to help consumers make better choices. These reports use administrative billing data or sometimes clinical data to create objective performance measures that are usually presented as events (e.g., mortality, misadventures) per procedures performed or conditions treated. For example, the Center for Medicare and Medicaid Services have a website to help consumers evaluate the quality of hospital care. In California, my organization, the Office of Statewide Health Planning and Development, produces quality ratings for hospitals and for surgeons performing specific heart operations such as coronary artery bypass surgery. Interestingly, the California Hospital Association working with the University of California also publishes hospital ratings. This site, called calhospitalcompare.org, is much more consumer friendly than our state website. Almost every other state has numerous organizations that publish such report cards, and a great deal of energy and money are put into creating performance ratings. Given all this work, is there solid evidence that consumers use this information online to make better decisions when selecting healthcare providers? No.
An article in the prestigious journal Health Affairs by David Bates and Atul Gawande describe that few patients use organizational report cards (though this might be changing), and there is little evidence to date that the report cards alter consumer behavior. There are many other complaints about these reports such as too much reliance on poor quality data and too little attention paid to the multiple processes that lead to outcomes of interest. However, given the recent attention to the transparency of healthcare, and the fact that the reports are becoming more scientific, it seems that report cards will only become more important in the future. Meanwhile, patients are using the Internet in different ways to evalate quality. The Bates and Gawande article, as well as a number of more recent studies, provide evidence that consumers prefer to seek providers with high quality reputations based on word-of-mouth communication with friends and family. There is also evidence that more and more consumers are using Internet blogs to both supply and obtain information about high-quality providers. There are numerous sites emerging in which patients can rate their physicians, thus providing some information to others about variation among provider care. Interestingly, there is also some evidence that consumer ratings actually correlate fairly well with more objective performance measured based on hospital data.
How will these two paths of Internet use evolve in the future? It is very likely that the transparency movement will continue to push organizations to produce report cards. More importantly, there is promise that report cards will become more consumer oriented, and provide more opportunity for patients to use health information to select high quality (and maybe lower cost) providers. An interesting website to keep an eye on is published by Consumer Reports. This site does a good job of translating complex scientific outcomes studies into consumer friendly information. Of course, it also seems that the use of health blogs and patient rating sites will also increase in popularity. Thus, it is interesting to think about how these two methods of use could augment one another, and in the end, create an increased opportunity for quality improvement. I list below a two ways that could lead to positive synergy between Internet report cards and word-of-mouth communication.
1.) Report cards might start to offer people a chance to blog about the information that they see. It is unlikely government sites could allow this to happen, but the non-profit sites could do this easily. In fact, the Consumer Reports website for healthcare quality does have some simple ways for people to comment about what they see on the site. It is possible that in the future, some clever health informaticists will find a way to bridge the objective outcomes and process measures with more subjective comments from users.
2.) Organizations that create report cards might try to create their own systems for people to rate their satisfaction with providers, and then publish this along with more objective performance measures. Some sites such as calhospitalcompare.org do present data on patient satisfaction, but these measures are based on pre-collected survey data. Could patients enter ratings directly on the site, and then aggregate their responses in an ongoing measure of satisfaction?
The Internet is not going away, and neither is the drive to improve the quality of US healthcare. Lets hope that patients are given every opportunity to review “objective” report cards as well as document their own personal experiences in some type of positive way.
References
Healthcare Quality and Cost Transparency Using Web-Based Tools, by Jiao Ma and Cynthia LeRouge. In Patient-Centered E-Health (2009) E. Vance Wilson
The Impact Of The Internet On Quality Measurement:
Word-of-mouth advice about providers is gaining respectability through the Web.
by David W. Bates and Atul A. Gawande, Health Affairs vol 19 #6 2000
You Can Lead Patients to Quality Data, But Will They Use It?
HealthGrades
First, lets consider report cards that are produced by many government and non-government organizations to help consumers make better choices. These reports use administrative billing data or sometimes clinical data to create objective performance measures that are usually presented as events (e.g., mortality, misadventures) per procedures performed or conditions treated. For example, the Center for Medicare and Medicaid Services have a website to help consumers evaluate the quality of hospital care. In California, my organization, the Office of Statewide Health Planning and Development, produces quality ratings for hospitals and for surgeons performing specific heart operations such as coronary artery bypass surgery. Interestingly, the California Hospital Association working with the University of California also publishes hospital ratings. This site, called calhospitalcompare.org, is much more consumer friendly than our state website. Almost every other state has numerous organizations that publish such report cards, and a great deal of energy and money are put into creating performance ratings. Given all this work, is there solid evidence that consumers use this information online to make better decisions when selecting healthcare providers? No.
An article in the prestigious journal Health Affairs by David Bates and Atul Gawande describe that few patients use organizational report cards (though this might be changing), and there is little evidence to date that the report cards alter consumer behavior. There are many other complaints about these reports such as too much reliance on poor quality data and too little attention paid to the multiple processes that lead to outcomes of interest. However, given the recent attention to the transparency of healthcare, and the fact that the reports are becoming more scientific, it seems that report cards will only become more important in the future. Meanwhile, patients are using the Internet in different ways to evalate quality. The Bates and Gawande article, as well as a number of more recent studies, provide evidence that consumers prefer to seek providers with high quality reputations based on word-of-mouth communication with friends and family. There is also evidence that more and more consumers are using Internet blogs to both supply and obtain information about high-quality providers. There are numerous sites emerging in which patients can rate their physicians, thus providing some information to others about variation among provider care. Interestingly, there is also some evidence that consumer ratings actually correlate fairly well with more objective performance measured based on hospital data.
How will these two paths of Internet use evolve in the future? It is very likely that the transparency movement will continue to push organizations to produce report cards. More importantly, there is promise that report cards will become more consumer oriented, and provide more opportunity for patients to use health information to select high quality (and maybe lower cost) providers. An interesting website to keep an eye on is published by Consumer Reports. This site does a good job of translating complex scientific outcomes studies into consumer friendly information. Of course, it also seems that the use of health blogs and patient rating sites will also increase in popularity. Thus, it is interesting to think about how these two methods of use could augment one another, and in the end, create an increased opportunity for quality improvement. I list below a two ways that could lead to positive synergy between Internet report cards and word-of-mouth communication.
1.) Report cards might start to offer people a chance to blog about the information that they see. It is unlikely government sites could allow this to happen, but the non-profit sites could do this easily. In fact, the Consumer Reports website for healthcare quality does have some simple ways for people to comment about what they see on the site. It is possible that in the future, some clever health informaticists will find a way to bridge the objective outcomes and process measures with more subjective comments from users.
2.) Organizations that create report cards might try to create their own systems for people to rate their satisfaction with providers, and then publish this along with more objective performance measures. Some sites such as calhospitalcompare.org do present data on patient satisfaction, but these measures are based on pre-collected survey data. Could patients enter ratings directly on the site, and then aggregate their responses in an ongoing measure of satisfaction?
The Internet is not going away, and neither is the drive to improve the quality of US healthcare. Lets hope that patients are given every opportunity to review “objective” report cards as well as document their own personal experiences in some type of positive way.
References
Healthcare Quality and Cost Transparency Using Web-Based Tools, by Jiao Ma and Cynthia LeRouge. In Patient-Centered E-Health (2009) E. Vance Wilson
The Impact Of The Internet On Quality Measurement:
Word-of-mouth advice about providers is gaining respectability through the Web.
by David W. Bates and Atul A. Gawande, Health Affairs vol 19 #6 2000
You Can Lead Patients to Quality Data, But Will They Use It?
HealthGrades
Wednesday, August 12, 2009
Why the Geography of Medicine is Important
As we hear more and more information about health reform efforts, it is very easy to become confused about what needs to be changed and why. Health is a very complex topic, and the organization and finance of medicine adds more layers of complexitiy. As a result, it can be a daunting task to understand how to improve our health services delivery system in the US.
The purpose of this blog is to focus attention to the human ecology of health and medicine by looking at medical outcomes on a map. Most people are good at reading maps, and maps put complex issues in our own backyards. Most importantly, we can compare our areas, or where our friends and family live, to other areas. Recent efforts to map healthcare outcomes as described below allow people to quickly make comparisons and then think about why these differences might occur (assuming the differences are meaningful and real).
I believe the variation in healthcare costs and quality as illustrated by maps is often real variation. This means that some places have better medical care than others. Once more people look at health in this way, they will be less likely to be confused by biased media and "noise machines". I think they are more likely to say, "Hey wait, the data on the maps show huge differences in costs and quality, so lets focus on the real problem."
The purpose of this blog is to focus attention to the human ecology of health and medicine by looking at medical outcomes on a map. Most people are good at reading maps, and maps put complex issues in our own backyards. Most importantly, we can compare our areas, or where our friends and family live, to other areas. Recent efforts to map healthcare outcomes as described below allow people to quickly make comparisons and then think about why these differences might occur (assuming the differences are meaningful and real).
I believe the variation in healthcare costs and quality as illustrated by maps is often real variation. This means that some places have better medical care than others. Once more people look at health in this way, they will be less likely to be confused by biased media and "noise machines". I think they are more likely to say, "Hey wait, the data on the maps show huge differences in costs and quality, so lets focus on the real problem."
Saturday, August 1, 2009
The Geography of Healthcare
For more than twenty years, the Dartmouth Atlas of Healthcare has shown variation associated with the costs and quality of healthcare across geographic areas of the United States. Some areas are much more costly than other areas, and there is little evidence that high-cost areas provide better quality of care. Indeed, high-cost regions seem to provide lower quality care. The reasons for this variation are complex, but evidence is growing to support the hypothesis that specialist-driven medicine leads to fragmented and uncoordinated care. Moreover, many medical conditions and treatments are not guided by scientific evidence, and practicing physicians often do not adhere to guidelines when they are available. A popular article in the New Yorker by Atul Gawande is based on some of this research.
Managing the finance of healthcare is important for increasing access to healthcare for uninsured Americans, yet high costs and variable levels of quality must be addressed before any sustainable solution will be reached. In my opinion there is a strong need to transform the culture of medicine that is currently based on physician autonomy to a system in which medical providers work as a team to provide patient-centered care. The Internet may be the force that will empower patients to learn more about their own health, and then motivate them to work together with their providers to achieve the best outcomes possible. Once patients have more information about their health, and are better able to understand risks and benefits of their options, it is likely that they will select less costly treatments that lead to higher quality outcomes. It is likely that once physicians embrace these changes, they will enjoy working with patients who have the capacity to understand more about complex health issues.
Managing the finance of healthcare is important for increasing access to healthcare for uninsured Americans, yet high costs and variable levels of quality must be addressed before any sustainable solution will be reached. In my opinion there is a strong need to transform the culture of medicine that is currently based on physician autonomy to a system in which medical providers work as a team to provide patient-centered care. The Internet may be the force that will empower patients to learn more about their own health, and then motivate them to work together with their providers to achieve the best outcomes possible. Once patients have more information about their health, and are better able to understand risks and benefits of their options, it is likely that they will select less costly treatments that lead to higher quality outcomes. It is likely that once physicians embrace these changes, they will enjoy working with patients who have the capacity to understand more about complex health issues.
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