Abstract
Amid calls for physicians to become better stewards of the nation’s health care resources, it is important to gain insight into how physicians think about the cost-effectiveness of new treatments. Expensive new cancer treatments that can extend life raise questions about whether physicians are prepared to make “value for money” tradeoffs when treating patients. We asked oncologists in the United States and Canada how much benefit, in additional months of life expectancy, a new drug would need to provide to justify its cost and warrant its use in an individual patient. The majority of oncologists agreed that a new cancer treatment that might add a year to a patient’s life would be worthwhile if the cost was less than $100,000. But when given a hypothetical case of an individual patient to review, the oncologists also endorsed a hypothetical drug whose cost might be as high as $250,000 per life-year gained. The results show that oncologists are not consistent in deciding how many months an expensive new therapy should extend a person’s life before the cost of therapy is justified. Moreover, the benefit that oncologists demand from new treatments in terms of length of survival does not necessarily increase according to the price of the treatment. The findings suggest that policy makers should find ways to improve how physicians are educated on the use of cost-effectiveness information and to influence physician decision making through clinical guidelines that incorporate cost-effectiveness information.
In the past decade, new cancer treatments have emerged that offer the hope of increased survival for patients with previously untreatable diseases. Patients with lung, colon, gynecologic, and other cancers have benefited modestly from these new therapies.1–4
But many of these promising new therapies come at staggering financial costs.5 Drugs like bevacizumab (Avastin)—designed to impede the growth of blood vessels and tumors—can cost more than $100,000 per patient.6–8 With pressure from insurers, employers, and governments to control health care costs, experts have begun to ask whether even developed nations can afford to offer these treatments to all patients who might benefit from them.9
Medical oncologists in the United States and Canada are on the front line of this controversy.10 Their decisions to recommend treatments with modest clinical benefit to their patients are complicated by the cost of these new therapies. The financial burden of even a 10 percent copayment on a $100,000 treatment is beyond the means of many people.11
In addition, even when patients are not burdened by the cost of therapy, oncologists may wonder whether society, more generally, can afford these treatments.12 The use of new technology is, by some estimates, the greatest contributor to health care inflation,13 and rising health care costs place burdens on employers, insurance enrollees, and governments.14
But are physicians prepared to make “value for money” trade-offs at the bedside?15 This question is a crucial one for health policy experts because physicians’ decisions still play a large role in driving up health care costs.16 Ultimately, the proliferation of expensive medical technologies has resulted from the accumulated decisions of individual physicians caring for individual patients. Health care policies often succeed or fail depending on how they influence physicians’ behaviors. Thus, it is important to gain more insight into how physicians think about the cost-effectiveness of new technologies.
In this article we report the results of a survey of oncologists in the United States and Canada that we conducted to gauge how much benefit oncologists believe new treatments need to provide so as to justify their costs. To determine the stability of the oncologists’ attitudes about what constitutes a cost-effective treatment, we randomized oncologists to receive different versions of our survey, in which we varied the price of the new treatment.
Study Data And Methods
We surveyed oncologists in the United States and Canada, presenting them with a hypothetical new chemotherapy drug and asking them how much benefit, in months of life expectancy gain, this drug would need to provide to warrant its use. We randomly varied the scenario across respondents, as described below, to assess the stability of oncologists’ attitudes.
SURVEY METHODS
In the United States, we surveyed a random sample of members of the American Society of Clinical Oncology, the largest clinical oncology organization in the country. More than two-thirds of the oncologists in the United States are members of this society (Allen S. Lichter, American Society of Clinical Oncology, personal communication). We mailed surveys to 1,389 randomly selected society members. Twenty-four surveys were returned to us by the post office as undeliverable, leaving our study denominator at 1,365. We randomized society members to receive either a $50 incentive on the first mailing and none on the second, or a $20 incentive on both mailings. All responses were anonymous. Our overall response rate of 59 percent did not vary as a function of the financial incentive (p > 0.10).
In Canada, we distributed the survey to all 238 medical oncologists outside of Quebec Province using the following sources: the membership list of the Canadian Association of Medical Oncologists, the Canadian Medical Directory, and the directory of Fellows of the Royal Canadian College of Physicians and Surgeons. We excluded oncologists in Quebec Province because our survey was written in English. Participants received an e-mail link to a web-based version of the survey as well as a hard-copy version by mail. E-mail reminders were sent to enhance the response rate.
GENERAL ATTITUDES TOWARD VALUE FOR MONEY
In a portion of the questionnaire assessing oncologists’ general attitudes toward the cost of cancer care, we asked them: “What do you think is a reasonable definition of good value for money or cost-effectiveness per life-year gained?” Response categories were $0–50,000, $50,001–$100,000, $100,001–$150,000, $150,001–$200,000, and more than $200,000.
A HYPOTHETICAL CLINICAL SCENARIO
Our clinical scenario was adapted from the work of Eric Nadler and coauthors.17 The scenario involved a patient with metastatic cancer who was expected to survive for twelve months with standard chemotherapy at a cost of $25,000. The survey asked oncologists: “What minimum improvement in median survival (in months) over standard treatment’s median survival would cause you to prescribe the new medication instead of standard treatment? (Assume that patients bear no out-of-pocket costs for the medication.)” Thus, our scenario essentially asked oncologists to consider a societal perspective on treatment cost.
Across oncologists, we randomly varied the cost of the hypothetical new drug, indicating that it cost either $75,000 or $150,000. In other words, we asked some oncologists to consider a $75,000 drug, and others a $150,000 drug. This experimental randomization enabled us to test whether the implicit cost-effectiveness ratio endorsed by physicians in this scenario was stable or, instead, whether respondents were relatively insensitive to the financial cost of the new drug.
The $75,000 drug cost $50,000 more than the standard treatment. A physician who indicated that the new drug must extend a patient’s life by at least three months to justify its use therefore implicitly endorsed a cost-effectiveness ratio of $200,000 per year of life, because $50,000 for three months equates to $200,000 per year. In contrast, the $150,000 drug cost $125,000 more than the standard treatment. An oncologist using the same cost-effectiveness ratio for this drug would require that it extend a patient’s life by 7.5 months: $125,000 for 7.5 months equates to $200,000 per year.
Later in the survey, we presented oncologists with a second scenario, focused on treatments that improve quality of life but do not extend length of life. We did not experimentally vary the price of the treatments in the second scenario. Because the focus of our current analysis is price sensitivity, we do not report the responses on the quality of life scenario here.
DATA ANALYSIS
All data were entered by two separate research assistants. Discrepancies in data entry were resolved by referring to the original questionnaire. Because of the interests of one of our funders, the California HealthCare Foundation, we oversampled oncologists practicing in California. To adjust for this sampling strategy, we used poststratification weights in all analyses.
The primary outcome measure in this study was the cost-effectiveness ratio implied by physicians’ responses. See the online Appendix for details of our calculation.18
To test the influence of our experimental factor (drug price) on physicians’ cost-effectiveness judgments, we conducted linear regression analyses. The dependent variable was the implicit cost-effectiveness ratio. The independent variable was drug price. We adjusted for respondents’ age, sex, and percentage of time spent in clinical practice.
The implicit cost-effectiveness ratios were skewed. Therefore, we ran analyses again, with the natural log of the cost-effectiveness ratio as the dependent variable. All of our results were robust.
LIMITATIONS
Our study has a few limitations. First, it was limited to US and Canadian oncologists and does not necessarily reflect the views of oncologists in other countries, who typically practice in very different health systems. Nevertheless, the health systems in the United States and Canada, although geographically close, are quite different. The similarity in attitudes in the two countries suggests that our findings are potentially of widespread interest.
Second, a response rate of 59 percent means that our results might be biased, although it is similar to that reported in the majority of physician surveys.19 However, nonresponse bias has no bearing on our main experimental finding: that cost-effectiveness ratios were significantly influenced by the cost of the hypothetical new drug. On a related point, our US sample—members of the American Society of Clinical Oncology—was not a representative sample of US oncologists. Nonetheless, the sample included the majority of the country’s medical oncologists.
Third, our survey relied on responses to a hypothetical clinical scenario. It therefore may not reflect how oncologists behave in practice. However, research has shown that responses to clinical scenarios closely mirror actual practice.20 In addition, by posing a hypothetical scenario, we were able to control other factors relevant to such decisions, such as patients’ out-of-pocket costs and the cost of the new treatments.
Fourth, our scenario did not describe the quality of life of the hypothetical cancer patient in enough detail for respondents to be able to calculate the quality-adjusted life-years created by treatment. To account for this, in our cost-effectiveness threshold analyses, we made the generous assumption that patients experienced the maximal quality of life. This means that the cost-effectiveness thresholds presented here are best-case scenarios.
Study Results
The online Appendix18 shows basic demographic information for our respondents. None of these demographic characteristics varied significantly across the two versions of the questionnaire (p > 0.10). We received responses from 788 US oncologists and 158 Canadian oncologists, for an overall response rate of 59 percent. For US oncologists, the response rate was 57 percent; for Canadian oncologists, it was 65 percent.
When we asked oncologists to explicitly indicate what constitutes “good value for money,” Canadian oncologists, on average, endorsed higher cost-effectiveness thresholds than their US colleagues (p = 0.04) (Exhibit 1). However, only 30 percent of US oncologists and 35 percent of Canadian oncologists endorsed cost-effectiveness ratios of higher than $100,000 per life-year.
Exhibit 1.
Treatment Cost Per Life-Year Gained That Represents ‘Good Value For Money’ To Oncologists In The United States And Canada
SOURCE Authors’ analysis.
Responses to the clinical scenario revealed very different attitudes toward the cost-effectiveness of oncology treatments. Exhibit 2 shows the increase in median life expectancy that oncologists indicated would warrant the use of a new drug, according to whether the drug cost $75,000 or $150,000. Responses to the clinical scenario did not significantly differ between US and Canadian oncologists (p > 0.10; data not shown). However, the cost of the drug was significantly associated with the number of additional months that oncologists felt patients needed to live to justify use of the drug. For the $75,000 drug, oncologists required a mean of 6.0 additional months of life, versus 7.8 months for the $150,000 drug (p < 0.001).
Exhibit 2.
Increase In Life Expectancy, In Months, That Warrants Use Of New Drug To Oncologists, By Cost Of Hypothetical New Drug
SOURCE Authors’ analysis.
Oncologists demanded longer survival from the $150,000 drug, but their demands did not rise in proportion to the drug’s incremental cost. Consequently, the cost-effectiveness ratios implied by their responses to the clinical scenarios differed significantly, depending on the cost of the drug (Exhibit 3).
Exhibit 3.
Cost-Effectiveness Ratios Implied By Oncologists’ Responses To The Clinical Scenario
SOURCE Authors’ analysis. NOTES For the $150,000 drug, the median is the middle line, with arrows pointing up to the 75th percentile and down to the 25th. For the $75,000 drug, both the 25th and 50th percentiles were $100,000 per life-year.
For example, of the oncologists presented with the lower-cost drug, the median respondent endorsed a cost-effectiveness ratio of $100,000 per year of life gained. That ratio equates to a median increase in life expectancy of six months because the drug cost $50,000 more than standard therapy. The twenty-fifth percentile of those oncologists also endorsed a cost-effectiveness ratio of $100,000 per year of life. However, the seventy-fifth percentile endorsed a cost-effectiveness ratio of $200,000 per year of life—stating that the drug would need to extend life by four months.
In contrast, of the oncologists presented with the more expensive drug, the median respondent endorsed a cost-effectiveness ratio of $250,000 per year of life gained. These oncologists did not adjust their life expectancy demands in proportion to the increased price of the treatment. Indeed, this $250,000 ratio equates, once again, to a median life expectancy of six months because the drug cost $125,000 more than standard therapy.
Discussion
When asked what cost per year of life represents “good value for money,” the majority of oncologists endorsed cost-effectiveness ratios of less than $100,000 per life year. Yet, when presented with a hypothetical patient with metastatic cancer and the chance to prescribe an expensive new drug, both US and Canadian oncologists implicitly endorsed much higher cost-effectiveness ratios, often several hundred thousand dollars per life-year gained. In addition, responses to the clinical scenario revealed that oncologists were relatively insensitive to the cost of drugs, failing to adjust their expectations of a drug’s benefits in proportion to its price.
In theory, cost-effectiveness information is supposed to guide decision makers by letting them compare the value of a given intervention to an implicit cost-effectiveness threshold.21 However, the results of this study show that oncologists do not have consistent opinions about how many months an expensive new therapy should extend a person’s life before the cost of therapy is justified. In fact, their responses suggest that oncologists are relatively insensitive to the costs of such drugs when making these decisions.
Such results are not entirely surprising, nor should they be viewed as a criticism of oncologists. Most physicians receive very little training in how to factor cost-effectiveness information into their decision making, and many indicate that they are uncomfortable using cost-effectiveness information.22 And most physicians are often unaware of the costs of the medications they prescribe.15,23,24 In fact, most physicians are taught that they should disregard this information when treating individual patients and should leave such judgments up to policy makers.25
IMPLICATIONS
The relative price insensitivity exhibited by the oncologists in our study has important implications for the pricing of new oncology therapies. Pharmaceutical companies price drugs based in large measure on what the market will bear.26 The market price depends in part on the willingness of third-party payers to reimburse treatment. But it also depends on oncologists’ decisions about whether or not a therapy yields enough benefit to justify its cost. The extremely high price of many new treatments may, in part, reflect a phenomenon uncovered in this study—that the benefit oncologists demand from new treatments does not necessarily increase according to the price of the treatment.
Cost-effectiveness experts usually endorse thresholds of between $50,000 and $100,000 per quality-adjusted life-year (QALY).19 The concept of a QALY is designed to capture both the length and degree of treatment benefit, so that a life extension of one year in perfect health yields a benefit of one QALY. Extending a patient’s life for a year, but at less than perfect health, would yield less than one QALY. Indeed, the United Kingdom’s National Institute for Health and Clinical Excellence has adopted this threshold as a key input in deciding whether to recommend payment for a new treatment.27 Oncologists’ responses to our clinical scenario raise questions about the appropriateness of this $50,000–$100,000 threshold because most of the cost-effectiveness ratios implied by their responses far exceed it.
However, oncologists’ apparent rejection of the threshold needs to be considered with caution. First, the implicit cost-effectiveness thresholds used by our respondents varied widely across physicians, reflecting a lack of consensus about these issues. Our observation of a large difference in oncologists’ implicit cost-effectiveness thresholds based on the cost of the drug further reflected this lack of consensus.
Second, when questioned directly about what constitutes a reasonable threshold, more than two-thirds of our respondents indicated that treatments costing more than $100,000 per QALY were not good value for money, an attitude that directly contradicted their answers to the clinical scenario. In other words, they endorsed the $50,000–$100,000 threshold in the abstract but abandoned it when indicating how they would treat an individual patient.
IMPORTANT ASPECTS OF PHYSICIANS’ ATTITUDES
Our study takes advantage of an experimental design to determine the stability of oncologists’ attitudes. Oncologists’ explicit views of what constitutes value for money correlated with the implicit cost-effectiveness ratios suggested by their responses to the clinical scenario.28 This set of results could be interpreted as evidence of a potentially stable underlying value. But our experimental design highlights a much more important aspect of physicians’ attitudes about the cost-effectiveness of oncology treatment: These attitudes are neither well developed nor consistent.
In their earlier article,17 Nadler and coauthors surveyed oncologists in the Boston area, presenting them with a scenario similar to the one in our study. Nadler and coauthors asked oncologists how much longer a patient would need to survive to warrant the prescription of an expensive new medication. That article has been widely cited as evidence of how oncologists think about the cost-effectiveness of their treatments.
The current study expands on the earlier study by including a randomized experiment, in which we varied the price of the hypothetical drug in the scenario. Such experimental survey designs, widely used in behavioral economics, enable researchers to test the stability and consistency of people’s values and attitudes.29 In the current study, the experimental design reveals that oncologists’ attitudes may not be stable enough to guide policy decisions.
LESSONS FOR POLICY MAKERS
Our study has several implications for policy makers looking for ways to control health care spending. First, it suggests that making physicians aware of the costs of the treatments they prescribe, a policy recommended by some experts,30,31 may not on its own have much effect on physicians’ decision making. Educating physicians about how to use cost-effectiveness information may improve their decision making, but other studies show that such an approach would also face obstacles—such as physicians’ unwillingness to apply the same cost-effectiveness thresholds to established treatments as they do to new ones.32
A better approach might be to more strongly influence physicians’ decision making through clinical guidelines that incorporate cost-effectiveness information.33 Such guidelines would both signal to physicians whether specific interventions were appropriate and give them the flexibility to deviate from the guidelines in special circumstances. If such guidelines failed to produce the desired effect, policy makers might need to resort to stronger interventions. For example, they might take the approach of the UK National Institute for Health and Clinical Excellence, using cost-effectiveness information to inform coverage decisions for new treatments. Policy makers may need to take more of a leadership role in determining affordability, instead of leaving these decisions to individual physicians.
Conclusion
Industrialized societies face many difficult decisions about when to pay for expensive new health interventions to extend patient life. Physicians are likely to play a prominent role in making these decisions. But they need help. Oncologists responding to our survey demonstrated that they held inconsistent views on how much benefit expensive new drugs should provide to be considered worthwhile. The physicians’ decisions about new treatments may not be appropriately sensitive to the cost and value of such therapies.
We need to improve the way physicians are trained and supported to incorporate economic consequences of their clinical decisions into their decision-making process, or develop other ways to ensure that medical treatments bring good value for their cost.
Acknowledgments
This research was funded by a grant from the California HealthCare Foundation. Peter Ubel was also supported by the National Institutes of Health (Grant Nos. R01 CA087595 and P50 CA101451) and by an Investigator in Health Policy Award from the Robert Wood Johnson Foundation. Chaim Bell was supported by a Canadian Institutes of Health Research Award and a Canadian Patient Safety Institute Chair. The authors express their appreciation to their lead research assistant, Julie Parow, and to others who provided research assistance: Darryn Fitzgerald, Sarah Scheitler, Brenna Smith, Erinn Smith, Chris DeVries, Karis Crawford, Aimee Stanczyk, Nicole Exe, Amy Motomura, and Becky Uhlmann. The authors also thank Aleksandra Jankovic for assistance with statistical analyses.
Biographies
Peter A. Ubel is the John O. Blackburn Professor of Business, Public Policy, and Medicine at Duke University.
In this month’s Health Affairs, Peter Ubel and coauthors report on a survey of physicians’ attitudes about the value of expensive new cancer treatments that may extend life for a period of time. They find that physicians aren’t consistent in their opinions about how many months an expensive new therapy should extend a person’s life before the cost of therapy is justified—especially when asked to contemplate a hypothetical scenario involving an individual patient. The authors identify a need to improve how physicians are educated on the use of cost-effectiveness information and to influence their decision making through clinical guidelines that incorporate such information.
Ubel is the John O. Blackburn Professor of Business, Public Policy, and Medicine at Duke University and a Robert Wood Johnson Foundation health policy investigator. His research explores topics in medical decision making using the tools of behavioral economics and decision psychology. He recently completed a book on the psychology of shared decision making, and he is conducting a series of studies exploring the psychological barriers to controlling health care costs.
Ubel received a medical degree from the University of Minnesota and pursued fellowship training in bioethics at the University of Chicago and the University of Pittsburgh.
Scott R. Berry is an associate professor of medicine at the University of Toronto.
Scott Berry is a medical oncologist at Sunnybrook Odette Cancer Centre and an associate professor of medicine at the University of Toronto. His academic focus is education, clinical research, and the ethical issues in cancer care. He received both a medical degree and master’s degree in health sciences, with a concentration in bioethics, from the University of Toronto.
Eric Nadler is codirector of the lung and the head and neck cancer programs at Baylor Charles A. Sammons Cancer Center.
Eric Nadler is codirector of the lung and the head and neck cancer programs at Baylor Charles A. Sammons Cancer Center. His research focuses on health informatics, cost of care, and clinical research. Nadler earned a master’s degree in public policy and a medical degree from Harvard University.
Chaim M. Bell is a hospital physician and clinician-scientist at the University of Toronto.
Chaim Bell is a hospital physician and clinician-scientist at the University of Toronto and St. Michael’s Hospital, in addition to being a member of the pan-Canadian Oncology Drug Review. He holds a joint Canadian Institutes of Health Research and Canadian Patient Safety Institute Chair in Continuity of Care and Patient Safety. His research interests include quality of care, medical errors, and the role of cost-effectiveness in health policy.
Bell completed his medical degree and specialty training in internal medicine at the University of Toronto, where he also received a doctorate in clinical epidemiology and health services research. He was a visiting fellow in medical economics and cost-effectiveness analysis at the Harvard School of Public Health.
Michael A. Kozminski is a resident in urology at the University of Michigan, in Ann Arbor.
Michael Kozminski is a urology resident at the University of Michigan, where he received his medical degree.
Jennifer A. Palmer is a doctoral student at the Boston University School of Public Health.
Jennifer Palmer is a doctoral student in the Department of Health Policy and Management at the Boston University School of Public Health. Her research interests include quality of life in the elderly and at nursing homes. Palmer has a master’s degree in communication disorders from Boston University.
William K. Evans is a professor at McMaster University.
William Evans is a medical oncologist, president of the Juravinski Cancer Centre, and a professor at McMaster University. His areas of interest include health services research, the cost and cost-effectiveness of anticancer drugs, and lung cancer. Evans earned his medical degree at the University of Toronto.
Elizabeth L. Strevel is a medical oncologist at Credit Valley Hospital.
Elizabeth Strevel is a medical oncologist at Credit Valley Hospital, in Mississauga, Ontario. Her research interests are in oncology clinical trials, with a specific focus on gastrointestinal and lung disease sites. In 2007 she received the American Society of Clinical Oncology Foundation Merit Award. Strevel received her medical degree from the University of Western Ontario.
Peter J. Neumann is a professor of medicine at Tufts University School of Medicine.
Peter Neumann is director of the Center for the Evaluation of Value and Risk in Health at the Institute for Clinical Research and Health Policy Studies at Tufts Medical Center and a professor of medicine at Tufts University School of Medicine. His primary interest is in conducting research that explores the roles of cost-effectiveness analysis in health policy. He holds a doctorate in health policy and management from Harvard University.
Contributor Information
Peter A. Ubel, Email: peter.ubel@duke.edu, John O. Blackburn Professor of Business, Public Policy, and Medicine at Duke University, in Durham, North Carolina
Scott R. Berry, Associate professor of medicine at the University of Toronto, in Ontario, and a medical oncologist at Sunnybrook Odette Cancer Centre
Eric Nadler, Codirector of the lung and the head and neck cancer programs at Baylor Charles A. Sammons Cancer Center, in Dallas, Texas.
Chaim M. Bell, Hospital physician and clinician-scientist at the University of Toronto
Michael A. Kozminski, Resident in urology at the University of Michigan, in Ann Arbor
Jennifer A. Palmer, Doctoral student in the Department of Health Policy and Management at the Boston University School of Public Health, in Massachusetts
William K. Evans, Medical oncologist, president of the Juravinski Cancer Centre, and professor at McMaster University, in Hamilton, Ontario
Elizabeth L. Strevel, Medical oncologist at Credit Valley Hospital, in Mississauga, Ontario
Peter J. Neumann, Director of the Center for the Evaluation of Value and Risk in Health, Institute of Clinical Research and Health Policy Studies, Tufts Medical Center; and a professor of medicine at Tufts University School of Medicine, in Boston
NOTES
- 1.Hurwitz H, Fehrenbacher L, Novotny W, Cartwright T, Hainsworth J, Heim W, et al. Bevacizumab plus irinotecan, fluorouracil, and leuco-vorin for metastatic colorectal cancer. N Engl J Med. 2004;350(23):2335–42. doi: 10.1056/NEJMoa032691. [DOI] [PubMed] [Google Scholar]
- 2.Cunningham D, Humblet Y, Siena S, Khayat D, Bleiberg H, Santoro A, et al. Cetuximab monotherapy and cetuximab plus irinotecan in irinotecan-refractory metastatic colorectal cancer. N Engl J Med. 2004;351(4):337–45. doi: 10.1056/NEJMoa033025. [DOI] [PubMed] [Google Scholar]
- 3.Rocconi R, Case A, Straughn J, Estes J, Partridge E. Role of chemotherapy for patients with recurrent platinum-resistant advanced epithelial ovarian cancer: a cost-effectiveness analysis. Cancer. 2006;107(3):536–43. doi: 10.1002/cncr.22045. [DOI] [PubMed] [Google Scholar]
- 4.Sandler A, Gray R, Perry M, Brahmer J, Schiller J, Dowlati A, et al. Pacli-taxel-carboplatin alone or with bevacizumab for non-small-cell lung cancer. N Engl J Med. 2006;355(24):2542–50. doi: 10.1056/NEJMoa061884. [DOI] [PubMed] [Google Scholar]
- 5.Meropol NJ, Schulman KA. Cost of cancer care: issues and implications. J Clin Oncol. 2007;25(2):180–6. doi: 10.1200/JCO.2006.09.6081. [DOI] [PubMed] [Google Scholar]
- 6.Kolata G, Pollack A. New York Times. 2008. Jul 6, In costly cancer drug, hope and a dilemma. [Google Scholar]
- 7.Berenson A. Cancer drugs offer hope, but at huge expense. New York Times. 2008 Jul 12; [PubMed] [Google Scholar]
- 8.Schrag D. The price tag on progress—chemotherapy for colorectal cancer. N Engl J Med. 2004;351(4):317–9. doi: 10.1056/NEJMp048143. [DOI] [PubMed] [Google Scholar]
- 9.Abelson R. Health care costs create rising strain, studies find. New York Times. 2008 Sep 25; [Google Scholar]
- 10.Neumann P, Palmer J, Abrahams D, Ubel PA. Struggling with expensive new cancer therapies: a national survey of oncologists. Health Aff (Millwood) 2010;29(1):196–202. doi: 10.1377/hlthaff.2009.0077. [DOI] [PubMed] [Google Scholar]
- 11.Langa KM, Fendrick AM, Chernew ME, Kabeto MU, Paisley KL, Hayman JA. Out-of-pocket healthcare expenditures among older Americans with cancer. Value Health. 2004;7(2):186–94. doi: 10.1111/j.1524-4733.2004.72334.x. [DOI] [PubMed] [Google Scholar]
- 12.Schrag D, Hanger M. Medical oncologists’ views on communicating with patients about chemotherapy costs: a pilot study. J Clin Oncol. 2007;25(2):233–7. doi: 10.1200/JCO.2006.09.2437. [DOI] [PubMed] [Google Scholar]
- 13.Chernew ME, Fendrick AM, Hirth RA. Managed care and medical technology: implications for health care cost growth. Health Aff (Millwood) 1997;16(2):196–206. doi: 10.1377/hlthaff.16.2.196. [DOI] [PubMed] [Google Scholar]
- 14.Ubel PA. Pricing life: why it’s time for health care rationing. Cambridge (MA): MIT Press; 1999. [Google Scholar]
- 15.Ubel PA, Arnold RM. The unbearable rightness of bedside rationing. Physician duties in a climate of cost containment. Arch Intern Med. 1995;155(17):1837–42. [PubMed] [Google Scholar]
- 16.Schroeder SA, Sandy LG. Specialty distribution of U.S. physicians—the invisible driver of health care costs. N Engl J Med. 1993;328(13):961–3. doi: 10.1056/NEJM199304013281312. [DOI] [PubMed] [Google Scholar]
- 17.Nadler E, Eckert B, Neumann PJ. Do oncologists believe new cancer drugs offer good value? Oncologist. 2006;11(2):90–5. doi: 10.1634/theoncologist.11-2-90. [DOI] [PubMed] [Google Scholar]
- 18.To access the Appendix, click on the Appendix link in the box to the right of the article online.
- 19.Asch DA, Jedrziewski MK, Christakis NA. Response rates to mail surveys published in medical journals. J Clin Epidemiol. 1997;50(10):1129–36. doi: 10.1016/s0895-4356(97)00126-1. [DOI] [PubMed] [Google Scholar]
- 20.Peabody JW, Luck J, Glassman P, Dresselhaus TR, Lee M. Comparison of vignettes, standardized patients, and chart abstraction: a prospective validation study of 3 methods for measuring quality. JAMA. 2000;283(13):1715–22. doi: 10.1001/jama.283.13.1715. [DOI] [PubMed] [Google Scholar]
- 21.Gold MR, Siegel JE, Russell LB, Weinstein M, editors. Cost-effectiveness in health and medicine. New York (NY): Oxford University Press; 1996. [Google Scholar]
- 22.Berry SR, Bell CM, Ubel PA, Evans WK, Nadler E, Strevel EL, et al. Continental divide? The attitudes of US and Canadian oncologists on the costs, cost-effectiveness, and health policies associated with new cancer drugs. J Clin Oncol. 2010;28(27):4149–53. doi: 10.1200/JCO.2010.29.1625. [DOI] [PubMed] [Google Scholar]
- 23.Allan GM, Lexchin J, Wiebe N. Physician awareness of drug cost: a systematic review. PLoS Med. 2007;4(9) doi: 10.1371/journal.pmed.0040283. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Sulmasy D. Cancer care, money, and the value of life: whose justice? Which rationality? J Clin Oncol. 2007;25(2):217–22. doi: 10.1200/JCO.2006.08.0481. [DOI] [PubMed] [Google Scholar]
- 25.Berry SR, Hubay S, Soibelman H, Martin DK. The effect of priority setting decisions for new cancer drugs on medical oncologists’ practice in Ontario: a qualitative study. BMC Health Serv Res. 2007;7:193. doi: 10.1186/1472-6963-7-193. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Gregson N, Sparrowhawk K, Mauskopf J, Paul J. Pricing medicines: theory and practice, challenges and opportunities. Nat Rev Drug Discov. 2005;4(2):121–30. doi: 10.1038/nrd1633. [DOI] [PubMed] [Google Scholar]
- 27.Birch S, Gafni A. On being NICE in the UK: guidelines for technology appraisal for the NHS in England and Wales. Health Econ. 2002;11:185–91. doi: 10.1002/hec.706. [DOI] [PubMed] [Google Scholar]
- 28.Kozminski MA, Neumann PJ, Nadler ES, Jankovic A, Ubel PA. How long and how well: oncologists’ attitudes toward the relative value of life-prolonging v. quality of life-enhancing treatment. Med Decis Making. 2011;31(3):380–5. doi: 10.1177/0272989X10385847. [DOI] [PubMed] [Google Scholar]
- 29.Ubel PA. Free market madness: why human nature is at odds with economics—and why it matters. Boston (MA): Harvard Business Press; 2009. [Google Scholar]
- 30.Miller LG, Blum A. Physician awareness of prescription drug costs: a missing element of drug advertising and promotion. J Fam Pract. 1993;36(1):33–6. [PubMed] [Google Scholar]
- 31.Reichert S, Simon T, Halm EA. Physicians’ attitudes about prescribing and knowledge of the costs of common medications. Arch Intern Med. 2000;160:2799–803. doi: 10.1001/archinte.160.18.2799. [DOI] [PubMed] [Google Scholar]
- 32.Ubel PA, Jepson C, Baron J, Hershey JC, Asch DA. The influence of cost-effectiveness information on physicians’ cancer screening recommendations. Soc Sci Med. 2003;56(8):1727–36. doi: 10.1016/s0277-9536(02)00167-3. [DOI] [PubMed] [Google Scholar]
- 33.Laupacis A, Feeny D, Detsky AS, Tugwell PX. How attractive does a new technology have to be to warrant adoption and utilization? Tentative guidelines for using clinical and economic evaluations. CMAJ. 1992;146(4):473–81. [PMC free article] [PubMed] [Google Scholar]