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Journal articles on the topic 'Medical economics. Medical policy'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

Redelmeier, Donald A., Daniel N. Heller, and Milton C. Weinstein. "Time Preference in Medical Economics." Medical Decision Making 14, no. 3 (August 1994): 301–3. http://dx.doi.org/10.1177/0272989x9401400313.

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2

Coyte, Peter C., and Rashi Fein. "Medical Care, Medical Costs: The Search for a Health Insurance Policy." Southern Economic Journal 54, no. 4 (April 1988): 1055. http://dx.doi.org/10.2307/1059547.

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3

Simoens, Steven. "Health economics of medical devices: opportunities and challenges." Journal of Medical Economics 11, no. 4 (January 2008): 713–17. http://dx.doi.org/10.3111/13696990802596721.

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4

Arrow, Kenneth J. "Uncertainty and The Welfare Economics of Medical Care." Journal of Health Politics, Policy and Law 26, no. 5 (October 2001): 851–83. http://dx.doi.org/10.1215/03616878-26-5-851.

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5

Etzioni, Amitai. "Making Policy for Complex Systems: A Medical Model for Economics." Journal of Policy Analysis and Management 4, no. 3 (1985): 383. http://dx.doi.org/10.2307/3324192.

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6

Kornhauser, Lewis A., and P. M. Danzon. "Danzon's Medical Malpractice: Theory, Evidence, and Public Policy." RAND Journal of Economics 17, no. 2 (1986): 287. http://dx.doi.org/10.2307/2555391.

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7

Ruhm, Christopher J. "Policy Watch: The Family and Medical Leave Act." Journal of Economic Perspectives 11, no. 3 (August 1, 1997): 175–86. http://dx.doi.org/10.1257/jep.11.3.175.

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This article summarizes the provisions of the Family and Medical Leave Act, its possible effects on labor markets, and the resulting changes in the ability of workers to take leave. The author concludes that the actual provisions of the act are quite modest and have yielded neither large benefits to workers nor imposed significant costs on employers. One reason for this is that few workers gained significant new rights to time off work because the legislation contains many exemptions and employees often had other mechanisms for obtaining leave prior to its enactment.

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8

Matevosyan, Naira R. "Techno-borne Organs: Medical, Legal, and Policy Concerns." Journal of the Knowledge Economy 9, no. 2 (January 4, 2016): 544–60. http://dx.doi.org/10.1007/s13132-015-0346-4.

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9

Sclar, David Alexander. "Pharmaceutical economics & health policy." Clinical Therapeutics 20, no. 2 (March 1998): 326–27. http://dx.doi.org/10.1016/s0149-2918(98)80095-7.

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10

Johnston, Ian. "Book Reviews: Medical Ethics and Economics in Health Care." Health Services Management Research 1, no. 3 (November 1988): 187. http://dx.doi.org/10.1177/095148488800100312.

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11

Dang, Amit, and Jitendar Kumar Sharma. "Economics of Medical Devices in India." Value in Health Regional Issues 18 (May 2019): 14–17. http://dx.doi.org/10.1016/j.vhri.2018.06.004.

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12

Annandale, Ellen. "Professional Defenses: Medical Students' Perceptions of Medical Malpractice." International Journal of Health Services 26, no. 4 (October 1996): 751–75. http://dx.doi.org/10.2190/t5q8-gx9y-k55n-050e.

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Despite the pronounced interest in “challenges to professional dominance” in Britain, medical malpractice has been subject to little empirical attention. There has been a flurry of policy activity within the National Health Service over the last six or so years and a steady stream of commentary from professional bodies, yet we know very little about the views of various medical practitioners who occupy different positions in the professional hierarchy. This article explores the views of (first and fifth year) medical students and considers the extent to which they cohere with the public discourse of medical elites. The author suggests that while individual practice is the focal concern for medical students who seem acutely aware and concerned about litigation, elites construct malpractice as a macro economic-legal problem, strategically severing the association between individual practice and the experience of a malpractice suit.

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13

Hu, Teh-wei, and Ying-ying Meng. "Medical Technology Transfer in Major Chinese Medical Schools." International Journal of Technology Assessment in Health Care 7, no. 4 (1991): 553–60. http://dx.doi.org/10.1017/s026646230000711x.

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AbstractThis paper examines how the decision-making process and its consequences affect medical technology transfer in major Chinese medical schools. Data are from a 1987 survey of 13 key medical universities, directly supervised by the Ministry of Public Health in the People's Republic of China. This paper limits itself to four types of laboratory equipment — electron microscopes, UV/VIS spectrophotometers, high-performance liquid chromatographs, and polygraphs. Decisions on the transfer of medical technology have been more decentralized in China since the economic reform in 1978. The major reason for schools to import these four types of equipment is their dissatisfaction with the quality of domestic products. Chinese medical schools depend heavily on the information provided at medical equipment exhibits and their neighboring schools. Their decisions to acquire the equipment are based more on the quality and service available than on the prices. Chinese medical schools face serious infrastructure problems in acquiring and maintaining these pieces of equipment. A number of suggestions are made for improving the efficiency of medical technology transfer in China.

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14

Beecroft, Claire. "Why health economics deserves a place in the medical curriculum." Journal of Comparative Effectiveness Research 5, no. 4 (July 2016): 321–23. http://dx.doi.org/10.2217/cer-2016-0028.

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15

Hutton, John. "Economic Evaluation of Medical Technologies." International Journal of Technology Assessment in Health Care 2, no. 1 (January 1986): 43–52. http://dx.doi.org/10.1017/s0266462300002762.

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Economic techniques have been used for several years to evaluate health care expenditures, and there is reasonable agreement amongst economists as to the appropriate methodology. Comprehensive reviews of techniques and applications can be found in Drummond (3,4), Culyer and Horisberger (2) and a report from the Office of Technology Assessment (7). More recently Williams (13) has addressed the problems of evaluating a developing technology and Wagner (10) the specific problems of diagnostic technologies.

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16

Cooter, Raelynn, James B. Erdmann, Joseph S. Gonnella, Clara A. Callahan, Mohammadreza Hojat, and Gang Xu. "Economic Diversity in Medical Education." Evaluation & the Health Professions 27, no. 3 (September 2004): 252–64. http://dx.doi.org/10.1177/0163278704267041.

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17

WILBUR, RAY LYMAN. "The Economics of Public Health and Medical Care." Milbank Quarterly 83, no. 4 (November 9, 2005): 523–36. http://dx.doi.org/10.1111/j.1468-0009.2005.00390.x.

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18

Cohen, D. "Medical Ethics and Economics in Health Care." Journal of Medical Ethics 15, no. 1 (March 1, 1989): 54–55. http://dx.doi.org/10.1136/jme.15.1.54-a.

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19

Chuang, Elizabeth. "Expanding Medical Student and Resident Knowledge of Health Economics, Policy, and Management." Academic Medicine 86, no. 11 (November 2011): e1. http://dx.doi.org/10.1097/acm.0b013e318231e122.

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20

Gandjour, Afschin. "The Economic Value Of Medical Technology." Health Affairs 21, no. 1 (January 2002): 275–76. http://dx.doi.org/10.1377/hlthaff.21.1.275.

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21

Kirisits, Andreas, and W. Ken Redekop. "The Economic Evaluation of Medical Devices." Applied Health Economics and Health Policy 11, no. 1 (January 4, 2013): 15–26. http://dx.doi.org/10.1007/s40258-012-0006-9.

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22

Robinson, Ray. "Economics, QALYs and medical ethics: A practical agenda?" Health Care Analysis 3, no. 3 (August 1995): 229–32. http://dx.doi.org/10.1007/bf02197673.

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23

Menzell, Paul T. "Medical Costs, Moral Choices—A Philosophy of Health Care Economics in America." Journal of Ambulatory Care Management 8, no. 1 (February 1985): 83. http://dx.doi.org/10.1097/00004479-198502000-00013.

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24

Jacobs, Philip. "The Economics of Health and Medical Care (4th ed.)." Journal For Healthcare Quality 21, no. 5 (September 1999): 42. http://dx.doi.org/10.1097/01445442-199909000-00016.

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25

Peña-Mohr, Jorge. "Distributing and Transferring Medical Technology." International Journal of Technology Assessment in Health Care 3, no. 2 (April 1987): 281–91. http://dx.doi.org/10.1017/s026646230000057x.

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AbstractGreat variation exists in the health care delivery systems throughout Latin America and the Caribbean. In general, medical technology is concentrated in large cities at private hospitals that serve a small, elite segment of the population. What is missing in most of these countries is a clearly defined social policy guaranteeing distribution of medical technology to all segments of society. While data is scarce, it appears that political and economic concerns, rather than medical concerns, determine what and how much technology will be available to all segments of the society. Products are sometimes imported that compete with domestically produced ones. Moreover, transfers of technology often fail to include the necessary knowledge to make imported technology truly useful. However, current economic crises throughout the region are forcing changes in policies; as a result, there is a new emphasis on domestic production of technology over imports and the evaluation of medical technology for its appropriate use in Latin America and the Caribbean.

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26

Spurr, Stephen J., and Walter O. Simmons. "Medical Malpractice in Michigan: An Economic Analysis." Journal of Health Politics, Policy and Law 21, no. 2 (1996): 315–46. http://dx.doi.org/10.1215/03616878-21-2-315.

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27

Berman, Philip C. "Irish medical care resources: an economic analysis." Health Policy 6, no. 4 (January 1986): 379–80. http://dx.doi.org/10.1016/0168-8510(86)90058-8.

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28

Redelmeier, Donald A., and Allan S. Detsky. "Economic Theory and Medical Assistance in Dying." Applied Health Economics and Health Policy 19, no. 1 (May 6, 2020): 5–8. http://dx.doi.org/10.1007/s40258-020-00587-4.

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29

Doherty, N. J. G. "Economic implications of health care policy for medical technology." IEEE Technology and Society Magazine 7, no. 2 (June 1988): 18–23. http://dx.doi.org/10.1109/44.9197.

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30

Williams, Alan. "Economics, QALYs and medical ethics — A health economist's perspective." Health Care Analysis 3, no. 3 (August 1995): 221–26. http://dx.doi.org/10.1007/bf02197671.

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31

Lyles, Alan. "Pharmaceutical economics and health policy research using administrative data." Clinical Therapeutics 26, no. 7 (July 2004): 1122–23. http://dx.doi.org/10.1016/s0149-2918(04)90184-1.

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32

Mendoza, Roger Lee. "Bringing the patient back in: behavioral decision-making and choice in medical economics." Journal of Medical Economics 21, no. 4 (February 16, 2018): 313–17. http://dx.doi.org/10.1080/13696998.2018.1434532.

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33

Hackney, Donald D., Daniel L. Friesner, and Erica H. Johnson. "Towards a Working Profile of Medical Bankruptcy." Journal of Financial Counseling and Planning 29, no. 1 (June 2018): 75–90. http://dx.doi.org/10.1891/1052-3073.29.1.75.

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Medical bankruptcy refers to individuals with serious medical conditions who feel compelled to file for bankruptcy to seek relief from their medical debts. Noticeably lacking in the literature is a consistent, evidence-based criterion to define who may be classified as medically bankrupt. A more concrete definition would allow policy makers to understand the magnitude of the problem and allow financial counselors to better inform certain households about seeking bankruptcy protection when faced with medical bills. This study uses data drawn from the U.S. Bankruptcy Court’s Eastern Washington District to create an empirical profile of bankruptcy petitioners with medical debt. We then identify those characteristics statistically associated with being “at-risk” of a medical bankruptcy to better understand and define medical bankruptcy.

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34

Black, Douglas. "Expensive Medical and Surgical Technology." International Journal of Technology Assessment in Health Care 5, no. 3 (July 1989): 308–12. http://dx.doi.org/10.1017/s0266462300007376.

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The very title - “Expensive Medical and Surgical Technology” - expresses in coded form a myth that is widely prevalent among those who consider the political and economic aspects of health care. Strangely, it is a myth that finds favor mainly at the extreme ends of the range of attitudes toward health care. Monetarists see it as an incentive toward increasing private provision of health care, while extreme egalitarians see it as another example of unjust privilege. The content of the myth is that there is a definable group of costly procedures, which can somehow be isolated from the general practice of medicine and surgery, after which such procedures can either be made the subject of special private provision or, alternatively, discarded from a rationed system of health care.

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35

Doerpinghaus, Helen I. "Effect of Ambulatory Surgery Policy Provisions on Medical Expense Insurance Claims." Journal of Risk and Insurance 57, no. 4 (December 1990): 608. http://dx.doi.org/10.2307/252946.

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36

Doessel, D. P. "Medical diagnosis as a problem in the economics of information." Information Economics and Policy 2, no. 1 (January 1986): 49–68. http://dx.doi.org/10.1016/0167-6245(86)90014-4.

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37

Gruber, Jonathan, and Helen Levy. "The Evolution of Medical Spending Risk." Journal of Economic Perspectives 23, no. 4 (November 1, 2009): 25–48. http://dx.doi.org/10.1257/jep.23.4.25.

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How has the economic risk of health spending changed over time for U.S. households? We describe trends in aggregate health spending in the United States and how private insurance markets and public insurance programs have changed over time. We then present evidence from Consumer Expenditure Survey microdata on how the distribution of household spending on health—that is, out-of-pocket payments for medical care plus the household's share of health insurance premiums—has changed over time. This distribution has shifted up over time—households spend more on medical care and insurance than they used to—but for the purposes of measuring change in risk, it is not the mean but the dispersion of this distribution that is of interest. We consider two measures of dispersion that serve as proxies for household risk: the standard deviation of the distribution of household health spending and the ratio of the 90th percentile of spending to the median (the so-called “90/50 gap”). We find, surprisingly, that neither has increased despite the rapid rise in aggregate health spending. This conclusion holds true for broad subgroups of the population (for example, the nonelderly as a group) but not for some narrowly-defined subgroups (for example, low-income families with children). We next consider how much risk households should face, from the perspective of economic efficiency. Household risk may not have changed much over the past several decades, but do we have any evidence that this level represents either too much or too little risk? Finally, we discuss implications for public policy—in particular, for current debates over expanding health insurance coverage to the uninsured.

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38

Liljas, Bengt, Göran S. Karlsson, and Nils-Olov Stålhammar. "On future non-medical costs in economic evaluations." Health Economics 17, no. 5 (2008): 579–91. http://dx.doi.org/10.1002/hec.1279.

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39

Towse, Adrian, and Patricia Danzon. "Medical negligence and the NHS: an economic analysis." Health Economics 8, no. 2 (March 1999): 93–101. http://dx.doi.org/10.1002/(sici)1099-1050(199903)8:2<93::aid-hec419>3.0.co;2-g.

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40

Lehocka, L., L. Masarykova, M. Snopkova, and S. Bohusova. "Influence of Medical–Economic Analysis on the Categorization of Special Medical Equipment." Value in Health 19, no. 7 (November 2016): A707. http://dx.doi.org/10.1016/j.jval.2016.09.2067.

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41

Boas, Gijs, Hans van der Stel, Hans Peters, Manuela Joore, and Lucien Anteunis. "DYNAMIC MODELING IN MEDICAL TECHNOLOGY ASSESSMENT." International Journal of Technology Assessment in Health Care 17, no. 4 (October 2001): 618–25. http://dx.doi.org/10.1017/s0266462301107178.

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Objectives: The main objective of this article is to demonstrate the usefulness of dynamic modeling for an economic assessment of technology in health care. Specifically, this approach is applied to assess the impact of the use of hearing aids in Dutch health care.Methods: The population is divided into different health classes between which, over time, transitions occur. Transition probabilities are derived from exogenous data. The transitions are associated with economic and societal costs and benefits. People who are satisfied with their hearing aids experience benefits. These benefits are expressed by quality-adjusted life-years (QALYs). Costs are made during transitions (mainly the fitting of hearing aids). A cohort analysis is carried out, starting with people in a particular age group. The starting point is a fixed number of people within this age group, who are followed during their whole lifetime.Results: Costs per QALY ratios are calculated for two health programs. The Fitting Hearing Aid Program describes the present situation in the Netherlands; the Post-purchase Counseling Hearing Aid Program is a hypothetical addition to the first program, where an intervention based on a Dutch study is undertaken to improve satisfaction with hearing aids. Future benefits and costs are discounted at a rate of 5%.Conclusions: The dynamic modeling approach provides a more realistic picture than a static approach. Particularly, the cost-effectiveness of the Fitting Hearing Aid Program is compared with the Post-purchase Counseling Hearing Aid Program.

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42

Grennan, Matthew, and Robert J. Town. "Regulating Innovation with Uncertain Quality: Information, Risk, and Access in Medical Devices." American Economic Review 110, no. 1 (January 1, 2020): 120–61. http://dx.doi.org/10.1257/aer.20180946.

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We study the impact of regulating product entry and quality information requirements on an oligopoly equilibrium and consumer welfare. Product testing can reduce consumer uncertainty, but also increase entry costs and delay entry. Using variation between EU and US medical device regulations, we document patterns consistent with valuable learning from more stringent US requirements. To derive welfare implications, we pair the data with a model of supply, demand, and testing regulation. US policy is indistinguishable from the policy that maximizes total surplus in our estimated model, while the European Union could benefit from more testing. “Post-market surveillance” could further increase surplus. (JEL D43, I18, L13, L51, L64, O31, O38)

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43

Blüher, Maximilian, Virginie Mittard, Rafael Torres, and Rhodri Saunders. "OP98 Limitations In Health-Economic Guidance For Medical Devices." International Journal of Technology Assessment in Health Care 35, S1 (2019): 25. http://dx.doi.org/10.1017/s026646231900148x.

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IntroductionHealth technology assessment (HTA) includes consideration of health and economic factors, playing a key role in optimizing healthcare provision in Europe. Medical devices are an important contributor to both health outcomes and the cost of healthcare provision, yet they are rarely addressed in current guidance for health-economic evaluation. Our aim is to help improve assessment of medical devices via review of European health-economic guidelines and recent research.MethodsSearches for European HTA guidelines were performed and where available were reviewed by two researchers working independently. Additionally, a systematic review of published literature focused on assessment of medical devices was conducted. English, German, or French literature published between 2000 and 2017 was analyzed. The status of HTA guidance to date was subsequently reviewed in light of current research findings and suggestions made to help improve standardization.ResultsOf the 41 investigated European countries, 22 had official HTA guidance. Only four of 22 (18 percent) dedicated documentation to guidance specific to medical devices. Where differences between pharmaceuticals and medical devices were highlighted, specifics for health-economic assessment of medical devices were generally absent. The systematic review yielded 472 unique articles, 28 of which underwent full-text review. Issues surrounding medical device value assessment that commonly emerged were: limited evidence base, learning curve effects, organizational impact, incremental innovation, diversity of devices, dynamic pricing, and transferability. While identification of issues was ubiquitous, actionable suggestions on how to overcome them were less common. The most frequent recommendations were use of Bayesian methods, inclusion of real-world data, and modelling the learning curve. Key to implementation is determination of the medical device type and its impact duration.ConclusionsCurrent guidelines rarely address the needs of medical devices. Practical recommendations for improvements exist and provide opportunity to start discussion on how best to serve the medical devices field and improve the HTA process.

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44

Howard, Ronald A. "Microrisks for Medical Decision Analysis." International Journal of Technology Assessment in Health Care 5, no. 3 (July 1989): 357–70. http://dx.doi.org/10.1017/s026646230000742x.

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Many would agree on the need to inform patients about the risks of medical conditions or treatments and to consider those risks in making medical decisions. The question is how to describe the risks and how to balance them with other factors in arriving at a decision. In this article, we present the thesis that part of the answer lies in defining an appropriate scale for risks that are often quite small. We propose that a convenient unit in which to measure most medical risks is the microprobability, a probability of 1 in 1 million. When the risk consequence is death, we can define a micromort as one microprobability of death. Medical risks can be placed in perspective by noting that we live in a society where people face about 270 micromorts per year from interactions with motor vehicles.Continuing risks or hazards, such as are posed by following unhealthful practices or by the side-effects of drugs, can be described in the same micromort framework. If the consequence is not death, but some other serious consequence like blindness or amputation, the microrisk structure can be used to characterize the probability of disability.Once the risks are described in the microrisk form, they can be evaluated in terms of the patient's willingness-to-pay to avoid them. The suggested procedure is illustrated in the case of a woman facing a cranial arteriogram of a suspected arterio-venous malformation. Generic curves allow such analyses to be performed approximately in terms of the patient's sex, age, and economic situation. More detailed analyses can be performed if desired.Microrisk analysis is based on the proposition that precision in language permits the soundness of thought that produces clarity of action and peace of mind.

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45

Liu, Bai, Shuyan Guo, and Bin Ding. "Technical Blossom in Medical Care: The Influence of Big Data Platform on Medical Innovation." International Journal of Environmental Research and Public Health 17, no. 2 (January 14, 2020): 516. http://dx.doi.org/10.3390/ijerph17020516.

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Medical innovation has consistently been an essential subject and a source of support for public health research. Furthermore, improving the level of medical research and development is of great concern in this field. This paper highlights the role of big data in public medical innovation. Based on a sample of China’s listed firms in the medical industry from 2013 to 2018, this paper explores the exogenous shock effect of China’s big data medical policy. Results show that the construction of the medical big data platform effectively promotes innovation investment and the innovation patent of medical firms. In addition, the heterogeneity of this promoting effect is reflected in firm size through the overcoming of different innovation bottlenecks. The research conclusions support the positive significance of the macro-led implementation of the medical big data platform, and suggest that the positive economic externalities generated by this policy are critical to public health.

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46

Newhouse, Joseph P. "Policy Watch: Medicare." Journal of Economic Perspectives 10, no. 3 (August 1, 1996): 159–67. http://dx.doi.org/10.1257/jep.10.3.159.

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The forecast growth for Medicare spending has created a highly visible budgetary impasse between the president and Congress. Both favor the growth of health plans that accept risk and would promote them by creating less restrictive options than heretofore. Nonetheless, the conference bill the president vetoed for other reasons did not envision price competition among plans but relied upon administered prices instead. The bill allowed Medical Savings Accounts; because of selection, the Congressional Budget Office estimated they would slightly increase Medicare costs. By eliminating the subsidy at the margin to hiring a resident, the bill's provisions would shift demand for residents down.

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47

Ackerly, D. Clay, Seth W. Glickman, and Kevin A. Schulman. "Economic Content in Medical Journal Advertisements for Medical Devices and Prescription Drugs." PharmacoEconomics 28, no. 5 (May 2010): 429–38. http://dx.doi.org/10.2165/11318780-000000000-00000.

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48

Wagner, Judith L. "Cost Containment and Computerized Medical Imaging." International Journal of Technology Assessment in Health Care 3, no. 3 (July 1987): 343–53. http://dx.doi.org/10.1017/s0266462300001161.

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AbstractToday, computers are used in several important and fast-growing medical imaging modalities, such as digital subtraction angiography, positron emission tomography, magnetic resonance imaging, nuclear medicine, and diagnostic ultrasound. The ultimate test for the computer in medical imaging will be its ability to replace traditional film-based radiography as the mechanism for displaying, communicating, and storing imaging information. This transition will require radiologists and other imagers to accept information in digital form. The speed of that acceptance depends on the economic incentives of the health care system. These are changing as a result of cost containment, which is moving away from fee-for-service toward bundled payment. The increase in capitated health plans will encourage the development of digital radiography systems that realistically trade-off the perceived quality needs of radiologists with the costs of producing and operating such systems.

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49

Mähs, Mareike. "OP60 Challenges In Evaluating Smart Medical Devices." International Journal of Technology Assessment in Health Care 35, S1 (2019): 15. http://dx.doi.org/10.1017/s0266462319001223.

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IntroductionSmart medical devices can empower elderly to live independently in their familiar surroundings. To enhance their dissemination, they have to be shown to be cost-effective. Economic studies evaluating such technologies are missing or are criticized for their low quality. There are several challenges in the evaluation of smart medical devices, including their complex nature and innovative character. The question arises: how can evaluations elicit the benefits and cost-effectiveness of smart medical devices. This research has the aim of outlining challenges and demands on the evaluation of smart medical devices.MethodsThe embedding of the technology in existing structures can influence the effectiveness of the technology. By comparing such a technology with a regular intervention, learning effects have to be considered. Regular modifications and further developments of these technologies can complicate the traceability of the effects. Complex cause-effect relationships with possible interactions arise that are difficult to quantify and express in standardized endpoints, utilities or monetary values. Demands on the evaluation of smart medical devices have been explored with literature reviews and scenario techniques using the example of intelligent rollators.ResultsIt is important to apply mixed-method approaches not only in the clinical but also practical setting and conduct observational as well as qualitative studies. Potential users, their relatives and care personnel should be involved in the evaluation of intelligent rollators and attention should be payed to subjects with disabilities. Prospective studies should be conducted at different stages along the lifecycle of the technology. A conceptual model should be developed and evaluated as well as adapted on a regular basis.ConclusionsThe research shows the need to adapt common methods used in economic evaluation to the characteristics of smart medical devices. As a next step, a framework for the economic evaluation of such technologies within the scope of Health Technology Assessment is developed based on these demands.

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50

Barr, Judith. "Use of patient-reported outcomes in pharmaceutical economics and health policy." Clinical Therapeutics 28, no. 10 (October 2006): 1710–11. http://dx.doi.org/10.1016/j.clinthera.2006.10.021.

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