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  • 1.
    Cao, Qi
    et al.
    University of Groningen, Netherlands.
    Buskens, Erik
    University of Groningen, Netherlands.
    Feenstra, Talitha
    University of Groningen, Netherlands; National Institute Public Health and Environm, Netherlands.
    Jaarsma, Tiny
    Linköping University, Department of Social and Welfare Studies, Division of Nursing Science. Linköping University, Faculty of Medicine and Health Sciences.
    Hillege, Hans
    University of Groningen, Netherlands; University of Groningen, Netherlands.
    Postmus, Douwe
    University of Groningen, Netherlands.
    Continuous-Time Semi-Markov Models in Health Economic Decision Making: An Illustrative Example in Heart Failure Disease Management2016In: Medical decision making, ISSN 0272-989X, E-ISSN 1552-681X, Vol. 36, no 1, p. 59-71Article in journal (Refereed)
    Abstract [en]

    Continuous-time state transition models may end up having large unwieldy structures when trying to represent all relevant stages of clinical disease processes by means of a standard Markov model. In such situations, a more parsimonious, and therefore easier-to-grasp, model of a patients disease progression can often be obtained by assuming that the future state transitions do not depend only on the present state (Markov assumption) but also on the past through time since entry in the present state. Despite that these so-called semi-Markov models are still relatively straightforward to specify and implement, they are not yet routinely applied in health economic evaluation to assess the cost-effectiveness of alternative interventions. To facilitate a better understanding of this type of model among applied health economic analysts, the first part of this article provides a detailed discussion of what the semi-Markov model entails and how such models can be specified in an intuitive way by adopting an approach called vertical modeling. In the second part of the article, we use this approach to construct a semi-Markov model for assessing the long-term cost-effectiveness of 3 disease management programs for heart failure. Compared with a standard Markov model with the same disease states, our proposed semi-Markov model fitted the observed data much better. When subsequently extrapolating beyond the clinical trial period, these relatively large differences in goodness-of-fit translated into almost a doubling in mean total cost and a 60-d decrease in mean survival time when using the Markov model instead of the semi-Markov model. For the disease process considered in our case study, the semi-Markov model thus provided a sensible balance between model parsimoniousness and computational complexity.

  • 2.
    Heintz, Emelie
    et al.
    Linköping University, Department of Medical and Health Sciences, Health Technology Assessment and Health Economics. Linköping University, Faculty of Health Sciences.
    Krol, Marieke
    Department of Health Policy and Management, Erasmus University, Rotterdam.
    Levin, Lars-Åke
    Linköping University, Department of Medical and Health Sciences, Health Technology Assessment and Health Economics. Linköping University, Faculty of Health Sciences.
    The impact of patients' subjective life expectancy on time trade-off valuations2013In: Medical decision making, ISSN 0272-989X, E-ISSN 1552-681X, Vol. 33, no 2, p. 261-270Article in journal (Refereed)
    Abstract [en]

    Background. Quality-adjusted life-year (QALY) calculations in economic evaluations are typically based on general public or patient health state valuations elicited with the time tradeoff method (TTO). Such health state valuations elicited among the general public have been shown to be affected by respondents subjective life expectancy (SLE). This suggests that TTO exercises based on time frames other than SLE may lead to biased estimates. It has not yet been investigated whether SLE also affects patient valuations. Objective. To empirically investigate whether patients SLE affects TTO valuations of their current health state. Methods. Patients with different severities of diabetic retinopathy were asked in a telephone interview to value their own health status using TTO. The TTO time frame (t) presented was based on age- and sex-dependent actuarial life expectancy. Patients were then asked to state their SLE. Simple and multiple regression techniques were used to assess the effect of the patients SLE on their TTO responses. Results. In total, 145 patients completed the telephone interview. Patients TTO values were significantly influenced by their SLE. The TTO value decreased linearly with every additional year of difference between t and the patients SLE; that is, patients were more willing to give up years the shorter their SLE compared with t. Conclusion. Patients SLE influenced their TTO valuations, suggesting that respondents SLE may be the most appropriate time frame to use in TTO exercises in patients. The use of other time periods may bias the TTO valuations, as the respondents may experience the presented time frame as a gain or a loss. The effect seems to be larger in patient valuations than in general public valuations.

  • 3.
    Kip, Michelle M. A.
    et al.
    Univ Twente, Netherlands.
    IJzerman, Maarten J.
    Univ Twente, Netherlands.
    Henriksson, Martin
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Merlin, Tracy
    Univ Adelaide, Australia.
    Weinstein, Milton C.
    Harvard TH Chan Sch Publ Hlth, MA USA.
    Phelps, Charles E.
    Univ Rochester, NY USA.
    Kusters, Ron
    Univ Twente, Netherlands; Jeroen Bosch Ziekenhuis, Netherlands.
    Koffijberg, Hendrik
    Univ Twente, Netherlands.
    Toward Alignment in the Reporting of Economic Evaluations of Diagnostic Tests and Biomarkers: The AGREEDT Checklist2018In: Medical decision making, ISSN 0272-989X, E-ISSN 1552-681X, Vol. 38, no 7, p. 778-788Article in journal (Refereed)
    Abstract [en]

    Objectives. General frameworks for conducting and reporting health economic evaluations are available but not specific enough to cover the intricacies of the evaluation of diagnostic tests and biomarkers. Such evaluations are typically complex and model-based because tests primarily affect health outcomes indirectly and real-world data on health outcomes are often lacking. Moreover, not all aspects relevant to the evaluation of a diagnostic test may be known and explicitly considered for inclusion in the evaluation, leading to a loss of transparency and replicability. To address this challenge, this study aims to develop a comprehensive reporting checklist. Methods. This study consisted of 3 main steps: 1) the development of an initial checklist based on a scoping review, 2) review and critical appraisal of the initial checklist by 4 independent experts, and 3) development of a final checklist. Each item from the checklist is illustrated using an example from previous research. Results. The scoping review followed by critical review by the 4 experts resulted in a checklist containing 44 items, which ideally should be considered for inclusion in a model-based health economic evaluation. The extent to which these items were included or discussed in the studies identified in the scoping review varied substantially, with 14 items not being mentioned in 47 (75%) of the included studies. Conclusions. The reporting checklist developed in this study may contribute to improved transparency and completeness of model-based health economic evaluations of diagnostic tests and biomarkers. Use of this checklist is therefore encouraged to enhance the interpretation, comparability, andindirectlythe validity of the results of such evaluations.

  • 4.
    Persson, Emil
    et al.
    Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Arts and Sciences.
    Andersson, David
    Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Arts and Sciences.
    Back, Lovisa
    Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Arts and Sciences.
    Davidson, Thomas
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences.
    Johannisson, Emma
    Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Arts and Sciences.
    Tinghög, Gustav
    Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Discrepancy between Health Care Rationing at the Bedside and Policy Level2018In: Medical decision making, ISSN 0272-989X, E-ISSN 1552-681X, Vol. 38, no 7, p. 881-887Article in journal (Refereed)
    Abstract [en]

    Background. Whether doctors at the bedside level should be engaged in health care rationing is a controversial topic that has spurred much debate. From an empirical point of view, a key issue is whether there exists a behavioral difference between rationing at the bedside and policy level. Psychological theory suggests that we should indeed expect such a difference, but existing empirical evidence is inconclusive. Objective. To explore whether rationing decisions taken at the bedside level are different from rationing decisions taken at the policy level. Method. Behavioral experiment where participants (n = 573) made rationing decisions in hypothetical scenarios. Participants (medical and nonmedical students) were randomly assigned to either a bedside or a policy condition. Each scenario involved 1 decision, concerning either a life-saving medical treatment or a quality-of-life improving treatment. All scenarios were identical across the bedside and policy condition except for the level of decision making. Results. We found a discrepancy between health care rationing at policy and bedside level for scenarios involving life-saving decisions, where subjects rationed treatments to a greater extent at the policy level compared to bedside level (35.6% v. 29.3%, P = 0.001). Medical students were more likely to ration care compared to nonmedical students. Follow-up questions showed that bedside rationing was more emotionally burdensome than rationing at the policy level, indicating that psychological factors likely play a key role in explaining the observed behavioral differences. We found no difference in rationing between bedside and policy level for quality-of-life improving treatments (54.6% v. 55.7%, P = 0.507). Conclusions. Our results indicate a robust bedside effect in the life-saving domain of health care rationing decisions, thereby adding new insights to the understanding of the malleability of preferences related to resource allocation.

  • 5.
    Wiss, Johanna
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences.
    Levin, Lars-Åke
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences.
    David, Andersson
    Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Arts and Sciences.
    Tinghög, Gustav
    Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences.
    Prioritizing Rare Diseases: Psychological Effects Influencing Medical Decision Making2017In: Medical decision making, ISSN 0272-989X, E-ISSN 1552-681XArticle in journal (Refereed)
    Abstract [en]

    Background. Measuring societal preferences for rarity has been proposed to determine whether paying pre- mium prices for orphan drugs is acceptable. Objective. To investigate societal preferences for rarity and how psychological factors affect such preferences. Method. A postal survey containing resource allocation dilemmas involving patients with a rare disease and patients with a common disease, equal in severity, was sent out to a randomly selected sample of the population in Sweden (return rate 42.3%, n = 1270). Results. Overall, we found no evidence of a general preference for prioritizing treat- ment of patients with rare disease patients over those with common diseases. When treatment costs were equal, most respondents (42.7%) were indifferent between the choice options. Preferences for prioritizing patients with common diseases over those with rare diseases were more frequently displayed (33.3% v. 23.9%). This tendency was, as expected, amplified when the rare disease was costlier to treat. The share of respondents choosing to treat patients with rare diseases increased when present- ing the patients in need of treatment in relative rather than absolute terms (proportion dominance). Surprisingly, identifiability did not increase preferences for rarity. Instead, identifying the patient with a rare disease made respondents more willing to prioritize the patients with common diseases. Respondents’ levels of education were significantly associated with choice—the lower the level of education, the more likely they were to choose the rare option. Conclusions. We find no support for the existence of a general preference for rarity when setting health care priorities. Psychological effects, especially proportion dominance, are likely to play an important role when pre- ferences for rarity are expressed.  

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