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Opportunity cost in healthcare priority setting
Linköping University, Department of Health, Medicine and Caring Sciences, Division of Society and Health. Linköping University, Faculty of Medicine and Health Sciences.ORCID iD: 0000-0003-4853-5576
2022 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The resources available for the public provision of health care are not unlimited. Cost-effectiveness evidence on new healthcare interventions can help us prioritise in order to use scarce resources wisely, but to interpret cost-effectiveness evidence, it may appear as if we must make trade-offs between life and money. This is not so. If we are able to quantify the health improvements that resources would or could have generated in alternative use, a decision about providing or denying treatment can instead be framed as a trade-off between health gained and health forgone. In this thesis, I seek to provide a more robust basis for this way of reporting and interpreting cost-effectiveness evidence.

In Chapter II, I discuss the definition of opportunity cost in economic evaluation. The opportunity cost of providing an intervention is what we must give up to provide it. More precisely, it is typically defined as the value of the best alternative forgone. In economic evaluation of health care, opportunity cost has been understood in terms of the least cost-effective, currently funded intervention, which should be displaced when funding new interventions subject to a fixed budget. I show that alternative uses forgone may be neither currently funded nor well-defined, which implies that we should not look to cost-effectiveness evidence on specific interventions for information on opportunity cost. Further, identifying a best alternative use assumes that priority setting is based on objectives that can be summarised into a single measure of value. If economic evaluation is used to inform trade-offs between one measure of value (e.g., quality-adjusted life years, QALYs) and other, unquantified objectives, I suggest that it would be more appropriate to define opportunity cost as value in expected alternative use.

To quantify opportunity cost as health forgone, we need evidence on the health that resources would or could have generated in alternative use. In Chapter III, I use panel data on health spending and life expectancy in Swedish regions to estimate the marginal cost of producing a QALY. My findings imply that Swedish health care can produce health at a marginal cost of SEK 180,000 per QALY, which could be used as an expectation on how productive health spending would be in alternative use. I discuss methodological issues with this approach and identify some credibility problems with selection-on-observables strategies plaguing this and similar research to date. I address (some of) these problems by assessing coefficient stability and the causal mechanisms between healthcare resource use and health outcomes, using a second panel on hospital bed capacity and mortality. This analysis finds that health could be gained at a cost of SEK 420,000 per QALY by providing more hospital beds.

To illustrate the role of this evidence in healthcare priority setting, Chapter IV considers how it could have been used to inform decision making in a case of pharmaceutical reimbursement. I propose that economic evaluation report cost-effectiveness evidence as QALYs forgone per QALY gained. This frames a decision about providing or denying treatment as a judgement on the relative priority of QALYs gained and QALYs forgone, which is more transparent about a trade-off between equity and efficiency than deciding whether the monetary cost per QALY is too high. Framing decisions as health gained versus health forgone could also lead to better decision making by making opportunity costs more salient to decision makers and the reason for sometimes denying costly treatments easier to communicate.

In summary, cost-effectiveness evidence can be used to achieve the theoretical objective of health maximisation, but economic evaluations rarely report opportunity costs explicitly as health forgone. This thesis provides the practical means to be explicit and implications for the definition of opportunity cost and the interpretation of cost-effectiveness evidence when health maximisation is not the sole objective of healthcare priority setting.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2022. , p. 79
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1795
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Identifiers
URN: urn:nbn:se:liu:diva-183527DOI: 10.3384/9789179291365ISBN: 9789179291358 (print)ISBN: 9789179291365 (electronic)OAI: oai:DiVA.org:liu-183527DiVA, id: diva2:1643930
Public defence
2022-04-08, Belladonna, Building 511, Campus US, Linköping, 09:00 (English)
Opponent
Supervisors
Available from: 2022-03-11 Created: 2022-03-11 Last updated: 2022-10-10Bibliographically approved
List of papers
1. Estimating the marginal cost of a life year in Sweden's public healthcare sector
Open this publication in new window or tab >>Estimating the marginal cost of a life year in Sweden's public healthcare sector
2019 (English)In: European Journal of Health Economics, ISSN 1618-7598, E-ISSN 1618-7601, Vol. 20, no 5, p. 751-762Article in journal (Refereed) Published
Abstract [en]

Although cost-effectiveness analysis has a long tradition of supporting healthcare decision-making in Sweden, there are no clear criteria for when an intervention is considered too expensive. In particular, the opportunity cost of healthcare resource use in terms of health forgone has not been investigated empirically. In this work, we therefore seek to estimate the marginal cost of a life year in Sweden's public healthcare sector using time series and panel data at the national and regional levels, respectively. We find that estimation using time series is unfeasible due to reversed causality. However, through panel instrumental variable estimation we are able to derive a marginal cost per life year of about SEK 370,000 (EUR 39,000). Although this estimate is in line with emerging evidence from other healthcare systems, it is associated with uncertainty, primarily due to the inherent difficulties of causal inference using aggregate observational data. The implications of these difficulties and related methodological issues are discussed.

Place, publisher, year, edition, pages
Springer, 2019
Keywords
Cost-effectiveness analysis, Healthcare expenditure, Life expectancy, Mortality, Opportunity cost, Threshold
National Category
Health Care Service and Management, Health Policy and Services and Health Economy Economics
Identifiers
urn:nbn:se:liu:diva-155512 (URN)10.1007/s10198-019-01039-0 (DOI)000474490700011 ()30796552 (PubMedID)2-s2.0-85062020116 (Scopus ID)
Note

Funding agencies:  Region ostergotland

Available from: 2019-03-20 Created: 2019-03-20 Last updated: 2022-03-11Bibliographically approved
2. Mutually Exclusive Interventions in the Cost-Effectiveness Bookshelf
Open this publication in new window or tab >>Mutually Exclusive Interventions in the Cost-Effectiveness Bookshelf
2020 (English)In: Medical decision making, ISSN 0272-989X, E-ISSN 1552-681X, Vol. 40, no 3, p. 399-403Article in journal (Refereed) Published
Abstract [en]

n/a

Place, publisher, year, edition, pages
SAGE PUBLICATIONS INC, 2020
Keywords
cost-effectiveness analysis; cost-effectiveness threshold; health economics; opportunity cost; resource allocation
National Category
Health Sciences
Identifiers
urn:nbn:se:liu:diva-165239 (URN)10.1177/0272989X20912261 (DOI)000523887000001 ()32172657 (PubMedID)
Available from: 2020-04-20 Created: 2020-04-20 Last updated: 2022-03-11
3. On the role of cost-effectiveness thresholds in healthcare priority setting
Open this publication in new window or tab >>On the role of cost-effectiveness thresholds in healthcare priority setting
2021 (English)In: International Journal of Technology Assessment in Health Care, ISSN 0266-4623, E-ISSN 1471-6348, Vol. 37, no 1, article id e23Article in journal, Editorial material (Other academic) Published
Abstract [en]

In the past few years, empirical estimates of the marginal cost at which health care produces a quality-adjusted life year (QALY, k) have begun to emerge. In theory, these estimates could be used as cost-effectiveness thresholds by health-maximizing decision makers, but prioritization decisions in practice often include other considerations than just efficiency. Pharmaceutical reimbursement in Sweden is one such example, where the reimbursement authority (TLV) uses a threshold range to give priority to disease severity and rarity. In this paper, we argue that estimates of k should not be used to inform threshold ranges. Instead, they are better used directly in health technology assessment (HTA) to quantify how much health is forgone when a new technology is funded in place of other healthcare services. Using a recent decision made by TLV as a case, we show that an estimate of k for Sweden implies that reimbursement meant forgoing 8.6 QALYs for every QALY that was gained. Reporting cost-effectiveness evidence as QALYs forgone per QALY gained has several advantages: (i) it frames the decision as assigning an equity weight to QALYs gained, which is more transparent about the trade-off between equity and efficiency than determining a monetary cost per QALY threshold, (ii) it makes it less likely that decision makers neglect taking the opportunity cost of reimbursement into account by making it explicit, and (iii) it helps communicate the reason for sometimes denying reimbursement in a way that might be less objectionable to the public than current practice.

Place, publisher, year, edition, pages
CAMBRIDGE UNIV PRESS, 2021
Keywords
Equity; Priority setting; Cost-effectiveness; Opportunity cost
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Identifiers
urn:nbn:se:liu:diva-175299 (URN)10.1017/S0266462321000015 (DOI)000639269400001 ()33491617 (PubMedID)
Note

Funding Agencies|Region Ostergotland

Available from: 2021-04-27 Created: 2021-04-27 Last updated: 2022-03-11Bibliographically approved
4. The health cost of reducing hospital bed capacity
Open this publication in new window or tab >>The health cost of reducing hospital bed capacity
2022 (English)In: Social Science and Medicine, ISSN 0277-9536, E-ISSN 1873-5347, Vol. 313, article id 115399Article in journal (Refereed) Published
Abstract [en]

In the past two decades, most high-income countries have reduced their hospital bed capacity. This could be a sign of increased efficiency but could also reflect a degradation in quality of care. In this paper, we use repeated cross-sections on mortality and staffed hospital beds per capita in all 21 Swedish regions to estimate the potential death toll from reduced bed capacity. Between 2001 and 2019, mortality and beds decreased across all regions, but regions making smaller bed reductions experienced on average greater decreases in mortality, equivalent to one less death per three beds retained. This estimate is stable to a wide range of specifications and to adjustment for potential confounders, which supports a causal interpretation. Our results imply that by providing one more bed, Swedish health care could produce about three quality-adjusted life years (QALYs) at a cost of SEK 400,000 (∼US$40,000) per QALY. These findings could be informative about the marginal productivity of health care and support the credibility of empirical work attempting to estimate the opportunity cost of funding new healthcare interventions subject to a constrained budget.

Place, publisher, year, edition, pages
Elsevier, 2022
Keywords
Hospital beds, Mortality, Population health, Cost-effectiveness, Opportunity cost, Sweden
National Category
Health Sciences
Identifiers
urn:nbn:se:liu:diva-189050 (URN)10.1016/j.socscimed.2022.115399 (DOI)000877679700007 ()36206659 (PubMedID)
Available from: 2022-10-10 Created: 2022-10-10 Last updated: 2022-11-23

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