Economic Evaluation of New Models of Care: Does the Decision Change Between Cost-Utility Analysis and Multi-Criteria Decision Analysis?

Unravelling Elements of Value of Healthcare and Assessing their Importance Using Evidence from Two Discrete-Choice Experiments in England

BACKGROUND

Health systems are moving towards value-based care, implementing new care models that allegedly aim beyond patient outcomes. Therefore, a policy and academic debate is underway regarding the definition of value in healthcare, the inclusion of costs in value metrics, and the importance of each value element. This study aimed to define healthcare value elements and assess their relative importance (RI) to the public in England.

METHOD

Using data from 26 semi-structured interviews and a literature review, and applying decision-theory axioms, we selected a comprehensive and applicable set of value-based elements. Their RI was determined using two discrete choice experiments (DCEs) based on Bayesian D-efficient DCE designs, with one DCE incorporating healthcare costs expressed as income tax rise. Respondent preferences were analysed using mixed logit models.

RESULTS

Six value elements were identified: additional life-years, health-related quality of life, patient experience, target population size, equity, and cost. The DCE surveys were completed by 402 participants. All utility coefficients had the expected signs and were statistically significant (p < 0.05). Additional life-years (25.3%; 95% confidence interval [CI] 22.5-28.6%) and patient experience (25.2%; 95% CI 21.6-28.9%) received the highest RI, followed by target population size (22.4%; 95% CI 19.1-25.6%) and quality of life (17.6%; 95% CI 15.0-20.3%). Equity had the lowest RI (9.6%; 95% CI 6.4-12.1%), decreasing by 8.8 percentage points with cost inclusion. A similar reduction was observed in the RI of quality of life when cost was included.

CONCLUSION

The public prioritizes value elements not captured by conventional metrics, such as quality-adjusted life-years. Although cost inclusion did not alter the preference ranking, its inclusion in the value metric warrants careful consideration.

Rationing in an Era of Multiple Tight Constraints: Is Cost-Utility Analysis Still Fit for Purpose?

Cost-utility analysis may not be sufficient to support reimbursement decisions when the assessed health intervention requires a large proportion of the healthcare budget or when the monetary healthcare budget is not the only resource constraint. Such cases include joint replacement, coronavirus disease 2019 (COVID-19) interventions and settings where all resources are constrained (e.g. post-COVID-19 or in low/middle-income countries). Using literature on health technology assessment, rationing and reimbursement in healthcare, we identified seven alternative frameworks for simultaneous decisions about (dis)investment and proposed modifications to deal with multiple resource constraints. These frameworks comprised constrained optimisation; cost-effectiveness league table; 'step-in-the-right-direction' approach; heuristics based on effective gradients; weighted cost-effectiveness ratios; multicriteria decision analysis (MCDA); and programme budgeting and marginal analysis (PBMA). We used numerical examples to demonstrate how five of these alternative frameworks would operate. The modified frameworks we propose could be used in local commissioning and/or health technology assessment to supplement standard cost-utility analysis for interventions that have large budget impact and/or are subject to additional constraints.

Exploring the association between primary care efficiency and health system characteristics across European countries: a two-stage data envelopment analysis

BACKGROUND

Primary care is widely seen as a core component of resilient and sustainable health systems, yet its efficiency is not well understood and there is a lack of evidence about how primary care efficiency is associated with health system characteristics. We examine this issue through the lens of diabetes care, which has a well-established evidence base for effective treatment and has previously been used as a tracer condition to measure health system performance.

METHODS

We developed a conceptual framework to guide the analysis of primary care efficiency. Using data on 18 European countries during 2010-2016 from several international databases, we applied a two-stage data envelopment analysis to estimate (i) technical efficiency of primary care and (ii) the association between efficiency and health system characteristics.

RESULTS

Countries varied widely in terms of primary care efficiency, with efficiency scores depending on the range of population characteristics adjusted for. Higher efficiency was associated with bonus payments for the prevention and management of chronic conditions, nurse-led follow-up, and a financial incentive or requirement for patients to obtain a referral to specialist care. Conversely, lower efficiency was associated with higher rates of curative care beds and financial incentives for patients to register with a primary care provider.

CONCLUSIONS

Our results underline the importance of considering differences in population characteristics when comparing country performance on primary care efficiency. We highlight several policies that could enhance the efficiency of primary care. Improvements in data collection would enable more comprehensive assessments of primary care efficiency across countries, which in turn could more effectively inform policymaking.

Medico-economic impact of thoracoscopy versus thoracotomy in lung cancer: multicentre randomised controlled trial (Lungsco01)

BACKGROUND

Lungsco01 is the first study assessing the real benefits and the medico-economic impact of video-thoracoscopy versus open thoracotomy for non-small cell lung cancer in the French context.

METHODS

Two hundred and fifty nine adult patients from 10 French centres were randomised in this prospective multicentre randomised controlled trial, between July 29, 2016, and November 24, 2020. Survival from surgical intervention to day 30 and later was compared with the log-rank test. Total quality-adjusted-life-years (QALYs) were calculated using the EQ-5D-3L®. For medico-economic analyses at 30 days and at 3 months after surgery, resources consumed were valorised (€ 2018) from a hospital perspective. First, since mortality was infrequent and not different between the two arms, cost-minimisation analyses were performed considering only the cost differential. Second, based on complete cases on QALYs, cost-utility analyses were performed taking into account cost and QALY differential. Acceptability curves and the 95% confidence intervals for the incremental ratios were then obtained using the non-parametric bootstrap method (10,000 replications). Sensitivity analyses were performed using multiple imputations with the chained equation method.

RESULTS

The average cumulative costs of thoracotomy were lower than those of video-thoracoscopy at 30 days (€9,730 (SD = 3,597) vs. €11,290 (SD = 4,729)) and at 3 months (€9,863 (SD = 3,508) vs. €11,912 (SD = 5,159)). In the cost-utility analyses, the incremental cost-utility ratio was €19,162 per additional QALY gained at 30 days (€36,733 at 3 months). The acceptability curve revealed a 64% probability of efficiency at 30 days for video-thoracoscopy, at a widely-accepted willingness-to-pay threshold of €25,000 (34% at 3 months). Ratios increased after multiple imputations, implying a higher cost for video-thoracoscopy for an additional QALY gain (ratios: €26,015 at 30 days, €42,779 at 3 months).

CONCLUSIONS

Given our results, the economic efficiency of video-thoracoscopy at 30 days remains fragile at a willingness-to-pay threshold of €25,000/QALY. The economic efficiency is not established beyond that time horizon. The acceptability curves given will allow decision-makers to judge the probability of efficiency of this technology at other willingness-to-pay thresholds.

TRIAL REGISTRATION

NCT02502318.

Substitution or addition: An observational study of a new primary care initiative in the Netherlands

OBJECTIVE

In 2014, the Primary Care Plus (PC+) model was introduced in the Netherlands to shift low-complex specialised care from the hospital to the primary care setting. While positive effects of PC+ have been documented at individual patient level concerning health-related quality of life, perceived quality of care and care costs, its impacts on service use at the population level remain uncertain.

METHODS

In this observational study, we used retrospective health insurance reimbursement claims data from the largest health insurer in the intervention region to determine service use. We assessed PC+ and secondary care insurance claims (i.e. claims of the regional hospital and claims of other secondary care settings in and outside the region visited by patients from the intervention region) from 2015 to 2018 and compared these to the national level.

RESULTS

The total number of claims related to low-complex specialised care in the intervention region showed an increase over time. The increase in claims was related to PC+. The number of claims related to the regional hospital and other secondary care settings decreased over time. During the same period, a declining trend in claims at the national level was observed.

CONCLUSION

The introduction of the PC+ model in one region in the Netherlands was associated with an increase in the use of low-complex specialised care. This suggests that the ability of the PC+ model to substitute for specialist care at population level may be limited. Going forward, it will be important to continue monitoring and evaluating service use as substitution effects may materialise only over a longer timeframe.

Commissioning [Integrated] Care in England: An Analysis of the Current Decision Context

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Moving Beyond Quality-Adjusted Life-Years in Elderly Care: How Can Multicriteria Decision Analysis Complement Cost-Effectiveness Analysis in Local-Level Decision Making

OBJECTIVES

This study aimed to investigate how multicriteria decision analysis (MCDA) could complement cost-effectiveness analysis (CEA) to support investment decisions in elderly care at local level.

METHODS

We used an integrated elderly care program in The Netherlands as a case study to demonstrate the application of both methods. In a 12-month quasi-experimental study (n = 384), data on the following outcome measures were collected: quality-adjusted life-years (CEA) and physical functioning, psychological well-being, social relationships and participation, enjoyment of life, resilience, person centeredness, continuity of care, and costs (MCDA). We performed regression analysis on inversed probability weighted data and controlled for potential confounders to obtain a double robust estimate of the outcomes. Probabilistic sensitivity analyses determined uncertainty for both methods.

RESULTS

The integrated elderly care program was not likely (ie, 36%) to be cost-effective according to the CEA (incremental cost-effectiveness ratios: €88 249 from a societal perspective) using the conventional Dutch willingness-to-pay threshold (ie, €50 000). The MCDA demonstrated that informal caregivers and professionals slightly preferred the intervention over usual care, driven by enjoyment of life and person centeredness. Patients did not prefer either the intervention or usual care, whereas payers and policy makers slightly preferred usual care, mainly due to higher costs of the intervention.

CONCLUSIONS

MCDA could provide local-level decision makers with a broader measurement of effectiveness by including outcomes beyond health and longevity and the preferences of multiple stakeholders. This additional information could foster the acceptability and implementability of cost-effective innovations in elderly care.