Abstract
ObjectivesTo experiment with new approaches of collaboration in healthcare delivery, local authorities implement new models of care. Regarding the local decision context of these models, multi-criteria decision analysis (MCDA) may be of added value to cost-utility analysis (CUA), because it covers a wider range of outcomes. This study compares the 2 methods using a side-by-side application. MethodsA new Dutch model of care, Primary Care Plus (PC+), was used as a case study to compare the results of CUA and MCDA. Data of patients referred to PC+ or care-as-usual were retrieved by questionnaires and administrative databases with a 3-month follow-up. Propensity score matching together with generalized linear regression models was used to reduce confounding. Univariate and probabilistic sensitivity analyses were performed to explore uncertainty in the results. ResultsAlthough both methods indicated PC+ as the dominant alternative, complementary differences were observed. MCDA provided additional evidence that PC+ improved access to care (standardized performance score of 0.742 vs 0.670) and that improvement in health-related quality of life was driven by the psychological well-being component (standardized performance score of 0.710 vs 0.704). Furthermore, MCDA estimated the budget required for PC+ to be affordable in addition to preferable (€521.42 per patient). Additionally, MCDA was less sensitive to the utility measures used. ConclusionsMCDA may facilitate an auditable and transparent evaluation of new models of care by providing additional information on a wider range of outcomes and incorporating affordability. However, more effort is needed to increase the usability of MCDA among local decision makers.
Highlights
New models of care are implemented worldwide to increase accessibility, equitability, and affordability of care by developing new approaches of collaboration and delivering health and social care.[1]
Before propensity score matching (PSM), patients referred to PC1 had better physical health status, and the distribution of the referred medical departments was uneven between the 2 groups (Table 2)
Nearest neighbor optimal matching with a 2:1 ratio was the best PSM technique, as it resulted in a high number of respondents with the least covariate imbalance (SMD .0.25) and with acceptable Rubin’s B (0.8%) and Rubin’s R (0.984)
Summary
New models of care are implemented worldwide to increase accessibility, equitability, and affordability of care by developing new approaches of collaboration and delivering health and social care.[1]. The appropriateness of the widely accepted cost-utility analysis (CUA) in local decision making is debatable This is because the decision context is different than in health interventions and technologies that are subject to reimbursement decisions or national clinical guidelines.[9,10] CUA includes qualityadjusted life-year (QALY) as a single measure of outcome and fails to incorporate outcomes of interest to local decision makers such as access to care, equity, patient satisfaction, and nonhealth-related quality of life.[11,12,13] It is widely argued that economic evaluations of new models of care should be carried out at a local level,[13,14] should be flexible to accommodate the selection of all relevant outcomes and costs at different levels (eg, individual, organizational, local),[15,16,17,18] and should incorporate the perspective of all relevant stakeholders.[19] Local decision makers are often using decision support tools, such as balanced scorecards and key performance indicators, to monitor various performances. These tools, similar to a cost-consequence analysis (CCA), lack clear decision rules to indicate costeffectiveness.[20,21]
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