Richard C. van Kleef

Risk equalization in The Netherlands: an empirical evaluation

The Netherlands relies on risk equalization to compensate competing health insurers for predictable variation in individual medical expenses. Without accurate risk equalization insurers are confronted with incentives for risk selection. The goal of this study is to evaluate the improvement in predictive accuracy of the Dutch risk equalization model since its introduction in 1993. Based on individual-level claims data (n = 15.6 million), we estimate the risk equalization models that have been successively applied in The Netherlands since 1993. Using individual-level survey data (n = 8735), we examine the average under-/overcompensation by these models for several relevant subgroups in the population. We find that in the course of years, the risk equalization model has been substantially improved. Even the current model (2012), however, does not eliminate incentives for risk selection completely. To achieve the public objectives, further improvement of the Dutch risk equalization model is crucial.The Netherlands relies on risk equalization to compensate competing health insurers for predictable variation in individual medical expenses. Without accurate risk equalization insurers are confronted with incentives for risk selection. The goal of this study is to evaluate the improvement in predictive accuracy of the Dutch risk equalization model since its introduction in 1993. Based on individual-level claims data (n = 15.6 million), we estimate the risk equalization models that have been successively applied in The Netherlands since 1993. Using individual-level survey data (n = 8735), we examine the average under-/overcompensation by these models for several relevant subgroups in the population. We find that in the course of years, the risk equalization model has been substantially improved. Even the current model (2012), however, does not eliminate incentives for risk selection completely. To achieve the public objectives, further improvement of the Dutch risk equalization model is crucial.

Prior use of durable medical equipment as a risk adjuster for health-based capitation

This paper examines a new risk adjuster for capitation payments to Dutch health plans, based on the prior use of durable medical equipment (DME). The essence is to classify users of DME in a previous year into clinically homogeneous classes and to apply the resulting classification as a risk adjuster for capitation payments in the subsequent year. We evaluate 143 DME types in terms of incentives, validity, predictive value, and measurability, resulting in 14 functional disability classes (FDCs). We conclude that FDCs can significantly improve the Dutch risk adjustment model, although possible incentives for oversupply have to be monitored.

Improving risk equalization using multiple-year high cost as a health indicator.

Background:More and more competitive health insurance markets use risk equalization to compensate health plans for the predictable high costs of chronically ill enrollees. In the presence of premium rate restrictions, an important goal of risk equalization is to reduce incentives for selection, while maintaining incentives for efficiency. The literature shows, however, that even the most sophisticated risk equalization models—which include both diagnoses-based and pharmacy-based indicators of health status—do not reduce incentives for selection sufficiently. Objectives:The goal of this study is to examine the extent to which a sophisticated risk-equalization model can be improved by using multiple-year high cost as a health indicator. The idea is that health plans receive an additional compensation for enrollees whose costs were in the top–15% in each of the 3 preceding years, assuming that this group contains a substantial overrepresentation of people with a chronic condition. Research design:We examine 3 types of additional compensation: (1) retrospective compensation, (2) fixed prospective compensation, and (3) continuous prospective compensation. Subjects:We use individual-level information on medical costs and risk characteristics from the period 2004 to 2007 for almost the entire Dutch population. Measures:The effect on selection incentives is measured by predictive ratios for subgroups of enrollees who were undercompensated in previous years. The effect on efficiency incentives is quantified by the relationship between cost and compensation. Results and conclusions:All 3 modalities substantially reduce incentives for selection, but—to some extent—also reduce incentives for efficiency. With respect to these criteria, the continuous prospective compensation outperforms the other 2 modalities.

Risk selection in a regulated health insurance market: a review of the concept, possibilities and effects

The Dutch basic health insurance is based on the principles of regulated competition. This implies that insurers and providers compete on price and quality while the regulator sets certain rules to achieve public objectives such as solidarity. Two regulatory aspects of this scheme are that insurers are not allowed to risk rate their premiums and are compensated for predictable variation in individual medical expenses (i.e., risk equalization). Research, however, indicates that the current risk equalization is imperfect, which confronts insurers and consumers with incentives for risk selection. The goal of this paper is to review the concept, possibilities and potential effects of risk selection in the Dutch basic health insurance. We conclude that the possibilities for risk selection are numerous and a potential threat to solidarity, efficiency and quality of care. Regulators should be aware that measurement of risk selection is a methodological and data-demanding challenge.The Dutch basic health insurance is based on the principles of regulated competition. This implies that insurers and providers compete on price and quality while the regulator sets certain rules to achieve public objectives such as solidarity. Two regulatory aspects of this scheme are that insurers are not allowed to risk rate their premiums and are compensated for predictable variation in individual medical expenses (i.e., risk equalization). Research, however, indicates that the current risk equalization is imperfect, which confronts insurers and consumers with incentives for risk selection. The goal of this paper is to review the concept, possibilities and potential effects of risk selection in the Dutch basic health insurance. We conclude that the possibilities for risk selection are numerous and a potential threat to solidarity, efficiency and quality of care. Regulators should be aware that measurement of risk selection is a methodological and data-demanding challenge.

Risicoverevening tussen zorgverzekeraars: Kwantificering modelverbeteringen 1993-2011

Het ex-ante vereveningsmodel van de Zorgverzekeringswet dient verzekeraars te compenseren voor voorspelbare, gezondheidsgerelateerde kostenverschillen tussen verzekerden. Zonder goed vereveningsmodel worden verzekeraars – vanwege het verbod op premiedifferentiatie – geconfronteerd met voorspelbare winsten op gezonde verzekerden en voorspelbare verliezen op chronisch zieken. Voorspelbare winsten en verliezen geven verzekeraars prikkels tot risicoselectie, indirecte premiedifferentiatie en productdifferentiatie. Bovendien kan sprake zijn van een ongelijk speelveld op de zorgverzekeringsmarkt wanneer chronisch zieken zich concentreren bij bepaalde verzekeraars. Het doel van dit artikel is inzicht te geven in 1) het effect van de verbeteringen die de afgelopen twee decennia in het vereveningsmodel zijn aangebracht en 2) de ontwikkeling van prikkels tot risicoselectie, indirecte premiedifferentiatie en productdifferentiatie. Hiertoe hebben wij schadegegevens van verzekeraars gekoppeld aan enquêtegegevens van het Permanent Onderzoek naar de Leefsituatie dat jaarlijks wordt uitgevoerd door het Centraal Bureau voor de Statistiek. Uit de resultaten blijkt dat het vereveningsmodel sinds de invoering in 1993 sterk is verbeterd: voor een brede set van subgroepen met een oververtegenwoordiging van chronisch zieken reduceert het ex-ante vereveningsmodel-2011 de voorspelbare verliezen met gemiddeld 70%; voor het ex-ante vereveningsmodel-1993 was dat nog gemiddeld 40%. In dezelfde periode is het financieel risico voor verzekeraars verhoogd van gemiddeld 3% in 1993 naar 74% in 2011. Combineren we de modelverbeteringen met de stijging van het financieel risico dan blijkt dat de prikkels tot risicoselectie, indirecte premiedifferentiatie en productdifferentiatie per saldo zijn toegenomen. Kijken we naar de afgelopen vijf jaar dan zijn deze prikkels in 2011 ruim een derde groter dan in 2007.

Measuring efficiency of health plan payment systems in managed competition health insurance markets

Adverse selection in health insurance markets leads to two types of inefficiency. On the demand side, adverse selection leads to plan price distortions resulting in inefficient sorting of consumers across health plans. On the supply side, adverse selection creates incentives for plans to inefficiently distort benefits to attract profitable enrollees. Reinsurance, risk adjustment, and premium categories address these problems. Building on prior research on health plan payment system evaluation, we develop measures of the efficiency consequences of price and benefit distortions under a given payment system. Our measures are based on explicit economic models of insurer behavior under adverse selection, incorporate multiple features of plan payment systems, and can be calculated prior to observing actual insurer and consumer behavior. We illustrate the use of these measures with data from a simulated market for individual health insurance.

Overpaying morbidity adjusters in risk equalization models.

Most competitive social health insurance markets include risk equalization to compensate insurers for predictable variation in healthcare expenses. Empirical literature shows that even the most sophisticated risk equalization models-with advanced morbidity adjusters-substantially undercompensate insurers for selected groups of high-risk individuals. In the presence of premium regulation, these undercompensations confront consumers and insurers with incentives for risk selection. An important reason for the undercompensations is that not all information with predictive value regarding healthcare expenses is appropriate for use as a morbidity adjuster. To reduce incentives for selection regarding specific groups we propose overpaying morbidity adjusters that are already included in the risk equalization model. This paper illustrates the idea of overpaying by merging data on morbidity adjusters and healthcare expenses with health survey information, and derives three preconditions for meaningful application. Given these preconditions, we think overpaying may be particularly useful for pharmacy-based cost groups.Most competitive social health insurance markets include risk equalization to compensate insurers for predictable variation in healthcare expenses. Empirical literature shows that even the most sophisticated risk equalization models—with advanced morbidity adjusters—substantially undercompensate insurers for selected groups of high-risk individuals. In the presence of premium regulation, these undercompensations confront consumers and insurers with incentives for risk selection. An important reason for the undercompensations is that not all information with predictive value regarding healthcare expenses is appropriate for use as a morbidity adjuster. To reduce incentives for selection regarding specific groups we propose overpaying morbidity adjusters that are already included in the risk equalization model. This paper illustrates the idea of overpaying by merging data on morbidity adjusters and healthcare expenses with health survey information, and derives three preconditions for meaningful application. Given these preconditions, we think overpaying may be particularly useful for pharmacy-based cost groups.

Improving the prediction model used in risk equalization: cost and diagnostic information from multiple prior years

Currently-used risk-equalization models do not adequately compensate insurers for predictable differences in individuals’ health care expenses. Consequently, insurers face incentives for risk rating and risk selection, both of which jeopardize affordability of coverage, accessibility to health care, and quality of care. This study explores to what extent the predictive performance of the prediction model used in risk equalization can be improved by using additional administrative information on costs and diagnoses from three prior years. We analyze data from 13.8 million individuals in the Netherlands in the period 2006–2009. First, we show that there is potential for improving models’ predictive performance at both the population and subgroup level by extending them with risk adjusters based on cost and/or diagnostic information from multiple prior years. Second, we show that even these extended models do not adequately compensate insurers. By using these extended models incentives for risk rating and risk selection can be reduced substantially but not removed completely. The extent to which risk-equalization models can be improved in practice may differ across countries, depending on the availability of data, the method chosen to calculate risk-adjusted payments, the value judgment by the regulator about risk factors for which the model should and should not compensate insurers, and the trade-off between risk selection and efficiency.

Health Plan Payment in the Netherlands

Abstract This chapter describes the institutional setting, design, and performance of health plan payment in the Netherlands. The primary focus is on the Health Insurance Act (2006), which is based on principles of regulated competition and strongly relies on health plan payment as a tool for achieving public objectives. In anticipation of the introduction of regulated competition, the construction of the current health plan payment system started in the early 1990s. More than two decades later we conclude that important progress has been made. We also conclude, however, that further improvements are necessary. Two main issues of the current system are the remaining incentives for risk selection and the strong dependence on endogenous variables in the risk equalization model. Incentives for risk selection threaten the solidarity, efficiency, and quality of care, while endogenous risk adjustor variables threaten efficiency in the delivery of care. Further improvements to health plan payment are crucial to overcome these potential failures.

Diagnosis-based Cost Groups in the Dutch Risk-equalization Model: Effects of Clustering Diagnoses and of Allowing Patients to be Classified into Multiple Risk-classes

Background: The risk-equalization (RE) model in the Dutch health insurance market has evolved to a sophisticated model containing direct proxies for health. However, it still has important imperfections, leaving incentives for risk selection. This paper focuses on refining an important health-based risk-adjuster in this model: the diagnosis-based costs groups (DCGs). The current (2017) DCGs are calibrated on “old” data of 2011/2012, are mutually exclusive, and are essentially clusters of about 200 diagnosis-groups (“dxgroups”). Methods: Hospital claims data (2013), administrative data (2014) on costs and risk-characteristics for the entire Dutch population (N≈16.9 million), and health survey data (2012, N≈387,000) are used. The survey data are used to identify subgroups of individuals in poor or in good health. The claims and administrative data are used to develop alternative DCG-modalities to examine the impact on individual-level and group-level fit of recalibrating the DCGs based on new data, of allowing patients to be classified in multiple DCGs, and of refraining from clustering. Results: Recalibrating the DCGs and allowing enrolees to be classified into multiple DCGs lead to nontrivial improvements in individual-level and group-level fit (especially for cancer patients and people with comorbid conditions). The improvement resulting from refraining from clustering does not seem to justify the increase in model complexity this would entail. Conclusions: The performance of the sophisticated Dutch RE-model can be improved by allowing classification in multiple (clustered) DCGs and using new data. Irrespective of the modality used, however, various subgroups remain significantly undercompensated. Further improvement of the RE-model merits high priority.