Asymmetric Information and Outcome-based Compensation in Health Care – Theoretical Implications

The discussion about health care systems focuses on the dynamics of expenditures and on the weak growth of revenues. In this discussion it is widely overseen that medical expenditures and the supply of medical services depend crucially on the compensation of physician services. The paper analyzes the implementation of an outcome-based payment system in the presence of asymmetric information. Two cases are studied in detail. First, the common situation of physician’s moral hazard is analyzed. Second, a double moral hazard model is developed. Here, the patient’s actions influence health outcome and cannot be monitored by the physician. It is shown that the choice of insurance and payment contracts depends on the characteristics of asymmetric information. In addition, lack of knowledge about health status and productivity of health inputs prevent a solution using outcome-based contracts.outcome-based contract, double moral hazard, health policy

Double Moral Hazard and Outcome-based Remuneration of Physicians

The discussion about health care systems focuses on the dynamics of expenditures and on the weak growth of the revenue base. In this discussion it is widely overseen that medical expenditures and supply of medical services crucially depend on the compensation of physician services. The paper analyses the implementation of an outcome-based payment system in the presence of asymmetric information. Two cases are studied in detail: first, the common situation of physician’s moral hazard and second, a double moral hazard model. The choice of insurance and payment contracts then depends on the characteristics of asymmetric information.outcome-based remuneration, double moral hazard, health policy

Asymmetric Information and the Demand for Health Care - the Case of Double Moral Hazard

The production of health does not only depend on the medical services supplied by the physi-cian but is also influenced by the patient’s compliance. A model of medical treatment is pre-sented in which both the actions of physician and patient are modeled as a productive input. The analysis distinguishes between three cases of strategic interaction. The consequences of asymmetric information between physician and patient are lower activity levels, only in the case of strategic substitutes the result might change. Furthermore, the effects of the implementation of a demand-side coinsurance are discussed.principal-agent theory, double moral hazard, strategic interaction, compliance

The Physician-Patient Relationship Revisited - the Patient's View

The importance of the physician-patient relationship for the health care market is beyond controversy. Most theoretical work is done in a principal-agent framework, dealing with moral hazard problems. Recent work emphasizes a two-sided asymmetric information relationship between physician and patient (double moral hazard). In contrast to most work looking only at the physician's perspectives, our paper concentrates on the patient's view. Estimation results using panel data support the hypotheses that physician consultation and health-relevant behavior are not stochastically independent. This means that health care demand is determined by the patient and not only by the physician. In the recursive bivariate probit model, the patient’s health-relevant behavior has a significant positive influence on the probability of a physician visit. This should be taken into account in the discussion that primary care physicians should function as gatekeepers.physician-patient relationship, health behavior, bivariate probit

Health Relevant Behavior and its Impact on the Physician-Patient Relationship

The importance of the physician-patient relationship for the health care market is beyond controversy. Recent work emphasizes a two-sided asymmetric information relationship between physician and patient. In contrast to most work looking only at the physician's perspective, our paper concentrates on the patient's view. Estimation results support the hypotheses that physician consultation and health relevant behavior are not stochastically independent. In the recursive bivariate probit model, patient’s health relevant behavior has a significant influence on the probability of a physician visit. This means that health care demand and not only the contact decision is determined by both, patient and physician.physician-patient relationship, health behavior, bivariate probit panel

Improving prevention compliance through appropriate incentives

This paper theoretically and empirically explores the effects of insurance parameters and a complementary information environment on patient´s primary prevention activity in the context of a managed care organisation. The theoretical model is based on a principal-agent setting in which the patient is acting as an agent in deciding about his preventive effort. Both for the patient and for the insurer the information distribution about prevention efforts is diluted. Hence, the theoretical results reflect the impact of insurance parameters as well as complementary information settings. The empirical investigation sheds the light on the patient´s prevention decision in the case of smoking. This depends on age effects, education, working time and health status. The research also stresses the relationship between monetary incentive schemes and individual behaviour as well as the influence of additional information schemes. In addition to the theoretical results, there is an evidence that changes in health behaviour depend on education and individual health assessment, too.Incentives in Prevention; Information distribution

Estimating ordered categorical variables using panel data: a generalized ordered probit model with an autofit procedure

Estimation procedures for ordered categories usually assume that the estimated coefficients of independent variables do not vary between the categories (parallel-lines assumption). This view neglects possible heterogeneous effects of some explaining factors. This paper describes the use of an autofit option for identifying variables that meet the parallel-lines assumption when estimating a random effects generalized ordered probit model. We combine the test procedure developed by Richard Williams (gologit2) with the random effects estimation command regoprob by Stefan Boes.generalized ordered probit; panel data; autofit, self-assessed health

Estimating ordered categorical variables using panel data: a generalized ordered probit model with an autofit procedure

Estimation procedures for ordered categories usually assume that the estimated coefficients of independent variables do not vary between the categories (parallel-lines assumption). This view neglects possible heterogeneous effects of some explaining factors. This paper describes the use of an autofit option for identifying variables that meet the parallel-lines assumption when estimating random effects generalized ordered probit model. We combine the test procedure developed by Richard Williams (gologit2) with the random effects estimation command regoprob by Stefan Boes.Generalized ordered probit; panel data; autofit, self-assessed health.

Estimating ordered categorical variables using panel data: a generalized ordered probit model with an autofit procedure

Estimation procedures for ordered categories usually assume that the estimated coefficients of independent variables do not vary between the categories (parallel-lines assumption). This view neglects possible heterogeneous effects of some explaining factors. This paper describes the use of an autofit option for identifying variables that meet the parallel-lines assumption when estimating a random effects generalized ordered probit model. We combine the test procedure developed by Richard Williams (gologit2) with the random effects estimation command regoprob by Stefan Boes.generalized ordered probit; panel data; autofit, self-assessed health

Reporting Heterogeneity in Self-Assessed Health among Elderly Europeans: The Impact of Mental and Physical Health Status

Self-assessed health (SAH) is a frequently used measure of individuals’ health status. It is also prone to reporting heterogeneity. To control for reporting heterogeneity valid measures of the objective health status are needed. The topic becomes even more complex for cross-country comparisons, as many key variables tend to vary strongly across countries, influenced by cultural and institutional differences. This study aims at exploring the key drivers for reporting heterogeneity in SAH in an international context. To this end, country specific effects are accounted for and the objective health measure is concretized, separating out effects of mental and physical health conditions. We use panel data from the Survey of Health, Ageing and Retirement in Europe (SHARE) which provides a rich dataset on the elderly European population. To obtain distinct indicators for physical and mental health conditions two indices were constructed. Finally, to identify potential reporting heterogeneity in SAH a generalized ordered probit model is estimated. We find evidence that health behaviour as well as health care utilization, mental and physical health condition as well as country characteristics affect reporting behaviour. We conclude that observed and unobserved heterogeneity play an important role when analysing SAH and have to be taken into account.reporting heterogeneity, SHARE, generalized ordered probit