Cost-Containment and Adverse Selection in Medicaid HMOs

Instrumental variable analysis for cost outcome: Application to the effect of primary care visit on medical cost among low-income adults

Medical cost data often consist of zero values as well as extremely right-skewed positive values. A two-part model is a popular choice for analyzing medical cost data, where the first part models the probability of a positive cost using logistic regression and the second part models the positive cost using a lognormal or Gamma distribution. To address the unmeasured confounding in studies on cost outcome under two-part models, two instrumental variable (IV) methods, two-stage residual inclusion (2SRI) and two-stage prediction substitution (2SPS) are widely applied. However, previous literature demonstrated that both the 2SRI and the 2SPS could fail to consistently estimate the causal effect among compliers under standard IV assumptions for binary and survival outcomes. Our simulation studies confirmed that it continued to be the case for a two-part model, which is another nonlinear model. In this article, we develop a model-based IV approach, Instrumental Variable with Two-Part model (IV2P), to obtain a consistent estimate of the causal effect among compliers for cost outcome under standard IV assumptions. In addition, we develop sensitivity analysis approaches to allow the evaluation of the sensitivity of the causal conclusions to potential quantified violations of the exclusion restriction assumption and the randomization of IV assumption. We apply our method to a randomized cash incentive study to evaluate the effect of a primary care visit on medical cost among low-income adults newly covered by a primary care program.

MEDICAL EXPENDITURE RISK AND HOUSEHOLD PORTFOLIO CHOICE

Medical expenses are an increasingly important contributor to household financial risk. We examine the effect of medical expenditure risk on the willingness of Medicare beneficiaries to hold risky assets. Using a discrete factor maximum likelihood method to address the endogeneity of insurance choices, we find that having a moderately protective Medigap or employer supplemental policy increases risky asset holding by 7.1 percentage points relative to those without supplemental coverage, while participation in a highly protective Medicare HMO increases risky asset holding by 13.0 percentage points. Our results highlight an important link between the availability of health insurance and financial behavior.

Prescription drug coverage and effects on drug expenditures among elderly Medicare beneficiaries

OBJECTIVE

To identify determinants of drug coverage among elderly Medicare beneficiaries and to investigate the impact of drug coverage on drug expenditures with and without taking selection bias into account.

DATA SOURCES/STUDY SETTING

The primary data were from the 2000 Medicare Current Beneficiary Survey (MCBS) Cost and Use file, linked to other data sources at the county or state-level that provided instrumental variables. Community-dwelling elderly Medicare beneficiaries who completed the survey were included in the study (N=7,525). A probit regression to predict the probability of having drug coverage and the effects of drug coverage on drug expenditures was estimated by a two-part model, assuming no correlation across equations. In addition, the discrete factor model estimated choice of drug coverage and expenditures for prescription drugs simultaneously to control for self-selection into drug coverage, allowing for correlation of error terms across equations.

PRINCIPAL FINDINGS

Findings indicated that unobservable characteristics leading elderly Medicare beneficiaries to purchase drug coverage also lead them to have higher drug expenditures on conditional use (i.e., adverse selection), while the same unobservable factors do not influence their decisions whether to use any drugs. After controlling for potential selection bias, the probability of any drug use among persons with drug coverage use was 4.5 percent higher than among those without, and drug coverage led to an increase in drug expenditures of $308 among those who used prescription drugs.

CONCLUSIONS

Given significant adverse selection into drug coverage before the implementation of the Medicare Prescription Drug Improvement and Modernization Act, it is essential that selection effects be monitored as beneficiaries choose whether or not to enroll in this voluntary program.

The effect of medicare health maintenance organizations on hospitalization rates for ambulatory care-sensitive conditions

OBJECTIVE

The objective of this study was to estimate the effect of Medicare Health Maintenance Organization (HMO) enrollment on hospitalization rates and total inpatient days for ambulatory care-sensitive conditions (ACSCs) after controlling for selection.

RESEARCH DESIGN

Simultaneous equations using a discrete factor selection model are used to estimate the probability of HMO enrollment, hospitalization rates, and total inpatient days for ACSCs.

SUBJECTS

Enrollment data on Medicare beneficiaries in California were linked to hospital discharge data from the California Office of Statewide Health Planning and Development for January through December 1996. The following beneficiaries were excluded: 1) end-stage renal disease, 2) under 65 years of age, 3) not covered by both Medicare Part A and Part B, 4) switched between HMOs and fee-for-service (FFS), and 5) switched between HMOs. The sample was stratified by age, gender, race, county, disability, Medicaid eligibility, HMO status, and death. A 2% random sample from the 4 California counties with the largest Medicare enrollment yielded 10,448 HMO enrollees and 11,803 FFS beneficiaries.

RESULTS

Using a discrete factor selection model, we estimated the rate of ACSC hospitalizations among FFS beneficiaries would decline from 51.2 to 44.2 per 1000 if all FFS beneficiaries joined an HMO. Similarly, the mean total inpatient days for ACSC hospitalizations would be reduced from 7.5 days to 5.1 days if all FFS beneficiaries joined an HMO.

CONCLUSIONS

After controlling for selection, Medicare HMO enrollees have lower hospitalization rates and fewer total inpatient days for 15 ACSCs than Medicare FFS beneficiaries. These findings suggest selection of healthier beneficiaries into HMOs does not completely explain their lower rates of ACSC hospitalization.

The magnitude and nature of risk selection in employer-sponsored health plans

OBJECTIVE

To determine whether health maintenance organizations (HMOs) attract enrollees who use relatively few medical resources and whether a simple risk-adjustment system could mitigate or eliminate the inefficiency associated with risk selection.

DATA SOURCES

The first and second rounds of the Community Tracking Study Household Survey (CTSHS), a national panel data set of households in 60 different markets in the United States.

STUDY DESIGN

We use regression analysis to examine medical expenditures in the first round of the survey between enrollees who switched plan types (i.e., from a non-HMO plan to an HMO plan, or vice versa) between the first and second rounds of the survey versus enrollees who remained in their original plan. The dependent variable is an enrollee's medical resource use, measured in dollars, and the independent variables include gender, age, self-reported health status, and other demographic variables.

DATA COLLECTION METHODS

We restrict our analysis to the 6,235 non-elderly persons who were surveyed in both rounds of the CTSHS, received health insurance from their employer or the employer of a household member in both years of the survey, and were offered a choice of an HMO and a non-HMO plan in both years.

PRINCIPAL FINDINGS

We find that people who switched from a non-HMO to an HMO plan used 11 percent fewer medical services in the period prior to switching than people who remained in a non-HMO plan, and that this relatively low use persisted once they enrolled in an HMO. Furthermore, people who switched from an HMO to a non-HMO plan used 18 percent more medical services in the period prior to switching than those who remained in an HMO plan.

CONCLUSIONS

HMOs are experiencing favorable risk selection and would most likely continue to do so even if employers adjusted health plan payments based on enrollees' gender and age because the selection is based on enrollee characteristics that are difficult to observe, such as preferences for medical care and health status.

A longitudinal evaluation of the effect of Medi-Cal managed care on supplemental security income and aid to families with dependent children enrollees in two California counties

OBJECTIVE

We examined the differential effect of Medicaid managed care (MMC) among Aid to Families With Dependent Children (AFDC) and Supplemental Security Income (SSI) enrollees over time by comparing the experiences of adult nonelderly enrollees in the Health Plan of San Mateo in California versus Ventura County's fee-for-service (FFS) enrollees.

RESEARCH DESIGN

Four years of administrative claims data were used to construct a longitudinal data set and estimate panel data models to decompose the effect of managed care over time.

RESULTS

AFDC MMC enrollees exhibited generally fewer ambulatory visits, lower expenditures, and higher monthly probabilities of a preventable hospitalization relative to comparably enrolled FFS patients. SSI MMC enrollees had more emergency department visits and higher monthly probabilities of hospitalization. However, SSI MMC enrollees had more ambulatory visits and more medications during the first year of enrollment relative to SSI FFS enrollees, although levels were similar in subsequent years. SSI MMC enrollees did not exhibit a significantly higher level of expenditures in the first year of enrollment, although in subsequent years, expenditure levels were significantly lower.

CONCLUSIONS

The results for emergency department visits and preventable hospitalizations presented a decidedly downbeat picture of access to care for AFDC and SSI enrollees in MMC. However, some aspects of utilization under managed care exhibited results consistent with long-term- oriented treatment for enrollees with a greater likelihood of remaining in the system for a longer period of time (SSI enrollees). By contrast, enrollees more likely to be enrolled for shorter periods (AFDC enrollees) tended to exhibit care patterns under MMC consistent with lower levels of care relative to FFS.

Expenditures for physician services under alternative models of managed care

This study compares expenditures for physician services in a closed panel gatekeeper health maintenance organization (HMO) and an open panel point of service HMO that share the same physician network. The study uses administrative files of the two study HMOs for 1994-1995 to assess differences in spending for primary care physicians' (PCPs') services, specialists' services, and total physician services. When the copayments for PCP visits and PCP-referred specialist visits were $0, total physician expenditures were 4 percent higher in the gatekeeper HMO than in the point of service plan (p < .05). When the copayments for PCP visits and PCP-referred specialist visits were $10, total physician expenditures ranged from equal in both HMOs to 7 percent higher in the gatekeeper HMO (p < .01), depending on the copayment for self-referred visits. Expenditures for specialists' services were not higher in the point of service plan. The authors conclude that direct patient access to specialists does not necessarily result in higher physician or specialist expenditures in HMOs.

HMO selection and Medicare costs: Bayesian MCMC estimation of a robust panel data tobit model with survival

The fraction of US Medicare recipients enrolled in health maintenance organizations (HMOs) has increased substantially over the past 10 years. However, the impact of HMOs on health care costs is still hotly debated. In particular, it is argued that HMOs achieve cost reduction through 'cream-skimming' and enrolling relatively healthy patients. This paper develops a Bayesian panel data tobit model of HMO selection and Medicare expenditures for recent US retirees that accounts for mortality over the course of the panel. The model is estimated using Markov Chain Monte Carlo (MCMC) simulation methods, and is novel in that a multivariate t-link is used in place of normality to allow for the heavy-tailed distributions often found in health care expenditure data. The findings indicate that HMOs select individuals who are less likely to have positive health care expenditures prior to enrollment. However, there is no evidence that HMOs disenrol high cost patients. The results also indicate the importance of accounting for survival over the panel, since high mortality probabilities are associated with higher health care expenditures in the last year of life.