Disenrollment Rates Research Articles

Disenrollment From Medicaid After Recent Cancer Diagnosis

We examine the frequency with which newly diagnosed cancer patients are covered by Medicaid in Washington State and the duration of coverage. Medicaid enrollment and claims files were linked to the Washington State Cancer Registry to identify all Medicaid enrollees with breast, cervical, lung, colorectal, and prostate cancer between 1997 and 2002. We identified 5009 newly diagnosed cancer patients covered by Medicaid, approximately 13% of the total cases diagnosed in subjects less than 65 years of age in Washington State. The majority, 2866 (57%), enrolled in Medicaid around the time of diagnosis; the remainder had been enrolled at least 3 months before diagnosis. Persons enrolled at diagnosis had later-stage cancer; those enrolled before diagnosis had more noncancer comorbidities. Overall, 18% had disenrolled by 6 months after diagnosis; 34% by 1 year; and 54% by 2 years. Medicaid patients with cancer in Washington State experience a high rate of disenrollment within 1 year after diagnosis. Further research is needed to determine whether disenrollment compromises initial therapy or follow-up care.

Assessing Potential Enrollment and Budgetary Effects of SCHIP Premiums: Findings from Arizona and Kentucky

To assess whether new premiums in SCHIP affect rates of disenrollment and reenrollment in SCHIP and whether they have spillover enrollment effects on Medicaid. We used SCHIP administrative enrollment data from Arizona and Kentucky. The enrollment data covered July 2001 to December 2005 in Arizona and November 2001 to August 2004 in Kentucky. We used administrative data from two states, Arizona and Kentucky, which introduced new premiums for certain income categories in their SCHIP programs in 2004 and 2003, respectively. We used multivariate hazard models to study rates of disenrollment and re-enrollment for the recipients who had been enrolled in the categories of SCHIP in which the new premiums were implemented. Competing hazard models were used to determine if recipients leaving SCHIP following the introduction of the premium were obtaining other public coverage or exiting public insurance entirely at higher rates. We also used time-series models to measure the effect of premiums on changes in caseloads in premium-paying SCHIP and other categories of public coverage and we assessed the budgetary implications of imposing premiums. In both states, the new premiums increased the rate of disenrollment and decreased the rate of re-enrollment in premium-paying SCHIP among the children who were enrolled in those categories before the premiums were implemented. The competing hazard models indicated that almost all of the increased disenrollment is caused by recipients leaving public insurance entirely. The time-series models indicated that the new premium reduced caseloads in premium-paying SCHIP, but that it might have increased caseloads for other types of public coverage. The amount of premiums collected net of the costs associated with administering premiums is small in both states. Estimating the full budgetary effects with certainty was not possible given the imprecision of the key time-series estimates. These results suggest that the new premium reduced enrollment in the premium-paying group by 18 percent (over 3,000 children) in Kentucky and by 5 percent (over 1,000 children) in Arizona, with some of these children apparently leaving public coverage altogether. While most children enrolled in these categories did not appear to be directly affected by the imposition of $10-$20 monthly premiums, the premiums may have caused some children to go without health insurance coverage, which in turn could have adverse effects on their access to care. Imposing nominal premiums may reduce state spending, but projected savings appear to be small relative to total state SCHIP spending and resulting increases in enrollment in other public programs and in uninsurance rates could offset those savings.

Assessing Gaps Between Policy and Practice in Medicaid Disenrollment of Jail Detainees With Severe Mental Illness

Assessing Gaps Between Policy and Practice in Medicaid Disenrollment of Jail Detainees With Severe Mental Illness

From Medicaid to Uninsured: Drop‐Out among Children in Public Insurance Programs

To estimate a national disenrollment rate among children in Medicaid and the Children's Health Insurance Program (CHIP); to determine what share of disenrollment is due to acquiring other insurance or losing eligibility; and to examine what demographic and policy factors make disenrollment more likely. Insurance status, income, and demographics from the Current Population Survey (CPS) March Supplement (1998-2001); eligibility data from the National Governors Association; and policy data from the former Health Care Financing Administration (HCFA), state welfare offices, and previous research. The study used a nationally representative sample of 5,551 children in Medicaid or CHIP. The key outcomes were the percentage of children still enrolled 1 year later, and the share of disenrollees who became uninsured despite remaining eligible. Multivariate logistic regression was used to explore demographics and policies predictive of disenrollment. CPS data were extracted using the Census Bureau's Federal Electronic Research and Review Extraction Tool 1.0. Data analysis was performed using Stata 7 (Stata Corporation 2001). Of the children enrolled in Medicaid or CHIP, 27.7 percent were no longer enrolled 12 months later. Of those, 45.4 percent dropped out despite apparently remaining eligible and having no other insurance--corresponding to 3.0 million children annually. Drop-out varied significantly across states. Children without siblings in public insurance were at a higher risk for drop-out. Children with more educated parents were more likely to leave Medicaid for private insurance or to lose Medicaid eligibility, while black children and infants were less likely to lose their eligibility. Decreased Medicaid provider reimbursement rates were strongly associated with drop-out, while Medicaid managed care increased the exodus to private insurance. Drop-out from Medicaid and CHIP is a significant policy concern and helps explain the persistence of uninsurance among millions of eligible children. Clinical encounters with providers appear to play a key role in preventing drop-out.

Context or composition: what explains variation in SCHIP disenrollment?

To investigate (1) the relative contributions of family and contextual characteristics to observed variation in disenrollment rates from the State Children's Health Insurance Program (SCHIP), and (2) whether context explains observed family-level patterns. We use secondary data on 24,628 families enrolled in New Jersey's SCHIP program (NJ KidCare), and county-level data from the Area Resource File, the Census, and the NJ FamilyCare provider roster. Information on family characteristics, SCHIP plan, and dates of enrollment and disenrollment are taken from NJ KidCare administrative records, which provided surveillance data from January 1998 through April 2000. We estimate a multilevel discrete-time-hazards model of SCHIP disenrollment. Families enrolled in plans involving cost-sharing, blacks, and those with only one enrolled child have higher than average rates of disenrollment. Disenrollment rates for blacks are lower in counties with a high share of black physicians. These characteristics account for part of the intercounty variation in disenrollment rates; remaining intercounty variation is largely explained by physician density or population density. It may be worthwhile to pay special attention to black families and counties with high disenrollment rates to address the reasons for their lower retention. Addressing cultural differences between physician and client and the geographic distribution of medical providers might reduce disenrollment.

Expanding developmental and behavioral services for newborns in primary care: Effects on parental well-being, practice, and satisfaction

Background Healthy Steps (HS) was designed to address, prospectively, behavioral and developmental support needs of young families in pediatric clinical care settings. PrePare (PP) initiates these services prenatally, whereas HS begins services in the postnatal period. Both interventions have universal and risk-directed components. Intervention effects in the first 3 months after birth are reported here. Methods A quasi-experimental design was used to allocate 439 participants to intervention or usual care conditions. Within the intervention group, enrollees were randomly assigned to receive HS or PP+HS services. Early outcomes were assessed by telephone survey at 1 week and 3 months postpartum. Results Mothers in either intervention condition were less likely to report depressive symptoms and more likely to describe themselves as pleased in their role as parents. Intervention families were more likely to continue breastfeeding and more likely to read to their 3-month-old. Knowledge of infant development and recognition of appropriate discipline was greater among intervention recipients. Satisfaction with pediatric care was higher among intervention recipients and the rate of health plan disenrollment was 75% lower at 3 months among those enrolled in the prenatal intervention. No other outcome difference emerged between HS and PP+HS enrollees. Conclusions Receipt of either intervention was associated with positive effects on health, safety, and developmentally appropriate parenting, as assessed in early infancy. There were positive effects on health plan disenrollment. No additional benefit could be ascribed to prenatal institution of services. A combination of universal and risk-based support for new parents is recommended, rather than the provision of risk-based services alone.

Demographics of disenrollment from SCHIP: evidence from NJ KidCare.

The State Children's Health Insurance Program (SCHIP) provides health insurance coverage for children in low-income families. Although there is evidence of substantial disenrollment from SCHIP, few studies have examined how disenrollment varies by demographic characteristics. This study uses data from administrative records of all 41,881 children enrolled prior to April 2000 in NJ KidCare (New Jersey's SCHIP) separate state plans for families with incomes between 133% and 350% of the Federal Poverty Level. Survival methods were used to analyze disenrollment according to demographic and plan characteristics. Reasons for disenrollment were also studied. Overall, 18.9% of children disenrolled within 12 months of enrollment. Disenrollment was higher among non-Hispanic black children, children aged 1 to 5, and children without siblings in NJ KidCare than among their counterparts. Surprisingly, English speakers had the highest disenrollment rate of all language groups. Children in families with moderate income categories for whom premium contributions were required were 3 times as likely as lower-income children to disenroll, principally due to non-payment of premiums. To maximize retention in SCHIP and ensure access to care and continuity of care for low-income children, research is needed concerning why some groups disenroll more quickly.

Reduction in Patient Enrollment in the Veterans Health Administration After Media Coverage of Adverse Medical Events

Health care organizations may experience costs associated with preventable adverse events in the form of poor brand image and subsequent patient disenrollment. A retrospective cohort design was used to determine whether media coverage of adverse events that occurred in Veterans Health Administration (VHA) hospitals was associated with subsequent veteran disenrollment. Twenty-four newspaper reports of medical adverse events that occurred between 1994 and 1999 within the VHA system were identified. Regionally adjusted changes in enrollment rates for VHA facilities that had reported adverse events were compared with those that had not one year before and one and three years after publication of the newspaper reports. Facilities that had published reports of adverse events had lower enrollment rates after publication of the report for two groups of veterans. Within the VHA system, health care organizations involved in adverse events that generated publicity suffered a greater rate of patient disenrollment. If safe patient care practices can reduce adverse publicity, they may enhance corporate value by maintaining enrollment of the patient population.

Adverse selection and generosity of alcohol treatment benefits.

Concerns about attracting disproportionate numbers of employees with alcohol problems limit employers' willingness to offer health plans with generous alcohol treatment benefits. This paper analyzes two potential avenues of adverse selection, namely biased enrollment into plans and biased exit from plans offered by 57 employers between 1991 and 1997. We compare alcohol treatment use rates and costs of new and old enrollees between more generous and less generous plans; we also analyze disenrollment rates and enrollment duration by plan generosity for users and nonusers of alcohol treatment services. To avoid confounding benefit generosity with other plan features, in particular the use of managed care mechanisms, we compare plans that were administered in the same way by a large managed behavioral health care organization. Overall, we find no evidence of adverse selection into more generous plans. Contrary to the selection hypothesis, treatment costs of new members compared to old members are lower in firms with more generous treatment benefits than in firms with more limited benefits. Also, users of alcohol treatment services do not remain disproportionately enrolled longer in plans with generous benefits.

Disenrollment From Medicare Managed Care Plans in Connecticut

PURPOSE: Disenrollment behavior has important implications for the cost, quality, and continuity of care under Medicare Managed Care (MMC). Although disenrollment data are sometimes used as a quality indicator, uncertainty about how personal and plan characteristics influence disenrollment decisions complicates their use as a valid quality measure. METHODS: To determine how personal characteristics influence MMC disenrollment decisions, we analyzed data from the Medicare Beneficiary File, the US Census, and MMC plans. The study population consisted of MBs enrolled in one of 9 MMC Risk plans during a 6 month period, January through June 1998. We estimated logistic regression models with disenrollment (i.e. leaving a plan during the study period) as the dependent variable, and individual MB characteristics (age, gender, race, education, economic indicators) as independent variables, adjusting for plan characteristics. For disenrolling MBs we also estimated models using rapid disenrollment and disenrollment to fee-for-service (FFS) as dependent variables. RESULTS: Of 84,443 Medicare Beneficiaries (MBs) enrolled in one of 9 MMC risk plans in Connecticut, 4,102 (4.9%) disenrolled at least once during the 6 month study period, January through June, 1998. Of 4,022 MBs who disenrolled only once, 2,661 (66.2%) joined another MMC plan, while 1,361 (33.8%) returned to fee-for-service (FFS). 948 (23.6%) disenrolled rapidly (<90 days after joining). MBs who switched to another MMC plan had been enrolled longer than those who went back to FFS (Median 303 vs. 120 days, p < .001). In logistic regression analysis, adjusting for plan characteristics, disenrollment was associated with non-White race/ethnicity, age <75, and residence in areas with higher poverty rates and lower education levels. Among disenrollees, rapid disenrollment and disenrollment to FFS were associated with female gender, age ≥75, and residence in areas with higher poverty rates. CONCLUSION: Higher disenrollment among poorer, minority MBs suggests that these groups may have more problematic experiences with MMC, or may be more severely affected by coverage limitations. The higher rate of rapid disenrollment and return to FFS among older, poor, female disenrollees may be related to inadequate plan information at enrollment. Further research is needed do determine how patient characteristics influence disenrollment decisions, and whether MMC plans can improve member retention by paying more attention to the medical needs of specific groups and the information provided to enrollees.

Who leaves managed behavioral health care?

The growth of managed care and the possibility of biased enrollment and dis-enrollment rates have raised concerns about cost shifting. This article analyzes the duration of continuous enrollment in a managed behavioral health organization among members with and without behavioral health care utilization and among members with different mental health conditions. Eleven large employers with more than 250,000 members who are enrolled in managed behavioral health plans are studied. Compared to managed care 10 years ago, the rate of dis-enrollment among patients with depression appears to have dropped. Moreover, there appear few differences in dis-enrollment among users and nonusers of behavioral health services, except for employees for whom coverage is linked to job performance. However, patients with substance abuse problems or severe types of disorders are significantly more likely to dis-enroll than patients with less severe problems.

Barriers and facilitators to providing common preventive screening services in managed care settings.

Despite increasing emphasis on disease prevention and health promotion, and ample evidence demonstrating the effectiveness of preventive services, such services are underutilized in the United States. The current trend of health care toward health maintenance organizations and other managed care systems opens the door, perhaps to more effective control of heart disease, cancers and other chronic diseases through preventive care. This warrants attention to the barriers/facilitators to the provision/utilization of preventive screening services in such settings. Overall goal of this study was to assess barriers/facilitators to the provision/utilization of preventive services in managed care organizations (MCOs). This was accomplished by a) identifying barriers/facilitators to the provision/utilization of three common preventive screening services (cholesterol screenings, mammograms, and Pap smears); and b) profiling typical MCO recipients of these three preventive screening services. A self-administered, mail questionnaire was used to obtain information from a national sample of 1,200 Directors of MCOs associated with preventive care. A total of 175 usable responses were received resulting in a 17.3 percent net response rate. The strongest barrier to the provision of all three screening services is the inability of them to generate short term savings for the MCO. Other barriers include high disenrollment rates, conflicting recommendations about effectiveness (for mammograms and cholesterol screenings), and patients' fears of getting a positive result (for mammograms and Pap smears). The improved health status as a result of early intervention, high consumer awareness (for mammograms and Pap smears), and long term savings are important facilitators to the provision/utilization of these screening services. Comparing barriers and facilitators across the three services shows the stronger barriers affecting the provision/utilization of mammograms. For all three screening services, typical managed care recipients are those in the high income groups with greater education levels. However, with the increasing enrollment of Medicaid beneficiaries into managed care, MCOs may find themselves selectively targeting these high risk low income and less educated individuals to receive the preventive screening services. Study findings should be useful to health planners, policymakers and researchers at all levels in their efforts to encourage and promote healthier lifestyle choices among U.S. residents. Future studies should address receipt of preventive services by Medicaid and Medicare beneficiaries in managed care settings.

Disenrollment of Medicare cancer patients from health maintenance organizations.

There is concern that financial incentives in health maintenance organizations (HMOs) might result in pressures to induce sicker members to disenroll. The authors compared disenrollment rates of Medicare HMO enrollees with cancer with disenrollment rates for cancer-free enrollees, using Medicare enrollment files linked to population-based tumor registry data from the Surveillance, Epidemiology, and End Results (SEER) Program. The authors identified all aged Medicare beneficiaries who enrolled in an HMO located in a SEER reporting area during 1985 to 1989. Time to disenrollment was analyzed using a proportional hazards model. Overall, cancer patients were no more likely to disenroll than others. However, persons diagnosed with cancer after enrollment were less likely to disenroll than other persons in Independent Practice Association (IPA) mode HMOs (relative risk [RR] = 0.79). Persons diagnosed with cancer after enrollment in group- and staff-model HMOs were about equally likely to disenroll as other persons (RR = 0.91). Persons diagnosed with cancer less than 18 months before enrollment were at high risk for disenrollment from both IPA and group-/staff-model HMOs (RR = 1.47 and 1.35). There was substantial variation among HMOs in overall disenrollment rates and in RRs for disenrollment by cancer patients. The low disenrollment rates of patients diagnosed after enrollment do not support the contention that features intrinsic to managed care make HMOs unattractive to the seriously ill. Monitoring of selective disenrollment could be used as a screen for possible access and quality problems.

Employee Premiums, Availability of Alternative Plans, and HMO Disenrollment

The notion that greater competition among health plans helps contain health-care costs presumes that consumers respond to economic incentives. This article tests that proposition through an examination of the factors that cause individuals to disenroll from health maintenance organizations (HMOs). The study relies upon a multivariate probit model of disenrollment behavior, estimated with data on 1,553 subscribers in three Minneapolis-St. Paul HMOs in 1984. The results indicate that disenrollments are a function largely of economic factors; disenrollments rise significantly with increases both in relative premiums and in the number of plan choices available to consumers. To illustrate, a +5.00 increase in the employee's monthly premium for one HMO, relative to the average change in the employees' premiums for all other available plans, would lead to a two thirds increase in that HMO's disenrollment rate.