Rural Health Clinics and Diabetes-Related Primary Care for Medicaid Beneficiaries in Oregon

ABSTRACT:  Background: This study assessed whether Rural Health Clinics (RHCs) were associated with higher rates of recommended primary care services for adult beneficiaries diagnosed with diabetes in Oregon's Medicaid program, the Oregon Health Plan (OHP). Methods: OHP claims data from 2002 to 2003 were used to assess quality of diabetic care for beneficiaries residing in urban areas or rural areas with or without at least 1 RHC. Study subjects included Temporary Assistance to Needy Families (TANF) or disabled beneficiaries, aged 18-64, who were enrolled in the OHP for 12 months per study year and had at least 1 claim with a diabetes diagnosis (n = 6,267). Diabetes-related primary care was measured by the proportion of patients receiving each of 3 recommended tests at least once during the calendar year: hemoglobin A1c (HbA1c), lipid profile, and eye exam. Logistic regression models were used to identify differences in testing rates across the geographic areas, after controlling for individual differences including age, race, sex, and health status. Results: Rural areas with no RHC had significantly lower rates of HbA1c testing, lipid profiles, and eye exams than urban areas (P < .01). Rural areas with at least 1 RHC had significantly higher rates for lipid profiles and eye exams than other rural areas (P < .05). No significant differences were detected in testing rates between rural areas with an RHC present and urban areas. Conclusions: RHCs in rural Oregon were associated with higher rates of recommended primary care for diabetes, consistent with the intent of the policy intervention.     

Identifying a Sample of HIV-Positive Beneficiaries From Medicaid Claims Data and Estimating Their Treatment Costs

Objectives. We sought to identify people living with HIV/AIDS from Medicare and Medicaid claims data to estimate Medicaid costs for treating HIV/AIDS in California. We also examined how alternate methods of identifying the relevant sample affect estimates of per capita costs.Methods. We analyzed data on Californians enrolled in Medicaid with an HIV/AIDS diagnosis reported in 2007 Medicare or Medicaid claims data. We compared alternative selection criteria by examining use of antiretroviral drugs, HIV-specific monitoring tests, and medical costs. We compared the final sample and average costs with other estimates of the size of California’s HIV/AIDS population covered by Medicaid in 2007 and their average treatment costs.Results. Eighty-seven percent (18 290) of potentially identifiable HIV-positive individuals satisfied at least 1 confirmation criterion. Nearly 80% of confirmed observations had claims for HIV-specific tests, compared with only 3% of excluded cases. Female Medicaid recipients were particularly likely to be miscoded as having HIV. Medicaid treatment spending for Californians with HIV averaged $33 720 in 2007.Conclusions. The proposed algorithm displays good internal and external validity. Accurately identifying HIV cases in claims data is important to avoid drawing biased conclusions and is necessary in setting appropriate HIV managed-care capitation rates.In 2010, the White House Office of National AIDS Policy outlined an ambitious National HIV/AIDS Strategy for the United States that called for evaluation strategies that would “obtain data (core indicators) that capture the care experiences of people living with HIV without substantial new investments.”1 Surveillance systems already in place in each state provide the Centers for Disease Control and Prevention with comprehensive data on incident HIV and AIDS cases.2 However, much less is known about the medical treatments received by people living with HIV/AIDS and the cost of those treatments.Much of the cost of HIV/AIDS treatment is borne by public insurance programs, principally Medicaid and Medicare. These 2 programs provide health insurance for more than half of people living with HIV/AIDS who are receiving care.3,4 The importance of Medicaid as a source of funding for HIV/AIDS treatment of low-income persons will grow substantially after full implementation of the Affordable Care Act, which eliminates the additional disability requirement for Medicaid eligibility in states accepting the Medicaid expansion, thereby extending coverage to nondisabled, low-income people living with HIV/AIDS in those states.Because of its prominent role in insuring low-income people living with HIV/AIDS, Medicaid can provide a rich source of data on the types and costs of treatments delivered to some of the most vulnerable individuals with HIV/AIDS. Insurance claims data can potentially allow us to monitor HIV/AIDS treatment without substantial new investments because most claims data are stored as computerized records. Claims data provide a comprehensive picture of medical care received from a variety of providers in multiple settings (outpatient, inpatient, laboratory, pharmacy), contain procedure codes that detail the services provided, and include cost of the treatment. By contrast, medical records tend to have smaller scope, in terms of both numbers of patients and services covered. Furthermore, medical records most often lack payment information.Insurance claims data can provide information on a large number of individuals, even among those with relatively low-prevalence conditions, which is valuable in reducing the variability of estimates of per capita expenditures. However, the greater precision afforded by large administrative data sets is of little value if estimates are based on an inappropriate sample. Claims data are primarily designed for billing purposes; thus, they generally lack clinical detail important for selecting cases with a particular disease.3,5 For example, claims data will document whether a laboratory test was performed, but not the test result. Therefore, analysts must rely on the diagnosis information on insurance claims.6 Professional medical records specialists code diagnoses on inpatient claims, leading to greater accuracy and reliability of diagnosis information coming from inpatient stays. However, diagnosis coding is more error-prone in the outpatient sector, which has accounted for an increasing percentage of HIV/AIDS care since 1996 when antiretroviral medication (ARV) began to dramatically reduce hospitalization for HIV/AIDS.7 This has increased the challenges of identifying people living with HIV/AIDS from insurance claims data.We applied a practical algorithm for identifying people living with HIV/AIDS in insurance claims data to estimate Medicaid costs for treating HIV/AIDS in California. We also examined how alternate methods of identifying the relevant sample affect estimates of per capita costs.     

The Effect of Medicaid on Management of Depression: Evidence From the Oregon Health Insurance Experiment

Policy Points:

• We take advantage of Oregon's Medicaid lottery to gauge the causal effects of Medicaid coverage on mental health care, how effectively it addresses unmet needs, and how those effects differ for those with and without a history of depression.
• Medicaid coverage reduced the prevalence of undiagnosed depression by almost 50% and untreated depression by more than 60%. It increased use of medications and reduced the share of respondents reporting unmet mental health care needs by almost 40%.
• There are likely to be substantial mental health consequences of policy decisions about Medicaid coverage for vulnerable populations.

Context

Expanding Medicaid to previously uninsured adults has been shown to increase detection and reduce the prevalence of depression, but the ways that Medicaid affects mental health care, how effectively it addresses unmet needs, and how those effects differ for those with and without a history of depression remain unclear.

Methods

We take advantage of Oregon's Medicaid lottery to gauge the causal effects of Medicaid coverage using a randomized‐controlled design, drawing on both primary and administrative data sources.

Findings

Medicaid coverage reduced the prevalence of undiagnosed depression by almost 50% and untreated depression by more than 60%. It increased use of medications frequently prescribed to treat depression and related mental health conditions and reduced the share of respondents reporting unmet mental health care needs by almost 40%. The share of respondents screening positive for depression dropped by 9.2 percentage points overall, and by 13.1 for those with preexisting depression diagnoses, with greatest relief in symptoms seen primarily in feeling down or hopeless, feeling tired, and trouble sleeping—consistent with the increase observed not just in medications targeting depression but also in those targeting sleep.

Conclusions

Medicaid coverage had significant effects on the diagnosis, treatment, and outcomes of a population with substantial unmet mental health needs. Coverage increased access to care, reduced the prevalence of untreated and undiagnosed depression, and substantially improved the symptoms of depression. There are likely to be substantial mental health consequences of policy decisions about Medicaid coverage for vulnerable populations.     

Medical Costs of Persons with Drug Use Disorders Among Medicaid Managed Care Beneficiaries in Puerto Rico

Drug use disorders (DUDs) can substantially increase the costs of health care, especially when left untreated. Yet, not much is known about the specific types of medical services that give rise to these cost differences. This study aimed to estimate the medical costs of beneficiaries with DUDs enrolled in the Medicaid Managed Care (MMC) program in Puerto Rico using claims data. These were compared to those of a matched group of patients without DUDs. On average, each beneficiary with a DUD incurred in $4539 annually on medical services compared to $2601 in the matched comparison group, a cost differential of $1938. Close to half of these additional medical costs (43.4%) were generated in the physical health services sector. Counts of service claims were also higher for beneficiaries with DUDs than for beneficiaries without DUDs in all service types, except in outpatient and laboratory services for physical health. A host of access strategies and treatment modalities should be tested to assess the extent to which providing adequate access and adequate treatment for a DUD can contribute to cost savings.     

Effects of Managed Mental Health Care on Service Use in Urban and Rural Maine

This study takes advantage of a "natural experiment" resulting from the reassignment of all Maine state employees to a managed behavioral health plan in December 1992. By comparing mental health claims before and after that date, the effects of a behavioral health carve-out on mental health utilization by rural and urban beneficiaries were investigated. Following the implementation of the carve-out, the penetration rate, defined as the proportion of beneficiaries who sought help for an affective disorder, increased significantly in both rural and urban areas (P < 0.001). However, the rural penetration rate remained significantly lower than the urban rate (before implementation, 25.8 vs. 52.2 users per 1,000 enrollees, P < 0.001; after implementation, 57.8 vs. 85.8 users per 1,000 enrollees, P < 0.001). Similarly, rural utilization rates, defined as the average number of outpatient mental health visits per user, were significantly lower than urban rates both before and after implementation of the carve-out (before, 9.2 us. 12.9 visits per user, P < 0.001; after, 9.8 vs. 13.3 visits per user, P < 0.001). Before-after differences were not significant. In addition, the proportion of mental health care provided in the primary care setting increased after implementation of the carve-out (from 9.5 percent of all visits before to 12.6 percent of all visits after, P < 0.001). The increase in penetration rates can be attributed, in part, to a member education initiative undertaken during the transition from fee-for-service to managed care. This type of carve-out arrangement does not threaten to reduce access to mental health services, provided the managed behavioral health organization (MBHO) managing the carve-out is willing to accept primary care practitioners as part of its provider network.     

Labor Supply of Poor Residents in Metropolitan Miami,Florida: The Role of Depression and the Co-Morbid Effects of Substance Use

BACKGROUND: Depression represents one of the most common behavioral health problems among the workforce in the United States, with about 1 in every 20 employees experiencing this condition. A recent study estimated that in 1990 the economic costs of depressive disorders in the American workplace amounted to as much as $43 billion, with absenteeism alone accounting for $12 billion. Recently, economists have been focusing attention on the relationship between mental health and labor supply, but a lack of quality data sets containing detailed information on mental health and labor market variables represents a significant barrier to rigorous research. AIMS OF THE STUDY: The primary aims of the present study were to (i) examine the relationship between depression and employment, (ii) conditional on being employed, estimate the effect of depression on annual weeks worked, and (iii) examine the stability of the model estimates to the co-morbid effects of substance use (illicit drugs and alcohol), which has been consistently found to be a correlate of depression. DATA: The study used a unique set of survey data collected between 1996 and 1997 in crime-ridden and low-income neighborhoods of Miami-Dade County, Florida. A targeted sampling strategy was used to recruit chronic drug users (including injection drug users) and non-drug users to examine local health care delivery system characteristics in relation to the population of substance users. The final analysis sample for the present study included 1,274 adults, aged 18 to 65. Depression status was measured from the 20-item Zung Self-Rating Depression Scale (SDS) that classified 384 individuals as depressed and 890 as non-depressed. According to the definition developed by the U.S. Office of National Drug Control Policy for chronic drug use (CDU), about 46 percent of the depressed individuals were found to be CDUs compared to 30 percent of the non-depressed sample. The survey instrument collected information on alcohol use and problem drinking as defined by the 10-item Michigan Alcoholism Screening Test (MAST-10). Based on criteria defined in the MAST-10, 26 percent of the depressed individuals were problematic alcohol users (PAUs) compared to about 16 percent of the non-depressed sample.METHODS: The labor supply measures included employment in the past 30 days and number of weeks worked in the past 12 months. The analysis estimated a univariate probit model of employment as well as a bivariate probit model of depression and employment, which accounted for the possible correlation between the unobserved determinants of depression and employment. The annual weeks worked specification was estimated by a standard Tobit model as well as an instrumental variable (IV) Tobit model, which, in addition to the censoring of the observations, accounted for the possible endogeneity of depression. The stability of the estimated effects of depression to comorbid illicit drug and alcohol use was assessed, by controlling for CDU and PAU in these models. RESULTS: Results from both the univariate probit and the bivariate probit models indicate that depression significantly decreased the probability of being employed. Specifically, depression reduced the probability of employment by an average of 19 percentage points in both models, from a sample average of 43 percent for the non- depressed to 24 percent for the depressed. Estimates from the Tobit models revealed that depression also significantly reduced the number of weeks worked. Conditional on being employed, depressed individuals worked an average of 7 fewer annual weeks than the non-depressed sample in the univariate Tobit model and 8 fewer weeks in the IV Tobit. The findings also showed that the effects of depression on employment and annual weeks worked may be over-estimated if the analysis does not account for the comorbid influence of substance use. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE: The results suggest that prevention and/or treatment of mental health problems such as depression may yield economic benefits by promoting employment and enhancing labor supply. While expansion of public mental health services may not lead to overall increases in employment, it may be justified on social grounds given the high unemployment rate in low-income and crime-ridden neighborhoods. Further insights can be gained by estimating these models with national and international data if one applies appropriate econometric tools to account for complex sample designs.     

Depression and Health Service Utilization From Age 70 to 85: The Jerusalem Longitudinal Study

BackgroundHealth service utilization rises with age, and yet, its determinants are poorly understood. Our objective was to examine the association between depression and health service utilization from age 70–85.MethodsA representative sample (born 1920–1921) from the Jerusalem Longitudinal Cohort Study (1990–2010) was assessed at age 70, 78, and 85 for depression (using the Brief Symptoms Inventory); emergency room (ER) visits, and hospitalization in the previous year; social, functional, and medical domains.ResultsWe examined 414, 674, and 1118 subjects at ages 70, 78, and 85, among whom prevalence of depression was 16.2%, 21.1%, and 36.7%, respectively. ER visits and hospitalization were higher among depressed subjects. We adjusted for sex as well as financial status (social model); physical activity, going outdoors, functional status (functional model); and diabetes, ischemic heart disease, hypertension, cancer, dementia, chronic pain, and smoking (medical model). Depressed subjects were more likely to report increased ER visits, after adjustment in social, functional or medical models at age 78 (odds ratio [OR], 2.1, 95% confidence interval [CI], 1.3–3.3; OR, 1.8, 95% CI, 1.1–2.9; OR, 2.0, 95% CI, 1.26–3.26), and at age 85 (OR, 1.7, 95% CI, 1.33–2.3; OR, 1.4, 95% CI, 1.04–1.81; and OR, 1.4, 95% CI, 1.1–1.94), respectively. Aside from the social model at age 85 (OR, 1.5, 95% CI, 1.1–2.0), depression was not associated with increased likelihood of hospitalization.ConclusionsDepression at ages 78 and 85 is consistently associated with increased ER visits and should be considered among older people presenting to the ER.