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Biomedical subjects

Ann M Holmes

Publications and source records attributed to Ann M Holmes.

7 recordsLinked to original sources
PubMed2006

The Indiana Chronic Disease Management Program.

The Indiana Chronic Disease Management Program (ICDMP) is intended to improve the quality and cost-effectiveness of care for Medicaid members with congestive heart failure (chronic heart failure), diabetes, asthma, and other conditions. The ICDMP is being assembled by Indiana Medicaid primarily from state and local resources and has seven components: (1) identification of eligible participants to create regional registries, (2) risk stratification of eligible participants, (3) nurse care management for high-risk participants, (4) telephonic intervention for all participants, (5) an Internet-based information system, (6) quality improvement collaboratives for primary care practices, and (7) program evaluation. The evaluation involves a randomized controlled trial in two inner-city group practices, as well as a statewide observational design. This article describes the ICDMP, highlights challenges, and discusses approaches to its evaluation.

Chronic Disease↗
PubMed2005

Indiana chronic disease management program risk stratification analysis.

OBJECTIVE: The objective of this study was to compare the ability of risk stratification models derived from administrative data to classify groups of patients for enrollment in a tailored chronic disease management program. SUBJECTS: This study included 19,548 Medicaid patients with chronic heart failure or diabetes in the Indiana Medicaid data warehouse during 2001 and 2002. MEASURES: To predict costs (total claims paid) in FY 2002, we considered candidate predictor variables available in FY 2001, including patient characteristics, the number and type of prescription medications, laboratory tests, pharmacy charges, and utilization of primary, specialty, inpatient, emergency department, nursing home, and home health care. METHODS: We built prospective models to identify patients with different levels of expenditure. Model fit was assessed using R statistics, whereas discrimination was assessed using the weighted kappa statistic, predictive ratios, and the area under the receiver operating characteristic curve. RESULTS: We found a simple least-squares regression model in which logged total charges in FY 2002 were regressed on the log of total charges in FY 2001, the number of prescriptions filled in FY 2001, and the FY 2001 eligibility category, performed as well as more complex models. This simple 3-parameter model had an R of 0.30 and, in terms in classification efficiency, had a sensitivity of 0.57, a specificity of 0.90, an area under the receiver operator curve of 0.80, and a weighted kappa statistic of 0.51. CONCLUSION: This simple model based on readily available administrative data stratified Medicaid members according to predicted future utilization as well as more complicated models.

Adult↗
PubMed2004

Adjusting for patient characteristics and selection effects in assessment of community mental health centers.

OBJECTIVE: The objective of this study was to determine the effect of patient socioeconomic characteristics and center selection of patients on measured performance of community mental health centers. DATA SOURCE/STUDY SETTING: Data were taken from the administrative records of Indiana's public mental health system for 16,516 adults with severe, persistent mental illness treated in 30 community mental health centers. Center performance was compared using longitudinal information on patient functioning. METHODS: A mixed random-effects model that is suitable for fitting data with a hierarchical structure was used to assess relative performance. PRINCIPAL FINDINGS: Measured performance was found to depend significantly on patient education, income, marital status, race, ethnicity, and baseline health (P<0.05). Results also indicated centers that were more successful at maintaining patients in treatment were unfairly underranked by unadjusted performance scores. CONCLUSIONS: Both the socioeconomic background of patients and patient selection by centers impact apparent performance in community mental health care. If observational data are used to evaluate community-based providers, analysts might need to account for both effects to ensure comparisons of relative performance are accurate.

Adult↗
PubMed2004

Performance assessment in community mental health care and at-risk populations.

We examine whether community mental health care centers (CMHCs) differ in their ability to serve at-risk populations, including clients with dual diagnoses for substance abuse, comorbid disabilities, and particularly severe functional impairment. Our analysis uses data from Indiana's public mental health system. Although at-risk clients experience, on average, worse outcomes than other clients, we find that some CMHCs achieve statistically significantly better outcomes than others. Although this information is useful to consumers and providers who wish to identify the most effective providers and treatment models for at-risk clients, it is not generated in standard performance assessments.

Community Mental Health Centers↗
PubMed2003

The effect of chronic illness on the psychological health of family members.

BACKGROUND: Chronic illness in a family member can cause emotional distress throughout the family, and may impair the family's ability to support the patient. OBJECTIVES: We compare the familial impact of mental illness to other common chronic conditions. We examine the impact of a person's chronic illness on the psychological health of all persons in his or her family and identify both individual and family-level risk factors associated with psychological spillovers. METHODS: Our analysis is based on data from the 1996 Medical Expenditure Panel Survey (MEPS) that, because of its sample design, can be used to model both individual and family health status. Psychological distress is measured using responses to the general mental health question for each family member. The chronic conditions considered include cancer, diabetes, stroke-related disorders, arthritis, asthma, and mental illness (including dementia). We estimate the relationships of interest using a semi-parametric method, the discrete random effects probit model. RESULTS: Brain-related conditions, including mental illness, impose the most significant risk to the psychological well-being of family members. The effects of the other chronic conditions studied, while not as significant, are notable in that their negative impacts on the psychological health of family members are sometimes larger than their direct psychological impacts on the patient. Economic distress not only directly increases the chance that an individual will experience emotional distress, but it appears it also reduces the family's ability as a whole to cope psychologically with chronic illness. DISCUSSION: Our analysis suffers from problems common to all cross-sectional designs, although the impact of selection bias appeared to be small in sensitivity analysis. While health conditions were based on unverified self-reports, condition categories were broadly defined to reduce the required precision of such reports. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE: Because psychological distress is fairly contagious in families confronted with chronic illness, effective treatment strategies may need to be targeted to all members of the primary patient's family. Providers should be particularly vigilant for intra-family effects when their patients come from families that lack the financial resources that might protect against the stress of caring for a family member with a chronic illness. IMPLICATIONS FOR HEALTH POLICIES: Results suggest that, of the chronic conditions considered, priority for respite care and supportive services should be given to families in which a member has a brain-related disorder, particularly in families with limited financial resources and inadequate insurance coverage. IMPLICATIONS FOR FURTHER RESEARCH: The use of the discrete random effects probit model identified important interpersonal health effects that could not have been detected with standard analytical methods. The potential clinical relevance of the resulting findings underlies the need for additional data collection efforts that, like the MEPS, consider individuals in a family context.

Chronic Disease↗
PubMedDate not supplied

Telephonic case-finding of major depression in a Medicaid chronic disease management program for diabetes and heart failure.

OBJECTIVE: Major depression is common in low-income and chronically ill persons and is a barrier for effective chronic disease care. We evaluated a Medicaid-sponsored strategy for detecting depressive symptoms in adults with diabetes or congestive heart failure. METHODS: Using a two-item screening tool, 890 adults enrolled in the Indiana Chronic Disease Management Program were assessed by telephone for depressive symptoms between December 2003 and March 2004. A subset of 386 participants also completed the eight-item Patient Health Questionnaire (PHQ-8) depression measure. Antidepressant use was examined using pharmacy claims. RESULTS: Depressed mood or anhedonia was reported by 51% of participants. About one in four participants had a PHQ-8 score indicating a high risk for major depression (score >or=10). The two-item screen was 96% sensitive [95% confidence interval (CI), 89-99%] and 60% specific (95% CI, 54-65%) for identifying members at high risk for depression by the full PHQ-8 instrument. Only half of participants with high-risk PHQ-8 scores had a pharmacy claim indicating that an antidepressant medication was filled within 120 days of the depression screening. CONCLUSIONS: A two-stage, telephonic approach involving the PHQ-8 instrument for Medicaid members with either depressed mood or anhedonia could identify two clinically depressed persons for every nine members screened.

Antidepressive Agents↗