Biomedical subjects

Donald J Bachman

Publications and source records attributed to Donald J Bachman.

6 recordsLinked to original sources

PubMed2006

Social support among women who died of ovarian cancer.

GOALS OF WORK: We investigated the effects of social support in the last 6 months of life for women who died of ovarian cancer. MATERIALS AND METHODS: The study population included women enrolled in one of three Managed Care Organizations who died of ovarian cancer (1995-2000). Information was collected on demographics, living environment, presence of escorts to oncology encounters, comorbidities, medications, outpatient and inpatient encounters, and referrals to home health and hospice. Two characteristics of social support were examined: living with others and being escorted to one or more oncology visits. RESULTS: Of 421 subjects, both aspects of social support were known for 345 (82%). Of these, 227 (66%) lived with others and were escorted, 33 (10%) lived with others but were never escorted, 59 (17%) lived alone but were escorted, and 26 (8%) lived alone and never were accompanied. Women living alone were less likely to be taking a psychotropic medication (57% vs 70%, p = 0.021) and were somewhat less likely to receive hospice referral (42% vs 53%, p = 0.054). Women who were never escorted had fewer outpatient encounters (12.60 vs 15.77, p = 0.033) and were less likely to be referred to home health (18% vs 30%, p = 0.046). CONCLUSIONS: This study indicates that social support has some beneficial effects on receipt of personal health services. Friends and family may act as proponents for the patient in obtaining services. Health care professionals should be encouraged to assess the cancer patient's social situation and identify areas where help may be needed.

Aged↗

PubMed2005

Building a virtual cancer research organization.

BACKGROUND: The Cancer Research Network (CRN) comprises the National Cancer Institute and 11 nonprofit research centers affiliated with integrated health care delivery systems. The CRN, a public/private partnership, fosters multisite collaborative research on cancer prevention, screening, treatment, survival, and palliation in diverse populations. METHODS: The CRN's success hinges on producing innovative cancer research that likely would not have been developed by scientists working individually, and then translating those findings into clinical practice within multiple population laboratories. The CRN is a collaborative virtual research organization characterized by user-defined sharing among scientists and health care providers of data files as well as direct access to researchers, computers, software, data, research participants, and other resources. The CRN's research management Web site fosters a high-functioning virtual scientific community by publishing standardized data definitions, file specifications, and computer programs to support merging and analyzing data from multiple health care systems. RESULTS: Seven major types of standardized data files developed to date include demographics, health plan eligibility, tumor registry, inpatient and ambulatory utilization, medication dispensing, laboratory tests, and imaging procedures; more will follow. Data standardization avoids rework, increases multisite data integrity, increases data security, generates shorter times from initial proposal concept to submission, and stimulates more frequent collaborations among scientists across multiple institutions. CONCLUSIONS: The CRN research management Web site and associated standardized data files and procedures represent a quasi-public resource, and the CRN stands ready to collaborate with researchers from outside institutions in developing and conducting innovative public domain research.

Biomedical Research↗

PubMed2005

Disparities and survival among breast cancer patients.

BACKGROUND: Although rates of survival for women with breast cancer have improved, the survival disparity between African American and white women in the United States has increased. PURPOSE: To determine whether this survival disparity persists in an insured population with access to medical care. METHODS: In this retrospective cohort study, we extracted data from the tumor registries of six nonprofit, integrated health care delivery systems affiliated with the Cancer Research Network and assessed the survival of African American (n = 2276) and white (n = 18 879) female enrollees who were diagnosed with invasive breast cancer from January 1, 1993, through December 31, 1998. Cox proportional hazards regression was used to estimate the death rate among African American women relative to that of white women after adjustment for potential explanatory factors including stage at diagnosis, tumor characteristics, and treatment. RESULTS: Five-year survival was lower for African American women (73.8%) than for white women (81.6%). African American women were less likely to have tumor characteristics with good prognosis. Controlling for age at diagnosis, stage, grade, tumor size, and estrogen and progesterone receptor status, the adjusted hazard rate ratio for African American women was 1.34 (95% confidence interval = 1.22 to 1.46). Similar risks were found among women ages 20-49 and 50 and older. Controlling for treatment slightly lowered the hazard rate ratio to 1.31 (95% confidence interval = 1.20 to 1.43). CONCLUSIONS: Among women with invasive breast cancer, being insured and having access to medical care does not eliminate the survival disparity for African American women.

Adult↗

PubMed2003

Risk adjustment using automated ambulatory pharmacy data: the RxRisk model.

OBJECTIVES: Develop and estimate the RxRisk model, a risk assessment instrument that uses automated ambulatory pharmacy data to identify chronic conditions and predict future health care cost. The RxRisk model's performance in predicting cost is compared with a demographic-only model, the Ambulatory Clinical Groups (ACG), and Hierarchical Coexisting Conditions (HCC) ICD-9-CM diagnosis-based risk assessment instruments. Each model's power to forecast health care resource use is assessed. DATA SOURCES: Health services utilization and cost data for approximately 1.5 million individuals enrolled in five mixed-model Health Maintenance Organizations (HMOs) from different regions in the United States. STUDY DESIGN: Retrospective cohort study using automated managed care data. SUBJECTS All persons enrolled during 1995 and 1996 in Group Health Cooperative of Puget Sound, HealthPartners of Minnesota and the Colorado, Ohio and Northeast Regions of Kaiser-Permanente. MEASURES RxRisk, an algorithm that classifies prescription drug fills into chronic disease classes for adults and children. RESULTS: HCCs produce the most accurate forecasts of total costs than either RxRisk or ACGs but RxRisk performs similarly to ACGs. Using the R(2) criteria HCCs explain 15.4% of the prospective variance in cost, whereas RxRisk explains 8.7% and ACGs explain 10.2%. However, for key segments of the cost distribution the differences in forecasting power among HCCs, RxRisk, and ACGs are less obvious, with all three models generating similar predictions for the middle 60% of the cost distribution. CONCLUSIONS: HCCs produce more accurate forecasts of total cost, but the pharmacy-based RxRisk is an alternative risk assessment instrument to several diagnostic based models and depending on the nature of the application may be a more appropriate option for medical risk analysis.

Adolescent↗

PubMed2003

Using risk-adjustment models to identify high-cost risks.

BACKGROUND: We examine the ability of various publicly available risk models to identify high-cost individuals and enrollee groups using multi-HMO administrative data. METHODS: Five risk-adjustment models (the Global Risk-Adjustment Model [GRAM], Diagnostic Cost Groups [DCGs], Adjusted Clinical Groups [ACGs], RxRisk, and Prior-expense) were estimated on a multi-HMO administrative data set of 1.5 million individual-level observations for 1995-1996. Models produced distributions of individual-level annual expense forecasts for comparison to actual values. Prespecified "high-cost" thresholds were set within each distribution. The area under the receiver operating characteristic curve (AUC) for "high-cost" prevalences of 1% and 0.5% was calculated, as was the proportion of "high-cost" dollars correctly identified. Results are based on a separate 106,000-observation validation dataset. MAIN RESULTS: For "high-cost" prevalence targets of 1% and 0.5%, ACGs, DCGs, GRAM, and Prior-expense are very comparable in overall discrimination (AUCs, 0.83-0.86). Given a 0.5% prevalence target and a 0.5% prediction threshold, DCGs, GRAM, and Prior-expense captured $963,000 (approximately 3%) more "high-cost" sample dollars than other models. DCGs captured the most "high-cost" dollars among enrollees with asthma, diabetes, and depression; predictive performance among demographic groups (Medicaid members, members over 64, and children under 13) varied across models. CONCLUSIONS: Risk models can efficiently identify enrollees who are likely to generate future high costs and who could benefit from case management. The dollar value of improved prediction performance of the most accurate risk models should be meaningful to decision-makers and encourage their broader use for identifying high costs.

Adolescent↗

PubMed2002

Issues in pooling administrative data for economic evaluation.

Managed care, in particular the health maintenance organization (HMO), now dominates US healthcare delivery, and economic evaluation is receiving increasing attention as a management tool that can be tailored to its perceived business needs. This encourages use of HMO administrative data as an efficient source of resource utilization and cost measures. Use of administrative data coincides with growing research interest in multisite analyses that increase external validity. The best alternative to a nationally representative data set is to pool administrative data from multiple sites within one database. However, pooling administrative data is problematic because HMO data sources reflect differences in systems of care, costing, and coding. This paper describes issues inherent in the pooling of HMO administrative cost data for use in multisite economic evaluations. We describe the attributes of administrative data that are relevant to costing and discuss their implications for multisite economic evaluations. We then briefly describe our experience with pooling multisite cost data, discuss lessons learned, and offer suggestions for researchers working with such data, followed by concluding comments. Multisite administrative data provide unique opportunities to conduct population-based clinical and economic research.

Community Health Planning↗