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Berlin Brandenburg

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  • 1
    In: Medical Care, 2009, Vol.47(2), pp.154-160
    Description: BACKGROUND:: Disease management programs have grown in popularity over the past decade as a strategy to curb escalating healthcare costs for persons with chronic diseases. OBJECTIVES:: To evaluate the effect of the Indiana Chronic Disease Management Program (ICDMP) on the longitudinal changes in Medicaid claims statewide. RESEARCH DESIGN:: Phased implementation of a chronic disease management program in 3 regions of the state. Fourteen repeated cohorts of Medicaid members were drawn over a period of 3.5 years and the trends in claims were evaluated using a repeated measures model. SUBJECTS:: A total of 44,218 Medicaid members with diabetes and/or congestive heart failure in 3 geographic regions in Indiana. RESULTS:: Across all 3 regions and both disease classes, we found a flattening of cost trends between the pre- and post-ICDMP-initiation periods. This change in the slopes was significant for all of the models except for congestive heart failure in southern Indiana. Thus, the average per member claims paid was increasing at a faster rate before ICDMP but slowed once the program was initiated. To distinguish shorter and longer-term effects related to ICDMP, we estimated annual slopes within the pre- and post-ICDMP- time periods. A similar pattern was found in all regions: claims were increasing before ICDMP, flattened in the years around program initiation, and remained flat in the final year of follow-up. CONCLUSIONS:: This analysis shows that the trend in average total claims changed significantly after the implementation of ICDMP, with a decline in the rate of increase in claims paid observed for targeted Medicaid program populations across the state of Indiana.
    Keywords: Medicine ; Public Health;
    ISSN: 0025-7079
    E-ISSN: 15371948
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  • 2
    In: Medical Care, 1988, Vol.26(7), pp.699-708
    Description: A multifaceted intervention was hypothesized to increase postdischarge ambulatory contacts and to reduce nonelective readmissions. Patients (N=1,001) discharged from the general medicine service were stratified by risk for nonelective readmission and randomized to the control or intervention group. Intervention patients received phone calls from nurses, mailings of appointment reminders and lists of early warning signs, and prompt rescheduling of visit failures. Patients were followed for 6 months, and the results were computed in units per patient per month. The intervention group had 10.4% more total office contacts (0.53 vs 0.48, P=0.005) than the control group. Although the intervention group had 7.6% fewer nonelective readmission days (0.85 vs 0.92), this was not statistically significant (P=0.5). Patients in the intervention group at high risk (N=181) had 28.1% more office visits (0.73 vs 0.57, P〈0.01) and 31.9% fewer nonelective readmission days (1.13 vs 1.66), but this was also not statistically significant (P=0.06). Thus, the intervention significantly increased postdischarge contacts, primarily in high-risk patients, but failed to reduce the incidence of nonelective readmission days significantly.
    Keywords: Aftercare ; Patient Readmission;
    ISSN: 0025-7079
    E-ISSN: 15371948
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  • 3
    In: Medical Care, 1998, Vol.36(5), pp.661-669
    Description: OBJECTIVES.: Each year approximately 100,000 Medicare patients undergo knee replacement surgery. Patients, referring physicians, and surgeons must consider a variety of factors when deciding if knee replacement is indicated. One factor in this decision process is the likelihood of revision knee replacement after the initial surgery. This study determined the chance that a revision knee replacement will occur and which factors were associated with revision. METHODS.: Data on all primary and revision knee replacements that were performed on Medicare patients during the years 1985 through 1990 were obtained. The probability that a revision knee replacement occurred was modeled from data for all patients for whom 2 full years of follow-up data were available. Two strategies for linking revisions to a particular primary knee replacement for each patient were developed. Predictive models were developed for each linking strategy. ICD-9-CM codes were used to determine hospitalizations for primary knee replacement and revision knee replacement. RESULTS.: More than 200,000 hospitalizations for primary knee replacements were performed, with fewer than 3% of them requiring revision within 2 years. The following factors increase the chance of revision within 2 years of primary knee replacement: (1) male gender, (2) younger age, (3) longer length of hospital stay for the primary knee replacement, (4) more diagnoses at the primary knee replacement hospitalization, (5) unspecified arthritis type, (6) surgical complications during the primary knee replacement hospitalization, and (7) primary knee replacement performed at an urban hospital. CONCLUSIONS.: Revision knee replacement is uncommon. Demographic, clinical, and process factors were related to the probability of revision knee replacement.
    Keywords: Medicine ; Public Health;
    ISSN: 0025-7079
    E-ISSN: 15371948
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  • 4
    In: Medical Care, 1986, Vol.24(3), pp.189-199
    Description: Patients who fail to show for scheduled visits or who fail to contact their provider when warning symptoms occur pose important problems for the primary care physician. A group of interventions was examined to determine the effectiveness in increasing the number of prescribed office visits in patients with diabetes mellitus. This group of interventions included mailed packets with information on how to use the clinic, providersʼ names and phone numbers, after-hours phone numbers, a list of early warning signs, and a booklet on managing diabetes mellitus; mailed appointment reminders; and intense followup of visit failures for prompt rescheduling. Eight hundred fifty-nine patients on drug therapy for diabetes mellitus were stratified by risk of hospitalization and randomly assigned within strata to control and intervention groups. The intervention group received all interventions. After 1 year, the intervention group averaged 12% more total contacts than the control group (5.8 vs. 5.2, P = 0.01), due largely to an increase in kept scheduled visits (4.1 vs. 3.6, P = 0.006). These effects were greatest in those patients at higher risk of hospitalization. Also, visit failures were reduced only in high-risk patients. The effect of the interventions did not diminish during the year of study. This systematic and repetitive intervention appears effective in increasing prescribed office visits and is especially effective in patients requiring more frequent care.
    Keywords: Medicine ; Public Health;
    ISSN: 0025-7079
    E-ISSN: 15371948
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