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2.
J Hosp Med ; 7(2): 124-30, 2012 Feb.
Article in English | MEDLINE | ID: mdl-22086871

ABSTRACT

BACKGROUND: Studies suggest that the inpatient to outpatient transition of care is a vulnerable period for patients, and socioeconomically disadvantaged populations may be particularly susceptible. OBJECTIVE: In this prospective cohort study, clustered by hospital, we sought to determine the feasibility and utility of a simple, post-discharge intervention in reducing hospital readmissions. METHODS: Chronically ill Medicaid managed care members were consecutively identified from the discharge records of 10 area hospitals. For patients from the 7 intervention hospitals, trained medical assistants performed a brief telephone needs assessment, within 1 week of discharge, in which issues requiring near-term resolution were identified and addressed. Patients with more complicated care needs were identified according to a 4-domain care needs framework and enrolled in more intensive care management. Patients discharged from the 3 control hospitals received usual care. We used a generalized estimating equation model, which adjusts for clustering by hospital, to evaluate the primary outcome of hospital readmission within 60 days. RESULTS: There were 97 intervention and 130 control patients. Intervention patients were slightly younger and had higher adjusted clinical group (ACG) scores. In unadjusted analysis, the intervention group had lower, but statistically similar, 60-day rehospitalization rates (23.7% vs 29.2%, P = 0.35). This difference became significant after controlling for ACG score, prior inpatient utilization, and age: adjusted odds ratio (OR) [95% confidence interval (CI)] 0.49 [0.24-1.00]. CONCLUSIONS: A simple post-discharge intervention and needs assessment may be associated with reduced recurrent hospitalization rates in a cohort of chronically ill Medicaid managed care patients with diverse care needs.


Subject(s)
Chronic Disease/therapy , Patient Discharge/statistics & numerical data , Patient Readmission/statistics & numerical data , Vulnerable Populations , Female , Humans , Male , Managed Care Programs , Middle Aged , Prospective Studies
3.
Care Manag J ; 9(2): 42-50, 2008.
Article in English | MEDLINE | ID: mdl-18619084

ABSTRACT

CareOregon, an Oregon-based not-for-profit Medicaid health plan, successfully piloted a "CareSupport" model that identifies high-risk members and clinically stratifies them for intervention. Internal analyses indicate that CareSupport lowers utilization and cost; CareOregon, however, has lacked patient-reported outcome data on the health-related quality of life (HRQL) of CareSupport participants. Between September 2005 and November 2006, we conducted a pilot study in which the Health Utilities Index Mark 3 (HUI3), a generic preference-based measure of health status and HRQL, was integrated into CareOregon's existing screening algorithm for possible admission into CareSupport. We obtained baseline data on 616 CareSupport candidates and 4-month HUI3 follow-up data on 143 candidates (104 CareSupport 39 non-CareSupport). On a 0.00 (dead)-to-1.00 (perfect health) scale, the mean overall baseline HUI3 score for CareSupport patients was 0.18 (0.20 for non-CareSupport patients), comparable to baseline means reported elsewhere for much older patients immediately after suffering serious acute medical events, such as stroke or hip fracture. A 0.05 mean 4-month improvement in overall HRQL among CareSupport enrollees relative to non-CareSupport enrollees was clinically important but not statistically significant. A 0.10 improvement in HUI3 emotion was both statistically significant and clinically important. Study results provide good preliminary evidence of the value of patient-reported outcomes in clarifying individual illness burden and assessing intervention effectiveness.


Subject(s)
Health Status , Medicaid , Quality of Life/psychology , Adult , Aged , Aged, 80 and over , Data Collection , Female , Health Status Indicators , Humans , Male , Middle Aged , Oregon , Pilot Projects , Surveys and Questionnaires , Time Factors , United States
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