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Identification of factors associated with hospital readmission and development of a predictive model.

Multiple hospital admissions, especially those related to the chronically ill, represent a particular challenge to both the acute and long-term care sectors to identify effective methods of resource management. This study analyzes the multiple admission patterns associated with a cohort of 4,219 adult medical-surgical patients discharged alive from a community teaching hospital in Michigan. The sample was divided into two groups: 3,818 patients who survived and 392 who expired during the one-year follow-up period. For the surviving subsample, the characteristics found to be directly associated with the likelihood of readmission included increased age, advanced stage of disease, greater index-episode length of stay, discharge by an internist rather than a surgeon, Medicare as expected source of payment, decreased physician age, discharge to a community setting, and increased number of prior hospital episodes. For the subsample who died, only one explanatory variable was significantly associated with an increased likelihood of readmission-discharge to a community setting (with or without home care) rather than a nursing home. The article includes illustrates of the importance of decisions regarding posthospital, long-term care services on the likelihood of rehospitalization.

Adult↗

[Adopting the method of correlation coefficient to improve the accuracy of the xylene isomer's prediction model].

This paper focuses on the detailed researches on the correlation coefficient in near infrared spectrum and points out its characteristics in multi-component solution; the paper also proves the principle of obtaining more accurate results when using high correlation coefficient for model building, and presents a practical experiment to test the conclusions by using para-xylene, meta-xylene, and orthoxylene's mixture.

Algorithms↗

Longitudinal model predicting mutual partner violence among White, Black, and Hispanic couples in the United States general population.

This analysis determines the longitudinal predictors of male-to-female (MFPV) or female-to-male (FMPV) alone and mutual partner violence (MPV) among White, Black, and Hispanic couples. A national sample of couples 18 years of age or older was interviewed in 1995 and again in 2000. Participants constitute a multistage area probability sample representative of married and cohabiting couples from the 48 contiguous United States. Results indicate that most couples reporting violence engage in MPV. After controlling for other factors, Blacks are 3 times more likely to report MPV at follow-up and Hispanics are 9 times more likely to report MFPV. The results indicate that ethnic minorities are at greater risk of MPV. In addition, the predictors of partner violence vary depending on the type of partner violence. These findings highlight the importance of distinguishing different types of partner violence and have important epidemiological and prevention implications.

Adult↗

Predictive modeling plus intensive case management deliver solid results for Medicaid plan.

That's what happened to AmeriHealth Mercy, a Medicaid health plan based in Harrisburg, PA. And it resulted in skyrocketing costs and runaway utilization. However, the health plan devised a comprehensive approach to managing the population that has worked so well that developers are now interested in sharing the approach with other Medicaid health plans.

Case Management↗