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The article presents a study aimed at developing and validating a model for predicting all-case re-hospitalization within one year of discharge and evaluating the predictive model performance by using key metrics. It concludes that the risk prediction model developed in the study can help health care providers target interventions to prevent unneeded hospital readmissions.

Abstract: Objectives: This study investigates whether administration data from universal health insurance can yield new insight from an old intervention. Specifically, did a guaranteed annual income experiment from the 1970s, designed to investigate labor market outcomes, reduce hospitalization rates? Method: The study re-examined the saturation site of a guaranteed annual income experiment in Dauphin, Manitoba (CANADA) conducted between 1974 and 1979 (MINCOME). We used health administration data generated by the universal government health insurance plan to identify subjects (approximately 12,500 residents of Dauphin and its rural municipality). We used propensity-score matching to select 3 controls for each subject from this database, matched on geography of residence, age, sex, family size and type. Outcome measures were hospital separations and physician claims. Results: Hospital separations declined 8.5% among subjects relative to controls during the experimental period. Accident and injury codes and mental health codes were most responsible for the decline. Conclusions: Even though MINCOME was designed to measure the impact of a GAI on the number of hours worked, one can re-visit old experiments with new data to determine the health impact of population interventions designed for other purposes. We determined that hospitalization rates declined significantly after the introduction of a guaranteed income. [Copyright &y& Elsevier]

This paper has two purposes. First, it documents the historical context of MINCOME, a Canadian guaranteed annual income field experiment (1974 to 1979). Second, it uses routinely collected health administration data and a quasi-experimental design to document an 8.5 percent reduction in the hospitalization rate for participants relative to controls, particularly for accidents and injuries and mental health. We also found that participant contacts with physicians declined, especially for mental health, and that more adolescents continued into grade 12. We found no increase in fertility, family dissolution rates, or improved birth outcomes. We conclude that a relatively modest GAI can improve population health, suggesting significant health system savings. [ABSTRACT FROM AUTHOR]

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Abstract: The objective of this study was to document the relationship between First Nation’s community characteristics and the rates of hospitalization for Ambulatory Care Sensitive Conditions (ACSC) in the province of Manitoba, Canada. A population-based time trend analysis of selected ACSC was conducted using the de-identified administrative data housed at the Manitoba Centre for Health Policy, including vital statistics and health information. The study population included all Manitoba residents eligible under the universal Manitoba Health Services Insurance Plan and living on First Nation reserves between 1984/85 and 2004/05. Twenty-nine ACSC defined using 3, 4 and 5 digit ICD-9-CM and ICD-10-CM codes permitted cross-sectional and longitudinal comparison of hospitalization rates. The analysis used Generalized Estimated Equation (GEE) modeling. Two variables were significant in our model: level of access to primary health care on-reserve; and level of local autonomy. Communities with local access to a broader complement of primary health care services showed a lower rate of hospitalization for ACSC. We also examined whether there was a significant trend in the rates of hospitalization for ACSC over time following the signature of an agreement increasing local autonomy over resource allocation. We found the rates of hospitalization for ACSC decreased with each year following the signature of such an agreement. This article demonstrates that communities with better local access to primary health care consistently show lower rates of ACSC. Secondly, the longer community health services have been under community control, the lower its ACSC rate. [ABSTRACT FROM AUTHOR]

Background: Medical Savings Accounts are an attempt to reduce health care costs by transferring responsibility for expenditures to patients, while providing them with state-supported base amounts to cover some of the costs. We wondered whether such a system would actually be effective, given the fact that medical care expenditures (and illness) are unequally distributed across the population., Methods: We used the Manitoba Population Health Research Data Respository to assess costs incurred by individual residents of Manitoba for all physician visits and admissions to hospital between 1997 and 1999, and we calculated an average expenditure per person per year over the 3 years., Results: During fiscal years 1997-1999, physician and hospital costs that could be attributed to individual Manitoba residents averaged $730 each year. Most users accounted for very little expenditure. About 40% of the entire population of Manitoba used less than $100 each, and 80% used less than $600. The highest-using 1% of the Manitoba population accounted for 26% of all spending on hospital and physician care, whereas the lowest-using 50% accounted for 4%. When examined by age category, the results were similar. Even in the highest age category, most of the population falls into the low-usage category. If the entitlement under a Medical Savings Account scheme was set at the current average cost of $730 per year, then total spending by government on health care for this healthy group would increase (by $505 million) rather than decrease. If the "catastrophic threshold," above which the insurer would pay costs, was set at $1,000 per year, then the sickest 20% of Manitoba residents would become personally responsible for just over $60 million of current health care costs. The net result is a 54% increase in spending on hospital and physician costs that can be allocated to individuals., Interpretation: Medical Savings Accounts will not save money but will instead, under most formulations, lead to an increase in spending on the healthiest members of the population.