Analysis of Injury- and Violence-Related Fatalities in the Ohio Medicaid Population: Identifying Opportunities for Prevention

SUMMARY Objective To assess long-term direct medical costs, health care utilization, and mortality following resective surgery in persons with uncontrolled epilepsy. Methods Retrospective longitudinal cohort study of Medicaid beneficiaries with epilepsy from 2000 - 2008. The study population included 7,835 persons with uncontrolled focal epilepsy age 18 to 64 years, with an average follow-up time of 5 years. Of these, 135 received surgery during the study period. To account for selection bias, we used risk-set optimal pairwise matching on a time-varying propensity score, and inverse probability of treatment weighting. Repeated measures generalized linear models were used to model utilization and cost outcomes. Cox proportional hazard was used to model survival. Results The mean direct medical cost difference between the surgical group and control group was $6,806 after risk-set matching. The incidence rate ratio of inpatient, emergency room, and outpatient utilization was lower among the surgical group in both unadjusted and adjusted analyses. There was no significant difference in mortality after adjustment. Among surgical cases, mean annual costs per subject were on average $6,484 lower, and all utilization measures were lower after surgery compared to before. Significance Subjects that underwent epilepsy surgery had lower direct medical care costs and health care utilization. These findings support that epilepsy surgery yield substantial health care cost savings.

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“…This algorithm uses a combination of social security number, first and last name, date of birth, and gender. 6…”

Section: Study Design and Data Sourcementioning

confidence: 99%

Long‐term reduction of health care costs and utilization after epilepsy surgery

et al. 2015

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“…Linkage of the 3 data sets was performed using a deterministic, multi-step process based on personal identifiers, including Social Security number (SSN), name, date of birth, and sex, consistent with other studies. [20][21][22] Successful identification of a decedent in the death certificates and the MACSIS and/or the PCS files implied that the decedent had been a recipient of Ohio's publicly funded mental health system, therefore an individual with mental illness.…”

Section: Data Sourcesmentioning

confidence: 99%

Analyzing excess mortality from cancer among individuals with mental illness

Musuuza

Sherman

Knudsen

et al. 2013

Cancer

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Objective To compare patterns of site-specific cancer mortality in a population of individuals with and without mental illness. Methods This was a cross-sectional, population-based study using a linked dataset comprised of death certificate data for the state of Ohio for the years 2004–2007 and data from the publicly funded mental health system in Ohio. Decedents with mental illness were those identified concomitantly in both data sets. We used age-adjusted standardized mortality ratios (SMRs) in race- and sex-specific person-year strata to estimate excess deaths for each of the anatomic cancer sites. Results Overall, there was excess mortality from cancer associated with having mental illness in all of the race/sex strata: SMR: 2.16, (95% Confidence Interval: 1.85–2.50) for Black men; 2.63 (2.31–2.98) for Black women; 3.89 (3.61–4.19) for non-Black men, and 3.34 (3.13–3.57) for non-Black women. In all of the race/sex strata except for Black women, the highest SMR was observed for laryngeal cancer 3.94 (1.45–8.75) in Black men; 6.51 (3.86–10.35) and 6.87 (3.01–13.60) in non-Black men and women, respectively). The next highest SMRs were noted for hepatobiliary cancer and that of the urinary tract in all race/sex strata, except for Black men. Conclusions Compared to the general population in Ohio, individuals with mental illness experienced excess mortality from most cancers, possibly explained by a higher prevalence of smoking, substance abuse, and chronic hepatitis B or C infections in individuals with mental illness. Excess mortality could also reflect late-stage diagnosis and receipt of inadequate treatment.

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“…In this age group, firearm-related homicide rates are nearly twice for African-Americans than what they are for Whites (2,277 per 100,000 for AfricanAmericans vs 1,255 per 100,000 for Whites) (8,9). A strong positive association also exists between socioeconomic status and violent injury, with one study finding that the Medicaid population bears a disproportionate burden of injuries and violence-related fatalities (10). Violent injury also varies by geography.…”

Section: Epidemiology Overviewmentioning

confidence: 87%