BACKGROUND: Disparities in hospitalization rates, particularly rates for avoidable hospitalizations, are indicators of potentially unmet health needs and inefficient use of health resources. Hospitalization rates that the Indian Health Service (IHS) can report underestimate disparities for American Indians (AIs) and Alaska Natives (ANs) relative to other Americans, because the IHS cannot track all hospitalizations of AIs/ANs in their user population. OBJECTIVES: To compare hospitalization and avoidable hospitalization rates for a rural AI/AN user population with those of non-Indians living in the same counties where both groups use the same hospital system, regardless of the expected source of payment. RESEARCH DESIGN: Retrospective analysis of California hospital discharge data for 1996 linked to rural IHS user data for 1995 and 1996 (3920 hospitalizations) compared with a random sample of discharge data for the rest of the non-Indian population in the 37 counties of the IHS Contract Health Service delivery area (7840 hospitalizations). MEASURES: Hospitalization and avoidable hospitalization rates and risk ratios (RRs). RESULTS: Hospitalization and avoidable hospitalization rates were both higher for the AI/AN user population than for the non-Indian general population. The age-adjusted hospitalization ratios were 72% higher for men (RR 1.72, confidence interval [CI] 1.40-2.12) and 52% higher for women (RR 1.52, CI 1.36-1.92). The comparable ratios for avoidable hospitalizations were 136% higher for men (RR 2.36, CI 1.52-3.29) and 106% higher for women (RR 2.06, CI 1.32-3.50). CONCLUSIONS: Disparities in both hospitalization and avoidable hospitalization rates of rural AIs/ANs in California were previously undetected by either federal IHS or state hospital discharge data alone. At least some of the disparities are likely reducible with improved access to care.
BACKGROUND: Disparities in hospitalization rates, particularly rates for avoidable hospitalizations, are indicators of potentially unmet health needs and inefficient use of health resources. Hospitalization rates that the Indian Health Service (IHS) can report underestimate disparities for American Indians (AIs) and Alaska Natives (ANs) relative to other Americans, because the IHS cannot track all hospitalizations of AIs/ANs in their user population. OBJECTIVES: To compare hospitalization and avoidable hospitalization rates for a rural AI/AN user population with those of non-Indians living in the same counties where both groups use the same hospital system, regardless of the expected source of payment. RESEARCH DESIGN: Retrospective analysis of California hospital discharge data for 1996 linked to rural IHS user data for 1995 and 1996 (3920 hospitalizations) compared with a random sample of discharge data for the rest of the non-Indian population in the 37 counties of the IHS Contract Health Service delivery area (7840 hospitalizations). MEASURES: Hospitalization and avoidable hospitalization rates and risk ratios (RRs). RESULTS: Hospitalization and avoidable hospitalization rates were both higher for the AI/AN user population than for the non-Indian general population. The age-adjusted hospitalization ratios were 72% higher for men (RR 1.72, confidence interval [CI] 1.40-2.12) and 52% higher for women (RR 1.52, CI 1.36-1.92). The comparable ratios for avoidable hospitalizations were 136% higher for men (RR 2.36, CI 1.52-3.29) and 106% higher for women (RR 2.06, CI 1.32-3.50). CONCLUSIONS: Disparities in both hospitalization and avoidable hospitalization rates of rural AIs/ANs in California were previously undetected by either federal IHS or state hospital discharge data alone. At least some of the disparities are likely reducible with improved access to care.
Authors: Kristyn M Bigback; Megan Hoopes; Jenine Dankovchik; Elizabeth Knaster; Victoria Warren-Mears; Sujata Joshi; Thomas Weiser Journal: Health Serv Res Date: 2015-07-01 Impact factor: 3.402
Authors: Vatsal Chikani; Maureen Brophy; Anne Vossbrink; Robyn N Blust; Mary Benkert; Chris Salvino; Conrad Diven; Rogelio Martinez Journal: Public Health Rep Date: 2016-08-22 Impact factor: 2.792