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2.
J Am Coll Emerg Physicians Open ; 5(3): e13168, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38699223

ABSTRACT

Objectives: This study aimed to assess the effectiveness of a continuous quality improvement initiative at the University of Florida Health Physicians practice in reducing the time to administer factor replacement therapy (FRT) for hemophilia patients presenting with bleeding in the emergency department (ED). Methods: The study, a quasi-experimental, interventional design, was conducted between January 2020 and January 2023. The intervention, implemented in September 2021, involved training ED physicians, creating a specialized medication order set within the electronic health record (EHR), and a rapid triage system. The effectiveness was measured by comparing the time from ED arrival to factor administration before and after the intervention and benchmarking it against the National Bleeding Disorders Foundation's Medical and Scientific Advisory Council (MASAC)-recommended 1-hour timeline for factor administration. An interrupted time series (ITS) analysis with a generalized least squares model assessed the intervention's impact. Results: A total of 43 ED visits (22 pre-intervention and 21 post-intervention) were recorded. Post-intervention, the average time from ED arrival to factor administration decreased from 5.63 to 3.15 hours. There was no significant increase (27% vs. 29%) in the patients receiving factor within 1-hour of ED arrival. The ITS analysis predicted a 20-hour reduction in the average quarterly time to administer factor by the end of the study, an 84% decrease. Conclusions: The quality improvement program decreased the time to administer FRT for patients with hemophilia in the ED. However, the majority of patients did not achieve the 1-hour MASAC-recommended timeline for factor administration after ED arrival.

3.
Diabetes Care ; 40(2): 239-245, 2017 Feb.
Article in English | MEDLINE | ID: mdl-27956384

ABSTRACT

OBJECTIVE: To contrast the effect of private insurance and deductibles (by size) on medical service use, health status, and medical debt for adult respondents with diabetes with low and high incomes. RESEARCH DESIGN AND METHODS: Using the 2011-2013 Medical Expenditure Panel Survey, bivariate and regression analyses were conducted to compare demographic characteristics, medical service use, diabetes care, and health status among privately insured adult respondents with diabetes, aged 18-64 years (N = 1,461) by lower (<200% of the federal poverty level) and higher (≥200% of the federal poverty level) income and deductible vs. no deductible (ND), low deductible ($1,000/$2,400) (LD), and high deductible (>$1,000/$2,400) (HD). The National Health Interview Survey 2012-2014 was used to analyze differences in medical debt and delayed/avoided needed care among adult respondents with diabetes (n = 4,058) by income. RESULTS: Compared with privately insured respondents with diabetes with ND, privately insured lower-income respondents with diabetes with an LD report significant decreases in service use for primary care, checkups, and specialty visits (27%, 39%, and 77% lower, respectively), and respondents with an HD decrease use by 42%, 65%, and 86%, respectively. Higher-income respondents with an LD report significant decreases in specialty (28%) and emergency department (37%) visits. Diabetes care measures are similar by income and insurance; there were no changes in physical health status. Medical debt is similar by income, but deferred service use is two times greater for those indebted and with lower income. CONCLUSIONS: Private insurance with a deductible substantially and problematically reduces medical service use for lower-income insured respondents with diabetes who have an HD; these patients are more likely to report forgoing needed medical services.


Subject(s)
Deductibles and Coinsurance/economics , Diabetes Mellitus/economics , Socioeconomic Factors , Adolescent , Adult , Emergency Service, Hospital/statistics & numerical data , Family Characteristics , Female , Health Expenditures , Humans , Income , Insurance, Health/economics , Logistic Models , Male , Middle Aged , Young Adult
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