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1.
Vaccine ; 41(3): 750-755, 2023 01 16.
Article En | MEDLINE | ID: mdl-36526502

INTRODUCTION: Public health department (PHD) led COVID-19 vaccination clinics can be a critical component of pandemic response as they facilitate high volume of vaccination. However, few patient-time analyses examining patient throughput at mass vaccination clinics with unique COVID-19 vaccination challenges have been published. METHODS: During April and May of 2021, 521 patients in 23 COVID-19 vaccination sites counties of 6 states were followed to measure the time spent from entry to vaccination. The total time was summarized and tabulated by clinic characteristics. A multivariate linear regression analysis was conducted to evaluate the association between vaccination clinic settings and patient waiting times in the clinic. RESULTS: The average time a patient spent in the clinic from entry to vaccination was 9 min 5 s (range: 02:00-23:39). Longer patient flow times were observed in clinics with higher numbers of doses administered, 6 or fewer vaccinators, walk-in patients accepted, dedicated services for people with disabilities, and drive-through clinics. The multivariate linear regression showed that longer patient waiting times were significantly associated with the number of vaccine doses administered, dedicated services for people with disabilities, the availability of more than one brand of vaccine, and rurality. CONCLUSIONS: Given the standardized procedures outlined by immunization guidelines, reducing the wait time is critical in lowering the patient flow time by relieving the bottleneck effect in the clinic. Our study suggests enhancing the efficiency of PHD-led vaccination clinics by preparing vaccinators to provide vaccines with proper and timely support such as training or delivering necessary supplies and paperwork to the vaccinators. In addition, patient wait time can be spent answering questions about vaccination or reviewing educational materials on other public health services.


COVID-19 , Vaccines , Humans , United States , COVID-19 Vaccines , COVID-19/prevention & control , Vaccination , Mass Vaccination
2.
J Public Health Manag Pract ; 28(6): 624-630, 2022.
Article En | MEDLINE | ID: mdl-36037518

OBJECTIVES: To estimate the costs to implement public health department (PHD)-run COVID-19 vaccination clinics. DESIGN: Retrospectively reported data on COVID-19 vaccination clinic characteristics and resources used during a high-demand day in March 2021. These resources were combined with national average wages, supply costs, and facility costs to estimate the operational cost and start-up cost of clinics. SETTING: Thirty-four PHD-run COVID-19 vaccination clinics across 8 states and 1 metropolitan statistical area. PARTICIPANTS: Clinic managers at 34 PHD-run COVID-19 vaccination clinics. INTERVENTION: Large-scale COVID-19 vaccination clinics were implemented by public health agencies as part of the pandemic response. MAIN OUTCOMES MEASURED: Operational cost per day, operational cost per vaccination, start-up cost per clinic. RESULTS: Median operational cost per day for a clinic was $10 314 (range, $637-$95 163) and median cost per vaccination was $38 (range, $9-$206). There was a large range of operational costs across clinics. Clinics used an average of 99 total staff hours per 100 patients vaccinated. Median start-up cost per clinic was $15 348 (range, $1 409-$165 190). CONCLUSIONS: Results show that clinics require a large range of resources to meet the high throughput needs of the COVID-19 pandemic response. Estimating the costs of PHD-run vaccination clinics for the pandemic response is essential for ensuring that resources are available for clinic success. If clinics are not adequately supported, they may stop functioning, which would slow the pandemic response if no other setting or approach is possible.


COVID-19 Vaccines , COVID-19 , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines/therapeutic use , Humans , Pandemics , Retrospective Studies , United States/epidemiology , Vaccination
3.
Public Health Rep ; 136(4): 441-450, 2021.
Article En | MEDLINE | ID: mdl-33673781

OBJECTIVE: Given the growth in national disability-associated health care expenditures (DAHE) and the changes in health insurance-specific DAHE distribution, updated estimates of state-level DAHE are needed. The objective of this study was to update state-level estimates of DAHE. METHODS: We combined data from the 2013-2015 Medical Expenditure Panel Survey, 2013-2015 Behavioral Risk Factor Surveillance System, and 2014 National Health Expenditure Accounts to calculate state-level DAHE for US adults in total, per adult, and per (adult) person with disability (PWD). We adjusted expenditures to 2017 prices and assessed changes in DAHE from 2003 to 2015. RESULTS: In 2015, DAHE were $868 billion nationally (range, $1.4 billion in Wyoming to $102.8 billion in California) accounting for 36% of total health care expenditures (range, 29%-41%). From 2003 to 2015, total DAHE increased by 65% (range, 35%-125%). In 2015, DAHE per PWD were highest in the District of Columbia ($27 839) and lowest in Alabama ($12 603). From 2003 to 2015, per-PWD DAHE increased by 13% (range, -20% to 61%) and per-capita DAHE increased by 28% (range, 7%-84%). In 2015, Medicare DAHE per PWD ranged from $10 067 in Alaska to $18 768 in New Jersey. Medicaid DAHE per PWD ranged from $9825 in Nevada to $43 365 in the District of Columbia. Nonpublic-health insurer per-PWD DAHE ranged from $7641 in Arkansas to $18 796 in Alaska. CONCLUSION: DAHE are substantial and vary by state. The public sector largely supports the health care costs of people with disabilities. State policy makers and other stakeholders can use these results to inform the development of public health programs that support and provide ongoing health care to people with disabilities.


Disabled Persons/statistics & numerical data , Health Expenditures/statistics & numerical data , State Government , Humans , Medicaid/economics , Medicare/economics , United States
4.
Med Care ; 58(9): 826-832, 2020 09.
Article En | MEDLINE | ID: mdl-32826747

BACKGROUND: In 2003, national disability-associated health care expenditures (DAHE) were $398 billion. Updated estimates will improve our understanding of current DAHE. OBJECTIVE: The objective of this study was to estimate national DAHE for the US adult population and analyze spending by insurance and service categories and to assess changes in spending over the past decade. RESEARCH DESIGN: Data from the 2013-2015 Medical Expenditure Panel Survey were used to estimate DAHE for noninstitutionalized adults. These estimates were reconciled with National Health Expenditure Accounts (NHEA) data and adjusted to 2017 medical prices. Expenditures for institutionalized adults were added from NHEA data. MEASURES: National DAHE in total, by insurance and service categories, and percentage of total expenditures associated with disability. RESULTS: DAHE in 2015 were $868 billion (at 2017 prices), representing 36% of total national health care spending (up from 27% in 2003). DAHE per person with disability increased from $13,395 in 2003 to $17,431 in 2015, whereas nondisability per-person spending remained constant (about $6700). Public insurers paid 69% of DAHE. Medicare paid the largest portion ($324.7 billion), and Medicaid DAHE were $277.2 billion. More than half (54%) of all Medicare expenditures and 72% of all Medicaid expenditures were associated with disability. CONCLUSIONS: The share of health care expenditures associated with disability has increased substantially over the past decade. The high proportion of DAHE paid by public insurers reinforces the importance of public programs designed to improve health care for people with disabilities and emphasizes the need for evaluating programs and health services available to this vulnerable population.


Disabled Persons/statistics & numerical data , Health Expenditures/statistics & numerical data , Activities of Daily Living , Adult , Age Factors , Aged , Chronic Disease , Female , Humans , Male , Medicaid/statistics & numerical data , Medicare/statistics & numerical data , Middle Aged , Physical Functional Performance , Racial Groups , Residence Characteristics , Sex Factors , Social Work/economics , Socioeconomic Factors , United States , Work Capacity Evaluation
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