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AHRQ Research Studies Date
Topics
- Access to Care (2)
- Ambulatory Care and Surgery (1)
- Behavioral Health (2)
- COVID-19 (2)
- Disparities (1)
- Healthcare Costs (3)
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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 7 of 7 Research Studies DisplayedZuvekas SH
AHRQ Author: Zuvekas SH
COVID-19, mental health, and mental health treatment among adults.
This AHRQ-authored paper seeks to examine the impact of the COVID-19 pandemic on mental health status and mental health treatment among adults residing in the U.S. civilian, non-institutionalized population. Data from the 2019-2020 MEPS was used. The author examined unadjusted and regression-adjusted differences between 2019 and 2020 in perceived mental health status (excellent, very good, good, fair, poor) and in the K6 general psychological distress, the PHQ-2 depression screener, and the VR-12 mental component summary score. Similarly, using the detailed MEPS data on health care encounters and prescription drug fills, he examined differences in mental health use treatment between 2019 and 2020. He focused specifically on changes in continuity of treatment among those already in treatment in January and February, before the pandemic fully struck, as well differences in the initiation of new episodes of treatment after the pandemic began. Results were that all four mental health scales included in the MEPS showed statistically significant declines in mental health between 2019 and 2020, particularly among younger adults. However, the percentage of US adults receiving mental health treatment did not change significantly. Continuity of treatment increased slightly in 2020, with 87.1% of adults in treatment January or February still receiving care in the second quarter, an increase of 2.5 percentage points. However, there were significant declines in the initiation of new treatment, especially in the second quarter of 2020.
AHRQ-authored.
Citation: Zuvekas SH .
COVID-19, mental health, and mental health treatment among adults.
J Ment Health Policy Econ 2023 Dec 1; 26(4):159-83..
Keywords: Medical Expenditure Panel Survey (MEPS), COVID-19, Behavioral Health
Bernard DM, Selden TM, Fang Z
AHRQ Author: Bernard
The joint distribution of high out-of-pocket burdens, medical debt, and financial barriers to needed care.
This AHRQ-authored paper examined the joint distribution of three financial problems related to healthcare: high out-of-pocket burdens, medical debt, and financial barriers to needed care. The authors applied relatively strict definitions of financial problems to data from the 2018-2019 MEPS and found that 27% of nonsenior adults lived in families with at least one of the three financial strains assessed. The percentage of participants who faced more broadly defined financial problems was 45.5%. This prevalence varied across sociodemographic characteristics, families' health care needs, insurance coverage, and financial resources.
AHRQ-authored.
Citation: Bernard DM, Selden TM, Fang Z .
The joint distribution of high out-of-pocket burdens, medical debt, and financial barriers to needed care.
Health Aff 2023 Nov; 42(11):1517-26. doi: 10.1377/hlthaff.2023.00604..
Keywords: Medical Expenditure Panel Survey (MEPS), Healthcare Costs, Access to Care, Health Insurance
Decker SL, Zuvekas SH
AHRQ Author: Decker SL, Zuvekas SH
Primary care spending in the US population.
This AHRQ-authored research letter describes an analysis of primary care spending estimates in the US population using MEPS data. This survey study looked at the entire population, regardless of insurance source. The authors reported 2019 estimates of primary care spending, total medical spending, percentage of medical spending on primary care visits, and percentage with 0 spending on primary care visits. They analyzed race and ethnicity data to test whether primary care spending was greater in some groups compared with others. A total of 28,512 MEPS participants were included in the sample with a mean age of 38.6 and weighted percentages of 51.1% female, 18.5% Hispanic, 12.3% non-Hispanic Black, 59.7% non-Hispanic White, and 9.6% non-Hispanic individuals of other races and ethnicities. Primary care spending totaled $439 per person in 2019. Spending was highest for the Medicare population, Hispanics (52.7%), non-Hispanic Black (49.0%), and non-Hispanic other (44.3%), 79.9% for uninsured individuals and lowest for the uninsured. Average spending was $461 for those with group private insurance. The percentage of medical spending on primary care was 7.0% for the population and was lower for those younger than age 65 (5.1%), those in worse health (5.6%), and those with Medicare (5.3%). Almost 41% of the population had no primary care spending.
AHRQ-authored.
Citation: Decker SL, Zuvekas SH .
Primary care spending in the US population.
JAMA Intern Med 2023 Aug; 183(8):880-81. doi: 10.1001/jamainternmed.2023.1551..
Keywords: Medical Expenditure Panel Survey (MEPS), Healthcare Costs, Primary Care
Leininger LJ, Tomaino M, Meara E
Health-related quality of life in high-cost, high-need populations.
This retrospective longitudinal study examined health care utilization, expenditures, and patient-reported health for high-cost, high-need (HCHN) populations comparing a baseline (year 1) and follow-up year (year 2). The sample included adults (n = 46,934) participating in the Medical Expenditure Panel Survey between 2011 and 2016. The authors estimated health-related quality of life (HRQOL) for each sample member using the physical and mental health scales from the Medical Outcomes Study Short Form 12. They compared HRQOL stratified by HCHN, defined as patients whose baseline (year 1) demographics, utilization, and clinical characteristics predicted top decile health spending in year 2. The physical health scale exhibited robust measure validity, reliability, and responsiveness, but the mental health scale did not. Mean physical health was 1.25 SDs lower in HCHN vs other patients (37.9 vs 51.0 on a 0-100 scale increasing in self-perceived health). Patient-reported health outcomes continued to remain poor in HCHN populations, even after health care utilization recedes.
AHRQ-funded; HS024075.
Citation: Leininger LJ, Tomaino M, Meara E .
Health-related quality of life in high-cost, high-need populations.
Am J Manag Care 2023 Jul; 29(7):362-68. doi: 10.37765/ajmc.2023.89396..
Keywords: Medical Expenditure Panel Survey (MEPS), Quality of Life, Healthcare Costs
Olfson M, Zuvekas SH, McClellan C
AHRQ Author: Zuvekas SH, McClellan C
Racial-ethnic disparities in outpatient mental health care in the United States.
Using data from the 2018-19 Medical Expenditure Panel Survey, researchers compared national rates and patterns of use for outpatient mental health care among Hispanic, non-Hispanic Black, and non-Hispanic White individuals. Analyses focused on individuals using psychotropic medications, psychotherapy, or both, and receipt of minimally adequate mental health care. The results showed that the rate of outpatient mental health service use was more than twice as high for White individuals, and that Black and Hispanic patients were significantly less likely to receive psychotropic medications; Black and Hispanic patients were more likely to receive psychotherapy. No significant differences were found in patients who received minimally adequate treatment for depression, anxiety, attention-deficit hyperactivity disorder, or disruptive behavior disorders. The authors concluded that achieving racial-ethnic equity will require dedicated efforts to promote greater mental health service access for Black and Hispanic persons in need.
AHRQ-authored.
Citation: Olfson M, Zuvekas SH, McClellan C .
Racial-ethnic disparities in outpatient mental health care in the United States.
Psychiatr Serv 2023 Jul; 74(7):674-83. doi: 10.1176/appi.ps.20220365..
Keywords: Medical Expenditure Panel Survey (MEPS), Racial and Ethnic Minorities, Disparities, Behavioral Health, Ambulatory Care and Surgery
Jacobs PD, Moriya AS
AHRQ Author: Jacobs PD, Moriya AS
Changes in health coverage during the COVID-19 pandemic.
This AHRQ-authored paper used data from MEPS to examine patterns of health insurance coverage during the COVID-19 pandemic. The authors compared the proportion of people whose source of coverage changed from 2019 to 2020 with the proportion of people whose source changed from 2018 to 2019. The sample was limited to those who were interviewed in both 2018 and 2019 or in both 2019 and 2020. The analysis looked at people aged 63 or younger in the first year of the sample. The authors found increased stability for children and nonelderly adults during the first year of the pandemic. Fewer people who had Medicaid in 2019 became uninsured in 2020 (4.3%) than in 2018-19 (7.8%). Residents of Medicaid expansion states who were enrolled in 2019 were less likely to become uninsured in 2020 (3.6%) than was the case in the 2018-2019 period (6.0%). This was also true in non-Medicaid expansion states (6.6% vs 12.4%). However, residents of expansion states were more likely to become enrolled in Medicaid in 2020 if they were previously uninsured in 2019 (21.5%) compared with 2018-2019 (15.3%). For nonexpansion states, there was no detectable change in the percentage transitioning from uninsured to Medicaid over the two time periods (8.5% compared with 6.9%).
AHRQ-authored.
Citation: Jacobs PD, Moriya AS .
Changes in health coverage during the COVID-19 pandemic.
Health Affairs 2023 May; 42(5):721-26. doi: 10.1377/hlthaff.2022.01469..
Keywords: Medical Expenditure Panel Survey (MEPS), COVID-19, Health Insurance, Medicaid, Access to Care
McClellan C, Mitchell E, Anderson J
AHRQ Author: McClellan C, Mitchell E, Anderson J, Zuvekas S
Using machine-learning algorithms to improve imputation in the Medical Expenditure Panel Survey.
This AHRQ-authored study’s aim was to assess the feasibility of applying machine-learning (ML) methods to imputation in the Medical Expenditure Panel Survey (MEPS), using all data from the 2016-2017 survey. The authors examined five alternatives to linear regression: Gradient Boosting, Random Forests, Extreme Random Forests, Deep Neural Networks, and a Stacked Ensemble approach. Additionally, they introduced an alternative matching scheme which matches on a vector of predicted expenditures by sources of payment instead of a single total expenditure prediction to generate potentially superior matches. Their principal findings were that ML algorithms perform better at both prediction and matching imputation than Ordinary Least Squares (OLS), the most common prediction algorithm used in predictive mean matching (PMM). On average, the Stacked Ensemble approach that combines all the ML algorithms performs best, improving expenditure prediction R(2) by 108% and final imputation R(2) by 227%. There was also an improvement on alignment of sources of payments between donor and recipient events by matching on a prediction vector.
AHRQ-authored.
Citation: McClellan C, Mitchell E, Anderson J .
Using machine-learning algorithms to improve imputation in the Medical Expenditure Panel Survey.
Health Serv Res 2023 Apr;58(2):423-32. doi: 10.1111/1475-6773.14115.
Keywords: Medical Expenditure Panel Survey (MEPS), Health Information Technology (HIT)