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1.
JAMA Netw Open ; 7(5): e2413127, 2024 May 01.
Article in English | MEDLINE | ID: mdl-38787558

ABSTRACT

Importance: Unprecedented increases in hospital occupancy rates during COVID-19 surges in 2020 caused concern over hospital care quality for patients without COVID-19. Objective: To examine changes in hospital nonsurgical care quality for patients without COVID-19 during periods of high and low COVID-19 admissions. Design, Setting, and Participants: This cross-sectional study used data from the 2019 and 2020 Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project State Inpatient Databases. Data were obtained for all nonfederal, acute care hospitals in 36 states with admissions in 2019 and 2020, and patients without a diagnosis of COVID-19 or pneumonia who were at risk for selected quality indicators were included. The data analysis was performed between January 1, 2023, and March 15, 2024. Exposure: Each hospital and week in 2020 was categorized based on the number of COVID-19 admissions per 100 beds: less than 1.0, 1.0 to 4.9, 5.0 to 9.9, 10.0 to 14.9, and 15.0 or greater. Main Outcomes and Measures: The main outcomes were rates of adverse outcomes for selected quality indicators, including pressure ulcers and in-hospital mortality for acute myocardial infarction, heart failure, acute stroke, gastrointestinal hemorrhage, hip fracture, and percutaneous coronary intervention. Changes in 2020 compared with 2019 were calculated for each level of the weekly COVID-19 admission rate, adjusting for case-mix and hospital-month fixed effects. Changes during weeks with high COVID-19 admissions (≥15 per 100 beds) were compared with changes during weeks with low COVID-19 admissions (<1 per 100 beds). Results: The analysis included 19 111 629 discharges (50.3% female; mean [SD] age, 63.0 [18.0] years) from 3283 hospitals in 36 states. In weeks 18 to 48 of 2020, 35 851 hospital-weeks (36.7%) had low COVID-19 admission rates, and 8094 (8.3%) had high rates. Quality indicators for patients without COVID-19 significantly worsened in 2020 during weeks with high vs low COVID-19 admissions. Pressure ulcer rates increased by 0.09 per 1000 admissions (95% CI, 0.01-0.17 per 1000 admissions; relative change, 24.3%), heart failure mortality increased by 0.40 per 100 admissions (95% CI, 0.18-0.63 per 100 admissions; relative change, 21.1%), hip fracture mortality increased by 0.40 per 100 admissions (95% CI, 0.04-0.77 per 100 admissions; relative change, 29.4%), and a weighted mean of mortality for the selected indicators increased by 0.30 per 100 admissions (95% CI, 0.14-0.45 per 100 admissions; relative change, 10.6%). Conclusions and Relevance: In this cross-sectional study, COVID-19 surges were associated with declines in hospital quality, highlighting the importance of identifying and implementing strategies to maintain care quality during periods of high hospital use.


Subject(s)
COVID-19 , Quality of Health Care , SARS-CoV-2 , Humans , COVID-19/epidemiology , COVID-19/therapy , COVID-19/mortality , United States/epidemiology , Cross-Sectional Studies , Female , Male , Quality of Health Care/statistics & numerical data , Middle Aged , Aged , Hospitalization/statistics & numerical data , Hospitals/statistics & numerical data , Hospital Mortality , Quality Indicators, Health Care , Patient Admission/statistics & numerical data , Patient Admission/trends , Adult
2.
Acad Pediatr ; 2024 Apr 16.
Article in English | MEDLINE | ID: mdl-38614214

ABSTRACT

OBJECTIVE: To measure the impact of the COVID-19 pandemic on racial and ethnic disparities in attendance to well-child visit recommendations. METHODS: We used the nationally representative Medical Expenditure Panel Survey (MEPS) to compare pre-pandemic (2018-2019) and pandemic (2020 and 2021) ratios of well-child visits to age-based recommendations, presenting both unadjusted and adjusted attendance disparities over time. We also used the 1996-2021 MEPS to place the pandemic changes in an historical context. RESULTS: Average attendance decreased from 66.6% in 2018-2019 (95% confidence interval [CI]: 64.1, 69.1) to 58.6% in 2020 (95% CI: 55.5, 61.6), rebounding to 65.1% in 2021 (95% CI: 61.5, 68.7). The unadjusted disparity in attendance between White non-Hispanic and Black non-Hispanic children widened from 9.6 percentage points in 2018-2019 (95% CI: 2.8, 16.4) to 24.8 percentage points in 2020 (95% CI: 17.5, 32.2) and 21.4 percentage points in 2021 (95% CI: 11.2, 31.5). The unadjusted disparity in attendance between White non-Hispanic and Hispanic children widened from 14.8 percentage points in 2018-2019 (95% CI: 9.7, 19.8) to 26.3 percentage points in 2020 (95% CI: 19.9, 32.7) and 24.9 percentage points in 2021 (95% CI: 17.5, 32.3). Changes in disparities were large even when we controlled for health status, demographic and socioeconomic characteristics, health insurance, and state of residence. Magnitudes of the racial and ethnic attendance disparities during the pandemic's first two years were unprecedented since 1996. CONCLUSIONS: Widening attendance disparities during the pandemic highlight the need to build a more equitable health care system for all children.

3.
JAMA Health Forum ; 4(12): e234206, 2023 Dec 01.
Article in English | MEDLINE | ID: mdl-38038986

ABSTRACT

Importance: The COVID-19 pandemic had unprecedented effects on hospital occupancy, with consequences for hospital operations and patient care. Previous studies of occupancy during COVID-19 have been limited to small samples of hospitals. Objective: To measure the association between COVID-19 admission rates and hospital occupancy in different US areas and at different time periods during 2020. Design, Setting, and Participants: This cross-sectional study used data from the Healthcare Cost and Utilization Project State Inpatient Databases (2019-2020) for patients in nonfederal acute care hospitals in 45 US states, including the District of Columbia. Data analysis was performed between September 1, 2022, and April 30, 2023. Exposures: Each hospital and week in 2020 was categorized based on the number of COVID-19 admissions per 100 beds (<1 [low], 1-4.9, 5-9.9, 10-14.9, or ≥15 [high]). Main Outcomes and Measures: The main outcomes were inpatient and intensive care unit (ICU) occupancy. We used regression analysis to estimate the average change in occupancy for each hospital-week in 2020 relative to the same hospital week in 2019. Results: This study included 3960 hospitals and 54 355 916 admissions. Of the admissions in the 40 states used for race and ethnicity analyses, 15.7% were for Black patients, 12.9% were for Hispanic patients, 62.5% were for White patients, and 7.2% were for patients of other race or ethnicity; 1.7% of patients were missing these data. Weekly COVID-19 admission rates in 2020 were less than 4 per 100 beds for 63.9% of hospital-weeks and at least 10 in only 15.9% of hospital-weeks. Inpatient occupancy decreased by 12.7% (95% CI, 12.1% to 13.4%) during weeks with low COVID-19 admission rates and increased by 7.9% (95% CI, 6.8% to 9.0%) during weeks with high COVID-19 admission rates. Intensive care unit occupancy rates increased by 67.8% (95% CI, 60.5% to 75.3%) during weeks with high COVID-19 admissions. Increases in ICU occupancy were greatest when weighted to reflect the experience of Hispanic patients. Changes in occupancy were most pronounced early in the pandemic. During weeks with high COVID-19 admissions, occupancy decreased for many service lines, with occupancy by surgical patients declining by 43.1% (95% CI, 38.6% to 47.2%) early in the pandemic. Conclusions and Relevance: In this cross-sectional study of US hospital discharges in 45 states in 2020, hospital occupancy decreased during weeks with low COVID-19 admissions and increased during weeks with high COVID-19 admissions, with the largest changes occurring early in the pandemic. These findings suggest that surges in COVID-19 strained ICUs and were associated with large decreases in the number of surgical patients. These occupancy fluctuations may have affected quality of care and hospital finances.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , COVID-19/therapy , Inpatients , Pandemics , Cross-Sectional Studies , Intensive Care Units , Hospitals
4.
Health Aff (Millwood) ; 42(11): 1517-1526, 2023 11.
Article in English | MEDLINE | ID: mdl-37931199

ABSTRACT

Health care financial pressures in the US can manifest themselves in a variety of ways. Some families face high out-of-pocket spending on insurance premiums and medical care relative to income and assets. Some face medical debt that must be paid off over time. And some face delays or go without needed care for reasons involving cost. Whereas prior research has generally focused on these problems separately, a more complete picture of the challenges facing US families can be obtained by examining the joint distribution of these three financial problems. Applying relatively strict definitions of financial problems to data from the 2018-19 Medical Expenditure Panel Survey, we found that 27.0 percent of nonsenior adults lived in families with at least one of the three financial strains assessed. The share of participants facing more broadly defined financial problems was 45.4 percent. Prevalence varied across sociodemographic characteristics, families' health care needs, insurance coverage, and financial resources. The wide distribution of financial strain provides context for ongoing reforms in billing, coverage, and medical debt, as well as for the urgency felt across the country for health care financing reform.


Subject(s)
Cost of Illness , Insurance, Health , Adult , Humans , United States , Income , Health Expenditures , Delivery of Health Care
6.
JAMA Pediatr ; 176(11): 1143-1145, 2022 11 01.
Article in English | MEDLINE | ID: mdl-35994255

ABSTRACT

This study examines trends of well-child care visits within key socioeconomic groups.


Subject(s)
Child Health Services , Humans , Child
7.
Health Serv Res ; 57(5): 1006-1019, 2022 10.
Article in English | MEDLINE | ID: mdl-35593121

ABSTRACT

OBJECTIVE: To characterize the quantity and quality of hospital capacity across the United States. DATA SOURCES: We combine a 2017 near-census of US hospital inpatient discharges from the Healthcare Cost and Utilization Project (HCUP) with American Hospital Association Survey, Hospital Compare, and American Community Survey data. STUDY DESIGN: This study produces local hospital capacity quantity and care quality measures by allocating capacity to zip codes using market shares and population totals. Disparities in these measures are examined by race and ethnicity, income, age, and urbanicity. DATA COLLECTION/EXTRACTION METHODS: All data are derived from pre-existing sources. All hospitals and zip codes in states, including the District of Columbia, contributing complete data to HCUP in 2017 are included. PRINCIPAL FINDINGS: Non-Hispanic Black individuals living in zip codes supplied, on average, 0.11 more beds per 1000 population (SE = 0.01) than places where non-Hispanic White individuals live. However, the hospitals supplying this capacity have 0.36 fewer staff per bed (SE = 0.03) and perform worse on many care quality measures. Zip codes in the most urban parts of America have the least hospital capacity (2.11 beds per 1000 persons; SEM = 0.01) from across the rural-urban continuum. While more rural areas have markedly higher capacity levels, urban areas have advantages in staff and capital per bed. We do not find systematic differences in care quality between rural and urban areas. CONCLUSIONS: This study highlights the importance of lower hospital care quality and resource intensity in driving racial and ethnic, as well as income, disparities in hospital care-related outcomes. This study also contributes an alternative approach for measuring local hospital capacity that accounts for cross-hospital service area flows. Adjusting for these flows is necessary to avoid underestimating the supply of capacity in rural areas and overestimating it in places where non-Hispanic Black individuals tend to live.


Subject(s)
Black or African American , White People , Ethnicity , Healthcare Disparities , Hospitals , Humans , Rural Population , United States
8.
Int J Health Econ Manag ; 22(1): 1-52, 2022 Mar.
Article in English | MEDLINE | ID: mdl-33963977

ABSTRACT

The U.S. has addressed the opioid crisis using a two-front approach: state regulations limiting opioid prescriptions for acute pain patients, and voluntary federal CDC guidelines on shifting chronic pain patients to lower opioid doses and non-opioids. No opioid policy research to date has accounted for this two-pronged approach in their research design. We develop a theory of physician prescribing behavior under this two-pronged incentive structure. Using the Medical Expenditure Panel Survey, we empirically corroborate the theory: regulations and guidelines have the intended effects of reducing opioid prescriptions for acute and chronic pain, respectively, as well as the predicted unintended effects-income effects cause regulations on acute pain treatment to increase chronic pain opioid prescriptions and the chronic pain treatment guidelines spillover to reduce opioids for acute pain. Moreover, we find that the guidelines worked as intended in terms of the reduced usage, with chronic pain patients shifting to non-opioids and also tapering opioid doses. For those who discontinued opioids under regulations and guidelines, we find no harm in terms of increased work limitations due to pain a year after discontinuing opioids. Finally, we observe an unexplained dichotomy-regulations reduce opioid use by causing fewer new starts, whereas guidelines reduce opioid use by discontinuing current users, with no impact on new starts.


Subject(s)
Analgesics, Non-Narcotic , Chronic Pain , Opioid-Related Disorders , Analgesics, Opioid/therapeutic use , Centers for Disease Control and Prevention, U.S. , Chronic Pain/drug therapy , Humans , Opioid-Related Disorders/drug therapy , United States
10.
Health Aff (Millwood) ; 39(11): 2002-2009, 2020 11.
Article in English | MEDLINE | ID: mdl-32941086

ABSTRACT

Across the United States, school districts are grappling with questions of whether and how to reopen and keep open elementary and secondary schools in the 2020-21 academic year. Using household data from before the pandemic (2014-17), we examined how often people who have health conditions placing them at risk for severe coronavirus disease 2019 (COVID-19) were connected to schools, either as employees or by living in the same households as school employees or school-age children. Between 42.0 percent and 51.4 percent of all school employees met the Centers for Disease Control and Prevention's (CDC's) definition of having or potentially having increased risk for severe COVID-19. Among all adults with CDC-defined risk factors for severe COVID-19, between 33.9 million and 44.2 million had direct or within-household connections to schools.


Subject(s)
Coronavirus Infections , Employment/statistics & numerical data , Family Characteristics , Pandemics , Pneumonia, Viral , School Teachers/statistics & numerical data , Schools , Adolescent , Adult , Betacoronavirus/isolation & purification , COVID-19 , Centers for Disease Control and Prevention, U.S. , Child , Child, Preschool , Chronic Disease/epidemiology , Coronavirus Infections/diagnosis , Coronavirus Infections/transmission , Female , Humans , Male , Middle Aged , Obesity , Pneumonia, Viral/diagnosis , Pneumonia, Viral/transmission , Risk Factors , SARS-CoV-2 , United States
11.
Health Aff (Millwood) ; 39(9): 1624-1632, 2020 Sep.
Article in English | MEDLINE | ID: mdl-32663045

ABSTRACT

We used data from the Medical Expenditure Panel Survey to explore potential explanations for racial/ethnic disparities in coronavirus disease 2019 (COVID-19) hospitalizations and mortality. Black adults in every age group were more likely than White adults to have health risks associated with severe COVID-19 illness. However, Whites were older, on average, than Blacks. Thus, when all factors were considered, Whites tended to be at higher overall risk compared with Blacks, with Asians and Hispanics having much lower overall levels of risk compared with either Whites or Blacks. We explored additional explanations for COVID-19 disparities-namely, differences in job characteristics and how they interact with household composition. Blacks at high risk for severe illness were 1.6 times as likely as Whites to live in households containing health-sector workers. Among Hispanic adults at high risk for severe illness, 64.5 percent lived in households with at least one worker who was unable to work from home, versus 56.5 percent among Black adults and only 46.6 percent among White adults.


Subject(s)
Communicable Disease Control/organization & administration , Coronavirus Infections/epidemiology , Family Characteristics/ethnology , Healthcare Disparities/economics , Healthcare Disparities/ethnology , Pandemics/statistics & numerical data , Pneumonia, Viral/epidemiology , Adult , Aged , COVID-19 , Coronavirus Infections/prevention & control , Cross-Sectional Studies , Databases, Factual , Employment/statistics & numerical data , Ethnicity/statistics & numerical data , Female , Health Status Disparities , Humans , Male , Middle Aged , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Racial Groups/statistics & numerical data , Risk Assessment , United States , Vulnerable Populations
12.
Health Aff (Millwood) ; 39(1): 94-99, 2020 01.
Article in English | MEDLINE | ID: mdl-31905058

ABSTRACT

In 2000-12 payments for inpatient hospital stays, emergency department visits, and outpatient hospital care for privately insured patients grew much faster than payments for Medicare and Medicaid patients. This widening of private-public payment gaps slowed or even reversed itself in 2012-16.


Subject(s)
Hospitals, Private/statistics & numerical data , Hospitals, Public/statistics & numerical data , Length of Stay/trends , Reimbursement Mechanisms , Ambulatory Care/statistics & numerical data , Ambulatory Care/trends , Emergency Service, Hospital/statistics & numerical data , Humans , Medicaid/statistics & numerical data , Medicare/statistics & numerical data , Reimbursement Mechanisms/statistics & numerical data , Reimbursement Mechanisms/trends , United States
13.
Health Aff (Millwood) ; 38(11): 1791-1800, 2019 11.
Article in English | MEDLINE | ID: mdl-31618081

ABSTRACT

Spending on health care in the United States amounted to 17.9 percent of gross domestic product in 2017. Households paid for this care through out-of-pocket medical spending and a complex mix of out-of-pocket premiums, employer premium contributions, taxes, and subsidies that combined to finance private employer-sponsored insurance, nongroup insurance, and multiple public insurance programs. Our analysis examined the impact of this complex system of health care financing on households in the period 2005-16, tracking how economic and policy changes affected incidence-that is, the amount paid to finance health care, either directly or indirectly, by households as a share of their pretax income. Health care financing was regressive at the start of our study period, with households in the bottom 20 percent of income paying 26.8 percent of their income compared to about half that amount for those with income in the top 1 percent. By 2016 incidence had become approximately proportional (the same percentage across all income levels). In part, these results reflect increases in coverage through Medicaid and the Affordable Care Act Marketplaces, which are progressively financed through the federal tax system.


Subject(s)
Financing, Personal/trends , Health Expenditures/trends , Healthcare Financing , Patient Protection and Affordable Care Act , Socioeconomic Factors , United States
14.
Health Serv Res ; 54(4): 752-763, 2019 08.
Article in English | MEDLINE | ID: mdl-31070264

ABSTRACT

OBJECTIVE: To analyze factors associated with changes in prescription drug use and expenditures in the United States from 1999 to 2016, a period of rapid growth, deceleration, and resumed above-average growth. DATA SOURCES/STUDY SETTING: The Medical Expenditure Panel Survey (MEPS), containing household and pharmacy information on over five million prescription drug fills. STUDY DESIGN: We use nonparametric decomposition to analyze drug use, average payment per fill, and per capita expenditure, tracking the contributions over time of socioeconomic characteristics, health status and treated conditions, insurance coverage, and market factors surrounding the patent cycle. DATA COLLECTION/EXTRACTION METHODS: Medical Expenditure Panel Survey data were combined with information on drug approval dates and patent status. PRINCIPAL FINDINGS: Per capita utilization increased by nearly half during 1999-2016, with changes in health status and treated conditions accounting for four-fifths of the increase. In contrast, per capita expenditures more than doubled, with individual characteristics only explaining one-third of the change. Other drivers of spending during this period include the changing pipeline of new drugs, drugs losing exclusivity, and changes in generic competition. CONCLUSIONS: Long-term trends in treated conditions were the fundamental drivers of medication use, whereas factors involving the patent cycle accelerated and decelerated spending growth relative to trends in use.


Subject(s)
Drug Utilization/economics , Drug Utilization/statistics & numerical data , Prescription Drugs/economics , Drugs, Generic/economics , Health Status , Humans , Insurance Coverage/statistics & numerical data , Insurance, Pharmaceutical Services/statistics & numerical data , Patents as Topic/statistics & numerical data , Socioeconomic Factors , United States
15.
Int J Health Econ Manag ; 18(4): 409-423, 2018 Dec.
Article in English | MEDLINE | ID: mdl-29696508

ABSTRACT

The past decade witnessed a dramatic increase in inpatient hospital payment rates for patients with private insurance relative to payment rates for those covered by Medicare. A natural question is whether the widening private-Medicare payment rate difference had implications for the hospital care received by patients just before and after turning 65-the age at which there is a substantial shift from private to Medicare coverage. Using a large discharge dataset covering the period 2001-2011, we tracked changes at age 65 in the following dimensions of hospital care: overall hospitalization rates, case mix, referral-sensitive surgeries, length of stay, full established charges, number of procedures, mortality, and composite measures of inpatient quality and patient safety. In all cases we found either no change or a change that was small and inconsistent with payment rate changes during the study period.


Subject(s)
Economics, Hospital/statistics & numerical data , Hospitalization/statistics & numerical data , Insurance, Health/statistics & numerical data , Private Sector/statistics & numerical data , Age Factors , Aged , Diagnosis-Related Groups , Female , Hospital Costs , Hospital Mortality , Hospitalization/economics , Humans , Inpatients/statistics & numerical data , Insurance, Health/economics , Length of Stay/statistics & numerical data , Male , Medicare/economics , Medicare/statistics & numerical data , Middle Aged , Models, Economic , Patient Safety , Private Sector/economics , Quality Indicators, Health Care , Referral and Consultation/statistics & numerical data , United States
16.
Health Aff (Millwood) ; 36(12): 2069-2077, 2017 12.
Article in English | MEDLINE | ID: mdl-29200332

ABSTRACT

Affordable Care Act (ACA) provisions implemented in 2014 provide a valuable case study regarding the merits of using public versus subsidized private insurance to help low-income people obtain and finance health care. In particular, nonelderly adults with incomes of 100-138 percent of the federal poverty level gained Medicaid eligibility if they lived in states that implemented the ACA's Medicaid expansion, whereas those in nonexpansion states became eligible for subsidized Marketplace coverage. Using data for 2008-15 from the National Health Interview Survey, we found that as of 2015, adults with family incomes in this range had experienced large declines in uninsurance rates in both expansion and nonexpansion states (the adjusted declines were 22 percentage points and 18 percentage points, respectively). Adults in expansion and nonexpansion states also experienced similar increases in having a usual source of care and primary care visits, and similar reductions in delayed receipt of medical care due to cost. There were, however, important differences: Adults in expansion states experienced larger reductions in out-of-pocket spending but also faced greater difficulty accessing physician care relative to adults in nonexpansion states.


Subject(s)
Eligibility Determination/methods , Health Expenditures , Health Insurance Exchanges/statistics & numerical data , Health Services Accessibility , Insurance Coverage/statistics & numerical data , Medicaid/statistics & numerical data , Adult , Female , Health Services Accessibility/statistics & numerical data , Health Surveys , Humans , Male , Middle Aged , Poverty , United States
17.
Health Aff (Millwood) ; 36(12): 2160-2164, 2017 12.
Article in English | MEDLINE | ID: mdl-29200346

ABSTRACT

We used data for 2014-15 from the Medical Expenditure Panel Survey to estimate standardized payments for nonelderly adults' physician office visits by type of insurance. Adults with public insurance, especially Medicaid, had substantially lower provider payments, out-of-pocket spending, and third-party payments than their peers with employer-sponsored or Marketplace insurance. Quantifying public-private payment differences can help clarify choices for financing health care among low-income Americans.


Subject(s)
Health Benefit Plans, Employee/statistics & numerical data , Health Expenditures/statistics & numerical data , Insurance, Health, Reimbursement/statistics & numerical data , Medicaid/statistics & numerical data , Medicare/statistics & numerical data , Office Visits/statistics & numerical data , Adult , Female , Humans , Insurance, Health/economics , Insurance, Health/statistics & numerical data , Male , Middle Aged , Poverty , Surveys and Questionnaires , United States
18.
Health Aff (Millwood) ; 36(9): 1637-1642, 2017 09 01.
Article in English | MEDLINE | ID: mdl-28874492

ABSTRACT

Understanding the health care spending and utilization of various types of Medicaid enrollees is important for assessing the budgetary implications of both expansion and contraction in Medicaid enrollment. Despite the intense debate surrounding the Affordable Care Act (ACA), however, little information is available on the spending and utilization patterns of the nonelderly adult enrollees who became newly eligible for Medicaid under the ACA. Using data for 2012-14 from the Medical Expenditure Panel Survey, we compared health care spending and utilization of newly eligible Medicaid enrollees with those of nondisabled adults who were previously eligible and enrolled. We found that average monthly expenditures for newly eligible enrollees were $180-21 percent less than the $228 average for previously eligible enrollees. Utilization differences between these groups likely contributed to this differential.


Subject(s)
Eligibility Determination , Health Expenditures/statistics & numerical data , Insurance Coverage/statistics & numerical data , Medicaid/statistics & numerical data , Adult , Humans , Patient Protection and Affordable Care Act/economics , Poverty , Surveys and Questionnaires , United States
19.
Health Aff (Millwood) ; 35(12): 2297-2301, 2016 12 01.
Article in English | MEDLINE | ID: mdl-27920319

ABSTRACT

The increased prevalence of high-deductible health plans raises concerns regarding high financial burdens from health care, particularly for low-income adults.


Subject(s)
Deductibles and Coinsurance/economics , Health Benefit Plans, Employee/economics , Insurance Coverage/economics , Insurance, Health/economics , Adult , Delivery of Health Care , Health Expenditures/statistics & numerical data , Humans , Middle Aged , Poverty/economics , Surveys and Questionnaires , United States
20.
Med Care ; 54(3): 243-52, 2016 Mar.
Article in English | MEDLINE | ID: mdl-26871642

ABSTRACT

BACKGROUND: Veteran access to care is an important policy issue that has not previously been examined with population-based survey data. OBJECTIVES: This study compares access to care for nonelderly adult Veterans versus comparable non-Veterans, overall and within subgroups defined by simulated eligibility for health care from the Veterans Health Administration and by insurance status. RESEARCH DESIGN: We use household survey data from the Medical Expenditure Panel Survey from 2006 to 2011. We use iterative proportional fitting to standardize (control for) differences in age, sex, income, medical conditions, disability, Census region, and Metropolitan Statistical Area. SUBJECTS: Nonelderly Veterans and comparable non-Veterans. MEASURES: For medical, dental, and prescription medicine treatments, we use 4 access measures: delaying care, inability to obtain care, perceiving delay as a big problem, and perceiving inability to obtain care as a big problem. We also examine having a usual source of care. RESULTS: Frequencies of access barriers are similar for nonelderly Veterans and comparable non-Veterans for dental and prescription medicine treatments. For medical treatment, we find that Veterans eligible for VA health care and Veterans with VA use who are uninsured report fewer access problems than the comparable non-Veteran populations for 2 measures: inability to obtain care and reporting inability to obtain care as a big problem. CONCLUSIONS: Our results show that uninsured Veterans, the most policy-relevant group, have better access to care than comparable non-Veterans. Our results highlight the importance of adjusting Veteran and non-Veteran comparisons to account for the higher than average health care needs of Veterans.


Subject(s)
Health Services Accessibility/statistics & numerical data , Residence Characteristics/statistics & numerical data , United States Department of Veterans Affairs/statistics & numerical data , Veterans/statistics & numerical data , Adult , Age Factors , Female , Health Status , Humans , Insurance Coverage/statistics & numerical data , Male , Mental Health , Middle Aged , Prescription Drugs , Sex Factors , Socioeconomic Factors , United States , Waiting Lists , Young Adult
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