National Healthcare Quality and Disparities Report
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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 3 of 3 Research Studies DisplayedSmith K, Padmanabhan P, Chen A
The impacts of the 340B Program on health care quality for low-income patients.
This study’s objective was to assess the effects of hospital 340B eligibility on quality of inpatient care provided to Medicaid and uninsured patients and for all patients. HCUP State Inpatient Data, Hospital Cost Reporting Information System Data, Office of Pharmacy Affairs Information System Data, and the American Hospital Association Annual Survey were all used to extract inpatient data from general acute care hospitals from 2008 to 2014 in 15 states. Data was linked on hospital 340B eligibility and participation. The authors did not find discontinuities in inpatient care quality across the Program eligibility threshold for Medicaid and uninsured patients; specifically, on all-cause mortality, 30-day readmission rates, or other measures. Among insured and non-Medicaid patients, they found discontinuities for acute myocardial infarction and postoperative sepsis mortality.
AHRQ-funded; HS026980.
Citation: Smith K, Padmanabhan P, Chen A .
The impacts of the 340B Program on health care quality for low-income patients.
Health Serv Res 2023 Oct; 58(5):1089-97. doi: 10.1111/1475-6773.14204..
Keywords: Low-Income, Hospitals, Vulnerable Populations, Medicaid, Uninsured, Inpatient Care, Quality of Care
Desai SM, Padmanabhan P, Chen AZ
Hospital concentration and low-income populations: evidence from New York State Medicaid.
The purpose of this study was to utilize comprehensive discharge data from New York State to assess the effects of changes in market concentration on hospital-level inpatient Medicaid volumes. The study found that for the average hospital, a one percent increase in HHI led to a 0.6% decrease in the number of Medicaid admissions. The strongest effects were on admissions for birth. These hospital-level decreases primarily reflect redistribution of Medicaid patients across hospitals, rather than overall reductions in hospitalizations for Medicaid patients. Specifically, hospital concentration leads to a redistribution of admissions from non-profit hospitals to public hospitals. The researchers found evidence that for births, physicians serving high proportions of Medicaid beneficiaries experience decreased admissions as concentration increased.
AHRQ-funded; HS026980.
Citation: Desai SM, Padmanabhan P, Chen AZ .
Hospital concentration and low-income populations: evidence from New York State Medicaid.
J Health Econ 2023 Jul; 90:102770. doi: 10.1016/j.jhealeco.2023.102770..
Keywords: Hospitals, Low-Income, Medicaid
Toomey SL, Elliott MN, Zaslavsky AM
Improving response rates and representation of hard-to-reach groups in family experience surveys.
This study examined the use of an audio-enabled tablet to survey parents of children discharged from 4 units of a children’s hospital. Normal mail survey response rates are very low, especially for black, Latino, and low-income respondents. This survey was done day of discharge at the hospital and there was a response rate of 71.1% via tablet versus 16.3% for mail only. The Child Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey was used. Tablet response rates were highest with fathers, those more likely to have a high school education or less, less likely to be white, and more likely to be publicly insured. The results are promising for future surveys using tablet administration.
AHRQ-funded; HS020513; HS025299.
Citation: Toomey SL, Elliott MN, Zaslavsky AM .
Improving response rates and representation of hard-to-reach groups in family experience surveys.
Acad Pediatr 2019 May - Jun;19(4):446-53. doi: 10.1016/j.acap.2018.07.007..
Keywords: Caregiving, Children/Adolescents, Consumer Assessment of Healthcare Providers and Systems (CAHPS), Health Information Technology (HIT), Hospitals, Low-Income, Patient Experience, Quality of Care, Quality Improvement, Racial and Ethnic Minorities