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Abhijit V Kshirsagar

Biographic Data

ID1258877
NAMEAbhijit V Kshirsagar
GIVEN NAMESAbhijit V
FAMILY NAMEKshirsagar
SIGNATUREKSHIRSAGAR A V
AFFILIATIONSUniversity of North Carolina at Chapel Hill
ORCID0000-0001-6669-7523
VERIFIEDYes
TOTAL WORKS5
TOTAL CITATIONS4
WORKS AS AUTHOR5
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2008
LATEST PUBLICATION YEAR2020
H-INDEX1
  • Assessing the Impacts of Misclassified Case-Mix Factors on Health Care Provider Profiling

    Open Access•Yi Mu, Andrew I Chin et al.•ARTICLE•INQUIRY The Journal of Health…•2020

    Quantitative metrics are used to develop profiles of health care institutions, including hospitals, nursing homes, and dialysis clinics. These profiles serve as measures of quality of care, which are used to compare institutions and determine reimbursement, as a part of a national effort led by the Center for Medicare and Medicaid Services in the United States. However, there is some concern about how misclassification in case-mix factors, which …

  • Assessing Residual Bias in Estimating Influenza Vaccine Effectiveness

    Anne M Butler, J Bradley Layton et al.•ARTICLE•Medical Care•2019•References: 25

    BACKGROUND: Estimating influenza vaccine effectiveness using an unvaccinated comparison group may result in biased effect estimates. OBJECTIVES: To explore the reduction of confounding bias in an active comparison of high-dose versus standard-dose influenza vaccines, as compared with vaccinated versus unvaccinated comparisons. METHODS: Using Medicare data from the United States end-stage renal disease program (2009-2013), we compared the risk of …

  • Regional and Temporal Variations in Comorbidity Among US Dialysis Patients

    Open Access•Yi Mu, Andrew I Chin et al.•ARTICLE•INQUIRY The Journal of Health…•2018

    Medicare claims data are commonly used to query comorbidities for case-mix adjustment in research of patients with end-stage renal disease (ESRD) in the United States. These adjustments may affect reimbursement and quality rating through comparative profiling and ranking of dialysis facilities. We studied regional and temporal variations in comorbidity from claims data in the United States Renal Data System. Patients with a previous 1-year Medica…

  • Hospitalization and Skilled Nursing Care are Predictors of Influenza Vaccination Among Patients on Hemodialysis

    Leah J McGrath, Stephen R Cole et al.•ARTICLE•Medical Care•2013•References: 7

    BACKGROUND: Observational studies of preventive medications, such as vaccinations, can suffer from the healthy-user bias because vaccinated patients may be healthier than unvaccinated patients. Indicators of health status and frailty suitable for attenuating this bias could be identified in administrative data. OBJECTIVE: To examine the association of baseline variables and time-dependent hospitalization and skilled nursing care with the receipt …

  • Kidney disease and the cumulative burden of life course socioeconomic conditions

    Open Access•David A Shoham, Suma Vupputuri et al.•ARTICLE•Social Science & Medicine•2008•Cited by: 4•References: 54

  • Kidney disease and the cumulative burden of life course socioeconomic conditions

    Open Access•David A Shoham, Suma Vupputuri et al.•ARTICLE•Social Science & Medicine•2008•Cited by: 4•References: 54

  • Kidney disease and the cumulative burden of life course socioeconomic conditions

    Open Access•David A Shoham, Suma Vupputuri et al.•ARTICLE•Social Science & Medicine•2008•Cited by: 4•References: 54

  • Hospitalization and Skilled Nursing Care are Predictors of Influenza Vaccination Among Patients on Hemodialysis

    Leah J McGrath, Stephen R Cole et al.•ARTICLE•Medical Care•2013•References: 7

    BACKGROUND: Observational studies of preventive medications, such as vaccinations, can suffer from the healthy-user bias because vaccinated patients may be healthier than unvaccinated patients. Indicators of health status and frailty suitable for attenuating this bias could be identified in administrative data. OBJECTIVE: To examine the association of baseline variables and time-dependent hospitalization and skilled nursing care with the receipt …

  • Regional and Temporal Variations in Comorbidity Among US Dialysis Patients

    Open Access•Yi Mu, Andrew I Chin et al.•ARTICLE•INQUIRY The Journal of Health…•2018

    Medicare claims data are commonly used to query comorbidities for case-mix adjustment in research of patients with end-stage renal disease (ESRD) in the United States. These adjustments may affect reimbursement and quality rating through comparative profiling and ranking of dialysis facilities. We studied regional and temporal variations in comorbidity from claims data in the United States Renal Data System. Patients with a previous 1-year Medica…

  • Assessing Residual Bias in Estimating Influenza Vaccine Effectiveness

    Anne M Butler, J Bradley Layton et al.•ARTICLE•Medical Care•2019•References: 25

    BACKGROUND: Estimating influenza vaccine effectiveness using an unvaccinated comparison group may result in biased effect estimates. OBJECTIVES: To explore the reduction of confounding bias in an active comparison of high-dose versus standard-dose influenza vaccines, as compared with vaccinated versus unvaccinated comparisons. METHODS: Using Medicare data from the United States end-stage renal disease program (2009-2013), we compared the risk of …

  • Assessing the Impacts of Misclassified Case-Mix Factors on Health Care Provider Profiling

    Open Access•Yi Mu, Andrew I Chin et al.•ARTICLE•INQUIRY The Journal of Health…•2020

    Quantitative metrics are used to develop profiles of health care institutions, including hospitals, nursing homes, and dialysis clinics. These profiles serve as measures of quality of care, which are used to compare institutions and determine reimbursement, as a part of a national effort led by the Center for Medicare and Medicaid Services in the United States. However, there is some concern about how misclassification in case-mix factors, which …

Medicine (5 works) · Internal Medicine (4 works) · Demography (3 works) · Healthcare Policy and Management (3 works) · Internal Medicine (3 works) · Cohort (2 works) · Confidence interval (2 works) · Cumulative incidence (2 works) · Demography (2 works) · Emergency Medicine (2 works)

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