Jonathan Weiner
Affiliations: | Johns Hopkins University, Baltimore, MD |
Area:
Public Health, Public and Social Welfare, Health Care ManagementGoogle:
"Jonathan Weiner"Cross-listing: PHTree
Children
Sign in to add traineeTimothy K. Lake | grad student | 2001 | Johns Hopkins |
Deanie M. Leonard | grad student | 2002 | Johns Hopkins |
Susan F. Milner | grad student | 2005 | Johns Hopkins |
Lyn M. Sibley | grad student | 2007 | Johns Hopkins |
Hsien-Yen Chang | grad student | 2009 | Johns Hopkins |
Kenneth M. Shermock | grad student | 2009 | Johns Hopkins |
Roger A. Johns | grad student | 2013 | Johns Hopkins |
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Publications
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Kitchen C, Chang HY, Weiner JP, et al. (2022) Assessing the Added Value of Vital Signs Extracted from Electronic Health Records in Healthcare Risk Adjustment Models. Risk Management and Healthcare Policy. 15: 1671-1682 |
Pandya CJ, Hatef E, Wu J, et al. (2022) Impact of Social Needs in Electronic Health Records and Claims on Health Care Utilization and Costs Risk-Adjustment Models Within Medicaid Population. Population Health Management |
Chang HY, Kitchen C, Bishop MA, et al. (2022) Claims-based pharmacy markers for comprehensive medication management program case identification: Validation against concurrent and prospective healthcare costs and utilization. Research in Social & Administrative Pharmacy : Rsap |
Kitchen CA, Chang HY, Bishop MA, et al. (2022) Comparing and validating medication complexity from insurance claims against electronic health records. Journal of Managed Care & Specialty Pharmacy. 28: 473-484 |
Howson SN, McShea MJ, Ramachandran R, et al. (2022) Improving the Prediction of Persistent High Health Care Utilizers: Retrospective Analysis Using Ensemble Methodology. Jmir Medical Informatics. 10: e33212 |
Kharrazi H, Chang HY, Weiner JP, et al. (2021) Assessing the Added Value of Blood Pressure Information Derived from Electronic Health Records in Predicting Health Care Cost and Utilization. Population Health Management |
Ramachandran R, McShea MJ, Howson SN, et al. (2021) Assessing the Value of Unsupervised Clustering in Detecting Key Classes of Diagnostic and Medication Codes to Improve the Prediction of Persistent High Healthcare Utilizers. Jmir Medical Informatics |
Kitchen C, Hatef E, Chang HY, et al. (2021) Assessing the association between area deprivation index on COVID-19 prevalence: a contrast between rural and urban U.S. jurisdictions. Aims Public Health. 8: 519-530 |
Bishop MA, Chang HY, Kitchen C, et al. (2021) Development of measurable criteria to identify and prioritize patients for inclusion in comprehensive medication management programs within primary care settings. Journal of Managed Care & Specialty Pharmacy. 27: 1009-1018 |
Chang HY, Tang W, Hatef E, et al. (2021) Differential impact of mitigation policies and socioeconomic status on COVID-19 prevalence and social distancing in the United States. Bmc Public Health. 21: 1140 |