Harold P Lehmann
Biographic Data
| ID | 267899 |
|---|---|
| NAME | Harold P Lehmann |
| GIVEN NAMES | Harold P |
| FAMILY NAME | Lehmann |
| SIGNATURE | LEHMANN H P |
| AFFILIATIONS | Johns Hopkins University |
| ORCID | 0000-0002-7698-219X |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 10 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1956 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Racial disparities in diabetes care and outcomes for people with visual impairment: A descriptive analysis of the TriNetX research network
This study uncovers pronounced disparities in diabetes prevalence and management among individuals with visual impairments who seek care, particularly among White and African American groups. Our DAG analysis illuminates the intricate interplay between SDoH, healthcare access, and frequency of crucial diabetes monitoring practices, highlighting visual impairment as both a medical and social issue
Measuring the Impact of Data Quality and Computable Phenotypes on Potential Racial Disparities in Predicting Healthcare Utilization Among Type 2 Diabetes Populations
Associations of County-Level Social Determinants of Health with Covid-19 Related Hospitalization Among People with HIV: A Retrospective Analysis of the U.S. National Covid Cohort Collaborative (N3C)
Individually, the COVID-19 and HIV pandemics have differentially impacted minoritized groups due to the role of social determinants of health (SDoH) in the U.S. Little is known how the collision of these two pandemics may have exacerbated adverse health outcomes. We evaluated county-level SDoH and associations with hospitalization after a COVID-19 diagnosis among people with (PWH) and without HIV (PWOH) by racial/ethnic groups. We used the U.S. N…
The Intersections of Covid-19, HIV, and Race/Ethnicity: Machine Learning Methods to Identify and Model Risk Factors for Severe Covid-19 in a Large U.S. National Dataset
What influences the “when” of eating and sleeping?A qualitative interview study
Caveats for the Use of Operational Electronic Health Record Data in Comparative Effectiveness Research
The growing amount of data in operational electronic health record systems provides unprecedented opportunity for its reuse for many tasks, including comparative effectiveness research. However, there are many caveats to the use of such data. Electronic health record data from clinical settings may be inaccurate, incomplete, transformed in ways that undermine their meaning, unrecoverable for research, of unknown provenance, of insufficient granul…
Clinical Information Technology Capabilities in Four U.S. Hospitals: Testing a New Structural Performance Measure
BACKGROUND: Few tools exist to quantify the performance of a hospital's information system from a user perspective. OBJECTIVES: Our objective was to develop and evaluate a survey-based metric that assesses the automation and usability of a hospital's information system. RESEARCH DESIGN AND METHODS: This is a cross-sectional study of 117 physicians and 3 chief information officers (CIOs) working in 2 community hospitals with historically low inves…
Why do patients and families request transfers to tertiary care? a qualitative study
A New Tool for Population-Based Quality-Adjusted Life Years
Johns Hopkins School of Medicine; Department of Pediatrics and Division of Biomedical Information Sciences; Baltimore, Maryland
The Finding of Haemoglobin D Disease in a Sikh
The Finding of Haemoglobin D Disease in a Sikh
A New Tool for Population-Based Quality-Adjusted Life Years
Johns Hopkins School of Medicine; Department of Pediatrics and Division of Biomedical Information Sciences; Baltimore, Maryland
Why do patients and families request transfers to tertiary care? a qualitative study
Clinical Information Technology Capabilities in Four U.S. Hospitals: Testing a New Structural Performance Measure
BACKGROUND: Few tools exist to quantify the performance of a hospital's information system from a user perspective. OBJECTIVES: Our objective was to develop and evaluate a survey-based metric that assesses the automation and usability of a hospital's information system. RESEARCH DESIGN AND METHODS: This is a cross-sectional study of 117 physicians and 3 chief information officers (CIOs) working in 2 community hospitals with historically low inves…
Caveats for the Use of Operational Electronic Health Record Data in Comparative Effectiveness Research
The growing amount of data in operational electronic health record systems provides unprecedented opportunity for its reuse for many tasks, including comparative effectiveness research. However, there are many caveats to the use of such data. Electronic health record data from clinical settings may be inaccurate, incomplete, transformed in ways that undermine their meaning, unrecoverable for research, of unknown provenance, of insufficient granul…
What influences the “when” of eating and sleeping?A qualitative interview study
Associations of County-Level Social Determinants of Health with Covid-19 Related Hospitalization Among People with HIV: A Retrospective Analysis of the U.S. National Covid Cohort Collaborative (N3C)
Individually, the COVID-19 and HIV pandemics have differentially impacted minoritized groups due to the role of social determinants of health (SDoH) in the U.S. Little is known how the collision of these two pandemics may have exacerbated adverse health outcomes. We evaluated county-level SDoH and associations with hospitalization after a COVID-19 diagnosis among people with (PWH) and without HIV (PWOH) by racial/ethnic groups. We used the U.S. N…
The Intersections of Covid-19, HIV, and Race/Ethnicity: Machine Learning Methods to Identify and Model Risk Factors for Severe Covid-19 in a Large U.S. National Dataset
Racial disparities in diabetes care and outcomes for people with visual impairment: A descriptive analysis of the TriNetX research network
This study uncovers pronounced disparities in diabetes prevalence and management among individuals with visual impairments who seek care, particularly among White and African American groups. Our DAG analysis illuminates the intricate interplay between SDoH, healthcare access, and frequency of crucial diabetes monitoring practices, highlighting visual impairment as both a medical and social issue
Measuring the Impact of Data Quality and Computable Phenotypes on Potential Racial Disparities in Predicting Healthcare Utilization Among Type 2 Diabetes Populations
Medicine (10 works) · Internal Medicine (6 works) · Gerontology (5 works) · Public health (5 works) · Family medicine (4 works) · Disease (3 works) · Health care (3 works) · Nursing (3 works) · Cohort (2 works) · Computer Science (2 works)