Hadi Kharrazi
Datos Biográficos
| ID | 4238063 |
|---|---|
| NOMBRE | Hadi Kharrazi |
| NOMBRES | Hadi |
| APELLIDO | Kharrazi |
| FIRMA | KHARRAZI H |
| AFILIACIONES | Johns Hopkins University |
| ORCID | 0000-0003-1481-4323 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 18 |
| TOTAL DE CITAS | 0 |
| TOTAL COMO AUTOR | 18 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2017 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2026 |
| ÍNDICE H | 0 |
Navigating extreme class imbalance in suicide risk prediction
A low precision for estimated suicide risk can be understood as a consequence of some tradeoffs during model development, particularly training models with matched cases, balanced classes or within short time horizons. This work demonstrates the improved AUPRC performance of regression models in a cross validated framework when these conditions are made more realistic, in the context of class imbalance or less restrictive in that of time horizon.…
Associations of Race, Area-level Income, and Air Quality on Hospitalization Risk in Pediatric Asthma Patients
Measuring the Impact of Data Quality and Computable Phenotypes on Potential Racial Disparities in Predicting Healthcare Utilization Among Type 2 Diabetes Populations
Latent Class Analysis of Social Needs in Medicaid Population and Its Impact on Risk Adjustment Models
BACKGROUND: A growing number of US states are implementing programs to address the social needs (SNs) of their Medicaid populations through managed care contracts. Incorporating SN might also improve risk adjustment methods used to reimburse Medicaid providers. OBJECTIVES: Identify classes of SN present within the Medicaid population and evaluate the performance improvement in risk adjustment models of health care utilization and cost after incor…
Clinical, social, and policy factors in Covid-19 cases and deaths
Our findings demonstrate that the set of SDoH features that are significant for COVID-19 outcomes varies based on the time from the start date of the pandemic and when COVID-19 was present in a county. These results could assist researchers with variable selection and inform decision makers when creating public health policy
Measuring the Value of a Practical Text Mining Approach to Identify Patients With Housing Issues in the Free-Text Notes in Electronic Health Record
Introduction: Despite the growing efforts to standardize coding for social determinants of health (SDOH), they are infrequently captured in electronic health records (EHRs). Most SDOH variables are still captured in the unstructured fields (i.e., free-text) of EHRs. In this study we attempt to evaluate a practical text mining approach (i.e., advanced pattern matching techniques) in identifying phrases referring to housing issues, an important SDO…
Performance of a Predictive Model versus Prescription-Based Thresholds in Identifying Patients at Risk of Fatal Opioid Overdose
Background: Prescription Drug Monitoring Programs (PDMPs) collect controlled substance prescriptions dispensed within a state. Many PDMP programs perform targeted outreach (i.e., “unsolicited reporting”) for patients who exceed numerical thresholds, however, the degree to which patients at highest risk of fatal opioid overdose are identified has not been compared with one another or with a predictive model. Methods: A retrospective analysis was p…
Social and Behavioral Variables in the Electronic Health Record
PURPOSE: Social and behavioral determinants of health (SBDH) are important factors that affect the health of individuals but are not routinely captured in a structured and systematic manner in electronic health records (EHRs). The purpose of this study is to generate recommendations for systematic implementation of SBDH data collection in EHRs through (1) reviewing SBDH conceptual and theoretical frameworks and (2) eliciting stakeholder perspecti…
Differential impact of mitigation policies and socioeconomic status on Covid-19 prevalence and social distancing in the United States
Neighborhoods with varying levels of socioeconomic disadvantage reacted differently to the implementation and relaxation of COVID-19 mitigation policies. Policymakers should consider investing more resources in disadvantaged counties as the pandemic may not stop until most neighborhoods have it under control
Assessing the Impact of Neighborhood Socioeconomic Characteristics on Covid-19 Prevalence Across Seven States in the United States
Introduction: The spread of Coronavirus Disease 2019 (COVID-19) across the United States has highlighted the long-standing nationwide health inequalities with socioeconomically challenged communities experiencing a higher burden of the disease. We assessed the impact of neighborhood socioeconomic characteristics on the COVID-19 prevalence across seven selected states (i.e., Arizona, Florida, Illinois, Maryland, North Carolina, South Carolina, and…
Assessing the geographical distribution of comorbidity among commercially insured individuals in South Africa
Our results show underlying disparities in CMI at national, provincial, and district levels. Use of geo-level CMI scores, along with other social data affecting health outcomes, can enable public health departments to improve the management of disease burdens locally and nationally. Our results could also improve the identification of underserved individuals, hence bridging the gap between public health and population health management efforts
Behavioral Intentions to Use Patient Portals to Disclose HIV and Other Sexually Transmitted Infection Testing Histories with Sexual Partners Among U.S. Sexual Minority Men
Health Education Serious Games Targeting Health Care Providers, Patients, and Public Health Users
BACKGROUND Serious educational games have shown effectiveness in improving various health outcomes. Previous reviews of health education games have focused on specific diseases, certain medical subjects, fixed target groups, or limited outcomes of interest. Given the recent surge in health game studies, a scoping review of health education games is needed to provide an updated overview of various aspects of such serious games. OBJECTIVE This stud…
A Practical Comparison Between the Predictive Power of Population-based Risk Stratification Models Using Data From Electronic Health Records Versus Administrative Claims
Department of Health Policy and Management, Center for Population Health Information Technology, Johns Hopkins School of Public Health, Baltimore, MD This manuscript has been prepared by faculty and staff at The Johns Hopkins University (JHU). The manuscript also references the Adjusted Clinical Groups (ACG) system. JHU holds the copyright to the ACG System and receives royalties from the global distribution of the ACG system. The authors are mem…
Defining and Assessing Geriatric Risk Factors and Associated Health Care Utilization Among Older Adults Using Claims and Electronic Health Records
BACKGROUND: Using electronic health records (EHRs), in addition to claims, to systematically identify patients with factors associated with adverse outcomes (geriatric risk) among older adults can prove beneficial for population health management and clinical service delivery. OBJECTIVE: To define and compare geriatric risk factors derivable from claims, structured EHRs, and unstructured EHRs, and estimate the relationship between geriatric risk …
Assessing the Impact of Body Mass Index Information on the Performance of Risk Adjustment Models in Predicting Health Care Costs and Utilization
BACKGROUND: Using electronic health records (EHRs) for population risk stratification has gained attention in recent years. Compared with insurance claims, EHRs offer novel data types (eg, vital signs) that can potentially improve population-based predictive models of cost and utilization. OBJECTIVE: To evaluate whether EHR-extracted body mass index (BMI) improves the performance of diagnosis-based models to predict concurrent and prospective hea…
Evaluating the Impact of Prescription Fill Rates on Risk Stratification Model Performance
BACKGROUND: Risk adjustment models are traditionally derived from administrative claims. Prescription fill rates-extracted by comparing electronic health record prescriptions and pharmacy claims fills-represent a novel measure of medication adherence and may improve the performance of risk adjustment models. OBJECTIVE: We evaluated the impact of prescription fill rates on claims-based risk adjustment models in predicting both concurrent and prosp…
Comparing Population-based Risk-stratification Model Performance Using Demographic, Diagnosis and Medication Data Extracted From Outpatient Electronic Health Records Versus Administrative Claims
BACKGROUND: There is an increasing demand for electronic health record (EHR)-based risk stratification and predictive modeling tools at the population level. This trend is partly due to increased value-based payment policies and the increasing availability of EHRs at the provider level. Risk stratification models, however, have been traditionally derived from claims or encounter systems. This study evaluates the challenges and opportunities of us…
Sin obras prominentes en esta página.
Evaluating the Impact of Prescription Fill Rates on Risk Stratification Model Performance
BACKGROUND: Risk adjustment models are traditionally derived from administrative claims. Prescription fill rates-extracted by comparing electronic health record prescriptions and pharmacy claims fills-represent a novel measure of medication adherence and may improve the performance of risk adjustment models. OBJECTIVE: We evaluated the impact of prescription fill rates on claims-based risk adjustment models in predicting both concurrent and prosp…
Comparing Population-based Risk-stratification Model Performance Using Demographic, Diagnosis and Medication Data Extracted From Outpatient Electronic Health Records Versus Administrative Claims
BACKGROUND: There is an increasing demand for electronic health record (EHR)-based risk stratification and predictive modeling tools at the population level. This trend is partly due to increased value-based payment policies and the increasing availability of EHRs at the provider level. Risk stratification models, however, have been traditionally derived from claims or encounter systems. This study evaluates the challenges and opportunities of us…
A Practical Comparison Between the Predictive Power of Population-based Risk Stratification Models Using Data From Electronic Health Records Versus Administrative Claims
Department of Health Policy and Management, Center for Population Health Information Technology, Johns Hopkins School of Public Health, Baltimore, MD This manuscript has been prepared by faculty and staff at The Johns Hopkins University (JHU). The manuscript also references the Adjusted Clinical Groups (ACG) system. JHU holds the copyright to the ACG System and receives royalties from the global distribution of the ACG system. The authors are mem…
Defining and Assessing Geriatric Risk Factors and Associated Health Care Utilization Among Older Adults Using Claims and Electronic Health Records
BACKGROUND: Using electronic health records (EHRs), in addition to claims, to systematically identify patients with factors associated with adverse outcomes (geriatric risk) among older adults can prove beneficial for population health management and clinical service delivery. OBJECTIVE: To define and compare geriatric risk factors derivable from claims, structured EHRs, and unstructured EHRs, and estimate the relationship between geriatric risk …
Assessing the Impact of Body Mass Index Information on the Performance of Risk Adjustment Models in Predicting Health Care Costs and Utilization
BACKGROUND: Using electronic health records (EHRs) for population risk stratification has gained attention in recent years. Compared with insurance claims, EHRs offer novel data types (eg, vital signs) that can potentially improve population-based predictive models of cost and utilization. OBJECTIVE: To evaluate whether EHR-extracted body mass index (BMI) improves the performance of diagnosis-based models to predict concurrent and prospective hea…
Health Education Serious Games Targeting Health Care Providers, Patients, and Public Health Users
BACKGROUND Serious educational games have shown effectiveness in improving various health outcomes. Previous reviews of health education games have focused on specific diseases, certain medical subjects, fixed target groups, or limited outcomes of interest. Given the recent surge in health game studies, a scoping review of health education games is needed to provide an updated overview of various aspects of such serious games. OBJECTIVE This stud…
Assessing the Impact of Neighborhood Socioeconomic Characteristics on Covid-19 Prevalence Across Seven States in the United States
Introduction: The spread of Coronavirus Disease 2019 (COVID-19) across the United States has highlighted the long-standing nationwide health inequalities with socioeconomically challenged communities experiencing a higher burden of the disease. We assessed the impact of neighborhood socioeconomic characteristics on the COVID-19 prevalence across seven selected states (i.e., Arizona, Florida, Illinois, Maryland, North Carolina, South Carolina, and…
Assessing the geographical distribution of comorbidity among commercially insured individuals in South Africa
Our results show underlying disparities in CMI at national, provincial, and district levels. Use of geo-level CMI scores, along with other social data affecting health outcomes, can enable public health departments to improve the management of disease burdens locally and nationally. Our results could also improve the identification of underserved individuals, hence bridging the gap between public health and population health management efforts
Behavioral Intentions to Use Patient Portals to Disclose HIV and Other Sexually Transmitted Infection Testing Histories with Sexual Partners Among U.S. Sexual Minority Men
Measuring the Value of a Practical Text Mining Approach to Identify Patients With Housing Issues in the Free-Text Notes in Electronic Health Record
Introduction: Despite the growing efforts to standardize coding for social determinants of health (SDOH), they are infrequently captured in electronic health records (EHRs). Most SDOH variables are still captured in the unstructured fields (i.e., free-text) of EHRs. In this study we attempt to evaluate a practical text mining approach (i.e., advanced pattern matching techniques) in identifying phrases referring to housing issues, an important SDO…
Performance of a Predictive Model versus Prescription-Based Thresholds in Identifying Patients at Risk of Fatal Opioid Overdose
Background: Prescription Drug Monitoring Programs (PDMPs) collect controlled substance prescriptions dispensed within a state. Many PDMP programs perform targeted outreach (i.e., “unsolicited reporting”) for patients who exceed numerical thresholds, however, the degree to which patients at highest risk of fatal opioid overdose are identified has not been compared with one another or with a predictive model. Methods: A retrospective analysis was p…
Social and Behavioral Variables in the Electronic Health Record
PURPOSE: Social and behavioral determinants of health (SBDH) are important factors that affect the health of individuals but are not routinely captured in a structured and systematic manner in electronic health records (EHRs). The purpose of this study is to generate recommendations for systematic implementation of SBDH data collection in EHRs through (1) reviewing SBDH conceptual and theoretical frameworks and (2) eliciting stakeholder perspecti…
Differential impact of mitigation policies and socioeconomic status on Covid-19 prevalence and social distancing in the United States
Neighborhoods with varying levels of socioeconomic disadvantage reacted differently to the implementation and relaxation of COVID-19 mitigation policies. Policymakers should consider investing more resources in disadvantaged counties as the pandemic may not stop until most neighborhoods have it under control
Clinical, social, and policy factors in Covid-19 cases and deaths
Our findings demonstrate that the set of SDoH features that are significant for COVID-19 outcomes varies based on the time from the start date of the pandemic and when COVID-19 was present in a county. These results could assist researchers with variable selection and inform decision makers when creating public health policy
Latent Class Analysis of Social Needs in Medicaid Population and Its Impact on Risk Adjustment Models
BACKGROUND: A growing number of US states are implementing programs to address the social needs (SNs) of their Medicaid populations through managed care contracts. Incorporating SN might also improve risk adjustment methods used to reimburse Medicaid providers. OBJECTIVES: Identify classes of SN present within the Medicaid population and evaluate the performance improvement in risk adjustment models of health care utilization and cost after incor…
Measuring the Impact of Data Quality and Computable Phenotypes on Potential Racial Disparities in Predicting Healthcare Utilization Among Type 2 Diabetes Populations
Navigating extreme class imbalance in suicide risk prediction
A low precision for estimated suicide risk can be understood as a consequence of some tradeoffs during model development, particularly training models with matched cases, balanced classes or within short time horizons. This work demonstrates the improved AUPRC performance of regression models in a cross validated framework when these conditions are made more realistic, in the context of class imbalance or less restrictive in that of time horizon.…
Associations of Race, Area-level Income, and Air Quality on Hospitalization Risk in Pediatric Asthma Patients
Medicine (16 obras) · Environmental health (11 obras) · Health care (10 obras) · Population (10 obras) · Chronic Disease Management Strategies (8 obras) · Family medicine (8 obras) · Internal Medicine (7 obras) · Public health (7 obras) · Gerontology (6 obras) · Demography (5 obras)