April 21, 2022
PAR-22-145 - Leveraging Health Information Technology (Health IT) to Address and Reduce Health Care Disparities (R01 Clinical Trial Optional)
National Institute on Minority Health and Health Disparities (NIMHD)
The purpose of this Notice is to inform potential applicants of a correction to Funding Opportunity Announcement (FOA) PAR-22-145 Leveraging Health Information Technology (Health IT) to Address and Reduce Health Care Disparities (R01 Clinical Trial Optional) regarding the specific areas of interest of participating Institute/Centers and Scientific/Research Contact(s).
Currently Reads:
In Part 2. Full Text of Announcement
Section I: Funding Opportunity Description
National Institute on Aging (NIA) is interested in:
- Studies that utilize the NIA Framework on Health Disparities to evaluate health IT interventions among older adults.
- Studies that can identify and facilitate the integration of core data elements related to social determinants of health and adverse childhood experiences, and family-level data of relevance to patient health, safety, and risks and that would be relevant to care plan implementation (for both chosen and biological families).
- Development of EHR-integrated family-centered goal-setting andadvance care and financial planning tools.
- Research that can improve the detection of bias in phenotyping algorithms in diagnosis and clinical care plans.
- Integration of cohort-sensitive sexual orientation and gender identity measures in the development of care plans for older adults.
- Research that can assess the quality and extent to which EHR clinical communication informs clinical testing, diagnostic and treatment decision making, care plan adherence, and patient outcomes, for clinical communications involving patients and/or caregivers.
- Evaluation of health IT interventions among people living with Alzheimer’s Disease and Related Dementias.
- Health IT interventions that leverage health IT to reduce disparities among people living with Alzheimer’s Disease and Related Dementias.
NIMHD Areas of Special interests include but are not limited to the following:
- Interventions that address the utility and impact of including SDoH and community level geocoded data and/or perceived community level measures in EHRs on the health outcomes of populations affected by health disparities.
- Evaluation of when in the clinical workflow would SDoH and community level geocoded data in EHRs have the most beneficial impact on health outcomes and evaluation of unintended adverse effects (e.g., stigma) of incorporating SDoH in EHRs.
- Interventions that address the addtional health literacy and numeracy demands of EHR driven conversations on shared decision making, quality of patient-clinician communication, and health outcomes; types of interventions and personalize tailoring needed to foster engagement of patients with EHR portals for communication and access to PHRs to encourage informed shared decisions and quality of communication between patient and clinician in a sustained and relevant way.
- Examination of the differences in adoption rates of patient access to portals for communication and review of PHRs-including addressing reasons (e.g., distrust of medical research, privacy) - among older users, rural residents, low-income patients, persons with LEP and/or limited health literacy, and racial/ethnic minority patients.
- The unintended consequences of EHR use on patient – clinician and clinician-clinician communication and relationships, and health outcomes among populations affected by health disparities; The impact of using automated algorithms (ML/AI) to inform disease risk assessment, detection, diagnoses, and treatment decision-making on disparities in healthcare quality or outcomes.
- Interventions to utilize patient generated health data (PGHD) which can include NIH patient-reported outcomes measures, (e.g., www.nihpromis.org), in ambulatory care practices to improve health outcomes.
- Interventions to address clinician and patient burden, caregiver burden, poor usability, and workflow integration faced by clinicians to effectively utilize PGHD in clinics.
- Evaluation of telehealth policies (e.g., regulatory waivers issued by the Centers for Medicare and Medicare Services; Accountable Care Organization/ACO payment model; credentialing of clinicians/care team delivering telehealth services) on access to care.
- Impact of telehealth care delivery models on quality of care, health outcomes, healthcare utilization, patient self-management/decision making, and costs.
- Interventions to address the challenges, including SDoH and health literacy, that can impact telehealth engagement and adherence to treatment plans.
- Multi-level (patient, caregivers or support system of patient, clinicians, and health care system) interventions that leverage health IT to improve the care of complex chronic diseases in diverse primary care settings – including safety net clinics and patient-centered medical home (PCMH).
- Intervention studies of leveraging health IT for quality improvement in less resourced primary care practices.
- Intervention studies of EHRs/CDS use to manage care in diverse settings (e.g., small practices, rural settings, safety net clinics) and the usability of these tools to determine what is working &and what is missing in reducing disparities in quality of care and outcomes, as well as to improve patient safety (e.g., identification of patients at risk for medication errors/care delays; reduction of diagnostic errors; patients at risk of low or inadequate adherence to medical therapy; patients at increased risk of drug-drug interactions and medication adverse events).
- Enable interoperability of health IT tools (e.g., mobile apps, wearables, and other devices) with EHR systems to support the integration across high and low-resource clinical settings, health care systems- including communication between different segments of health care such as pharmacy chains with providers- to screen, communicate, share data, and enhance decision support for patients and providers.
- Advance human-centered design methodologies/novel approaches of tailoring innovations to fit end-users to develop multilevel communication tools to translate, transcribe, and analyze patient information into digital platforms.
Specific Areas of Research Interest for National Cancer Institute (NCI)
The National Cancer Institute encourages applications designed to study the impact of leveraging health IT tools (including, but not limited to, electronic medical records, patient portals, telehealth, and digital health tools, if data are linked to health system tools following the scope of this PAR) to reduce cancer health disparities and promote health equity. NCI is interested in research across the cancer control continuum, including cancer prevention, detection, diagnosis, treatment, survivorship, or end-of-life. Studies that incorporate two or more of the following levels of influence on cancer control outcomes are a priority: individual (patient, caregiver, clinical provider), family, clinical team, health care institution, community, and policy environment. Studies should focus on improving cancer-related health communication; healthcare delivery processes including coordination of cancer care, collaboration and other teamwork processes; behavioral and health outcomes; access to care across the cancer control continuum; or quality of cancer-related care among populations affected by cancer health disparities. Studies that examine whether health IT tools can be leveraged to address structural barriers to equitable cancer care are within scope. Studies that examine the efficacy, acceptability, and implementation of health IT tools to reduce digital, communication, and health inequalities, with consideration for usability and clinical workflow integration in cancer-related care, are encouraged. Studies that evaluate patient-centered, clinician and patient facing health IT to improve cancer-related outcomes and healthcare services are also encouraged. Studies may examine the adoption and adaptation of cancer-focused evidence-based interventions in health IT platforms or the scale up and implementation of cancer-focused evidence-based health IT interventions. NCI encourages intervention components to be clearly specified and guided by theory, and disparities and inequalities defined within the scope of this PAR. Mixed methods study designs and practitioner engaged approaches are within scope. NCI encourages studies to consider the influence of social determinants of health (e.g., broadband access, health literacy, healthcare access, structural racism and bias) on health IT interventions, and efforts to mitigate unintended consequences for health IT interventions to exacerbate health inequalities.
Note, NCI’s definition for health disparities and health equity: https://cancercontrol.cancer.gov/hdhe/about/background
Specific Areas of Research Interest for National Eye Institute (NEI)
The National Eye Institute (www.nei.nih.gov) supports basic and clinical research into diseases and disorders of the visual system and the special needs of people with impaired vision or who are blind. NEI is particularly interested in research of improved methods for delivering vision care and rehabilitation in underserved populations including people in urban and rural settings. Research topics may include but are not limited to telemedicine, screening and automated diagnosis, medication adherence, quality of life, and rehabilitation strategies for those with vision loss.
NEI would only support clinical trial applications for this FOA that fulfill the NIH requirements for either a mechanistic or minimal risk trials. A mechanistic trial is designed to understand a biological or behavioral process, the pathophysiology of a disease, or the mechanism of action of an intervention. A minimal risk trial is one in which the probability and magnitude of harm or discomfort anticipated in the research are not greater in and of themselves than those ordinarily encountered in daily life or during the performance of routine physical or psychological examinations or tests.
Specific Areas of Research Interest for National Institute of Mental Health (NIMH) in the Division of Services and Intervention Research (DSIR)
NIMH encourages research that addresses the institute’s scientific priorities, including the National Advisory Mental Health Council workgroup report on Opportunities and Challenges of Developing Information Technologies on Behavioral and Social Science Clinical Research and NOT-MH-18-031. NIMH encourages research that is aligned with these recommended areas for domestic non-AIDS and AIDS-related mental health research. All applications to NIMH involving clinical trials are expected to follow the NIMH mechanism-based, experimental therapeutics approach to intervention development and testing (see Support for Clinical Trials at NIMH and contact NIMH program staff for more information about NIMH clinical trials practices and research priorities).
NIMH encourages a deployment-focused model of intervention and services design and testing that takes into account the perspective of relevant stakeholders (e.g., service users, providers, administrators, payers) and the key characteristics of the settings (e.g., resources, including workforce capacity; existing clinical workflows) that are intended to implement mental health interventions. This attention to end-user perspectives and characteristics of intended clinical and/or community practice settings is intended to ensure the resultant interventions and service delivery strategies are acceptable to consumers and providers, the approaches are feasible and scalable in the settings where individuals are served, and the research results will have utility for end users.
NIMH’s DSIR areas of interest include, but are not limited to, research focused on the following:
- evaluating health IT tools to address disparities in the early detection and treatment of mental illnesses and suicide risk.
- optimizing and testing health IT tools to address factors perpetuating disparities in mental health service access, engagement, quality, and health outcomes across diverse settings.
- evaluating health IT tools to improve equity in the detection and treatment of the general health of people with serious mental illness and to address disparities in premature mortality in this population.
- examining health IT tools to help promote equity in the rapid identification of people with early psychosis and to facilitate timely engagement in evidence-based Coordinated Specialty Care.
- developing and testing health IT tools that support shared decision making to improve equity in the availability and delivery of appropriate, high quality mental health care.
- optimizing the integration of information regarding psychiatric/suicide risk, including crisis services information (e.g., emergency services (ED or 911) or crisis center encounters and assessments; safety plans; precipitating stressors such as housing or food insecurity, etc.) to improve coordination, continuity, and overall quality of mental health services.
- examining the impact of integrating individual- and/or community-level SDoH in heath IT systems on the mental health services outcomes of populations affected by heath disparities.
- examining sources of bias in ML/AI applications and related approaches that utilize health information and other data and developing strategies to facilitate accuracy and fairness in predictive algorithms and other AI-based health IT tools to improve disparities in mental health services outcomes and related morbidity and mortality (e.g., suicide).
- developing and testing stakeholder-informed decision-making tools, and evaluating the implementation, adoption, and systems integration of ML/AI algorithms within existing clinic workflows (e.g., for detection and treatment of mental disorders, comorbidities such as substance use, and suicide risk) to reduce health care inequalities.
- leveraging health IT data by integrating additional data sources (e.g., geolocation data, social media streams) to investigate of the role of social (e.g., stigma), economic (e.g., employment), and structural factors (e.g., structural racism and discrimination, geographic and neighborhood factors) on the uptake of HIV testing, preexposure prophylaxis (PrEP) and other biomedical HIV prevention strategies among individuals from high-incidence populations.
- investigating health IT tools, including the ongoing identification, mitigation, and elimination of implicit biases, to optimize PrEP access, uptake, and retention in hard-to-reach populations.
- optimizing telehealth care delivery models to increase access to HIV prevention and care services in underserved populations.
- leveraging patient perspectives in evaluating the implementation, adoption, and systems integration of ML/AI algorithms within existing HIV clinic workflows to reduce health care inequalities.
- leveraging health IT data by integrating additional data sources (e.g., geolocation data, social media streams) to investigate of the role of social (e.g., stigma), economic (e.g., employment), and structural factors (e.g., structural racism and discrimination, geographic and neighborhood factors) on the uptake of antiretroviral therapy (adherence or persistence) among people living with HIV from marginalized communities.
- examining health IT tools used to assess, monitor, and support antiretroviral adherence and treatment that considers privacy, confidentiality, and equitable access for people living with HIV.
- examining the impact of using ML/AI algorithms to inform HIV risk assessments, diagnoses, and treatment decision-making on disparities in healthcare quality or outcomes.
Specific Areas of Research Interest for The National Library of Medicine (NLM)
- The National Library of Medicine (NLM) is interested in submissions that incorporate innovative biomedical informatics and data science approaches that harness the digital healthcare ecosystem and have the potential to reduce health disparities while improving access to care, continuity of care, and/or health outcomes. Further, NLM is interested in research that leverages health data and develops approaches (e.g., clinical decision support systems and machine learning/artificial intelligence applications) that account for systematic biases and blind spots in health data and leads to tools and approaches that are accurate for all patient populations
Modified to Read: (in bold italics):
In Part 2. Full Text of Announcement
Section I. Funding Opportunity Description
NIMHD Areas of Special interests include but are not limited to the following:
- Interventions that address the utility and impact of including SDoH and community level geocoded data and/or perceived community level measures in EHRs on the health outcomes of populations affected by health disparities.
- Evaluation of when in the clinical workflow would SDoH and community level geocoded data in EHRs have the most beneficial impact on health outcomes and evaluation of unintended adverse effects (e.g., stigma) of incorporating SDoH in EHRs.
- Interventions that address the additional health literacy and numeracy demands of EHR driven conversations on shared decision making, quality of patient-clinician communication, and health outcomes; types of interventions and personalized tailoring needed to foster engagement of patients with EHR portals for communication and access to PHRs to encourage informed shared decisions and quality of communication between patient and clinician in a sustained and relevant way.
- Examination of the differences in adoption rates of patient access to portals for communication and review of PHRs-including addressing reasons (e.g., distrust of medical research, privacy).
- The unintended consequences of EHR use on patient – clinician and clinician-clinician communication and relationships, and health outcomes among populations affected by health disparities.
- The impact of using automated algorithms (ML/AI) to inform disease risk assessment, detection, diagnoses, and treatment decision-making on disparities in healthcare quality or outcomes.
- Interventions to utilize patient generated health data (PGHD) which can include NIH patient-reported outcomes measures, (e.g., www.nihpromis.org), in ambulatory care practices to improve health outcomes.
- Interventions to address clinician and patient burden, caregiver burden, poor usability, and workflow integration faced by clinicians to effectively utilize PGHD in clinics.
- Evaluation of telehealth policies (e.g., regulatory waivers issued by the Centers for Medicare and Medicare Services; Accountable Care Organization/ACO payment model; credentialing of clinicians/care team delivering telehealth services) on access to care.
- Impact of telehealth care delivery models on quality of care, health outcomes, healthcare utilization, patient self-management/decision making, and costs.
- Interventions to address the challenges, including SDoH and health literacy, that can impact telehealth engagement and adherence to treatment plans.
- Multi-level (patient, caregivers or support system of patient, clinicians, and health care system) interventions that leverage health IT to improve the care of complex chronic diseases in diverse primary care settings – including safety net clinics and patient-centered medical homes (PCMH).
- Intervention studies of leveraging health IT for quality improvement in less resourced primary care practices.
- Intervention studies of EHRs/CDS use to manage care in diverse settings (e.g., small practices, rural settings, safety net clinics) and the usability of these tools to determine what is working and what is missing in reducing disparities in quality of care and outcomes, as well as to improve patient safety (e.g., identification of patients at risk for medication errors/care delays; reduction of diagnostic errors; patients at risk of low or inadequate adherence to medical therapy; patients at increased risk of drug-drug interactions and medication adverse events).
- Enable interoperability of health IT tools (e.g., mobile apps, wearables, and other devices) with EHR systems to support the integration across high and low-resource clinical settings, health care systems- including communication between different segments of health care such as pharmacy chains with providers- to screen, communicate, share data, and enhance decision support for patients and providers.
- Advance human-centered design methodologies/novel approaches of tailoring innovations to fit end-users to develop multilevel communication tools to translate, transcribe, and analyze patient information into digital platforms.
National Institute on Aging (NIA) is interested in:
- Studies that utilize the NIA Framework on Health Disparities to evaluate health IT interventions among older adults.
- Studies that can identify and facilitate the integration of core data elements related to social determinants of health and adverse childhood experiences, and family-level data of relevance to patient health, safety, and risks and that would be relevant to care plan implementation (for both chosen and biological families).
- Development of EHR-integrated family-centered goal-setting andadvance care and financial planning tools.
- Research that can improve the detection of bias in phenotypingalgorithms in diagnosis and clinical care plans.
- Integration of cohort-sensitive sexual orientation and gender identity measures in the development of care plans for older adults.
- Research that can assess the quality and extent to which EHR clinical communication informs clinical testing, diagnostic and treatment decision making, care plan adherence, and patient outcomes, for clinical communications involving patients and/or caregivers.
- Evaluation of health IT interventions among people living with Alzheimer’s Disease and Related Dementias.
- Health IT interventions that leverage health IT to reduce disparities among people living with Alzheimer’s Disease and Related Dementias.
Specific Areas of Research Interest for the National Cancer Institute (NCI)
- The National Cancer Institute encourages applications designed to study the impact of leveraging health IT tools (including, but not limited to, electronic medical records, patient portals, telehealth, and digital health tools, if data are linked to health system tools following the scope of this PAR) to reduce cancer health disparities and promote health equity. NCI is interested in research across the cancer control continuum, including cancer prevention, detection, diagnosis, treatment, survivorship, or end-of-life. Studies that incorporate two or more of the following levels of influence on cancer control outcomes are a priority: individual (patient, caregiver, clinical provider), family, clinical team, health care institution, community, and policy environment. Studies should focus on improving cancer-related health communication; healthcare delivery processes including coordination of cancer care, collaboration and other teamwork processes; behavioral and health outcomes; access to care across the cancer control continuum; or quality of cancer-related care among populations affected by cancer health disparities. Studies that examine whether health IT tools can be leveraged to address structural barriers to equitable cancer care are within scope. Studies that examine the efficacy, acceptability, and implementation of health IT tools to reduce digital, communication, and health inequalities, with consideration for usability and clinical workflow integration in cancer-related care, are encouraged. Studies that evaluate patient-centered, clinician and patient facing health IT to improve cancer-related outcomes and healthcare services are also encouraged. Studies may examine the adoption and adaptation of cancer-focused evidence-based interventions in health IT platforms or the scale up and implementation of cancer-focused evidence-based health IT interventions. NCI encourages intervention components to be clearly specified and guided by theory, and disparities and inequalities defined within the scope of this PAR. Mixed methods study designs and practitioner engaged approaches are within scope. NCI encourages studies to consider the influence of social determinants of health (e.g., broadband access, health literacy, healthcare access, structural racism and bias) on health IT interventions, and efforts to mitigate unintended consequences for health IT interventions to exacerbate health inequalities.
- Note NCI’s definition for health disparities and health equity: https://cancercontrol.cancer.gov/hdhe/about/background
Specific Areas of Research Interest for the National Eye Institute (NEI)
The National Eye Institute (www.nei.nih.gov) supports basic and clinical research into diseases and disorders of the visual system and the special needs of people with impaired vision or who are blind. NEI is particularly interested in research of improved methods for delivering vision care and rehabilitation in underserved populations including people in urban and rural settings. Research topics may include but are not limited to telemedicine, screening and automated diagnosis, medication adherence, quality of life, and rehabilitation strategies for those with vision loss.
NEI would only support clinical trial applications for this FOA that fulfill the NIH requirements for either a mechanistic or minimal risk trials. A mechanistic trial is designed to understand a biological or behavioral process, the pathophysiology of a disease, or the mechanism of action of an intervention. A minimal risk trial is one in which the probability and magnitude of harm or discomfort anticipated in the research are not greater in and of themselves than those ordinarily encountered in daily life or during the performance of routine physical or psychological examinations or tests.
Specific Areas of Research Interest for the National Institute on Aging (NIA):
- Studies that utilize the NIA Framework on Health Disparities to evaluate health IT interventions among older adults.
- Studies that can identify and facilitate the integration of core data elements related to social determinants of health and adverse childhood experiences, and family-level data of relevance to patient health, safety, and risks and that would be relevant to care plan implementation (for both chosen and biological families).
- Development of EHR-integrated family-centered goal-setting and advance care and financial planning tools.
- Research that can improve the detection of bias in phenotyping algorithms in diagnosis and clinical care plans.
- Integration of cohort-sensitive sexual orientation and gender identity measures in the development of care plans for older adults.
- Research that can assess the quality and extent to which EHR clinical communication informs clinical testing, diagnostic and treatment decision making, care plan adherence, and patient outcomes, for clinical communications involving patients and/or caregivers.
- Evaluation of health IT interventions among people living with Alzheimer’s Disease and Related Dementias.
- Health IT interventions that leverage health IT to reduce disparities among people living with Alzheimer’s Disease and Related Dementia
Specific Areas of Research Interest for National Institute of Biomedical Imaging and Bioengineering (NIBIB)
- For this Funding Opportunity Announcement, if an application proposes a clinical trial, NIBIB funding of clinical trials will be in accordance with NOT-EB-21-005, “NIBIB Guidance for Support of Clinical Trial Applications.” Briefly, NIBIB will only support mission-focused (see NIBIB’s program areas) early clinical trial applications, i.e., feasibility, phase1, first-in-human, safety, or other small clinical trials, that inform early-stage technology development. NIBIB will not support applications proposing pivotal, phase II, III, IV, or trials in which the primary outcome is efficacy, effectiveness, or a post-market concern. Also, mechanistic trials are not supported unless the primary focus of the project is on technology development.
- Applicants are strongly encouraged to contact NIBIB Scientific Contact listed in this FOA for guidance in advance of submitting an application that includes human subjects research to ensure their proposed project is in compliance with new NIH human subjects research and clinical trial policies (https://grants.nih.gov/policy/clinical-trials.htm) and consistent with the types of clinical trial applications that NIBIB supports.
Specific Areas of Research Interest for National Institute of Mental Health (NIMH) in theDivision of Services and Intervention Research (DSIR)
NIMH encourages research that addresses the Institute’s scientific priorities, including the National Advisory Mental Health Council workgroup report on Opportunities and Challenges of Developing Information Technologies on Behavioral and Social Science Clinical Research and NOT-MH-18-031. NIMH encourages research that is aligned with these recommended areas for domestic non-AIDS and AIDS-related mental health research. All applications to NIMH involving clinical trials are expected to follow the NIMH mechanism-based, experimental therapeutics approach to intervention development and testing (see Support for Clinical Trials at NIMH and contact NIMH program staff for more information about NIMH clinical trials practices and research priorities).
NIMH encourages a deployment-focused model of intervention and services design and testing that takes into account the perspective of relevant stakeholders (e.g., service users, providers, administrators, payers) and the key characteristics of the settings (e.g., resources, including workforce capacity; existing clinical workflows) that are intended to implement mental health interventions. This attention to end-user perspectives and characteristics of intended clinical and/or community practice settings is intended to ensure the resultant interventions and service delivery strategies are acceptable to consumers and providers, the approaches are feasible and scalable in the settings where individuals are served, and the research results will have utility for end users.
NIMH’s DSIR areas of interest include, but are not limited to, research focused on the following:
- Evaluating health IT tools to address disparities in the early detection and treatment of mental illnesses and suicide risk.
- Optimizing and testing health IT tools to address factors perpetuating disparities in mental health service access, engagement, quality, and health outcomes across diverse settings.
- Evaluating health IT tools to improve equity in the detection and treatment of the general health of people with serious mental illness and to address disparities in premature mortality in this population.
- Examining health IT tools to help promote equity in the rapid identification of people with early psychosis and to facilitate timely engagement in evidence-based Coordinated Specialty Care.
- Developing and testing health IT tools that support shared decision making to improve equity in the availability and delivery of appropriate, high quality mental health care.
- Optimizing the integration of information regarding psychiatric/suicide risk, including crisis services information (e.g., emergency services (ED or 911) or crisis center encounters and assessments; safety plans; precipitating stressors such as housing or food insecurity, etc.) to improve coordination, continuity, and overall quality of mental health services.
- Examining the impact of integrating individual- and/or community-level SDoH in heath IT systems on the mental health services outcomes of populations affected by heath disparities.
- Examining sources of bias in ML/AI applications and related approaches that utilize health information and other data and developing strategies to facilitate accuracy and fairness in predictive algorithms and other AI-based health IT tools to improve disparities in mental health services outcomes and related morbidity and mortality (e.g., suicide).
- Developing and testing stakeholder-informed decision-making tools, and evaluating the implementation, adoption, and systems integration of ML/AI algorithms within existing clinic workflows (e.g., for detection and treatment of mental disorders, comorbidities such as substance use, and suicide risk) to reduce health care inequalities.
- Leveraging health IT data by integrating additional data sources (e.g., geolocation data, social media streams) to investigate the role of social (e.g., stigma), economic (e.g., employment), and structural factors (e.g., structural racism and discrimination, geographic and neighborhood factors) on the uptake of HIV testing, preexposure prophylaxis (PrEP) and other biomedical HIV prevention strategies among individuals from high-incidence populations.
- Investigating health IT tools, including the ongoing identification, mitigation, and elimination of implicit biases, to optimize PrEP access, uptake, and retention in hard-to-reach populations.
- Optimizing telehealth care delivery models to increase access to HIV prevention and care services in underserved populations.
- Leveraging patient perspectives in evaluating the implementation, adoption, and systems integration of ML/AI algorithms within existing HIV clinic workflows to reduce health care inequalities.
- Leveraging health IT data by integrating additional data sources (e.g., geolocation data, social media streams) to investigate of the role of social (e.g., stigma), economic (e.g., employment), and structural factors (e.g., structural racism and discrimination, geographic and neighborhood factors) on the uptake of antiretroviral therapy (adherence or persistence) among people living with HIV from marginalized communities.
- Examining health IT tools used to assess, monitor, and support antiretroviral adherence and treatment that considers privacy, confidentiality, and equitable access for people living with HIV.
- Examining the impact of using ML/AI algorithms to inform HIV risk assessments, diagnoses, and treatment decision-making on disparities in healthcare quality or outcomes.
Specific Areas of Research Interest for the National Library of Medicine (NLM)
- The National Library of Medicine (NLM) is interested in submissions that incorporate innovative biomedical informatics and data science approaches that harness the digital healthcare ecosystem and have the potential to reduce health disparities while improving access to care, continuity of care, and/or health outcomes. Further, NLM is interested in research that leverages health data and develops approaches (e.g., clinical decision support systems and machine learning/artificial intelligence applications) that account for systematic biases and blind spots in health data and leads to tools and approaches that are accurate for all patient populations.
Currently Reads:
Part 2. Full Text of Announcement
Section VII. Agency Contacts
Scientific/Research Contact(s)
Yewande A. Oladeinde, Ph.D.
National Institute on Minority Health and Health Disparities (NIMHD)
Telephone: 301-402-4307
Email: yewande.oladeinde@nih.gov
April Oh, Ph.D., MPH
National Cancer Institute (NCI)
Telephone: 240-276-6709
Email: April.oh@mail.nih.gov
NLM - NATIONAL LIBRARY OF MEDICINE
Phone: 301.761.6249
E-mail: sufianm@mail.nih.gov
Christine M. Ulbricht, Ph.D.
National Institute of Mental Health (NIMH)
Telephone: 301-480-6928
Email: christine.ulbricht@nih.gov
James Gao
NEI - NATIONAL EYE INSTITUTE
Phone: 301.594.6074
E-mail: james.gao@nih.gov
Lori A J. Scott-Sheldon, Ph.D.
National Institute on Mental Health (NIMHD).
Telephone: 301-792-2309
Email: lori.scott-sheldon@nih.gov.
Christopher Barnhart, PhD
Sexual & Gender Minority Research Office (SGMRO)
Telephone: 301-594-8983
Email: christopher.barnhart@nih.gov
Meryl Sufian
NLM - NATIONAL LIBRARY OF MEDICINE
Phone: 301.761.6249
E-mail: sufianm@mail.nih.gov
Tiffani Bailey Lash
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Phone: 301-451-4778
E-mail: baileyti@mail.nih.gov
Priscilla Novak, PhD MPH
Program Official
Email: Priscilla.Novak@nih.gov
Phone 301-496-3136
Division of Behavioral and Social Research
National Institute on Aging
Christine M. Ulbricht, Ph.D.
National Institute of Mental Health (NIMH)
Telephone: 301-480-6928
Email: christine.ulbricht@nih.gov
James Gao
NEI - NATIONAL EYE INSTITUTE
Phone: 301.594.6074
E-mail: james.gao@nih.gov
Modified to Read (in bold italics):
Part 2. Full Text of Announcement
Section VII. Agency Contacts
Scientific/Research Contact(s)
Yewande A. Oladeinde, Ph.D.
National Institute on Minority Health and Health Disparities (NIMHD)
Phone: 301-402-4307
Email: yewande.oladeinde@nih.gov
Heather D-Angelo, Ph.D., MHS
National Cancer Institute (NCI)
Phone: 240-276-5518
Email: heather.dangelo@nih.gov
James Gao, Ph.D.
National Eye Institute (NEI)
Phone: 301.594.6074
Email: james.gao@nih.gov
Priscilla Novak, Ph.D., MPH
National Institute on Aging (NIA)
Phone 301-496-3136
Email: Priscilla.Novak@nih.gov
Tiffany Bailey Lash, Ph.D.
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Phone: 301-451-4778
Email: baileyti@mail.nih.gov
Qi Duan, Ph.D.
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Phone: 301-451-4780
Email: qi.duan@nih.gov
Christine M. Ulbricht, Ph.D.
National Institute of Mental Health (NIMH)
Phone: 301-480-6928
Email: christine.ulbricht@nih.gov
Lori A J. Scott-Sheldon, Ph.D.
National Institute on Mental Health (NIMH)
Division of AIDS Research
Phone: 301-792-2309
Email: lori.scott-sheldon@nih.gov
Meryl Sufian, Ph.D.
National Library of Medicine (NLM)
Phone: 301.761.6249
Email: sufianm@mail.nih.gov
Christopher Barnhart, PhD
Sexual & Gender Minority Research Office (SGMRO)
Phone: 301-594-8983
Email: christopher.barnhart@nih.gov
All other aspects of this FOA remain the same.
Yewande A. Oladeinde, Ph.D.
National Institute on Minority Health and Health Disparities (NIMHD)
Phone: 301-402-4307
Email: yewande.oladeinde@nih.gov
and Human Services (HHS)
