This funding opportunity announcement (FOA) seeks to support research that examines the impact of leveraging health information technology (health IT) to reduce disparities by increasing access to care, delivery of higher quality of care, improving patient-clinician communication, and health outcomes for minority health and health disparity populations in the U.S. .
Recommended length: 1-5 pages. Present the purpose of the funding opportunity in paragraph form, addressing all of the items below. Please keep in mind that readers will appreciate clarity and brevity. The following headers may be useful in preparing this section:
Purpose/Research objectives (describe the nature and need of the research opportunity)
Specific Areas of Research Interest (include examples of research topics. In such cases, add a statement indicating that appropriate topics “include but are not limited to those listed below.” If R01, R21, and R03 companions are issued, add a few sentences to the R21 and R03 to differentiate them. The parent announcements can be used as reference.
Background:
Health information technology (health IT) has tremendous potential for increasing health equity for racial and ethnic populations. Health IT tools such as electronic health records (EHRs), patient portals/patient health records (PHRs), and clinical decision support (CDS) may yield population health benefits for underserved populations by enhancing patient engagement, improving implementation of clinical guidelines, patient safety, and reducing adverse outcomes. EHRs and CDS may help improve documentation of social determinants of health (SDoH) & inform patient care for those most vulnerable who have multiple chronic diseases and higher health risks. Availability of real time actionable patient data , clinical care coordination, and decision support enabled by health IT tools may also reduce disparities in quality of care for underserved populations who often experience a greater burden of chronic diseases and are more likely to demonstrate signs of poor management of chronic disease. Better clinical care coordination via health IT could improve clinician performance and adherence to clinical guidelines, reduce redundant testing due to clinician biases, detect treatment risks, and thus consequently facilitate equitable treatment for underserved populations.
Although health IT holds much promise for reducing disparities in underserved populations by facilitating behavior change and improving quality of health care services and health outcomes, few studies have examined the impact of health IT adoption on racial/ethnic disparities in outcomes. In fact, the federal health IT strategic plan 2015-2020 (https://www.healthit.gov/sites/default/files/9-5-federalhealthitstratplanfinal_0.pdf ) calls for research evidence on how health IT can reduce disparities in the quality, accessibility, and safety of health care and long-term support services.
Of the limited studies, the findings, for example, indicate that health IT investment can reduce disparities in process of care and care standardization. Additionally, attention to unintended consequences associated with the use of health IT needs to be monitored to ensure health disparities are not inadvertently exacerbated. Research is needed to investigate the potential unintended consequences of health technologies such as, impact on clinician-patient communication in general and with vulnerable patients in particular, barriers that prevent the uptake and engagement with EHRs and PHRs by medically underserved patients, effective approaches and models to deliver CDS in safety net clinical settings, and the best models for the inclusion and utility of SDoH in EHR systems/CDS tools that will have the most effect of improving health equity for racial and ethnic populations.
Health IT and Primary Care Transformation :
Research is also needed to explore the contributions of health IT on new models of primary care delivery such as advanced primary care and the patient-centered medical home (PCMH), in a variety of settings- particularly in safety net clinics . Health IT tools are vital to the success of the PCMH innovation effort which holds promise for achieving the triple aim of improved population health, lower co sts, and better patient experiences in health care. For example, clinical data from patient registries can help clinicians identify gaps in care and opportunities for outreach. EHRs can facilitate teamwork to ensure follow up of key test results are completed and care gaps of patients are addressed. E vidence-based solutions are also called for in low resource primary practice settings where the potential benefits of health IT are greater g iven challenges to utilize EHR systems for quality improvement of care processes.
Health IT tools can also have potential for great utility in the care of complex chronic diseases (e.g., CKD/ Chronic Kidney Disease, RA/ R heumatoid Arthrit is, COPD/Chronic Obstructive Pulmonary Disease , post-solid organ transplants ) in primary care settings that serve health disparity populations who often experience a disproportionate burden of chronic diseases and require more complex care because of co-morbidit ies. For example, CKD is often poorly detected in primary care and treatment is suboptimal. Emerging evidence indicates support for the use of electronic CKD registries to enable guideline-concordant care of CKD in primary care settings.
Research is needed to explore the potential of decision support tools, and new technologies such as artificial intelligence and natural language processing on EHR platforms , to improve health outcomes for complex chronic diseases . Limited studies exist that investigate RA outcome improvements via EHR interventions in clinical care in diverse settings. Primary care EHR data and CDS tools to improve the uptake of COPD guidelines also warrants further investigation to determine the practice patterns most effective for disease management in diverse primary care settings . I mple mentation models that leverage health IT to manage the health outcomes of vulnerable patients who have received solid organ transplants in partnership with transplant specialists are also needed.
Health IT and Patient-Clinician Communication:
The complexities of patient-clinician communication in the era of EHRs will also need to be evaluated with ethnically diverse vulnerable populations with chronic disease since communication barriers during medical encounters may further augment health disparities via decreased patient participation in shared decision making. Additionally, changes such as information overload, documentation burden, and stress that EHRs bring to relationships – between patients and clinicians or between clinicians – warrant further investigation in the context of minority health and health disparity populations . Patients of safety net clinics often face challenges of limited digital and health literacy, and/or English proficiency, that impede their usability of patient portals. This disparity in usability of patient health portals raises the concern that a “digital divide” may exclude the most vulnerable patients from the benefits of portal use. The issue of a “digital divide” will also need to be investigated in other specialty settings such as oncology to determine how patients from vulnerable populations access incoming portal data.
Health IT and Social Determinants of Health (SDoH) :
Finally, the inclusion of SDoH in EHR/CDs is critical for advancing population health equity. R esearch is needed to explore the optimal approaches of collecting and integrating SDoH into EHRs /CDs to effectively guide clinical care and increase shared decision making between physicians and patients . The American College of Physicians published a position statement on SDoH (https://www.acponline.org/acp_policy/policies/addressing_social_determinants_to_improve_patient_care_2018.pdf ) recommending the development of best practices of utilizing EHRs to screen and collect SDoH data to assist in health impact assessment and inform evidence driven decisions. Documentation of SDoH into EHRs is also supported by the National Academy of Medicine (2014). SDoH, as defined by healthyPeople.gov ( https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-of-health ) are “conditions in the environment in which people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks.” Examples of SDoH factors of interest include finance (e.g., employment, income, debt, food security) , neighborhood/built environment (e.g., housing, transportation, public safety, walkability, parks, social capital, access to local food markets, residential segregation) , education (e.g, literacy, access to job training) , and a ccess to health care services .
Advances in big data, geospatial technology, and public access to large data sets that provide contextual information also make it feasible to embed community level geocoded data into EHRs. Having this geocoded data readily available would allow healthcare teams to see for example, if patients live in a high poverty area, have access to healthy food sources, walkable streets, social capital, and how these resources (or lack of) predict increase risks for adverse health outcomes and impact treatment adherence. CDS tools could provide alerts to healthcare teams of patients who, for example, may need to be screen or monitored for depression based on a community level predictor (e.g. high unemployment) or public health concern. Research is needed to examine when and how in the clinical workflow geocoded community level data can be utilized with CDS tools to have the most impact on health outcomes of vulnerable patients. In addition, individual perception of community level metrics such as perceived safety, access to healthy food and community cohesion, may be utilized in a similar manner.
Research Objectives
This funding opportunity announcement (FOA) seeks to support the use of clinical trials, comparative effectiveness research, observational studies, and implementation science to investigate how to leverage health information technology (health IT) to improve minority health care and reduce health disparities by increasing access to care, delivery of higher quality care, improving patient-clinician communication and health outcomes for minority health and health disparity populations in the U.S.
Research Methodology
Projects should include a focus on one or more NIH-designated health disparity populations in the United States, which include Blacks/African Americans, Hispanics/Latinos, American Indians/Alaska Natives, Asians, Native Hawaiians and other Pacific Islanders, socioeconomically disadvantaged populations of any race, underserved rural populations, and sexual and gender minorities. Projects should involve collaborations from relevant stakeholders in U.S. health disparity population groups, such as researchers, community organizations, healthcare systems or clinics, clinicians, public health organizations, consumer advocacy groups, and faith-based organizations.
Projects that focus exclusively on mHealth interventions at the patient level (e.g., the use of fitness related mobile applications), in the absence of incorporation of health IT elements within a healthcare system, are not targeted for support in this FOA.
Projects that examine the financing of health care or the cost and efficiency of health care service delivery, without linking such economic analysis to measurable health outcomes, are considered outside of NIH’s mission and will not be supported. See NOT-OD-16-025 for more information.
Specific Areas of Research Interest
Areas of research interest include but are not limited to the following:
- Implementation models of delivering CDS in diverse settings (e.g. small, rural, safety net clinics) and the usability of these tools to determine what is working & what is missing in reducing disparities in quality of care and outcomes;
- Multi-level (system, clinician , patient) i nterventions that leverage health IT to improve the care of complex chronic diseases in diverse primary care settings – including PCMH- that serve health disparity populations ;
- Implementation models of leveraging health IT for quality improvement in less resourced primary care practices that serve health disparity populations;
- 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 systems, to screen, communicate, share data, and enhance decision support for patients and providers.
- Advance human-centered design methodologies to develop multilevel communication tools to translate, transcribe and analyze patient information into digital platforms. Studies may include examination of implementation and systems integration of digital health technologies within existing health care workflows and home/community settings and organizational and policy impact.
- The unintended negative effects of EHR use on patient – clinician & clinician-clinician communication , relationships, and health outcomes and the impact on underserved health disparity populations;
- The impact of using automated algorithms to inform disease risk assessment, detection, diagnoses, and treatment decision-making on disparities in healthcare quality or outcomes;
- Interventions that address the health literacy demands of EHR driven conversations on shared decision making and the health outcomes of patients in safety net clinics ;
- Disparities in adoption rates of patient portals/PHRs especially among older minority users, rural residents, low-income patients, persons with LEP and/or limited health literacy, and racial/ethnic minority patients;
- The types of interventions/personalization needed to foster patient engagement of patient portals/PHRs in a sustained and relevant way for underserved populations;
- The utility and effectiveness of the inclusion of SDoH & community level geocoded data and/or perceived community level measures in EHRs/CDS on health outcomes;
- Evaluation of when in the clinical workflow can SDoH & community level geocoded data in EHRs/CDS have the most beneficial impact on health outcomes;
National Cancer Institute (NCI)
The National Cancer Institute encourages submission of applications designed to study development, testing and implementation of multi-level digital health technology interventions aimed at improving cancer prevention and control along any aspect of the cancer control continuum to reduce cancer health disparities and promote health equity. These digital health technologies should enable identification or monitoring of health disparities, integration of social determinants of health in patient care and public health (without exacerbating existing disparities), or enable the delivery of interventions to reduce health disparities. Importantly, NCI defines multi-level broadly, to include studies that incorporate interventions addressing two or more of the following levels: individual (patient, caregiver, clinical provider), clinical team (two or more providers including primary and specialty care and support staff), Health care institution ( Collection of primary and specialty care providers, and support staff, health care administrators, medical facilities, and organizational structures. Together these people, institutions and resources provide the environment for the comprehensive delivery of healthcare services) , home, workplace, social network, community setting, , public health, social service, and policy environments. NCI encourages intervention components to be clearly specified and explicitly linked to new, refined, or existing multi-level theories and the digital health technology should be used to connect data, information, communication, interventions across levels. The use of novel and alternative research and intervention designs (e.g., sequential multiple assignment randomized trial (SMART), multiphase optimization strategy (MOST), hybrid effectiveness and implementation designs and factorial experimental designs, human centered design approaches are highly encouraged. Note, NCI’s definition for health disparities and health equity: https://cancercontrol.cancer.gov/research-emphasis/health-disparities.html
NCI is interested in diverse submissions – including but not limited to those that:
- Develop and test effectiveness, acceptability, and adoption of health communication platforms tailored to different environments among racial/ethnic populations and underserved low resource communities for cancer prevention and control.
- Develop and test digital health tools that enable integration of geospatial information and technology designed to facilitate health-related uses of social and environmental data that are spatially linked, including integration that allows for studies examining barriers to accessing health care services and/or cancer care and prevention.
- Development of data visualization, NLP, AI and other products that facilitate communication of electronic health information for prevention or control of cancer or cancer co-morbidities to patients, caregivers and providers in clinical settings. These may include integration of innovative combinations of data (e.g., genetic information, environmental exposures, contextual factors) to inform the design of multi-level interventions aimed at cancer prevention and control.
- Develop and test digital health tools for monitoring and surveillance of health care treatment disparities and racial/ethnic, socioeconomic, gender, and sexual orientation/identity bias, to enhance quality of care for cancer patients and survivors.
- Develop and test IT-based interventions that improve information sharing and care coordination across time and space among clinicians delivering care to cancer patients, especially in rural and other under-served areas.
- Examination of implementation outcomes (e.g., adaptation, acceptability) in developing tools for implementation of decision support tools, mobile health behavioral monitoring protocols, and cancer symptom management platforms.
- Integrate novel patient-generated data capture tools (i.e., wearable technology) to identify clinically-relevant, actionable information to improve patient care and outcomes for cancer health disparities related outcomes.
- Develop, test and or implement tools that enable and enhance patient engagement in chronic disease management and prevention among cancer survivors across age, sociodemographic, health and digital literacy and linguistic barriers.
- Develop and test the efficacy of digital health tools (mobile, EHR) that can be used collectively to promote recruitment, enrollment and data collection for clinical trials, particularly for groups underrepresented in clinical trials.
Office of Behavioral and Social Sciences Research (OBSSR)
The research priorities described in this funding opportunity announcement align well with the OBSSR Strategic Plan (https://obssr.od.nih.gov/about/strategic-plan/ – Priority Two: Enhance and promote the research infrastructure, methods, and measures needed to support a more cumulative and integrated approach to behavioral and social sciences research). OBSSR will not be assigned any applications from this funding opportunity announcement. Instead, OBSSR supports the stated research priorities of the participating Institutes/Centers, and the office may co-fund applications assigned to those Institutes/Centers.
Deadlines: March 4, 2019, March 4, 2020, March 4, 2021 (full proposals; letters of intent due 30 days prior to deadline)
URL: https://grants.nih.gov/grants/guide/pa-files/PAR-19-093.html
Filed Under: Funding Opportunities