ASP.MD — Department of Health and Human Services STTR Phase I: 102
ASP.MD — STTR Phase I award from Department of Health and Human Services.
- Amount
- $255,147
- Agency
- Department of Health and Human Services · National Institutes of Health
- Program / Phase
- STTR · Phase I
- Topic
- 102
- Solicitation
- MD21-005
- NAICS
- —
- Place of performance
- MA
- Period
- 2022-01-13 → 2022-12-31
Description
PROJECT SUMMARY There is an emerging digital divide in healthcare between those who care for disadvantaged patients and those who care for less vulnerable populations. In the past decade, electronic health record (EHR) adoption and use has increased but unequally. Providers caring for disadvantaged populations are less likely to have and use advanced EHRs with sophisticated clinical decision support, analytics, and other functionalities. While EHRs are failing to meet the needs of United States’ providers more generally, EHR-related challenges are particularly acute for providers who treat disadvantaged populations due to time pressures, limited resources, and the need to address many social issues. Furthermore, EHRs have resulted in the accumulation of vast amounts of data, but providers do not have time to sift through it all in a patient encounter – better tools are needed to summarize, organize, and display the data in a way that better supports care. For chronic conditions such as diabetes, providers need to instantly see, assess, and take action on their patients’ status in a glance, without searching through laboratory results, weights, diet, history, medications, notes, and comorbidities scattered throughout a system. ASP.MD and the RAND Corporation have developed preliminary designs for a more usable EHR user interface (UI) that organizes and consolidates clinical data into “Viewers” based on clinically meaningful problems. Viewers are far more advanced than traditional problem lists. They visualize context- relevant longitudinal data, set visit agendas, track tasks, and execute other clinically useful activities. These visual innovations help providers quickly assess a patient’s overall status and specific clinical needs based on their data and symptoms. In this work, we will engage providers who care for Medicaid and other disadvantaged populations to further develop and test this novel EHR UI. In Aim 1, we will use user-centered design methods to develop detailed prototypes and clinical scenarios for testing. The scenarios will be common for providers who treat disadvantaged populations and they will promote improvement on established quality measures. We will integrate these prototypes into an existing EHR, developed by ASP.MD. In Aim 2, we will test the usability of the prototypes through structured sessions. ASP.MD is an ideal setting for developing and testing this innovation by building off its existing, federally certified commercial EHR and practice management systems. ASP.MD’s EHR is web-based, making it possible to immediately distribute new features to all users. We will build using the standards-based fast health interoperability resource (FHIR) application programming interfaces (API), making it possible to use our Viewers with other EHRs as well. This work has the potential to substantially reduce disparities by giving providers who care for disadvantaged populations an affordable, advanced EHR. Providers will have access to relevant, organized, synthesized clinical data at the point of care, facilitating their ability to close quality of care gaps and reducing burnout. It also has the potential to greatly improve the quality of data in EHRs, which can enable further innovation.PROJECT NARRATIVE Healthcare providers who serve Medicaid and other disadvantaged populations struggle to afford and use electronic health records to improve care for their patients. We will design and develop a novel, affordable approach for organizing clinical and social data so that these providers will be able to have relevant, actionable data at the point of care through a cloud-based electronic health record. This innovation has the potential to reduce disparities by empowering providers who care for disadvantaged populations to work more efficiently, optimize their access to relevant clinical data, and facilitate improvements in patient health outcomes.