Using Technology to Support Patient-Centered, Shared Decision Making in Care and Treatment Decisions
Patient-centered shared decision making refers to the collaborative effort of a healthcare provider, patient, and possibly a caregiver, to reach a healthcare decision that is best for the patient and will help better manage their care. The ideal patient-centered decision considers evidence-based information about available options, the provider's understanding, and the patient's preferences. The following research explores digital healthcare tools for patient-centered, shared decision making:
Dr. Jennifer Blumenthal-Barby and research team at the Baylor College of Medicine are studying the use of a customized CDS system to support left ventricular assist device (LVAD) implementation in patients with advanced heart failure. They are updating and integrating a validated, artificial intelligence-based, online risk-prediction and communication tool, the Cardiac Outcomes Risk Assessment (CORA) tool, and the research team’s own validated LVAD decision aid, Deciding Together, to create a novel tool called the VADDA-CORA. This new tool will offer patients a better understanding of how treatment options align with their values and personalized risks, along with the functionality to communicate these values to the patient’s clinical team.
Dr. Karen Beekman Eden and team at the Oregon Health and Science University are studying the integration of MammoScreen, a breast cancer risk assessment and clinical decision aid, into an EHR system as well as its effect on patient-personalized decision support and acceptability in clinical practice. MammoScreen provides evidence-based guidance for patients facing decisions about mammography screening and genetic counseling and is an effective tool for identifying individual-level risk and promoting shared decision making with clinicians. The research team will use Substitutable Medical Applications Reusable Technologies (SMART)® on Fast Healthcare Interoperability Resources (FHIR) standards to allow seamless data exchange between the external MammoScreen application with the designated EHR. The study aims to inform the implementation and use of health information technology applications for improving the transfer of new evidence into practice and data interoperability across healthcare settings.
Drs. David H. Gustafson and Marie-Louise Mares of the University of Wisconsin–Madison are studying the use of voice-controlled technology to augment Elder Tree, an evidence-based, eHealth laptop application that provides tools and resources for older adults with multiple chronic conditions (MCCs) to manage their health. Through user-centered design, Elder Tree will be enhanced by adding voice command and a smart display. The study aims to increase the accessibility and sustainability of healthcare self-management tools for older adults with MCCs with the goal of increasing quality of life, improving overall health, and reducing hospital readmissions.
Using Patient-Reported Outcomes to Improve Patient Care
Incorporation of brief, validated PRO measures into clinical care to assess outcomes—such as changes in symptoms, emotional health and well-being, and physical and social functioning—is essential to high-quality healthcare. Most PRO data are collected via pen and paper, which is difficult for patients, providers, and researchers to access and use later. While some EHRs capture structured PROs, clinicians do not routinely collect and integrate this information at the point of care. AHRQ is at the forefront of funding innovative research to collect and use PROs that leverage digital healthcare tools to improve patient care and well-being. This research also provides foundational knowledge on how to scale and spread these successful PRO strategies:
Drs. Kevin John Bozic and Joel Tsevat of the University of Texas–Austin are evaluating the effectiveness of a PRO-informed, shared decision making (SDM) tool that estimates the probability of a successful clinical outcome regarding operative versus non-operative treatment for patients with osteoarthritis (OA) of the knee. The research team will implement and evaluate the SDM tool with different patient populations and EHR systems. By centering patients and enabling them to participate in informed medical decision making, the research aims to strengthen the evidence for and promote the scaling of a PRO-guided SDM tool for OA treatment nationally.
Dr. Robert Samuel Rudin and team at RAND Corporation are adapting a successful mHealth app that tracks patients’ self-reported asthma symptoms, and scaling it to primary care settings, where most asthma patients are treated. The app will also incorporate functionality relevant to the COVID-19 pandemic to provide insight into how health systems can identify and recruit high-risk patients for digital home monitoring to reduce utilization of pandemic-related limited emergency and hospital resources.