Patient-centered clinical decision support challenges and opportunities identified from workflow execution models

Abstract

Objective: To use workflow execution models to highlight new considerations for patient-centered clinical decision support policies (PC CDS), processes, procedures, technology, and expertise required to support new workflows.

Methods: To generate and refine models, we used (1) targeted literature reviews; (2) key informant interviews with 6 external PC CDS experts; (3) model refinement based on authors' experience; and (4) validation of the models by a 26-member steering committee.

Results and discussion: We identified 7 major issues that provide significant challenges and opportunities for healthcare systems, researchers, administrators, and health IT and app developers. Overcoming these challenges presents opportunities for new or modified policies, processes, procedures, technology, and expertise to: (1) Ensure patient-generated health data (PGHD), including patient-reported outcomes (PROs), are documented, reviewed, and managed by appropriately trained clinicians, between visits and after regular working hours. (2) Educate patients to use connected medical devices and handle technical issues. (3) Facilitate collection and incorporation of PGHD, PROs, patient preferences, and social determinants of health into existing electronic health records. (4) Troubleshoot erroneous data received from devices. (5) Develop dashboards to display longitudinal patient-reported data. (6) Provide reimbursement to support new models of care. (7) Support patient engagement with remote devices.

Conclusion: Several new policies, processes, technologies, and expertise are required to ensure safe and effective implementation and use of PC CDS. As we gain more experience implementing and working with PC CDS, we should be able to begin realizing the long-term positive impact on patient health that the patient-centered movement in healthcare promises.

Keywords: clinical; decision support systems; patient-generated health data; patient-reported outcome measures; workflow.

Figure 1.

Illustration of a complete, idealized set of relationships and a preferred sequence of processes and tasks between patients, clinicians, EHRs, dashboards, and patient portals or apps for PROs. The process begins in the upper left-hand corner of the model below. In many cases, there are tasks or processes that are performed in parallel (ie, at or near the same point in time) by different actors (either humans or computer applications).

Figure 2.

Description of a complete, idealized set of relationships and a preferred sequence of processes and tasks between patients, clinicians, EHRs, dashboards, PGHD devices, and patient portals or apps for collecting and utilizing PGHD. The process begins in the upper left-hand corner of the model below. In many cases, some tasks or processes are performed in parallel (ie, at or near the same point in time) by different actors (either humans or computer applications).

Figure 3.

Illustration of a process which begins in the upper left-hand corner of the model below. In many cases, there are tasks or processes that are performed in parallel (ie, at or near the same point in time) by different actors (either humans or computer applications).