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. 2024 Oct 23;7(4):ooae109. doi: 10.1093/jamiaopen/ooae109

Table 3.

Summary of stakeholder perspectives of the current state and future challenges for PC CDS.

Key theme Perspectives on the current supportive PC CDS environment Challenges for PC CDS developers and stakeholders moving forward
Gathering patient-contributed data and creating meaningful feedback loops between patients and clinicians
  • Value-based care is driving a shifting mindset amongst clinicians and health systems towards patient-centered care.6

  • There is a growing number of digital tools available to gather patient inputs inside and outside of clinical settings that can facilitate communication and care planning when shared with their clinicians.7,8

  • Patients often contribute data via apps and other digital tools that are subsequently not reviewed by clinicians or integrated into the care process.9

  • There is a need to explore how data collected from patients can be integrated into PC CDS tools and used to create meaningful feedback loops between patients and their clinicians.

Workflows, policies, and procedures for PC CDS
  • Patient data vary by frequency and volume depending on the patient’s conditions and types of data they want to share (eg, health history, biometric, and health activity).

  • Health care systems are adopting various approaches for incorporating patient-generated health data into routine care.10

  • Large volumes of data from digital tools are difficult to integrate into EHRs in an actionable way, and some clinicians have concerns around additional burden to review and act on patient data.11

  • Current workflows in most health systems are not set up to receive and manage patient-contributed data outside of the clinical encounter.12

Expand the evidence base for PC CDS tools
  • PC CDS is a new and emerging field and there is excitement to build the evidence base for the successful use of these tools.

  • Federal efforts from AHRQ and the Assistant Secretary for Technology Policy and Office of the National Coordinator for Health Information Technology aim to build standards for evidence-based PC CDS.13–15

  • There is limited information on best practices and guidance for implementing PC CDS.

  • There is a lack of validated studies and measures for PC CDS in different settings (including low-resource settings) and for a range of use cases.

CDS Five Rights for patient-centered CDS
  • The CDS Five Rights (the right information, to the right person, in the right intervention format, through the right channel, at the right time in the workflow) have guided successful CDS implementation thus far.16

  • The CDS Five Rights apply differently in the context of PC CDS when the patient or caregiver is the receiver.

  • There is a lack of validated frameworks and guidance on how to make PC CDS “fit for purpose,” or how solutions will work for each patient given their specific needs and preferences.

Collection of SDOH and health equity data
  • The Assistant Secretary for Technology Policy and Office of the National Coordinator for Health Information Technology is exploring ways to better capture SDOH data and incorporate it into patient care by establishing new standardized data elements on SDOH Goals17 and assessing guideline recommendations that reference SDOH for standards-based CDS implementation.18

  • There are concerns around integrating SDOH data into the clinical workflow, clinician burden, and lack of trained staff to collect and act on this information.

  • Some EHRs lack the capability to store SDOH data in a standardized format and transmit referrals for social services.

  • There are concerns around PC CDS tools leading to greater inequities in care if not developed, tested, and deployed considering diverse patient populations and low-resource settings.

Stakeholder perspectives of use of AI for PC CDS
  • The emergence of AI has potential to improve patient and clinician outcomes, reduce health care costs, and impact population health.19

  • Federal efforts include the Assistant Secretary for Technology Policy and Office of the National Coordinator for Health Information Technology’s new rule revising the existing CDS criterion to include AI15 and the Food and Drug Administration’s clarified guidance for AI and machine learning technologies that qualify as a medical device.20

  • There is limited data on patient and clinician perspectives on the use of AI in health care and how to maintain trust in healthcare.21

  • More effort and guidance will be needed to minimize disparities driven by health technology and predictive algorithms.22,23

Encourage widespread use and scalability of PC CDS
  • The federal regulatory landscape has introduced standards and harmonization that support the scalability of PC CDS. For example, the Health Level Seven International CDS Hooks, which embeds functionality within a clinician’s workflow of an EHR, has a “patient-view” that triggers when a patient chart is opened and sends basic information about the patient.24

  • While there are public repositories of CDS artifacts, local customization is often needed to support the adoption and use of CDS artifacts.13

  • There is a lack of guidance for articulating the value of PC CDS.

  • There are limitations with writing data to the EHR via FHIR application program interfaces.

  • There is a need to disseminate and scale PC CDS beyond one-time pilot studies.

Abbreviations: AI = artificial intelligence, AHRQ = agency for healthcare research and quality, CDS = clinical decision support, EHR = electronic health record, FHIR = fast healthcare interoperability resources, PC CDS = patient-centered clinical decision support, SDOH = social determinants of health.