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Moving the Needle on Advancing Patient-Centered Clinical Decision Support through the CDSiC’s Four Workgroups

Prashila Dullabh, MD, FAMIA; Priyanka Desai, PhD, MSPH, CPH; Elizabeth Cope, PhD, MPH; Rina Dhopeshwarkar, MPH; James Swiger, MBE; Edwin Lomotan, MD

This CDSiC Leadership Viewpoint provides an overview of the Stakeholder Center’s four Workgroups and how their products will contribute to patient-centered clinical decision support (PC CDS).

Introduction

On March 22, 2022, the Clinical Decision Support Innovation Collaborative (CDSiC) launched its Stakeholder and Community Outreach Center (Stakeholder Center), which was convened to address current gaps, needs, and challenges in the field of patient-centered clinical decision support (PC CDS). The four established Workgroups are:

  • The CDS Outcomes and Objectives Workgroup
  • The Scaling, Measurement, and Dissemination of CDS Workgroup
  • The Trust and Patient-Centeredness Workgroup
  • The CDS Standards and Regulatory Frameworks Workgroup

Since the kickoff, 46 Workgroup members – including patients, clinicians, researchers, developers, informaticians, payors, and policymakers – have helped develop 12 written products that will advance development, implementation, and measurement of PC CDS. To gain an understanding of the landscape of PC CDS, the CDSiC Workgroup support teams screened thousands of peer-reviewed and grey literature resources, engaged dozens of PC CDS experts in key informant interviews or focus groups, and convened technical expert panels to support the development of the products.

In this Viewpoint, we provide a brief overview of each Workgroup, the products they are developing, and the products’ anticipated contributions to the PC CDS field.

CDS Outcomes and Objectives Workgroup

The CDS Outcomes and Objectives Workgroup is exploring how to best measure the safety and effectiveness of PC CDS interventions, with a special focus on measuring patient-relevant clinical outcomes. This Workgroup will produce three products that will promote PC CDS measurement.

Product 1: Analysis of Most Appropriate Outcomes for PC CDS

Although a broad set of outcome measures exist for CDS, it is not clear which measures may be appropriate specifically for patient-centered (PC) CDS. This product will focus on the appropriate measures and related considerations for conducting outcomes/impact evaluations of PC CDS initiatives, and a key element of this will be a focus on outcomes that are important to patients. 

The Analysis of Most Appropriate Outcomes for PC CDS will provide a synthesis of outcome measures relevant for measuring the impact of PC CDS. It will also include a description of patient-relevant clinical outcomes, patient-reported outcomes, patient satisfaction and engagement in care, and shared decision-making outcomes. Established measure domains, such as clinical outcomes and patient-reported quality of life, will be discussed through illustrative use cases that highlight exemplar measures and available measure inventories that can be used when evaluators are selecting measures appropriate for their setting.

Product 2: Framework for Understanding the Role of PC CDS in Shared Decision Making

Although much is known about shared decision-making (SDM), there is a knowledge gap regarding how to use PC CDS to facilitate the integration of SDM into clinical practice.[1] The Framework for Understanding the Role of PC CDS will describe the potential role PC CDS can play in supporting each aspect of SDM, outline an agenda for further research, and identify how PC CDS can advance SDM.

Product 3: Framework for Understanding the Role Patient Preferences Play in PC CDS

Patient-centeredness, by definition, means the patient’s needs, values, and preferences are considered in the care process.[2] Along with other patient-generated data such as patient-reported outcomes (PROs), patient preference information can support the generation of clinical recommendations directly informed by patients’ needs and desires.[3] There is no overall framework, however, for understanding which patient preferences should be considered as part of PC CDS.  The Framework for Understanding the Role Patient Preferences Play in PC CDS will be a taxonomy of PC CDS-relevant patient preferences, implementation considerations for the capture and use of patient preferences, and a research agenda to advance the inclusion of patient preferences in PC CDS.

Scaling, Measurement, and Dissemination of CDS Workgroup

The Scaling, Measurement, and Dissemination of CDS Workgroup is identifying measures of PC CDS adoption, implementation, and use to support the scaling of safe and effective PC CDS. This Workgroup will produce three products that will promote the scalability of PC CDS.

Product 1: PC CDS Implementation Description Framework

No overarching framework currently exists for describing implementation of PC CDS interventions and identifying lessons learned and best practices to support continuous improvements in PC CDS implementations. The PC CDS Implementation Description Framework will address this gap by providing a framework for consistency and completeness in reporting on PC CDS interventions, guiding the implementation of new PC CDS applications(e.g., by ensuring implementers attend to all key dimensions of the intervention that support safe, effective, and patient-centered care).

Product 2: Catalog of Approaches Used to Measure Workflow Impact of CDS Interventions

Assessing and improving PC CDS effects on workflow and ‘life flow’ is critical for fully realizing the potential for PC CDS to accelerate care transformation. Minimal work has been done in this area. While CDS interventions can improve care process and outcomes, many CDS interventions are ignored and/or cause excessive burden (e.g., alert fatigue), potentially contributing to the growing problem of clinician burnout.[4] Relatively little is known across studies about how CDS interventions affect clinical workflow. CDS directly involving patients (a major component of PC CDS) is an increasing focus for driving care transformation, but even less is known across studies about how PC CDS affects pertinent patient activities or ‘life flow.’ More information is needed about current approaches to measuring these effects and benchmarking the results to inform development and use of more robust measurement approaches. The Catalog of Approaches Used to Measure Workflow Impact of CDS Interventions will provide an overarching framework for approaches to measure the effects of PC CDS on clinician workflows and patient ‘life flows.’

Product 3: CDS Performance and Value Measurement Guide

Evaluating the development, implementation, and performance of PC CDS tools is key to understanding and maximizing their impact. There is, however, considerable complexity in CDS measurement implementation and interpretation; we lack an understanding of what we should measure and how we should measure it.[5] Further, current CDS performance measurements, which focus on clinician-facing CDS, do not incorporate the unique features of either patient or patient/clinician-facing PC CDS. PC CDS requires special measurement approaches. Improved standardization of measures will help ensure such measurements are accurate and consistent, allowing for valid comparisons across different types of PC CDS and different patient-centered interactions. The CDS Performance and Value Measurement Guide will include recommended measurement and evaluation frameworks, approaches, and measures for evaluating each step of the PC CDS development and implementation process, as well as patient-oriented process outcomes.

Trust and Patient-Centeredness Workgroup

The Trust and Patient-Centeredness Workgroup is exploring how to increase transparency in the process of PC CDS design, development, testing, implementation, and use to build trust in these tools among both patients and clinicians. This Workgroup will produce three products that will promote PC CDS transparency.

Product 1: Handbook to Ensure Patient-Centered Input is Incorporated into CDS Artifact Development

There is a void of guidance documents for incorporating patients and/or stakeholders into the artifact and intervention development process to ensure CDS tools are meaningful to patients and care teams. There is also a lack of standard methods for consistent collection of patient-centered input at time of artifact/intervention development. The Handbook to Ensure Patient-Centered Input is Incorporated into CDS Artifact Development will provide guidance on facilitating inclusion of patient-centric input into the entire PC CDS life-cycle — including guideline selection, prioritization for PC CDS, design, development, and implementation.

Product 2: Best Practices and Methodology for Patient-Centered Co-Design and Co-Deployment of CDS Artifacts

Processes of developing and deploying PC CDS tools that exclude patients limit the likelihood that patient-specific needs will be accounted for and ultimately met, which has implications for the use of these tools. Co-design methodologies (intentionally engaging diverse stakeholders in collaborative design and development activities), which have been successfully applied to software design[6], could provide one model for ensuring more patient-centered approaches to CDS design and deployment.  As of today, few materials document best practices for partnering with patients in co-design and co-deployment of PC CDS. Best Practices and Methodology for Patient-Centered Co-Design and Co-Deployment of CDS Artifacts will document best practices for engaging patients in the co-design and co-deployment of PC CDS. 

Product 3: Root Cause Analysis and Recommendations for Optimization of Trust and Mitigation of Mistrust in CDS Artifacts Due to Source Credibility

For PC CDS to be both used and effective, recipients of the information (e.g., clinicians or patients receiving alerts) must perceive the PC CDS information sources as trustworthy and credible.[7]  Evidence suggests perceptions of source credibility can significantly influence health attitudes, behaviors, and ultimately outcomes. Examination of the specific relationship between perceived source credibility and PC CDS is emerging.  However, there is no common set of best practices or standards-based recommendations that ensure minimum requirements are met to mitigate mistrust in PC CDS artifacts due to a perceived lack of source credibility. The report on Root Cause Analysis and Recommendations for Optimization of Trust and Mitigation of Mistrust in CDS Artifacts Due to Source Credibility will identify and define the factors that influence source credibility of PC CDS tools to improve clinician and patient trust in these resources.  

CDS Standards and Regulatory Frameworks Workgroup

The CDS Standards and Regulatory Frameworks Workgroup is identifying, monitoring, and promoting standards for PC CDS, recommending how to enhance both existing standards, and identifying where new standards and regulatory frameworks are needed. This Workgroup will produce three products that will promote standardized PC CDS.

Product 1: Standards and Regulatory Frameworks Environmental Scan

For PC CDS to scale, computable knowledge must be sharable and interoperable and PC CDS tools must interoperate with electronic health records (EHRs), personal health records, and other clinical systems. The Standards and Regulatory Frameworks Environmental Scan will provide a comprehensive inventory of current PC CDS standards and regulatory frameworks, as well as an action plan for addressing gaps. The environmental scan will characterize the technical landscape of PC CDS and focus on priorities and future directions for standards and regulatory frameworks to further develop, implement, and support PC CDS.

Product 2: Interoperability of Patient Apps with the Health IT Ecosystem

Clinicians are increasingly recommending and prescribing apps to patients to help manage clinical conditions.  Although apps are being prescribed more often,[8] their limited integration with EHRs and other technologies in the health IT ecosystem can cause many issues with the coordination and quality of care, which burdens care teams and patients.[9], [10] A report on the Interoperability of Patient Apps with the Health IT Ecosystem will identify and promote necessary standards to improve interoperability between patient apps and the healthcare IT systems care teams use.

Product 3: Standardized Representation for Patient Preferences

Both clinician and patient-facing CDS apps will require data relevant to patients' specific situations, needs, values, and preferences. Despite the central and prominent role of patient preferences and values in healthcare decision-making, no standard for representing or integrating this information into CDS applications exists. Further, the nature of data on patient preferences and values can vary by clinical domain, medical condition, clinical situation and setting, treatment goal, and patient circumstances. A report on Standardized Representation for Patient Preferences will characterize the state of standards for representing patient preferences and values and identify opportunities for advancing the standards. To fully characterize the needs related to patient preferences standards, the Workgroup will focus on identifying standards for integrating different types of patient preference data into CDS.

Moving Forward

The Workgroups will continue developing their products into Fall 2023. As these products come together, the CDSiC will ensure that each provides value individually and as a collection of complementary resources. Workgroup products will be disseminated to promote PC CDS by providing design, implementation, and measurement guidance. These products will also be used by the CDSiC Innovation Center to further support development of PC CDS tools for implementation in real-world settings.

Stay current on the Workgroup’s product development by reading our Stakeholder Center Quarterly Reports. If you have questions or would like to join a Workgroup, please email us at CDSiC@norc.org.

Continue reading additional CDSiC Leadership Viewpoints here.


[1] Elwyn G, Frosch D, Thomson R, et al. Shared decision making: a model for clinical practice. J Gen Intern Med. 2012;27(10):1361-1367. doi:10.1007/s11606-012-2077-6

[2] Institute of Medicine (IOM). Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, D.C: National Academy Press; 2001.

[3] Dullabh P, Sandberg SF, Heaney-Huls K, et al. Challenges and opportunities for advancing patient-centered clinical decision support: findings from a horizon scan. J Am Med Inform Assoc. 2022;29(7):1233-1243. doi:10.1093/jamia/ocac059

[4] Bright TJ, Wong A, Dhurjati R, et al. Effect of Clinical Decision-Support Systems. Ann Intern Med. 2012;157(1):29-43. doi:10.7326/0003-4819-157-1-201207030-00450

[5] Mengting J, Guangjun Y, Huiqin X, Ting X, Yanwen Q. Measures of success of computerized clinical decision support systems: An overview of systematic reviews. Health Policy and Technology. 2020;10(1): 196-208. doi: 10.1016/j.hlpt.2020.11.001.

[6] Kautz K. Participatory Design Activities and Agile Software Development. In: Pries-Heje, J., Venable, J., Bunker, D., Russo, N.L., DeGross, J.I. (eds) Human Benefit through the Diffusion of Information Systems Design Science Research. TDIT 2010. IFIP Advances in Information and Communication Technology. 2010 (318). Springer, Berlin, Heidelberg. 

[7] Dullabh P, Sandberg SF, Heaney-Huls K, et al. Challenges and opportunities for advancing patient-centered clinical decision support: findings from a horizon scan. J Am Med Inform Assoc. 2022;29(7):1233-1243. doi:10.1093/jamia/ocac059

[8] Byambasuren O, Sanders S, Beller E, Glasziou P. Prescribable mHealth apps identified from an overview of systematic reviews. NPJ Digit Med. 2018;1:12. Published 2018 May 9. doi:10.1038/s41746-018-0021-9

[9] Cohen DJ, Keller SR, Hayes GR, Dorr DA, Ash JS, Sittig DF. Integrating patient-generated health data into clinical care settings or clinical decision-making: lessons learned from project HealthDesign. JMIR Human Factors 2016; 3 (02) e26

[10] Ye J. The impact of electronic health record-integrated patient-generated health data on clinician burnout. J Am Med Inform Assoc 2021; 28 (05) 1051-1056