- Agency for Healthcare Research and Quality (AHRQ)
- Linking of Clinical and Other Data for Research
- Use of Enhanced Publically-Funded Data Systems for Research
- Use of Clinical Data for Research
STATUS: Completed Project
The AHRQ Registry of Patient Registries contains almost 4,000 registries for research, quality improvement, public reporting, and post market surveillance as of April 2018. These registries have considerable potential to be used for PCOR. However, because these data do not share standardized definitions of outcomes measures, analysis of data derived across registries is impossible. Stakeholders in AHRQ’s OS-PCORTF funded project to harmonize measures in five clinical areas, titled Harmonization of Clinical Data Element Definitions for Outcome Measures in Registries, identified three major barriers to the implementation of measures: 1) burden on clinical sites to collect data; 2) disruption to clinical care and challenges in extracting data from the clinical records; and 3) challenges with working with electronic health records (EHRs). While stakeholders recognize the importance of harmonized outcomes measures, these barriers contribute to reluctance to implement.
The main goal of this project was to address these barriers, using the depression topic as an example. Researchers collected complex outcome measure information on depression from clinical sites and will transfer that data to existing patient registries. This project utilized many patient reported outcome (PRO) and structured data collection tools developed by the OS-PCORTF funded project Advancing the Collection and Use of Patient-Reported Outcomes through Health Information Technology. These tools included a mobile and web-based platform with reminders for patients to fill out forms at specific time intervals and automatic generation of outcome measures that are presented back to physicians through integration with EHRs. While these tools can address the barriers, they had not yet been broadly implemented.
Researchers implemented outcome measures for depression into a variety of settings by linking clinical data to two different registries and testing the exchange of data back from the registries to participating clinical sites. The project collected outcome measures through three different methods: 1) by extracting data already available in the EHR; 2) from those calculated from items in the nine item Patient Health Questionnaire (PHQ-9); and 3) using new data collection from structured data capture or through natural language processing of clinical notes.
This project worked with clinical sites of an integrated health system and two distinct registries (a primary care focused registry and a specialty care registry) to address and overcome challenges while developing registry enhancements. Knowledge gained from this project addresses barriers with accessible tools so that other registries can enable collection and use of data that is cost effective for sites and will reasonably fit into their clinical workflow.
PROJECT PURPOSE & GOALS
The overall goal of the project was to examine whether this approach to data collection enhanced the use of registries of research on patient outcomes by completion of the following outcomes:
Tools for clinicians and patients to facilitate integration of the harmonized depression outcome measures into EHRs and registries so that these data will be available for clinical research, PCOR, quality improvement and implementation research.
Proof of concept for a standards-based approach for collecting and reporting patient outcomes information to clinicians within their workflow and simultaneously transmitting the data to registries to make it available for research.
Tools, such as instructions and pieces of code, to make it easier for researchers and registry developers to integrate registries with clinical systems.
PROJECT ACHIEVEMENTS AND HIGHLIGHTS
The project team selected six harmonized depression outcome measures to examine: response, remission, recurrence, suicide ideation and behavior, adverse effects of treatment, and death from suicide. The team developed standardized processes to collect depression measures from the EHR, the Patient Health Questionnaire-9 (PHQ-9), and clinical notes.
The team demonstrated the feasibility of using two registries —the American Board of Family Medicine’s PRIME Registry™ and the American Psychiatric Association’s PsychPRO—to extract standardized depression data from EHRs to calculate the harmonized outcome measures.
The team developed and then implemented a Substitutable Medical Applications and Reusable Technologies (SMART) on Fast Healthcare Interoperability Resources (FHIR®) app across cross 21 clinical sites within Baystate Health, an integrated health system. The app integrates clinical and patient-reported data from multiple sources to provide a ‘snapshot’ view of a patient’s depression treatment and harmonized outcomes.
The project team developed several resources that can be used by other clinical sites interested in adopting harmonized outcome measures. These include white papers, a data use and governance toolkit, FHIR® profiles and implementation guides, app source code, and documentation.
PUBLICATIONS, PRESENTATIONS, AND OTHER PUBLICALLY AVAILABLE RESOURCES
The project team published a final report, “Outcome Measure Harmonization and Data Infrastructure for Patient-Centered Outcomes Research in Depression,” which is available here: https://aspe.hhs.gov/sites/default/files/documents/f29f18ff94f7ac05031e8a357d36e3b5/ahrq-posted-final-report-fy18.pdf
The team created the FHIR® Library for Depression Outcome Measures, which includes the harmonized depression outcome measures and links to appropriate value sets. This library is available here: https://github.com/HL7/fhir-outcome-criteria-framework-ig
The source code and related technical documentation for the Major Depression Outcomes App are available here: https://apps.smarthealthit.org/app/major-depression-outcomes-app
The FHIR® Outcome Criteria Framework and Implementation Guide (version 1.0): Standardized implementation models, FHIR® profiles, and implementation guide for AHRQ’s Outcome Measures Framework (OMF) are publicly available.
The project team published a Standardized Library of Depression Outcome Measures White Paper, which describes the technical approach used to prepare the Standardized Library of Depression Outcome Measures: https://effectivehealthcare.ahrq.gov/products/library-depression/white-paper
The team published “A Prioritized Research Agenda for Using the Harmonized Outcome Measures in the Support Patient-Centered Outcomes Research in Depression Research,” which summarizes research priorities and questions for future work on harmonized outcome measures in depression, as determined by a stakeholder panel. The report is located here: https://effectivehealthcare.ahrq.gov/sites/default/files/pdf/prioritized-research-agenda.pdf
The team published a Data Use and Governance Toolkit White Paper, which summarizes the best practices in sharing registry data and provides additional information to assist registries in sharing data. The toolkit is available here: https://effectivehealthcare.ahrq.gov/sites/default/files/pdf/outcomes-research-depression.pdf
The team published “Beyond Harmonization: Implementing Standardized Outcome Measures to Support Value-Based Care,” which outlines AHRQ’s Outcomes Measures Framework. The article is available here: https://www.ispor.org/publications/journals/value-outcomes-spotlight/vos-archives/issue/view/unlocking-the-promise-of-real-world-evidence/beyond-harmonization-implementing-standardized-outcome-measures-to-support-value-based-care
Below is a list of ASPE-funded PCORTF projects that are related to this project
Harmonization of Clinical Data Element Definitions for Outcome Measures in Registries – Electronic health records (EHRs) and registries contain a variety of rich clinical information including demographics, diagnoses, medications, allergies, and laboratory values. These data have the potential to support hypothesis generation and large-scale clinical research studies. However, it is essential to address the variability in clinical definitions in order to meaningfully interpret results of studies and use the results to improve patient outcomes. To address this need AHRQ developed an Outcomes Measures Framework (OMF) – a conceptual model classifying outcome measures across condition areas that could be used to develop standardized outcome measures for use in research and clinical practice. This project convened a series of clinical topic specific working groups to discuss the various clinical outcome definitions currently in use and how these definitions could be harmonized to promote common definitions across data collection and reporting systems. The working groups solicited input from a broad stakeholder community, including registry holders, EHR developers, policymakers developing quality measures, and clinicians, among others.
Developing a Strategically Coordinated Registry Network (CRN) for Women’s Health Technology – The Food and Drug Administration, together with the Office of the National Coordinator (ONC) and the National Institutes of Health/National Library of Medicine establish a CRN for research on Women’s Health Technologies by developing a community of stakeholders interested in working together to make system changes in an area of women’s health device safety and effectiveness. This project developed tools to facilitate collection of data within registries, improve the value and sustainability of registries through leveraging electronic data, and demonstrating that the data in the registries can be reused to answer additional questions through the addition of new data elements and patient cohorts.
Advancing the Collection and Use of Patient-Reported Outcomes (PROs) through Health Information Technology (IT) – While some EHRs can capture some structured PRO data, this information is not commonly collected at the point of care. Led by AHRQ and ONC, this project aimed to refine and harmonize health IT standards and implementation specifications that can be used to support sharing of PRO data through application programming interfaces (APIs) and relevant health IT products for research. The project also developed technical tools for collecting and integrating PRO assessments into EHRs or other health IT products.