Prospects for Care Coordination Measurement Using Electronic Data Sources
Care coordination, defined as the deliberate organization of patient care activities between two or more participants (including the patient) involved in a patient's care to facilitate the appropriate delivery of health care services,1 has been recognized as a priority area for improving health care delivery in the U.S.2 Robust measures of care coordination processes will be essential tools to evaluate, guide, and support efforts to understand and improve deficits in care coordination.
This report presents an assessment of the potential for measuring care coordination processes using data from electronic data sources, in particular from existing and emerging health information technology (IT) systems such as electronic health records (EHR), health information exchanges (HIE), and all-payer claims databases (APCD). This assessment relies on background research and input from individual and group discussions with a panel of informants with expertise in health IT systems development and use, HIEs, EHRs, APCDs, insurance plans, health data standards, and quality measurement. This effort did not aim to develop new measures of care coordination, but to synthesize the background relevant to such future work.
Advantages of Measurement Using Electronic Data
Interest in using electronic data, in particular data from health IT systems, for care coordination measurement has promising advantages over data most commonly used today to measure coordination processes (e.g., surveys, chart review). Electronic data offer:
- Minimal data collection burden. Structured data may be automatically extracted for quality measurement.
- Rich clinical context. Health IT systems populated with clinical data (e.g., information on physician orders, laboratory results, etc) offer a view of processes of care and clinical outcomes not possible from data sets based only on claims data.
- Longitudinal patient data aggregated from multiple sources over time. EHRs, HIEs and APCDs aim to aggregate information for individual patients temporally from multiple providers, settings, and payers into a single location.
Current Challenges of Measurement Using Electronic Data
Panelists identified a number of challenges in using electronic data for care coordination measurement:
- Underutilization of health IT system capabilities, such as use of structured data fields.
- Clinical workflow barriers, which lead to limited attention to and documentation of coordination processes.
- Lack of data standardization, in particular coding of lab results and medication information.
- Limited health IT system interoperability.
- Unknown clinical data quality in various electronic data sources.
- Limitations in linking data.
- Technical hurdles to accessing data.
- Business models related to Health IT that facilitate competition rather than cooperation, especially in ways that prevent a full picture of the steps taken to care for a patient across settings and time.
Key Expert Panel Recommendations to Advance the Potential for Care Coordination Measurement Using Electronic Data
Panelists also recommended a number of ways to address these key challenges.
To address underutilization of health IT system capabilities and clinical workflow barriers:
- Align structured data fields with decision support tools.
- Create protocols for non-physician clinical or support staff to enter selected information in structured fields.
- Explain and, ideally, demonstrate how and under what circumstances structured data improves care coordination, and ultimately care delivery.
- Design health IT functionality to capture coordination activities more explicitly, both to support team practice and to measure the extent of these activities.
To address lack of data standardization and limited health IT system interoperability:
- Continue to support development of standards, both in areas where standards are undeveloped and by motivating adoption of existing standards through incentive programs.
- Align measurement and payment incentive initiatives with key standards gaps, such as coding of lab results and medication information.
- Align measure specifications with existing guidelines or elements of other quality measures.
- Develop well-defined measure concepts that will give vendors, EHR users, and HIE administrators clearly defined data elements to build into systems.
To address unknown clinical data quality in various electronic data sources:
- As part of measure development efforts, include an evaluation of the reliability and accuracy of any electronic data used for quality measurement.
- Disseminate and, preferably, publish evaluations of data quality.
To address limitations in linking data:
- Communicate the value of linked data to policymakers and the public.
- Develop strategies for overcoming privacy barriers.
To address technical hurdles to accessing data:
- Consider the accessibility of data to end-users when designing health IT systems.
- Consider the resources required to extract data from health IT systems when choosing a product.
- Consider whether any additional EHR certification requirements could help improve the ease of extracting data from within EHRs.
To address business models that facilitate competition rather than cooperation:
- Support and widely disseminate projects that demonstrate the value of information sharing.
- Seek out evidence that can demonstrate any cost savings for institutions that result from information sharing or other care coordination activities.
- Bring leaders of competing health care organizations together to facilitate dialog and encourage information sharing.
Near-term Measurement Opportunities Using Electronic Data
Panelists identified opportunities for measuring care coordination using electronic data that are likely to be feasible within the next 2-to-3 years.
Near-term measurement opportunities
|Measurement Approach||Data Source(s)|
|Use Meaningful Use measure data elements in new measures of care coordination||Certified EHRs from providers and hospitals participating in the Meaningful Use incentive program|
|Use CCD/CCR messages to confirm transmission of key pieces of information during care transitions||EHR or HIE* and claims data (APCD, payer files)|
|Use EHR data to confirm inclusion of key information from other health care settings within primary care record||EHR and claims data (APCD, payer files)|
|Use EHR audit files to evaluate whether information transferred from other settings is viewed by providers.||EHR audit files|
|Use claims data to confirm follow-up care occurred within expected time frame||APCDs, HIE* (if includes claims data) or payer files|
|Use claims data to examine instances of redundant testing||
APCDs, HIE* (if includes claims data) or payer files
Would be enhanced by addition of clinical data from EHR or HIE*
APCD—all-payer claims database; CCD—continuity of care document; CCR—continuity of care record; EHR—electronic health record; HIE—health information exchange.
*HIEs are only a data source if they include a data repository that stores data rather than just transmitting it.
Next steps required to implement these care coordination measure concepts include:
- Develop methods to link clinical and claims data and examine the reliability and accuracy of the linkage.
- Investigate the validity and quality of the specific data elements used within measures.
- Assess the accuracy of data automatically extracted from EHRs, for example by comparison with manual chart review.
- Carefully specify measures, with clear definitions of numerator, denominator, and exclusions. Develop risk adjustment models where necessary.
- Elicit clinical input and synthesize evidence from published literature and evidence-based guidelines, when available, to inform measure development.
Long-term Measurement Opportunities
Panelists also discussed some measurement opportunities that are promising in the long term, but likely not feasible within the next 3 years. These opportunities and their challenges included:
- Evidence that data are being linked across sites or across providers. Using aggregation of clinical information from multiple settings as evidence of care coordination will likely require further development of interoperability infrastructure, the evolution of EHRs and how data are recorded within them, and further conceptual development around what constitutes coordinated care.
- Lack of documentation in a coordinating practice's EHR (for example, of a primary care provider or medical home) regarding health care utilization in other settings (indicator of potentially poor care coordination). A limited application of this kind of measure is likely to be feasible in some cases within the next few years, but broader application is likely more distant. To be applicable to a broad patient population, such measures would require use of APCD data for the denominator linked with documentation from an EHR for the numerator. Currently, the ability to link APCD data with outside data sources, such as EHRs, is possible in only a limited number of States that collect identified data within their APCDs and permit such linkage. In addition, confirming the absence of information about outside health care utilization will pose a significant challenge given the variability in where and how such information is documented in health IT systems today.
- Linking EHRs to patient registries would offer a potentially rich data source for quality measurement. However, panelists emphasized that near-term measurement using patient registries, with or without linking to EHRs, is not likely. Although particular registries contain some data elements that would be useful for care coordination measurement, the lack of standard design or data elements included in various registries makes it impractical to design care coordination quality measures around registry data at this time.
The advantages of reduced measurement burden, rich clinical context, and longitudinal data have made electronic data, in particular data from health IT systems, the target of a growing interest in measuring care coordination processes in new ways. Feedback from experts who participated in this project suggests reason for optimism about this possibility, even while recognizing many challenges that must be overcome to make such measurement feasible. The rapidity with which the health IT landscape is changing will almost assuredly help resolve many of these challenges. Indeed, our discussions with panelists and review of background materials suggest that changes likely to resolve many challenges are already underway.