Structuring Care Recommendations for Clinical Decision Support (District of Columbia)

Project Final Report (PDF, 2.17 MB)

Project Details - Ended

Project Categories

Summary:

Historically, evidence-based clinical recommendations and performance measures have been resource intensive to implement into electronic health records (EHRs). This project developed a process for translating narrative, unstructured, evidence-based clinical recommendations and performance measures into a structured, coded format that can be implemented into health information technology (IT) systems, applications, and products. By developing such a process, the ability to integrate robust clinical decision support (CDS) rules into local health IT systems is made far easier, potentially broadening adoption of CDS and leading to improved patient care and outcomes. These structured recommendations became known as eRecommendations.

The main objectives of the project were to:

  • Increase use of interventions (e.g., tests, medications, and counseling) for which evidence-based clinical recommendations indicate a clear benefit to patients. An example is routine screening for colorectal cancer in individuals between the ages of 50 and 75.
  • Make it easier for clinical information system suppliers (e.g., government agencies and commercial vendors) and implementers (e.g., hospitals and physician practices) to develop and implement automated clinical reminders and related CDS tools based on widely accepted care recommendations.
  • Produce and populate, with broad stakeholder input, an "eRecommendation" format for expressing clinical recommendations as structured, coded logic statements that are widely useful. This includes leveraging codes and structures used to express clinical performance measures in a computable format to help tighten the measurement and CDS components of the clinical performance improvement cycle.
  • Leverage the eRecommendation format and project learning to help clinical guideline developers make their recommendations more precise and easier to translate into automated clinical reminders.

The project team developed, vetted with stakeholders, documented, and tested their formal methodology. They created structured eRecommendations for the 45 A and B recommendations from the U.S. Preventive Services Task Force and 12 rules relevant to Stage 1 Meaningful Use measures. The team created two guides to help users create and use eRecommendations. Throughout the project, the format and content of eRecommendations were vetted extensively with multiple stakeholders. Broad stakeholder feedback, which included health care provider organizations, guideline developers, EHR, and CDS suppliers, indicated wide interest in the eRecommendation work and belief that the project materials could deliver significant value.

Related projects have taken note of this project's work. The Advancing Clinical Decision Support portal project, an Office of the National Coordinator (ONC)-sponsored project, will be making eRecommendations available to the public on their portal. An additional ONC-sponsored project, the Strategic Health IT Advanced Research Projects C-2B project, will create an implementer's workbench to configuring setting specific factors related to converting eRecommendations into locally-useful CDS rules. This project interplay appears to have stimulated CDS rule development and value that is greater than the sum of the individual projects.

Structuring Care Recommendations for Clinical Decision Support - 2011

Summary Highlights

Summary: Incorporating widely accepted, evidence-based clinical care recommendations (also known as clinical guideline narratives), into clinical decision support (CDS) systems is a key method for improving health care and health outcomes. However, the process of translating such recommendations into "if... then..." logic statements (or rules) in CDS systems is inconsistent and inefficient, with many CDS developers independently translating text-based care recommendations into computer-executable code. Structured, coded clinical logic statements that can be electronically processed can increase the speed, consistency, and efficiency of guideline implementation as CDS rules. Such logic statements would reduce redundancy in extracting and structuring decision logic by assigning computer-interpretable codes to the elements of recommendations, such as inclusion and exclusion criteria for relevant patients and recommended treatment actions. Also, widely accepted formats and approaches for expressing the logic and variables of recommendations could help organizations that develop care recommendations write them in a more easily adapted way for use as automated clinical decision support rules. These rules could be used to trigger helpful clinician reminders and to identify groups of patients who may benefit from particular care interventions, as indicated by evidence-based medicine.

This project developed structured, coded logic statements called "eRecommendations" for all 45 A- and B-graded recommendations of the U.S. Preventive Services Task Force, and 12 recommendations relevant to "meaningful use" measures that, by regulation, must be reported to the Centers for Medicare and Medicaid Services. These eRecommendations leverage standard data elements, coding systems, and value sets developed for performance reporting under Meaningful Use to identify patients for whom a clinical recommendation applies and action should be taken.

Project Objectives:

  • Increase use of interventions (e.g., tests, medications, and counseling) for which evidence-based clinical recommendations indicate a clear benefit to patients. An example is routine screening for colorectal cancer in individuals between the ages of 50 and 75. (Ongoing)
  • Make it easier for clinical information system suppliers (e.g., government agencies and commercial vendors) and implementers (e.g., hospitals and physician practices) to develop and implement automated clinical reminders and related CDS tools based on widely accepted care recommendations. (Achieved)
  • Produce and populate, with broad stakeholder input, an "eRecommendation" format for expressing clinical recommendations as structured, coded logic statements that are widely useful. This includes leveraging codes and structures used to express clinical performance measures in a computable format to help tighten the measurement and CDS components of the clinical performance improvement cycle. (Achieved)
  • Leverage the eRecommendation format and project learning to help clinical guideline developers make their recommendations more precise and easier to translate into automated clinical reminders. (Achieved)

2011 Activities: The project engaged in activities to examine and enhance eRecommendation use in implementing CDS rules. This included launching a pilot analysis of eRecommendation use in two real world settings; one inpatient (Memorial Hermann Healthcare System), one outpatient (Tulane Community Health Centers). It also included building an expanded "eRecommendation Stakeholder Community" consisting of a cross-section of potential eRecommendation developers and users, and other CDS stakeholders. This community was convened in connection with the pilot site activities to identify next steps for supporting widespread eRecommendation use and value. Furthermore, additional eRecommendations were developed for high priority clinical rules, and two guides were created to facilitate the development and use of eRecommendations.

This project was completed in September 2011.

Impact and Findings: The project team was instructed to develop a method and format for translating clinical recommendations that went as far down the pathway to a machine-executable form as the process could be taken, while still ensuring widespread value from the material. A key component of the resulting eRecommendation method and format was an "implementation considerations" section that navigated the tension between implementers' need for more setting-specific factors and the vendors' desire for fewer of these specifics. In addition, the national push for Meaningful Use of health information technology (IT) and related efforts to apply electronic health records to performance measurement and improvement made it desirable to leverage momentum for this and related tools when the methods for structuring care recommendations were developed.

After extensive vetting, broad stakeholder feedback on the eRecommendation work indicated wide interest and a belief that the project materials could deliver significant value for improving the translation of clinical recommendations into CDS rules. The active engagement of this large group of public and private stakeholders in CDS-facilitated healthcare performance improvement is another important project by-product.

This project's impact also extends to related projects. The Advancing Clinical Decision Support portal project, an Office of the National Coordinator for Health IT (ONC)-sponsored project, may be making eRecommendations available to the public on their portal. An additional ONC-sponsored project, the Strategic Health IT Advanced Research Projects C-2B project, may create an implementer's workbench to configuring setting-specific factors related to converting eRecommendations into locally-useful CDS rules. This project interplay appears to have stimulated CDS rule development and value that is greater than the sum of the individual projects.

Target Population: General

Strategic Goal: Develop and disseminate health IT evidence and evidence-based tools to improve health care decisionmaking through the use of integrated data and knowledge management.

Business Goal: Implementation and Use

Structuring Care Recommendations for Clinical Decision Support - 2010

Summary Highlights



Target Population: General

Summary: Incorporating widely accepted, evidence-based clinical care recommendations, also known as clinical guideline narratives, into clinical decision support (CDS) systems is a key method for improving health care and health outcomes. However, the process of translating such recommendations into "if...then..." logic statements (or rules) in CDS systems is slow, inconsistent, and inefficient, with many CDS developers independently translating text-based care recommendations into computer-executable code. Structured, coded clinical logic statements that can be electronically processed can increase the speed, consistency, and efficiency of guideline implementation as CDS rules. Such logic statements will reduce redundancy related to extracting and structuring decision logic by assigning computer-interpretable codes to the elements of recommendations, such as inclusion and exclusion criteria for relevant patients and recommended treatment actions. Also, widely accepted formats and approaches for expressing the logic and variables of recommendations will help organizations that develop care recommendations write them in a way that can be more easily adapted for use as automated clinical decision support rules. These rules can be used to trigger helpful reminders to clinicians and to identify groups of patients that may benefit from particular care interventions, as indicated by evidence-based medicine.

This project involves developing structured, coded logic statements (called "eRecommendations") for all 45 A- and B-graded recommendations of the U.S. Preventive Services Task Force (USPSTF) and up to 20 recommendations underlying clinical performance measures required to be reported to the Centers for Medicare and Medicaid Services under "meaningful use" regulations. To identify patients for whom each clinical recommendation applies and actions that should be taken, these eRecommendations will leverage standard data elements, coding systems, and value sets being developed for performance reporting under meaningful use. The eRecommendations will be available for health information technology (IT) application developers, care providers, and others to access and further process into locally useful CDS.

Project Objective:

  • Increase use of interventions (e.g., tests, medications, and counseling) for which evidence-based clinical recommendations indicate a clear benefit to patients. An example is routine screening for colorectal cancer in individuals between the ages of 50 and 75. (Ongoing)
  • Make it easier for clinical information system suppliers (e.g., government agencies and commercial vendors) and implementers (e.g., hospitals and physician practices) to develop and implement automated clinical reminders and related CDS tools based on widely accepted care recommendations. (Ongoing)
  • Produce and populate, with broad stakeholder input, an "eRecommendation" format for expressing clinical recommendations as structured, coded logic statements that are widely useful. This includes leveraging codes and structures used to express clinical performance measures in a computable format to help tighten the measurement and CDS components of the clinical performance improvement cycle. (Ongoing)
  • Leverage the eRecommendation format and project learning to help clinical guideline developers make their recommendations more precise and easier to translate into automated clinical reminders. (Ongoing)

2010 Activities: The project devised, vetted, and documented a consistent method for transforming evidence-based clinical recommendations into a format that can be readily adapted further for widespread implementation in CDS systems and other health IT products. The project used the eRecommendations format to develop a collection of structured clinical recommendations for A and B grade USPSTF guideline statements, as well as a few meaningful use measures. To help ensure that the work performed was supported by the full range of stakeholder perspectives, a Rule Value Advisory Panel was convened to provide input about the value of proposed project deliverables and their potential future use. The project team specifically sought out potential users of structured recommendations who were interested in testing the usefulness of the eRecommendation template in the short term and possibly providing continuing feedback over a longer term.

In the last quarter of 2010, the project engaged in further activities to examine and enhance eRecommendation use in CDS rules. This included launching a pilot analysis of eRecommendation use in two real world settings – one inpatient (Memorial Hermann Healthcare System) and one outpatient (Tulane Community Health Centers). It also included building an "eRecommendation Stakeholder Community" consisting of a broad cross-section of potential eRecommendation developers and users and other relevant parties. This Community was formed to follow the pilot site findings in 2011 and identify next steps for supporting widespread eRecommendation use and value.

Preliminary Impact and Findings: The project team has held several key discussions with information system developers, implementers in both the public and private sector, associations that represent these stakeholders, and Federal care delivery organizations (i.e., Veterans Health Administration, Department of Defense, and Indian Health Service) to develop a report that synthesizes the background, existing approaches, and specific approach of this project for creating eRecommendations. A core strategy has been to align the format and methods for creating eRecommendations with corresponding work towards national standards and tools for integrating performance measurement and reporting into electronic health records. These include eMeasures for quality measurement, which draw on the Health Quality Measure Format and the Quality Data Model specifications from the National Quality Forum. Because of the strong motivation of information system suppliers and implementers to adopt eMeasures and related standards in order to achieve meaningful use, this alignment provides considerable synergy for CDS implementation efforts.

Multiple stakeholders validated that initial project deliverables hold promise for improving the efficiency and effectiveness with which clinical recommendations can be structured and coded for subsequent CDS rule implementation. The project has also cultivated synergies with other related national CDS initiatives that, if further developed, might help ensure widespread use of effective CDS rules. At the same time, the work to date has identified important issues that must be addressed to fully realize this promise.

Strategic Goal: Improve health care decisionmaking by developing and disseminating health IT tools that better manage the knowledge from evidence-based clinical guidelines and accepted quality measures.

Business Goal: Implementation and Use

Structuring Care Recommendations for Clinical Decision Support - Final Report

Citation:
Raetzman SO, Osheroff J, Greenes RA, et al. Structuring Care Recommendations for Clinical Decision Support - Final Report. (Prepared by Thomson Reuters under Contract No. 290-09-00022I-2). Rockville, MD: Agency for Healthcare Research and Quality, September 2011. AHRQ Publication No. 11-0025-2-EF. (PDF, 2.17 MB)
Principal Investigator: 
Document Type: 
Research Method: 

Structuring care recommendations for clinical decision support: background assessment, synthesis, and methods report.

Citation:
Raetzman SO, Sordo M, Osheroff J, et al. Structuring care recommendations for clinical decision support: background assessment, synthesis, and methods report. (Prepared by Thomson Reuters under Contract No. 290-09-00022I-2). Rockville, MD: Agency for Healthcare Research and Quality. March 2011. AHRQ Publication No. 11-0025-1-EF. (PDF, 1.52 MB)
Principal Investigator: 
Document Type: 
Research Method: 
This project does not have any related resource.
This project does not have any related survey.
This project does not have any related project spotlight.
This project does not have any related survey.
This project does not have any related story.
This project does not have any related emerging lesson.