GARDE: a standards-based clinical decision support platform for identifying population health management cohorts.

Unlabelled: Population health management (PHM) is an important approach to promote wellness and deliver health care to targeted individuals who meet criteria for preventive measures or treatment. A critical component for any PHM program is a data analytics platform that can target those eligible individuals.

Objective: The aim of this study was to design and implement a scalable standards-based clinical decision support (CDS) approach to identify patient cohorts for PHM and maximize opportunities for multi-site dissemination.

Leveraging Artificial Intelligence to Improve Chronic Disease Care: Methods and Application to Pharmacotherapy Decision Support for Type-2 Diabetes Mellitus.

Objectives: Artificial intelligence (AI), including predictive analytics, has great potential to improve the care of common chronic conditions with high morbidity and mortality. However, there are still many challenges to achieving this vision. The goal of this project was to develop and apply methods for enhancing chronic disease care using AI.

Integrated displays to improve chronic disease management in ambulatory care: A SMART on FHIR application informed by mixed-methods user testing.

Objective: The study sought to evaluate a novel electronic health record (EHR) add-on application for chronic disease management that uses an integrated display to decrease user cognitive load, improve efficiency, and support clinical decision making.

Materials And Methods: We designed a chronic disease management application using the technology framework known as SMART on FHIR (Substitutable Medical Applications and Reusable Technologies on Fast Healthcare Interoperability Resources). We used mixed methods to obtain user feedback on a prototype to support ambulatory providers managing chronic obstructive pulmonary disease.

Single-reviewer electronic phenotyping validation in operational settings: Comparison of strategies and recommendations.

Objective: Develop evidence-based recommendations for single-reviewer validation of electronic phenotyping results in operational settings.

Material And Methods: We conducted a randomized controlled study to evaluate whether electronic phenotyping results should be used to support manual chart review during single-reviewer electronic phenotyping validation (N=3104). We evaluated the accuracy, duration and cost of manual chart review with and without the availability of electronic phenotyping results, including relevant patient-specific details.

Challenges and Solutions in Optimizing Execution Performance of a Clinical Decision Support-Based Quality Measurement (CDS-QM) Framework.

Given the close relationship between clinical decision support (CDS) and quality measurement (QM), it has been proposed that a standards-based CDS Web service could be leveraged to enable QM. Benefits of such a CDS-QM framework include semantic consistency and implementation efficiency. However, earlier research has identified execution performance as a critical barrier when CDS-QM is applied to large populations.

Design, Development, and Initial Evaluation of a Terminology for Clinical Decision Support and Electronic Clinical Quality Measurement.

When coupled with a common information model, a common terminology for clinical decision support (CDS) and electronic clinical quality measurement (eCQM) could greatly facilitate the distributed development and sharing of CDS and eCQM knowledge resources. To enable such scalable knowledge authoring and sharing, we systematically developed an extensible and standards-based terminology for CDS and eCQM in the context of the HL7 Virtual Medical Record (vMR) information model. The development of this terminology entailed three steps: (1) systematic, physician-curated concept identification from sources such as the Health Information Technology Standards Panel (HITSP) and the SNOMED-CT CORE problem list; (2) concept de-duplication leveraging the Unified Medical Language System (UMLS) MetaMap and Metathesaurus; and (3) systematic concept naming using standard terminologies and heuristic algorithms.

Clinical Decision Support-based Quality Measurement (CDS-QM) Framework: Prototype Implementation, Evaluation, and Future Directions.

Electronic quality measurement (QM) and clinical decision support (CDS) are closely related but are typically implemented independently, resulting in significant duplication of effort. While it seems intuitive that technical approaches could be re-used across these two related use cases, such reuse is seldom reported in the literature, especially for standards-based approaches. Therefore, we evaluated the feasibility of using a standards-based CDS framework aligned with anticipated EHR certification criteria to implement electronic QM.

Chemical Stability of Admixtures Containing Ziconotide 25 mcg/mL and Morphine Sulfate 10 mg/mL or 20 mg/mL During Simulated Intrathecal Administration.

The chemical stability of an intrathecally administered analgesic combination may influence the frequency of pump refills necessary to maintain safe and effective analgesia. Previous work has shown that the stability of ziconotide at body temperature is reduced substantially by the presence of morphine sulfate 35 mg/mL. The current study was performed to evaluate the chemical stability of admixtures combining ziconotide with lower concentrations of morphine sulfate during simulated intrathecal infusion under laboratory conditions at 37 deg C.

Chemical stability of admixtures combining ziconotide with fentanyl or sufentanil during simulated intrathecal administration.

Although the U.S. Food and Drug Administration has not approved the combined use of intrathecal medications, practitioners frequently prescribe combination intrathecal therapy for patients who do not experience adequate analgesia with a single intrathecal agent; however, the chemical stability of an analgesic combination may influence the frequency of pump refills necessary to maintain safe and efective pain control.