An integrated web application for decision support and automation of EHR workflow: a case study of current challenges to standards-based messaging and scalability from the EMBED trial.

Computerized clinical decision support (CDS) faces challenges to interoperability and scalability. Centralized, web-based solutions offer a mechanism to share the cost of CDS development, maintenance, and implementation across practices. Data standards have emerged to facilitate interoperability and rapid integration of such third-party CDS.

Implementation of a Clinical Decision Support System for Children With Minor Blunt Head Trauma Who Are at Nonnegligible Risk for Traumatic Brain Injuries.

Study Objective: To determine the effect of providing risk estimates of clinically important traumatic brain injuries and management recommendations on emergency department (ED) outcomes for children with isolated intermediate Pediatric Emergency Care Applied Research Network clinically important traumatic brain injury risk factors.

Methods: This was a secondary analysis of a nonrandomized clinical trial with concurrent controls, conducted at 5 pediatric and 8 general EDs between November 2011 and June 2014, enrolling patients younger than 18 years who had minor blunt head trauma. After a baseline period, intervention sites received electronic clinical decision support providing patient-level clinically important traumatic brain injury risk estimates and management recommendations.

Use of Traumatic Brain Injury Prediction Rules With Clinical Decision Support.

Objectives: We determined whether implementing the Pediatric Emergency Care Applied Research Network (PECARN) traumatic brain injury (TBI) prediction rules and providing risks of clinically important TBIs (ciTBIs) with computerized clinical decision support (CDS) reduces computed tomography (CT) use for children with minor head trauma.

Methods: Nonrandomized trial with concurrent controls at 5 pediatric emergency departments (PEDs) and 8 general EDs (GEDs) between November 2011 and June 2014. Patients were <18 years old with minor blunt head trauma.

Screening Consolidated Clinical Document Architecture (CCDA) Documents for Sensitive Data Using a Rule-Based Decision Support System.

Background: The Centers for Medicare & Medicaid Services' Stage 2 final rule requires that eligible hospitals provide a visit summary electronically at transitions of care in order to qualify for "meaningful use" incentive payments. However, Massachusetts state law and Federal law prohibit the transmission of documents containing "sensitive" data unless there is a new patient consent for each transmission.

Objectives: To describe the implementation and evaluation of a rule-based decision support system used to screen transition of care documents for sensitive data.

Clinical Decision Support for a Multicenter Trial of Pediatric Head Trauma: Development, Implementation, and Lessons Learned.

Introduction: For children who present to emergency departments (EDs) due to blunt head trauma, ED clinicians must decide who requires computed tomography (CT) scanning to evaluate for traumatic brain injury (TBI). The Pediatric Emergency Care Applied Research Network (PECARN) derived and validated two age-based prediction rules to identify children at very low risk of clinically-important traumatic brain injuries (ciTBIs) who do not typically require CT scans. In this case report, we describe the strategy used to implement the PECARN TBI prediction rules via electronic health record (EHR) clinical decision support (CDS) as the intervention in a multicenter clinical trial.

Use of a remote clinical decision support service for a multicenter trial to implement prediction rules for children with minor blunt head trauma.

Objective: To evaluate the architecture, integration requirements, and execution characteristics of a remote clinical decision support (CDS) service used in a multicenter clinical trial. The trial tested the efficacy of implementing brain injury prediction rules for children with minor blunt head trauma.

Materials And Methods: We integrated the Epic(®) electronic health record (EHR) with the Enterprise Clinical Rules Service (ECRS), a web-based CDS service, at two emergency departments.

Leveraging the NLM map from SNOMED CT to ICD-10-CM to facilitate adoption of ICD-10-CM.

Objective: Develop and test web services to retrieve and identify the most precise ICD-10-CM code(s) for a given clinical encounter. Facilitate creation of user interfaces that 1) provide an initial shortlist of candidate codes, ideally visible on a single screen; and 2) enable code refinement.

Materials And Methods: To satisfy our high-level use cases, the analysis and design process involved reviewing available maps and crosswalks, designing the rule adjudication framework, determining necessary metadata, retrieving related codes, and iteratively improving the code refinement algorithm.

Taking advantage of continuity of care documents to populate a research repository.

Objective: Clinical data warehouses have accelerated clinical research, but even with available open source tools, there is a high barrier to entry due to the complexity of normalizing and importing data. The Office of the National Coordinator for Health Information Technology's Meaningful Use Incentive Program now requires that electronic health record systems produce standardized consolidated clinical document architecture (C-CDA) documents. Here, we leverage this data source to create a low volume standards based import pipeline for the Informatics for Integrating Biology and the Bedside (i2b2) clinical research platform.

A highly scalable, interoperable clinical decision support service.

Objective: To create a clinical decision support (CDS) system that is shareable across healthcare delivery systems and settings over large geographic regions.

Materials And Methods: The enterprise clinical rules service (ECRS) realizes nine design principles through a series of enterprise java beans and leverages off-the-shelf rules management systems in order to provide consistent, maintainable, and scalable decision support in a variety of settings.

Results: The ECRS is deployed at Partners HealthCare System (PHS) and is in use for a series of trials by members of the CDS consortium, including internally developed systems at PHS, the Regenstrief Institute, and vendor-based systems deployed at locations in Oregon and New Jersey.

A pilot study of distributed knowledge management and clinical decision support in the cloud.

Objective: Implement and perform pilot testing of web-based clinical decision support services using a novel framework for creating and managing clinical knowledge in a distributed fashion using the cloud. The pilot sought to (1) develop and test connectivity to an external clinical decision support (CDS) service, (2) assess the exchange of data to and knowledge from the external CDS service, and (3) capture lessons to guide expansion to more practice sites and users.

Materials And Methods: The Clinical Decision Support Consortium created a repository of shared CDS knowledge for managing hypertension, diabetes, and coronary artery disease in a community cloud hosted by Partners HealthCare.

Using a service oriented architecture approach to clinical decision support: performance results from two CDS Consortium demonstrations.

The Clinical Decision Support Consortium has completed two demonstration trials involving a web service for the execution of clinical decision support (CDS) rules in one or more electronic health record (EHR) systems. The initial trial ran in a local EHR at Partners HealthCare. A second EHR site, associated with Wishard Memorial Hospital, Indianapolis, IN, was added in the second trial.

Creating shareable decision support services: an interdisciplinary challenge.

Creating shareable decision support services is a complex task requiring effort from multiple interdisciplinary role players with a wide variety of experience and expertise. The CDS Consortium research project has developed such a service, defining a multi-layer representation of knowledge and building upon an architectural service design created at Partners Health Care, and is demonstrating its use in both a local and an external institutional setting. The process was iterative, and we encountered unexpected requirements based on decisions made at various points.

Laying the groundwork for enterprise-wide medical language processing services: architecture and process.

A systematic and standard process for capturing information within free-text clinical documents could facilitate opportunities for improving quality and safety of patient care, enhancing decision support, and advancing data warehousing across an enterprise setting. At Partners HealthCare System, the Medical Language Processing (MLP) services project was initiated to establish a component-based architectural model and processes to facilitate putting MLP functionality into production for enterprise consumption, promote sharing of components, and encourage reuse. Key objectives included exploring the use of an open-source framework called the Unstructured Information Management Architecture (UIMA) and leveraging existing MLP-related efforts, terminology, and document standards.

The adequacy of ICNP version 1.0 as a representational model for electronic nursing assessment documentation.

Objectives: The purpose of this study was to evaluate the adequacy of the International Classification of Nursing Practice (1) (ICPN) Version 1.0 as a representational model for nursing assessment documentation.

Design And Measurements: To identify representational requirements of nursing assessments, the authors mapped key concepts and semantic relations extracted from standardized and local nursing admission assessment documentation forms/templates and inpatient admission assessment records to the ICNP.

Challenges in creating an enterprise clinical rules service.

At Partners HealthCare, we are engaged in developing and implementing a strategy for our Clinical Decision Support systems and services that will enable CDS to be made available across the enterprise, allow development of consistent standards of care regardless of where a patient presents, and permit migration of current CDS functions to a supportable and scalable model. We report here on progress toward these goals, describe steps taken and proposed, and consider remaining challenges.

Representing nursing assessment documentation with ICNP.

The purpose of this study was to identify key concepts and semantic relations necessary to represent standardized and local patient assessment items in an electronic documentation system and to evaluate the degree to which coverage of both are represented by ICNP. A total of 805 unique assessment concepts were identified. Forty-three percent had exact matches in ICNP, and an additional 20% had matches in the ICNP classified as narrower, broader or other.

Early experiences in evolving an enterprise-wide information model for laboratory and clinical observations.

As Electronic Healthcare Records become more prevalent, there is an increasing need to ensure unambiguous data capture, interpretation, and exchange within and across heterogeneous applications. To address this need, a common, uniform, and comprehensive approach for representing clinical information is essential. At Partners HealthCare System, we are investigating the development and implementation of enterprise-wide information models to specify the representation of clinical information to support semantic interoperability.

Enhancing clinical problem lists through data mining and natural language processing.

The availability of timely, accurate, comprehensive, and coded clinical problem lists is essential for supporting a range of healthcare activities. Evidence and experience suggest, however, that problem lists are frequently out-of-date, sometimes omit clinically important problems, and contain uncoded entries. Here, we describe a study being performed at Partners HealthCare System to explore automated techniques for enhancing existing problem lists.

Evaluation of a commercial rule engine as a basis for a clinical decision support service.

Current implementation techniques constrain our ability to rapidly deploy and augment clinical decision support systems at Partners Healthcare Systems. We report on the use of a commercially-available rule engine system-iLog Rules-as the basis for a series of prototypes typifying Partners decision support applications. For three prototypical systems, we successfully decoupled the decision support component from application and support logic, and reimplemented that component using iLog.

Improving information prescription to parents of premature infants through an OWL-based knowledge mediator.

In the Baby CareLink system, information prescription plays an important role in preparing parents of premature infants for the eventual discharge to home of their children. However, the prescription process requires scarce clinician time in order to dispense information, and can become cumbersome as content bases grow in size. We describe the development of an OWL-based knowledge mediator to facilitate information prescription.