Exploring Different Approaches in Measuring EHR-based Adherence to Best Practice - A Case Study with Order Sets and Associated Outcomes.

In connection with a recent enterprise-wide rollout of a new electronic health record, Intermountain Healthcare is investing significant effort in building a central library of best-practice order sets. These order sets represent best practice guidelines for specific clinical scenarios and are deployed with the intent of standardizing care, reducing variation, and consistently delivering good clinical outcomes to the populations we serve. The importance of measuring their use and the level to which caregivers adhere to these standards becomes an important factor in understanding and characterizing the impact that they deliver.

A Statistical Approach for the Learning Curve of Physicians in Utilization of Electronic Order Sets.

Background:  Understanding a physician's behavior toward learning order sets is important as it is a key information to design order sets with optimized contents.

Objective:  The objective of this article is to test a hypothesis: for a physician using a new order set repeatedly, the utilization rate of order set contents has a pattern of either increase or decrease.

Methods:  To test the hypothesis, we retrieved empirical data of order set usage in local hospitals that adopted a new computerized physician order entry (CPOE) system and enterprise wide standard order sets.

Experience with Integrating Diagnostic Decision Support Software with Electronic Health Records: Benefits versus Risks of Information Sharing.

Introduction: Reducing misdiagnosis has long been a goal of medical informatics. Current thinking has focused on achieving this goal by integrating diagnostic decision support into electronic health records.

Methods: A diagnostic decision support system already in clinical use was integrated into electronic health record systems at two large health systems, after clinician input on desired capabilities.

Extracting Actionable Recommendations for Modifying Enterprise Order Set Templates from CPOE Utilization Patterns.

As part of an enterprise-wide rollout of a new EHR, Intermountain Healthcare is investing significant effort in building a central library of best-practice order sets. As part of this effort, we have built analytics tools that can capture and determine actionable opportunities for change to order set templates, as reflected by aggregate user data. In order to determine the acceptability of this system and set meaningful thresholds for actual use, we extracted recommendations for additions, removals, and change in initial order selection status for a series of thirteen order sets.

Profiling Fast Healthcare Interoperability Resources (FHIR) of Family Health History based on the Clinical Element Models.

In this study we developed a Fast Healthcare Interoperability Resources (FHIR) profile to support exchanging a full pedigree based family health history (FHH) information across multiple systems and applications used by clinicians, patients, and researchers. We used previously developed clinical element models (CEMs) that are capable of representing the FHH information, and derived essential data elements including attributes, constraints, and value sets. We analyzed gaps between the FHH CEM elements and existing FHIR resources.

Visualization of Order Set Creation and Usage Patterns in Early Implementation Phases of an Electronic Health Record.

Robust order set catalogs are considered to be a vital part of a computerized physician order entry (CPOE) implementation. Tools and processes for building, localizing, and maintaining these content sets in a centralized repository are important in facilitating the knowledge management lifecycle. Collectively, these order sets represent a significant investment of effort and expertise in capturing and distributing best clinical practice throughout an enterprise.

Infobutton usage in Patient Portal MyHealth.

Infobuttons have proven to be an important element in modern electronic health records (EHR), providing educational materials to both providers and patients. However, the usage of infobuttons in personalized health records (PHR) is only lightly documented in the literature. Patient-facing infobuttons pose a new challenge because patients have different questions and educational levels than professional users in EHRs.

Analysis of empty responses from electronic resources in infobutton managers.

Infobuttons provide context-aware educational materials to both providers and patients and are becoming an important element in modern electronic health records (EHR) and patient health records (PHR). However, the content from different electronic resources (e-resource) as responses from infobutton manager has not been fully analyzed and evaluated. In this paper, we propose a method for automatically analyzing responses from infobutton manager.

Combining infobuttons and semantic web rules for identifying patterns and delivering highly-personalized education materials.

Infobuttons have been established to be an effective resource for addressing information needs at the point of care, as evidenced by recent research and their inclusion in government-based electronic health record incentive programs in the United States. Yet their utility has been limited to wide success for only a specific set of domains (lab data, medication orders, and problem lists) and only for discrete, singular concepts that are already documented in the electronic medical record. In this manuscript, we present an effort to broaden their utility by connecting a semantic web-based phenotyping engine with an infobutton framework in order to identify and address broader issues in patient data, derived from multiple data sources.

Practical choices for infobutton customization: experience from four sites.

Context-aware links between electronic health records (EHRs) and online knowledge resources, commonly called "infobuttons" are being used increasingly as part of EHR "meaningful use" requirements. While an HL7 standard exists for specifying how the links should be constructed, there is no guidance on what links to construct. Collectively, the authors manage four infobutton systems that serve 16 institutions.

Enabling locally-developed content for access through the infobutton by means of automated concept annotation.

Infobuttons have proven to be an increasingly important resource in providing a standardized approach to integrating useful educational materials at the point of care in electronic health records (EHRs). They provide a simple, uniform pathway for both patients and providers to receive pertinent education materials in a quick fashion from within EHRs and Personalized Health Records (PHRs). In recent years, the international standards organization Health Level Seven has balloted and approved a standards-based pathway for requesting and receiving data for infobuttons, simplifying some of the barriers for their adoption in electronic medical records and amongst content providers.

Analysis of family health history based risk assessment algorithms: classification and data requirements.

Family Health History (FHH) is a valuable and potentially low-cost tool for risk assessment and diagnosis in patient-centered healthcare. In this study, we identified and analyzed existing FHH-based risk assessment algorithms (RAAs) for cardio-vascular disease (CVD) and colorectal cancer (CRC) to guide implementers of electronic health record (EHR) systems regarding the data requirements for computing risk using these algorithms. We found a core set of data elements that are required by most RAAs.

Disseminating context-specific access to online knowledge resources within electronic health record systems.

Clinicians' patient care information needs are frequent and largely unmet. Online knowledge resources are available that can help clinicians meet these information needs. Yet, significant barriers limit the use of these resources within the clinical workflow.

Evolution in clinical knowledge management strategy at Intermountain Healthcare.

In this manuscript, we present an overview of the clinical knowledge management strategy at Intermountain Healthcare in support of our electronic medical record systems. Intermountain first initiated efforts in developing a centralized enterprise knowledge repository in 2001. Applications developed, areas of emphasis served, and key areas of focus are presented.

Development and early usage patterns of a consumer-facing family health history tool.

Personalized medicine will require detailed clinical patient profiles, and a particular focus on capturing data that is useful in forecasting risk. A detailed family health history is considered a critical component of these profiles, insomuch that it has been coined as 'the best genetic test available'. Despite this, tools aimed at capturing this information for use in electronic health records have been characterized as inadequate.

Metadata extraction routines for improving infobutton performance.

Infobuttons have been proven as an effective means for providing quick, context-specific links to pertinent information resources at the point of care. Current infobutton manager implementations, however, lack the ability to exchange metadata, are limited to a relatively small set of information providers, and are targeted primarily for a clinician audience. As part of a local effort to implement infobuttons for patient use via a tethered personal health record, we present a series of metadata extraction routines.

A large-scale knowledge management method based on the analysis of the use of online knowledge resources.

Unlabelled: Online health knowledge resources can be integrated into electronic health record systems using decision support tools known as "infobuttons." In this study we describe a knowledge management method based on the analysis of knowledge resource use via infobuttons in multiple institutions.

Methods: We conducted a two-phase analysis of laboratory test infobutton sessions at three healthcare institutions accessing two knowledge resources.

Deriving consumer-facing disease concepts for family health histories using multi-source sampling.

The family health history has long been recognized as an effective way of understanding individuals' susceptibility to familial disease; yet electronic tools to support the capture and use of these data have been characterized as inadequate. As part of an ongoing effort to build patient-facing tools for entering detailed family health histories, we have compiled a set of concepts specific to familial disease using multi-source sampling. These concepts were abstracted by analyzing family health history data patterns in our enterprise data warehouse, collection patterns of consumer personal health records, analyses from the local state health department, a healthcare data dictionary, and concepts derived from genetic-oriented consumer education materials.

Glycemic control through computerized subcutaneous insulin calculators.

Sliding scale insulin (SSI) is a reactive therapy and does not maintain euglycemia in hospitalized patients. A combination of basal insulin, prandial insulin, and correction factor dosing provides a more consistent insulin state encouraging improved glycemic control. Intermountain Healthcare developed an application consisting of four calculators incorporating scheduled (basal and prandial) and correction-factor insulin.

Analysis of family health history data collection patterns in consumer-oriented Web-based tools.

Current trends have brought resurgent interest in developing consumer-oriented tools that gather patient-entered clinical data. Family health history data has long been recognized as valuable for risk assessment in primary care, but has gained renewed attention recently as part of IT-oriented efforts in personalized medicine. In order to better understand the breadth of data collected in consumer-oriented web applications, we evaluated their collection patterns using the recommendations issued by the American Health Information Community (AHIC).

Ideal features for a patient-entered family history and risk assessment tool.

Family history (FH) is an important risk factor for many diseases and its assessment can be a powerful tool for identifying and stratifying patients at risk. As part of an initiative to improve FH collection and decision support at Intermountain Healthcare we conducted a literature review on FH data collection and reviewed a number of current Web-based tools. An ideal list of features was produced to help implement goals of the initiative.

Towards an on-demand peer feedback system for a clinical knowledge base: a case study with order sets.

Objective: We have developed an automated knowledge base peer feedback system as part of an effort to facilitate the creation and refinement of sound clinical knowledge content within an enterprise-wide knowledge base. The program collects clinical data stored in our Clinical Data Repository during usage of a physician order entry program. It analyzes usage patterns of order sets relative to their templates and creates a report detailing the usage patterns of the order set template.

Towards ubiquitous peer review strategies to sustain and enhance a clinical knowledge management framework.

Widespread cooperation between domain experts and front-line clinicians is a key component of any successful clinical knowledge management framework. Peer review is an established form of cooperation that promotes the dissemination of new knowledge. The authors describe three peer collaboration scenarios that have been implemented using the knowledge management infrastructure available at Intermountain Healthcare.

Knowledge management strategies: Enhancing knowledge transfer to clinicians and patients.

At Intermountain Healthcare (Intermountain), executive clinical content experts are responsible for disseminating consistent evidence-based clinical content throughout the enterprise at the point-of-care. With a paper-based system it was difficult to ensure that current information was received and was being used in practice. With electronic information systems multiple applications were supplying similar, but different, vendor-licensed and locally-developed content.

Development and validation of XML-based calculations within order sets.

We have developed two XML Schemas to support the implementation of calculations within XML-based order sets. The models support the representation of variable-based algorithms and include data elements designed to support ancillary functions such as input range checking, rounding, and minimum/maximum value constraints. Two clinicians successfully authored 57 unique calculated orders derived from a set of 11 calculations using the models within our authoring environment.