W. Ed Hammond

Computerized Decision Support Based on a Clinical Practice Guideline Improves Compliance with Care Standards

PURPOSE Clinical guidelines are designed to assist in the management of specific diseases; however, these guidelines are often neglected in the delivery of care. The purpose of this study was to determine whether clinician use of an clinical practice guideline would increase in response to having, at the patient visit, a decision support system based on a practice guideline that generates a customized management protocol for the individual patient using data from the patients electronic medical record. SUBJECTS AND METHODS In a 6-month controlled trial at a primary care clinic, 58 primary care clinicians were randomized to receive either a special encounter form with the computer-generated guideline recommendations or a standard encounter form. The effect of computer-generated advice on clinician behavior was measured as rate of compliance with guideline recommendations. Data from 30 clinicians were analyzed; data from 28 clinicians were excluded because these clinicians did not meet predefined criteria for minimum exposure to diabetic patient care. RESULTS Availability of patient management recommendations generated by the decision support system resulted in a two-fold increase in clinician compliance with care guidelines for diabetes mellitus (P = 0.01). Median compliance for the group receiving the recommendations was 32.0% versus 15.6% for the control group. CONCLUSION Decision support based on a clinical practice guideline is an effective tool for assisting clinicians in the management of diabetic patients. This decision support system provides a model for how a clinical practice guideline can be integrated into the care process by computer to assist clinicians in managing a specific disease through helping them comply with care standards. Use of decision support systems based on clinical practice guidelines could ultimately improve the quality of medical care.

Accelerating U.S. EHR Adoption: How to Get There From Here. Recommendations Based on the 2004 ACMI Retreat

Despite growing support for the adoption of electronic health records (EHR) to improve U.S. healthcare delivery, EHR adoption in the United States is slow to date due to a fundamental failure of the healthcare information technology marketplace. Reasons for the slow adoption of healthcare information technology include a misalignment of incentives, limited purchasing power among providers, variability in the viability of EHR products and companies, and limited demonstrated value of EHRs in practice. At the 2004 American College of Medical Informatics (ACMI) Retreat, attendees discussed the current state of EHR adoption in this country and identified steps that could be taken to stimulate adoption. In this paper, based upon the ACMI retreat, and building upon the experiences of the authors developing EHR in academic and commercial settings we identify a set of recommendations to stimulate adoption of EHR, including financial incentives, promotion of EHR standards, enabling policy, and educational, marketing, and supporting activities for both the provider community and healthcare consumers.

The Clinical Document Architecture and the Continuity of Care Record: A Critical Analysis

Health care provides many opportunities in which the sharing of data between independent sites is highly desirable. Several standards are required to produce the functional and semantic interoperability necessary to support the exchange of such data: a common reference information model, a common set of data elements, a common terminology, common data structures, and a common transport standard. This paper addresses one component of that set of standards: the ability to create a document that supports the exchange of structured data components. Unfortunately, two different standards development organizations have produced similar standards for that purpose based on different information models: Health Level 7 (HL7)s Clinical Document Architecture (CDA) and The American Society for Testing and Materials (ASTM International) Continuity of Care Record (CCR). The coexistence of both standards might require mapping from one standard to the other, which could be accompanied by a loss of information and functionality. This paper examines and compares the two standards, emphasizes the strengths and weaknesses of each, and proposes a strategy of harmonization to enhance future progress. While some of the authors are members of HL7 and/or ASTM International, the authors stress that the viewpoints represented in this paper are those of the authors and do not represent the official viewpoints of either HL7 or of ASTM International.

Innovative information visualization of electronic health record data: a systematic review

Objective This study investigates the use of visualization techniques reported between 1996 and 2013 and evaluates innovative approaches to information visualization of electronic health record (EHR) data for knowledge discovery. Methods An electronic literature search was conducted May–July 2013 using MEDLINE and Web of Knowledge, supplemented by citation searching, gray literature searching, and reference list reviews. General search terms were used to assure a comprehensive document search. Results Beginning with 891 articles, the number of articles was reduced by eliminating 191 duplicates. A matrix was developed for categorizing all abstracts and to assist with determining those to be excluded for review. Eighteen articles were included in the final analysis. Discussion Several visualization techniques have been extensively researched. The most mature system is LifeLines and its applications as LifeLines2, EventFlow, and LifeFlow. Initially, research focused on records from a single patient and visualization of the complex data related to one patient. Since 2010, the techniques under investigation are for use with large numbers of patient records and events. Most are linear and allow interaction through scaling and zooming to resize. Color, density, and filter techniques are commonly used for visualization. Conclusions With the burgeoning increase in the amount of electronic healthcare data, the potential for knowledge discovery is significant if data are managed in innovative and effective ways. We identify challenges discovered by previous EHR visualization research, which will help researchers who seek to design and improve visualization techniques.

A comparison of phenotype definitions for diabetes mellitus

OBJECTIVE This study compares the yield and characteristics of diabetes cohorts identified using heterogeneous phenotype definitions. MATERIALS AND METHODS Inclusion criteria from seven diabetes phenotype definitions were translated into query algorithms and applied to a population (n=173 503) of adult patients from Duke University Health System. The numbers of patients meeting criteria for each definition and component (diagnosis, diabetes-associated medications, and laboratory results) were compared. RESULTS Three phenotype definitions based heavily on ICD-9-CM codes identified 9-11% of the patient population. A broad definition for the Durham Diabetes Coalition included additional criteria and identified 13%. The electronic medical records and genomics, NYC A1c Registry, and diabetes-associated medications definitions, which have restricted or no ICD-9-CM criteria, identified the smallest proportions of patients (7%). The demographic characteristics for all seven phenotype definitions were similar (56-57% women, mean age range 56-57 years).The NYC A1c Registry definition had higher average patient encounters (54) than the other definitions (range 44-48) and the reference population (20) over the 5-year observation period. The concordance between populations returned by different phenotype definitions ranged from 50 to 86%. Overall, more patients met ICD-9-CM and laboratory criteria than medication criteria, but the number of patients that met abnormal laboratory criteria exclusively was greater than the numbers meeting diagnostic or medication data exclusively. DISCUSSION Differences across phenotype definitions can potentially affect their application in healthcare organizations and the subsequent interpretation of data. CONCLUSIONS Further research focused on defining the clinical characteristics of standard diabetes cohorts is important to identify appropriate phenotype definitions for health, policy, and research.

Connecting Information To Improve Health

Effective health information systems require timely access to all health data from all sources, including sites of direct care. In most parts of the world today, these data most likely come from many different and unconnected systems-but must be organized into a composite whole. We use the word interoperability to capture what is required to accomplish this goal. We discuss five priority areas for achieving interoperability in health care applications (patient identifier, semantic interoperability, data interchange standards, core data sets, and data quality), and we contrast differences in developing and developed countries. Important next steps for health policy makers are to define a vision, develop a strategy, identify leadership, assign responsibilities, and harness resources.

The Clinical Document Architecture and the Continuity of Care Record

Health care provides many opportunities in which the sharing of data between independent sites is highly desirable. Several standards are required to produce the functional and semantic interoperability necessary to support the exchange of such data: a common reference information model, a common set of data elements, a common terminology, common data structures, and a common transport standard. This paper addresses one component of that set of standards: the ability to create a document that supports the exchange of structured data components. Unfortunately, two different standards development organizations have produced similar standards for that purpose based on different information models: Health Level 7 (HL7)s Clinical Document Architecture (CDA) and The American Society for Testing and Materials (ASTM International) Continuity of Care Record (CCR). The coexistence of both standards might require mapping from one standard to the other, which could be accompanied by a loss of information and functionality. This paper examines and compares the two standards, emphasizes the strengths and weaknesses of each, and proposes a strategy of harmonization to enhance future progress. While some of the authors are members of HL7 and/or ASTM International, the authors stress that the viewpoints represented in this paper are those of the authors and do not represent the official viewpoints of either HL7 or of ASTM International.

How the past teaches the future: ACMI distinguished lecture.

More than 30 years of experience in developing a computer-based patient record system, The Medical Record (TMR), in multiple settings, in multiple specialty groups, and at multiple sites has taught us many lessons. Lessons related to computer-based patient records include the importance of a data model in which input, storage, and planned use are independent; separation of patient-specific data from metadata; a modular design to localize the program code that deals with a set of data; redundant storage to optimize tasks and response time; and integration of decision support into work process. Lessons related to medical informatics include the importance of a clinical-technical partnership, control of tools at the leading edge, and rapid prototyping in the real world. Finally, changes in technology move the challenges but do not eliminate them.

Standardising clinical data elements

We report the development and implementation of a methodology for standardising clinical data elements. The methodology, piloted using Tuberculosis (TB) and Acute Coronary Syndromes (ACS) domains, relies on clinicians for natural language definitions and on informaticists for computable specifications. Data elements are represented using the ISO 11179 standard, UML class, and activity diagrams. Over 2000 candidate data elements were compiled for each domain. Initial sets of 21 data elements for ACS and 139 for TB, plus 300 valid values, were standardised and made publicly available. The methodology is now used in HL7 for data element definition in other clinical areas.

The status of healthcare standards in the United States

Healthcare standards in the US are produced by six standard developers organizations: ACR/NEMA, ASC X12N, ASTM, HL7, IEEE, and NCPDP. The activities of these groups are coordinated through the ANSI HISPP. While considerable progress has been made in the area of data interchange standards, little progress has been made in the area of vocabulary standards.