Biomedical subjects

Gilad Kuperman

Publications and source records attributed to Gilad Kuperman.

4 recordsLinked to original sources

PubMed2005

KnowledgeLink: impact of context-sensitive information retrieval on clinicians' information needs.

OBJECTIVE: Infobuttons are message-based content search and retrieval functions embedded within other applications that dynamically return information relevant to the clinical task at hand. The objective of this study was to determine whether infobuttons effectively answer providers' questions about medications or affect patient care decisions. DESIGN: The authors implemented and evaluated a medication infobutton application called KnowledgeLink. Health care providers at 18 outpatient clinics were randomized to one of two versions of KnowledgeLink, one that linked to information from Micromedex (Thomson Micromedex, Greenwood Village, Co) and the other to material from SkolarMD (Wolters Kluwer Health, Palo Alto, CA). MEASUREMENTS: Data were collected about the frequency of use and demographics of users, patients, and drugs that were queried. Users were periodically surveyed with short questionnaires and then with a more extensive survey at the end of one year. RESULTS: During the first year, KnowledgeLink was used 7,972 times by 359 users to look up information about 1,723 medications for 4,961 patients. Clinicians used KnowledgeLink twice a month on average, and during an average of 1.2% of patient encounters. KnowledgeLink was used by a wide variety of medical staff, not just physicians and nurse practitioners. The frequency of usage and the questions asked varied with user role (primary care physician, specialist physician, nurse practitioner). Although the median KnowledgeLink session was brief (21 seconds), KnowledgeLink answered users' queries 84% of the time, and altered patient care decisions 15% of the time. Users rated KnowledgeLink favorably on multiple scales, recommended extending KnowledgeLink to other content domains, and suggested enhancing the interface to allow refinement of the query and selection of the target resource. CONCLUSION: An infobutton can satisfy information needs about medications. Although used infrequently and for brief sessions, KnowledgeLink was positively received, answered most users' questions, and had a significant impact on medical decision making. The next steps would be to broaden the domains that KnowledgeLink covers to more specifically tailor results to the user type, to provide options when queries are not immediately answered, and to implement KnowledgeLink within other electronic clinical applications.

Analysis of Variance↗

PubMed2005

The costs of a national health information network.

BACKGROUND: The use of information technology may result in a safer and more efficient health care system. However, consensus does not exist about the structure or costs of a national health information network (NHIN). OBJECTIVES: To describe the potential structure and estimate the costs of an NHIN. DESIGN: Cost estimates of an NHIN model developed by an expert panel. SETTING: U.S. health care system. MEASUREMENTS: An expert panel estimated the existing and the expected prevalence in 5 years of critical information technology functionalities. They then developed a model of an achievable NHIN by defining key providers, functionalities, and interoperability functions. By using these data and published cost estimates, the authors determined the cost of achieving this model NHIN in 5 years given the current state of information technology infrastructure. RESULTS: To achieve an NHIN would cost 156 billion dollars in capital investment over 5 years and 48 billion dollars in annual operating costs. Approximately two thirds of the capital costs would be required for acquiring functionalities and one third for interoperability. Ongoing costs would be more evenly divided between functionality and interoperability. If the current trajectory continues, the health care system will spend 24 billion dollars on functionalities over the next 5 years or about one quarter of the cost for functionalities of a model NHIN. LIMITATIONS: Because of a lack of primary data, the authors relied on expert estimates. CONCLUSIONS: While an NHIN will be expensive, 156 billion dollars is equivalent to 2% of annual health care spending for 5 years. Assessments such as this one may assist policymakers in determining the level of investment that the United States should make in an NHIN.

Health Expenditures↗

PubMed2003

A meta-data model for knowledge in decision support systems.

Clinical decision support such as alerts, reminders and guidance are driven by rules often distributed among a variety of applications in a healthcare information system. Due to the increasing size of rule bases, there is a growing need to manage this dispersed knowledge in an integrated environment. A system for management of executable clinical knowledge such as rules should (1) assist in the development and maintenance of rules throughout the rules' life-cycles, (2) support search and retrieval of rules in the knowledge base (e.g., rules for diabetes, rules created by a particular individual), and (3) facilitate the analyses of rules in the knowledge base (e.g., identify rules not updated in the last year). In order to create such a clinical knowledge management system it is necessary to model the meta-data of rules. There have been efforts to document meta-data about rules within the Arden Syntax Medical Logical Modules' project. However, the maintenance and library categories in that project allow mainly free-text information about a rule. We have created a comprehensive meta-data structure and taxonomy for describing clinical rules that supports the features of a knowledge management system. We also tested this model using a representative set of rules.

Artificial Intelligence↗

PubMed2003

Enterprise-wide drug-drug interaction alerting system.

According to the Institute of Medicine's (IOM) 1999 report To Err is Human: Building a safer Health System, "medical errors kill some 44,000-98,0001 people in U.S. hospitals each year. Partners HealthCare System (PHS) is a large integrated delivery network in Boston, MA, which has as a goal improving patient care by preventing adverse drug events (ADE) and reducing medication errors enterprise-wide. PHS has developed a drug-drug Interaction (DDI) detection feature, for the suite of clinical applications currently used by its two major teaching institutions, Brigham & Women's Hospital (BWH) and Mass General Hospital (MGH). The following clinical applications will be using this drug-drug interaction feature: NICU Order Entry (OE) at BWH, MGH OE for pediatrics and adults, the Partners outpatient medical record, The LMR, and BICS OE at BWH.

Algorithms↗