Linas Simonaitis

Publications of Linas Simonaitis

• Development and evaluation of a comprehensive clinical decision support taxonomy: comparison of front-end tools in commercial and internally developed electronic health record systems.

  Authors: Adam Wright, Dean F Sittig, Joan S Ash, Joshua Feblowitz, Seth Meltzer, Carmit McMullen, Ken Guappone, Jim Carpenter, Joshua Richardson, Linas Simonaitis, R Scott Evans, W Paul Nichol, Blackford Middleton

  Journal of the American Medical Informatics Association : JAMIA. 03/2011; 18(3):232-42.

  Clinical decision support (CDS) is a valuable tool for improving healthcare quality and lowering costs. However, there is no comprehensive taxonomy of types of CDS and there has been limited researchClinical decision support (CDS) is a valuable tool for improving healthcare quality and lowering costs. However, there is no comprehensive taxonomy of types of CDS and there has been limited research on the availability of various CDS tools across current electronic health record (EHR) systems. To develop and validate a taxonomy of front-end CDS tools and to assess support for these tools in major commercial and internally developed EHRs. We used a modified Delphi approach with a panel of 11 decision support experts to develop a taxonomy of 53 front-end CDS tools. Based on this taxonomy, a survey on CDS tools was sent to a purposive sample of commercial EHR vendors (n=9) and leading healthcare institutions with internally developed state-of-the-art EHRs (n=4). Responses were received from all healthcare institutions and 7 of 9 EHR vendors (response rate: 85%). All 53 types of CDS tools identified in the taxonomy were found in at least one surveyed EHR system, but only 8 functions were present in all EHRs. Medication dosing support and order facilitators were the most commonly available classes of decision support, while expert systems (eg, diagnostic decision support, ventilator management suggestions) were the least common. We developed and validated a comprehensive taxonomy of front-end CDS tools. A subsequent survey of commercial EHR vendors and leading healthcare institutions revealed a small core set of common CDS tools, but identified significant variability in the remainder of clinical decision support content.

• Comparison of clinical knowledge management capabilities of commercially-available and leading internally-developed electronic health records.

  Authors: Dean F Sittig, Adam Wright, Seth Meltzer, Linas Simonaitis, R Scott Evans, W Paul Nichol, Joan S Ash, Blackford Middleton

  BMC medical informatics and decision making. 02/2011; 11:13.

  We have carried out an extensive qualitative research program focused on the barriers and facilitators to successful adoption and use of various features of advanced, state-of-the-art electronicWe have carried out an extensive qualitative research program focused on the barriers and facilitators to successful adoption and use of various features of advanced, state-of-the-art electronic health records (EHRs) within large, academic, teaching facilities with long-standing EHR research and development programs. We have recently begun investigating smaller, community hospitals and out-patient clinics that rely on commercially-available EHRs. We sought to assess whether the current generation of commercially-available EHRs are capable of providing the clinical knowledge management features, functions, tools, and techniques required to deliver and maintain the clinical decision support (CDS) interventions required to support the recently defined "meaningful use" criteria. We developed and fielded a 17-question survey to representatives from nine commercially available EHR vendors and four leading internally developed EHRs. The first part of the survey asked basic questions about the vendor's EHR. The second part asked specifically about the CDS-related system tools and capabilities that each vendor provides. The final section asked about clinical content. All of the vendors and institutions have multiple modules capable of providing clinical decision support interventions to clinicians. The majority of the systems were capable of performing almost all of the key knowledge management functions we identified. If these well-designed commercially-available systems are coupled with the other key socio-technical concepts required for safe and effective EHR implementation and use, and organizations have access to implementable clinical knowledge, we expect that the transformation of the healthcare enterprise that so many have predicted, is achievable using commercially-available, state-of-the-art EHRs.

• The state of the art in clinical knowledge management: An inventory of tools and techniques.

  Authors: Dean F Sittig, Adam Wright, Linas Simonaitis, James D Carpenter, George O Allen, Bradley N Doebbeling, Anwar Mohammad Sirajuddin, Joan S Ash, Blackford Middleton

  International journal of medical informatics. 10/2009;

  PURPOSE: To explore the need for, and use of, high-quality, collaborative, clinical knowledge management (CKM) tools and techniques to manage clinical decision support (CDS) content. METHODS: InPURPOSE: To explore the need for, and use of, high-quality, collaborative, clinical knowledge management (CKM) tools and techniques to manage clinical decision support (CDS) content. METHODS: In order to better understand the current state of the art in CKM, we developed a survey of potential CKM tools and techniques. We conducted an exploratory study by querying a convenience sample of respondents about their use of specific practices in CKM. RESULTS: The following tools and techniques should be priorities in organizations interested in developing successful computer-based provider order entry (CPOE) and CDS implementations: (1) a multidisciplinary team responsible for creating and maintaining the clinical content; (2) an external organizational repository of clinical content with web-based viewer that allows anyone in the organization to review it; (3) an online, collaborative, interactive, Internet-based tool to facilitate content development; (4) an enterprise-wide tool to maintain the controlled clinical terminology concepts. Even organizations that have been successfully using computer-based provider order entry with advanced clinical decision support features for well over 15 years are not using all of the CKM tools or practices that we identified. CONCLUSIONS: If we are to further stimulate progress in the area of clinical decision support, we must continue to develop and refine our understanding and use of advanced CKM capabilities.