Developing public health clinical decision support systems (CDSS) for the outpatient community in New York City: our experience
- Use of electronic health record systems for decision support. Machado, Lucila Ohno // Journal of the American Medical Informatics Association;Nov2011, Vol. 18 Issue 6, p729
An introduction is presented in which the editor discusses various reports within the issue related to electronic health records (EHRs) on topics including computer-based provider order entry, the effects of EHRs in health care, and the usability of different types of EHRs.
- Development, Implementation, and Evaluation of a Hybrid Electronic Medical Record System Specifically Designed for a Developing World Surgical Service. Laing, G.; Bruce, J.; Skinner, D.; Allorto, N.; Clarke, D.; Aldous, C. // World Journal of Surgery;Jun2014, Vol. 38 Issue 6, p1388
Background: The Pietermaritzburg Metropolitan Trauma Service previously successfully constructed and implemented an electronic surgical registry (ESR). This study reports on our attempts to expand and develop this concept into a multi-functional hybrid electronic medical record (HEMR) system for...
- Computer-based safety surveillance and patient-centered health records. Ohno-Machado, Lucila // Journal of the American Medical Informatics Association;Jan2012, Vol. 19 Issue 1, p1
An introduction is presented in which the editor discusses various reports within the issue on topics including development in safety surveillance systems, electronic health records, and real-time decision support systems used in drug dosing for elderly patients.
- A method for inferring medical diagnoses from patient similarities. Gottlieb, Assaf; Stein, Gideon Y.; Ruppin, Eytan; Altman, Russ B.; Sharan, Roded // BMC Medicine;2013, Vol. 11 Issue 1, p1
Background: Clinical decision support systems assist physicians in interpreting complex patient data. However, they typically operate on a per-patient basis and do not exploit the extensive latent medical knowledge in electronic health records (EHRs). The emergence of large EHR systems offers...
- A conceptual framework and protocol for defining clinical decision support objectives applicable to medical specialties. Timbie, Justin W.; Damberg, Cheryl L.; Schneider, Eric C.; Bell, Douglas S. // BMC Medical Informatics & Decision Making;2012, Vol. 12 Issue 1, p93
Background: The U.S. Centers for Medicare and Medicaid Services established the Electronic Health Record (EHR) Incentive Program in 2009 to stimulate the adoption of EHRs. One component of the program requires eligible providers to implement clinical decision support (CDS) interventions that can...
- Emphasis on Support in Decision Support. Freeman, Greg // HealthLeaders Magazine;May2012, Vol. 15 Issue 5, p40
The article discusses computer-based decision-support systems designed to aid physicians to ensure improved delivery of care and cut costs. It notes that the key to effective implementation of these technologies, such as the computerized physician order entry (CPOE) and electronic medical record...
- High-priority drugedrug interactions for use in electronic health records. Phansalkar, Shobha; Desai, Amrita A.; Bell, Douglas; Yoshida, Eileen; Doole, John; Czochanski, Melissa; Middleton, Blackford; Bates, David W. // Journal of the American Medical Informatics Association;Sep2012, Vol. 19 Issue 5, p735
Objective To develop a set of high-severity, clinically significant drugedrug interactions (DDIs) for use in electronic health records (EHRs). Methods A panel of experts was convened with the goal of identifying critical DDIs that should be used for generating medication-related decision support...
- A supervised framework for resolving coreference in clinical records. Rink, Bryan; Roberts, Kirk; Harabagiu, Sanda M. // Journal of the American Medical Informatics Association;Sep2012, Vol. 19 Issue 5, p875
Objective A method for the automatic resolution of coreference between medical concepts in clinical records. Materials and methods A multiple pass sieve approach utilizing support vector machines (SVMs) at each pass was used to resolve coreference. Information such as lexical similarity, recency...
- 3 tips for reducing risk from default values. // Healthcare Risk Management;Dec2013, Vol. 35 Issue 12, p139
The article offers three steps from the Pennsylvania Patient Safety Authority (PPSA) on how to reduce patient safety risk caused by default values in electronic health records (EHRs) and computerized physician order entry (CPOE) such as wrong-time errors.