Search AMIA.org

Electronic health records possess critical predictive information for machine-learning-based diagnostic aids. However, many traditional machine learning methods fail to simultaneously integrate textual data into the prediction process because of its high dimensionality. In this paper, we present a supervised method using Laplacian Eigenmaps to enable existing machine learning methods to estimate both low-dimensional representations of textual data and accurate predictors based on these low-dimensional representations at the same time.

The purpose of this integrative review based on the published literature was to identify information systems currently being used by local health departments and to determine the extent to which standard terminology was used to communicate data, interventions, and outcomes to improve public health informatics at the local health department (LHD) level and better inform research, policy, and programs.

Coding of clinical communication for fine-grained features such as speech acts has produced a substantial literature. However, annotation by humans is laborious and expensive, limiting application of these methods. We aimed to show that through machine learning, computers could code certain categories of speech acts with sufficient reliability to make useful distinctions among clinical encounters.

The objective was to assess whether rates of preventive counseling delivered at well child visits (WCVs) differ for practices with basic, fully functional, or no electronic health record (EHR). Cross-sectional analyses of WCVs included in the National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey Electronic Medical Records Supplement, 2007-2010 were performed. Practices with fully functional EHRs documented delivery of 34% more counseling topics than those without [...]

Little has been written about physician stress that may be associated with electronic medical records (EMR).

The intersection of electronic health records (EHR) and patient safety is complex. To examine the applicability of two previously developed conceptual models comprehensively to understand safety implications of EHR implementation in the English National Health Service (NHS).

To optimize a new visit-independent, population-based cancer screening system (TopCare) by using operations research techniques to simulate changes in patient outreach staffing levels (delegates, navigators), modifications to user workflow within the information technology (IT) system, and changes in cancer screening recommendations.

Few ambulatory medication reconciliation tools exist. Transitions between inpatient and outpatient care can result in medication discrepancies. An interdisciplinary team designed a new 'Secure Messaging for Medication Reconciliation Tool' (SMMRT) within a patient web portal and piloted it among 60 patients at a Veterans Affairs hospital, an integrated system with a shared electronic health record. Recently discharged patients used SMMRT to view their medications in a secure email message and [...]

To understand the impact of GeneInsight Clinic (GIC), a web-based tool designed to manage genetic information and facilitate communication of test results and variant updates from the laboratory to the clinics, we measured the use of GIC and the time it took for new genetic knowledge to be available to clinicians.

The potential of pharmacogenomics is well documented, and functionality exploiting this knowledge is about to be introduced into electronic medical records. To explore physicians' reactions to automatic interpretations of genetic tests, we built a prototype with a simple interpretive algorithm. The algorithm was adapted to the needs of physicians handling immunosuppressive treatment during organ transplantation. Nine physicians were observed expressing their thoughts while using the prototype for two patient scenarios [...]