Natural language processor as a tool to assess heparin induced thrombocytopenia awareness.

The life-threatening consequences of heparin induced thrombocytopenia (HIT) may be prevented with early recognition, prompt heparin withdrawal and direct thrombin inhibitor use. To determine the level of HIT awareness, electronic term recognition software can be used to query the electronic medical record (EMR) to assess the thought process and test ordering behavior of health care providers confronted with falling platelet counts. We sought to assess the awareness of HIT in a large teaching institution using these tools.

The Enterprise Data Trust at Mayo Clinic: a semantically integrated warehouse of biomedical data.

Mayo Clinic's Enterprise Data Trust is a collection of data from patient care, education, research, and administrative transactional systems, organized to support information retrieval, business intelligence, and high-level decision making. Structurally it is a top-down, subject-oriented, integrated, time-variant, and non-volatile collection of data in support of Mayo Clinic's analytic and decision-making processes. It is an interconnected piece of Mayo Clinic's Enterprise Information Management initiative, which also includes Data Governance, Enterprise Data Modeling, the Enterprise Vocabulary System, and Metadata Management.

Speech recognition as a transcription aid: a randomized comparison with standard transcription.

Objective: Speech recognition promises to reduce information entry costs for clinical information systems. It is most likely to be accepted across an organization if physicians can dictate without concerning themselves with real-time recognition and editing; assistants can then edit and process the computer-generated document. Our objective was to evaluate the use of speech-recognition technology in a randomized controlled trial using our institutional infrastructure.

Relative impact of risk factors for deep vein thrombosis and pulmonary embolism: a population-based study.

Objective: To assess the potential impact of controlling risk factors on the incidence of venous thromboembolism by estimating the population attributable risk (defined as the percentage of all cases of a disease in a population that can be "attributed" to a risk factor) for deep vein thrombosis and pulmonary embolism associated with venous thromboembolism risk factors.

Methods: Using data from a population-based, nested, case-control study of the 625 Olmsted County, Minnesota, residents with a definite first lifetime deep vein thrombosis or pulmonary embolism diagnosed during the 15-year period 1976 to 1990 and 625 unaffected Olmsted County residents matched for age and sex, we developed a conditional logistic regression model appropriate to the matched case-control study design and then estimated attributable risk for the risk factors individually and collectively.

Results: Fifty-nine percent of the cases of venous thromboembolism in the community could be attributed to institutionalization (current or recent hospitalization or nursing home residence).