Literature DB >> 16779116

Clinical terminology support for a national ambulatory practice outcomes research network.

Thomas N Ricciardi1, Michael I Lieberman, Michael G Kahn, F E Masarie.   

Abstract

The Medical Quality Improvement Consortium (MQIC) is a nationwide collaboration of 74 healthcare delivery systems, consisting of 3755 clinicians, who contribute de-identified clinical data from the same commercial electronic medical record (EMR) for quality reporting, outcomes research and clinical research in public health and practice benchmarking. Despite the existence of a common, centrally-managed, shared terminology for core concepts (medications, problem lists, observation names), a substantial "back-end" information management process is required to ensure terminology and data harmonization for creating multi-facility clinically-acceptable queries and comparable results. We describe the information architecture created to support terminology harmonization across this data-sharing consortium and discuss the implications for large scale data sharing envisioned by proponents for the national adoption of ambulatory EMR systems.

Mesh:

Year:  2005        PMID: 16779116      PMCID: PMC1560493     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  4 in total

1.  The use of SNOMED CT simplifies querying of a clinical data warehouse.

Authors:  Michael I Lieberman; Thomas N Ricciardi; F E Masarie; Kent A Spackman
Journal:  AMIA Annu Symp Proc       Date:  2003

2.  Impacts of computerized physician documentation in a teaching hospital: perceptions of faculty and resident physicians.

Authors:  Peter J Embi; Thomas R Yackel; Judith R Logan; Judith L Bowen; Thomas G Cooney; Paul N Gorman
Journal:  J Am Med Inform Assoc       Date:  2004-04-02       Impact factor: 4.497

3.  Unifying heterogeneous distributed clinical data in a relational database.

Authors:  K A Marrs; S A Steib; C A Abrams; M G Kahn
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1993

4.  Direct text entry in electronic progress notes. An evaluation of input errors.

Authors:  C R Weir; J F Hurdle; M A Felgar; J M Hoffman; B Roth; J R Nebeker
Journal:  Methods Inf Med       Date:  2003       Impact factor: 2.176

  4 in total
  5 in total

1.  Using NLP to extract concepts from chief complaints.

Authors:  Michael I Lieberman; Thomas N Ricciardi
Journal:  AMIA Annu Symp Proc       Date:  2005

2.  Application of information-theoretic data mining techniques in a national ambulatory practice outcomes research network.

Authors:  Adam Wright; Thomas N Ricciardi; Martin Zwick
Journal:  AMIA Annu Symp Proc       Date:  2005

3.  Implementing Single Source: the STARBRITE proof-of-concept study.

Authors:  Rebecca Kush; Liora Alschuler; Roberto Ruggeri; Sally Cassells; Nitin Gupta; Landen Bain; Karen Claise; Monica Shah; Meredith Nahm
Journal:  J Am Med Inform Assoc       Date:  2007-06-28       Impact factor: 4.497

4.  Inaccurate recording of routinely collected data items influences identification of COVID-19 patients.

Authors:  Eva S Klappe; Ronald Cornet; Dave A Dongelmans; Nicolette F de Keizer
Journal:  Int J Med Inform       Date:  2022-06-10       Impact factor: 4.730

5.  Identifying and prioritizing benefits and risks of using privacy-enhancing software through participatory design: a nominal group technique study with patients living with chronic conditions.

Authors:  Theodoros V Giannouchos; Alva O Ferdinand; Gurudev Ilangovan; Eric Ragan; W Benjamin Nowell; Hye-Chung Kum; Cason D Schmit
Journal:  J Am Med Inform Assoc       Date:  2021-07-30       Impact factor: 4.497

  5 in total

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