Literature DB >> 24551337

Does access modality matter? Evaluation of validity in reusing clinical care data.

Christopher P Danford1, Monica M Horvath2, W Edward Hammond2, Jeffrey M Ferranti3.   

Abstract

Self-service database portals may improve access to institutional data resources for clinical research or quality improvement, but questions remain about the validity of this approach. We tested the accuracy of data extracted from a clinical data repository using a self-service portal by comparing three approaches to measuring medication use among patients with coronary disease: (1) automated extraction using a portal, (2) extraction by an experienced data architect, and (3) manual chart abstraction. Outcomes included medications and diagnoses (e.g., myocardial infarction, heart failure). Charts were manually reviewed for 200 patients. Using matched criteria, self-service query identified 7327 of 7358 patients identified by the data analyst. For patients in both cohorts, agreement rates ranged from 0.99 for demographic data to 0.94 for laboratory data. Based on chart review, the self-service portal and the analyst had similar sensitivities and specificities for comorbid diagnoses and statin use.

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Mesh:

Year:  2013        PMID: 24551337      PMCID: PMC3900178     

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


  7 in total

1.  Practices and perspectives on building integrated data repositories: results from a 2010 CTSA survey.

Authors:  Sandra L MacKenzie; Matt C Wyatt; Robert Schuff; Jessica D Tenenbaum; Nick Anderson
Journal:  J Am Med Inform Assoc       Date:  2012-03-21       Impact factor: 4.497

Review 2.  Accuracy of data in computer-based patient records.

Authors:  W R Hogan; M M Wagner
Journal:  J Am Med Inform Assoc       Date:  1997 Sep-Oct       Impact factor: 4.497

3.  Association of diagnostic coding with trends in hospitalizations and mortality of patients with pneumonia, 2003-2009.

Authors:  Peter K Lindenauer; Tara Lagu; Meng-Shiou Shieh; Penelope S Pekow; Michael B Rothberg
Journal:  JAMA       Date:  2012-04-04       Impact factor: 56.272

4.  Automated identification of postoperative complications within an electronic medical record using natural language processing.

Authors:  Harvey J Murff; Fern FitzHenry; Michael E Matheny; Nancy Gentry; Kristen L Kotter; Kimberly Crimin; Robert S Dittus; Amy K Rosen; Peter L Elkin; Steven H Brown; Theodore Speroff
Journal:  JAMA       Date:  2011-08-24       Impact factor: 56.272

5.  The DEDUCE Guided Query tool: providing simplified access to clinical data for research and quality improvement.

Authors:  Monica M Horvath; Stephanie Winfield; Steve Evans; Steve Slopek; Howard Shang; Jeffrey Ferranti
Journal:  J Biomed Inform       Date:  2010-12-02       Impact factor: 6.317

6.  Predicting in-hospital deaths from coronary artery bypass graft surgery. Do different severity measures give different predictions?

Authors:  L I Iezzoni; A S Ash; M Shwartz; B E Landon; Y D Mackiernan
Journal:  Med Care       Date:  1998-01       Impact factor: 2.983

7.  Identifying patient smoking status from medical discharge records.

Authors:  Ozlem Uzuner; Ira Goldstein; Yuan Luo; Isaac Kohane
Journal:  J Am Med Inform Assoc       Date:  2007-10-18       Impact factor: 4.497

  7 in total
  2 in total

1.  What Is Asked in Clinical Data Request Forms? A Multi-site Thematic Analysis of Forms Towards Better Data Access Support.

Authors:  David A Hanauer; Gregory W Hruby; Daniel G Fort; Luke V Rasmussen; Eneida A Mendonça; Chunhua Weng
Journal:  AMIA Annu Symp Proc       Date:  2014-11-14

2.  Substance use disorders and medical comorbidities among high-need, high-risk patients with diabetes.

Authors:  Li-Tzy Wu; Udi E Ghitza; He Zhu; Susan Spratt; Marvin Swartz; Paolo Mannelli
Journal:  Drug Alcohol Depend       Date:  2018-03-03       Impact factor: 4.492

  2 in total

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