Literature DB >> 12467794

Data quality probes-exploiting and improving the quality of electronic patient record data and patient care.

Philip J B Brown1, Victoria Warmington.   

Abstract

Increasing reliance is being placed on electronic medical records to support clinical care and achieve improved quality standards. In order for clinical information systems (CIS) to deliver excellence the data within it needs to be complete, consistent and accurate. This capture of data is critical but forms only part of the procedure in delivering quality health care during the clinician-patient encounter. A number of processes are involved in this encounter, each of which has to be performed flawlessly to deliver a perfect outcome. This paper outlines a method of assessing the quality of these processes involved in healthcare provision and data quality within a CIS. It proposes the principle of Data Quality Probes (DQP) to assess the performance of the whole encounter system. The main feature of this is the generation of a query which clinical knowledge predicts should not retrieve any cases in a system performing flawlessly. Any cases retrieved (which fail the DQP) indicate an error in either data quality or clinical judgment. This approach is applied practically within the paradigm of a UK family practice testing the hypothesis that a series DQPs can provide a valuable method for monitoring both the data accuracy of a CIS and the provision of quality patient care.

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Year:  2002        PMID: 12467794     DOI: 10.1016/s1386-5056(02)00068-0

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  13 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.  Benefits of the DICOM modality performed procedure step.

Authors:  Rita Noumeir
Journal:  J Digit Imaging       Date:  2005-12       Impact factor: 4.056

3.  Electronic health records based phenotyping in next-generation clinical trials: a perspective from the NIH Health Care Systems Collaboratory.

Authors:  Rachel L Richesson; W Ed Hammond; Meredith Nahm; Douglas Wixted; Gregory E Simon; Jennifer G Robinson; Alan E Bauck; Denise Cifelli; Michelle M Smerek; John Dickerson; Reesa L Laws; Rosemary A Madigan; Shelley A Rusincovitch; Cynthia Kluchar; Robert M Califf
Journal:  J Am Med Inform Assoc       Date:  2013-08-16       Impact factor: 4.497

4.  Data quality assessment framework to assess electronic medical record data for use in research.

Authors:  Andrew P Reimer; Alex Milinovich; Elizabeth A Madigan
Journal:  Int J Med Inform       Date:  2016-03-24       Impact factor: 4.046

5.  Rule-Based Data Quality Assessment and Monitoring System in Healthcare Facilities.

Authors:  Zhan Wang; Serhan Dagtas; John Talburt; Ahmad Baghal; Meredith Zozus
Journal:  Stud Health Technol Inform       Date:  2019

6.  A Rule-Based Data Quality Assessment System for Electronic Health Record Data.

Authors:  Zhan Wang; John R Talburt; Ningning Wu; Serhan Dagtas; Meredith Nahm Zozus
Journal:  Appl Clin Inform       Date:  2020-09-23       Impact factor: 2.342

7.  Data quality assessment for comparative effectiveness research in distributed data networks.

Authors:  Jeffrey S Brown; Michael Kahn; Sengwee Toh
Journal:  Med Care       Date:  2013-08       Impact factor: 2.983

Review 8.  Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research.

Authors:  Nicole Gray Weiskopf; Chunhua Weng
Journal:  J Am Med Inform Assoc       Date:  2012-06-25       Impact factor: 4.497

9.  A Data Quality Assessment Guideline for Electronic Health Record Data Reuse.

Authors:  Nicole G Weiskopf; Suzanne Bakken; George Hripcsak; Chunhua Weng
Journal:  EGEMS (Wash DC)       Date:  2017-09-04

10.  Effectiveness of Implementation of Electronic Malaria Information System as the National Malaria Surveillance System in Thailand.

Authors:  Shaojin Ma; Saranath Lawpoolsri; Ngamphol Soonthornworasiri; Amnat Khamsiriwatchara; Kasemsak Jandee; Komchaluch Taweeseneepitch; Rungrawee Pawarana; Sukanya Jaiklaew; Boonchai Kijsanayotin; Jaranit Kaewkungwal
Journal:  JMIR Public Health Surveill       Date:  2016-05-06
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