A Vision for the Systematic Monitoring and Improvement of the Quality of Electronic Health Data

In parallel with the implementation of information and communications systems, health care organizations are beginning to amass large-scale repositories of clinical and administrative data. Many nations seek to leverage so-called Big Data repositories to support improvements in health outcomes, drug safety, health surveillance, and care delivery processes. An unsupported assumption is that electronic health care data are of sufficient quality to enable the varied use cases envisioned by health ministries. The reality is that many electronic health data sources are of suboptimal quality and unfit for particular uses. To more systematically define, characterize and improve electronic health data quality, we propose a novel framework for health data stewardship. The framework is adapted from prior data quality research outside of health, but it has been reshaped to apply a systems approach to data quality with an emphasis on health outcomes. The proposed framework is a beginning, not an end. We invite the biomedical informatics community to use and adapt the framework to improve health data quality and outcomes for populations in nations around the world.

[1]  Joseph Erdos,et al.  Comparison of Two VA Laboratory Data Repositories Indicates That Missing Data Vary Despite Originating From the Same Source , 2009, Medical care.

[2]  Carlo Batini,et al.  A Data Quality Methodology for Heterogeneous Data , 2011 .

[3]  N H Shah,et al.  Translational Bioinformatics Embraces Big Data , 2012, Yearbook of Medical Informatics.

[4]  David L. Buckeridge,et al.  Application of change point analysis to daily influenza-like illness emergency department visits , 2012, J. Am. Medical Informatics Assoc..

[5]  Carlo Batini,et al.  Methodologies for data quality assessment and improvement , 2009, CSUR.

[6]  David C. Kaelber,et al.  Patient characteristics associated with venous thromboembolic events: a cohort study using pooled electronic health record data , 2012, J. Am. Medical Informatics Assoc..

[7]  Christina Synowiec,et al.  E-health in low- and middle-income countries: findings from the Center for Health Market Innovations. , 2012, Bulletin of the World Health Organization.

[8]  J. Marc Overhage,et al.  A Framework for evaluating the costs, effort, and value of nationwide health information exchange , 2010, J. Am. Medical Informatics Assoc..

[9]  Ian Painter,et al.  Using Change Point Detection for Monitoring the Quality of Aggregate Data , 2013, Online Journal of Public Health Informatics.

[10]  Brian E. Dixon,et al.  Evaluating the Variation on Public Health’s Perceived Field Need of Communicable Disease Reports , 2013, Online Journal of Public Health Informatics.

[11]  Tony Norris,et al.  The strategic management of data quality in healthcare , 2008, Health Informatics J..

[12]  Marc Paladini,et al.  Detecting Changes in Chief Complaint Word Count: Effects on Syndromic Surveillance , 2013, Online Journal of Public Health Informatics.

[13]  Brian E Dixon,et al.  Incorporating Geospatial Capacity within Clinical Data Systems to Address Social Determinants of Health , 2011, Public health reports.

[14]  Yuni Xia,et al.  Using Information Entropy to Monitor Chief Complaint Characteristics and Quality , 2013, Online Journal of Public Health Informatics.

[15]  Diane M. Strong,et al.  Beyond Accuracy: What Data Quality Means to Data Consumers , 1996, J. Manag. Inf. Syst..

[16]  Lucila Ohno-Machado,et al.  Big science, big data, and a big role for biomedical informatics , 2012, J. Am. Medical Informatics Assoc..

[17]  J. Marc Overhage,et al.  A comparison of the completeness and timeliness of automated electronic laboratory reporting and spontaneous reporting of notifiable conditions. , 2008, American journal of public health.

[18]  Julie J McGowan,et al.  Electronic laboratory data quality and the value of a health information exchange to support public health reporting processes. , 2011, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[19]  C. Schoen,et al.  A survey of primary care doctors in ten countries shows progress in use of health information technology, less in other areas. , 2012, Health affairs.

[20]  Kitty S. Chan,et al.  Review: Electronic Health Records and the Reliability and Validity of Quality Measures: A Review of the Literature , 2010, Medical care research and review : MCRR.

[21]  David L Buckeridge,et al.  Patient, physician, encounter, and billing characteristics predict the accuracy of syndromic surveillance case definitions , 2012, BMC Public Health.

[22]  Richard Y. Wang,et al.  A product perspective on total data quality management , 1998, CACM.

[23]  Thomas Redman,et al.  The impact of poor data quality on the typical enterprise , 1998, CACM.

[24]  Ashish K. Jha,et al.  Electronic health records in small physician practices: availability, use, and perceived benefits , 2011, J. Am. Medical Informatics Assoc..

[25]  Jane Taggart,et al.  Health reform: Is routinely collected electronic information fit for purpose? , 2012, Emergency medicine Australasia : EMA.

[26]  S. Blount,et al.  Lead Visual Information Specialist , 2003 .

[27]  Mitchell J. Barnett,et al.  Assessing the accuracy of computerized medication histories. , 2004, The American journal of managed care.

[28]  Maulik S Joshi,et al.  Progress toward meaningful use: hospitals' adoption of electronic health records. , 2011, The American journal of managed care.