Optimising the use of observational electronic health record data: Current issues, evolving opportunities, strategies and scope for collaboration.

BACKGROUND With increasing computerisation in general practice, national primary care networks are mooted as sources of data for health services and population health research and planning. Existing data collection programs - MedicinesInsight, Improvement Foundation, Bettering the Evaluation and Care of Health (BEACH) - vary in purpose, governance, methodologies and tools. General practitioners (GPs) have significant roles as collectors, managers and users of electronic health record (EHR) data. They need to understand the challenges to their clinical and managerial roles and responsibilities. OBJECTIVE The aim of this article is to examine the primary and secondary use of EHR data, identify challenges, discuss solutions and explore directions. DISCUSSION Representatives from existing programs, Medicare Locals, Local Health Districts and research networks held workshops on the scope, challenges and approaches to the quality and use of EHR data. Challenges included data quality, interoperability, fragmented governance, proprietary software, transparency, sustainability, competing ethical and privacy perspectives, and cognitive load on patients and clinicians. Proposed solutions included effective change management; transparent governance and management of intellectual property, data quality, security, ethical access, and privacy; common data models, metadata and tools; and patient/community engagement. Collaboration and common approaches to tools, platforms and governance are needed. Processes and structures must be transparent and acceptable to GPs.

[1]  Wilson D. Pace,et al.  Electronic health record functionality needed to better support primary care , 2014, J. Am. Medical Informatics Assoc..

[2]  Simon Jones,et al.  Defining datasets and creating data dictionaries for quality improvement and research in chronic disease using routinely collected data: an ontology-driven approach. , 2011, Informatics in primary care.

[3]  Simon de Lusignan,et al.  What are the Barriers to Conducting International Research Using Routinely Collected Primary Care Data? , 2011, EFMI-STC.

[4]  H. Yee.  The Patient-Centered Medical Home Neighbor: A Subspecialty Physician's View , 2011, Annals of Internal Medicine.

[5]  Christopher Pearce,et al.  A personally controlled electronic health record for Australia , 2014, J. Am. Medical Informatics Assoc..

[6]  Jane Taggart,et al.  Data quality and fitness for purpose of routinely collected data--a general practice case study from an electronic practice-based research network (ePBRN). , 2011, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[7]  Pradeep Kumar Ray,et al.  Towards an ontology for data quality in integrated chronic disease management: A realist review of the literature , 2013, Int. J. Medical Informatics.

[8]  Christopher Pearce,et al.  A division's worth of data. , 2011, Australian family physician.

[9]  C. Sinsky.  The Patient-Centered Medical Home Neighbor: A Primary Care Physician's View , 2011, Annals of Internal Medicine.

[10]  S. de Lusignan,et al.  Accelerating the development of an information ecosystem in health care, by stimulating the growth of safe intermediate processing of health information (IPHI). , 2013, Informatics in primary care.

[11]  Hairong Yu,et al.  Data extraction from electronic health records - existing tools may be unreliable and potentially unsafe. , 2013, Australian family physician.

[12]  Harshana Liyanage,et al.  Reporting of Studies Conducted using Observational Routinely Collected Data (RECORD) statement: call for contributions from the clinical informatics community. , 2012, Informatics in primary care.

[13]  Simon de Lusignan,et al.  Ontologies to Improve Chronic Disease Management Research and Quality Improvement Studies - A Conceptual Framework , 2013, MedInfo.

[14]  Peter Basch,et al.  Clinical documentation in the 21st century: executive summary of a policy position paper from the American College of Physicians. , 2015, Annals of internal medicine.

[15]  S de Lusignan,et al.  Big Data Usage Patterns in the Health Care Domain: A Use Case Driven Approach Applied to the Assessment of Vaccination Benefits and Risks , 2014, Yearbook of Medical Informatics.

[16]  Peter Basch,et al.  Clinical Documentation in the 21 st Century : Executive Summary of a Policy Position Paper From the American College of Physicians , 2015 .

[17]  S de Lusignan,et al.  Key Concepts to Assess the Readiness of Data for International Research: Data Quality, Lineage and Provenance, Extraction and Processing Errors, Traceability, and Curation , 2011, Yearbook of Medical Informatics.

[18]  Clay Shirky,et al.  Exchanging health information: local distribution, national coordination. , 2005, Health affairs.

[19]  D. Thomas,et al.  The patient-centered medical home: history, components, and review of the evidence. , 2012, The Mount Sinai journal of medicine, New York.

[20]  Harshana Liyanage,et al.  An integrated organisation-wide data quality management and information governance framework: theoretical underpinnings. , 2014, Informatics in primary care.