Abstract

BackgroundAdvances in medical domain has led to an increase of clinical data production which offers enhancement opportunities for clinical research sector. In this paper, we propose to expand the scope of Electronic Medical Records in the University Malaya Medical Center (UMMC) using different techniques in establishing interoperability functions between multiple clinical departments involving diagnosis, screening and treatment of breast cancer and building automatic systems for clinical audits as well as for potential data mining to enhance clinical breast cancer research in the future.ResultsQuality Implementation Framework (QIF) was adopted to develop the breast cancer module as part of the in-house EMR system used at UMMC, called i-Pesakit©. The completion of the i-Pesakit© Breast Cancer Module requires management of clinical data electronically, integration of clinical data from multiple internal clinical departments towards setting up of a research focused patient data governance model. The 14 QIF steps were performed in four main phases involved in this study which are (i) initial considerations regarding host setting, (ii) creating structure for implementation, (iii) ongoing structure once implementation begins, and (iv) improving future applications. The architectural framework of the module incorporates both clinical and research needs that comply to the Personal Data Protection Act.ConclusionThe completion of the UMMC i-Pesakit© Breast Cancer Module required populating EMR including management of clinical data access, establishing information technology and research focused governance model and integrating clinical data from multiple internal clinical departments. This multidisciplinary collaboration has enhanced the quality of data capture in clinical service, benefited hospital data monitoring, quality assurance, audit reporting and research data management, as well as a framework for implementing a responsive EMR for a clinical and research organization in a typical middle-income country setting. Future applications include establishing integration with external organization such as the National Registration Department for mortality data, reporting of institutional data for national cancer registry as well as data mining for clinical research. We believe that integration of multiple clinical visit data sources provides a more comprehensive, accurate and real-time update of clinical data to be used for epidemiological studies and audits.

Highlights

  • Advances in medical domain has led to an increase of clinical data production which offers enhancement opportunities for clinical research sector

  • The completion of the University Malaya Medical Center (UMMC) i-Pesakit© Breast Cancer Module required populating Electronic Medical Record (EMR) including management of clinical data access, establishing information technology and research focused governance model and integrating clinical data from multiple internal clinical departments. This multidisciplinary collaboration has enhanced the quality of data capture in clinical service, benefited hospital data monitoring, quality assurance, audit reporting and research data management, as well as a framework for implementing a responsive EMR for a clinical and research organization in a typical middle-income country setting

  • We believe that integration of multiple clinical visit data sources provides a more comprehensive, accurate and realtime update of clinical data to be used for epidemiological studies and audits

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Summary

Introduction

Advances in medical domain has led to an increase of clinical data production which offers enhancement opportunities for clinical research sector. University Malaya Medical Centre (UMMC) Surgical Breast Unit has produced the first breast cancer outcomes data in Malaysia [2,3,4]. In Malaysia, data capture methods had been manual and done retrospectively by tracing notes of patients’ clinical characteristics and treatment characteristics. This method is expensive with high probability of missing values and inaccuracies. In a typical clinical set up, these primary data are used for surgical audits in measuring the hospital performance, while the secondary use data will be used in epidemiological analysis in breast cancer outcome research

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