Data Science and Bioinformatics Laboratory, Institute of Biological Sciences, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia.
Department of Surgery, University Malaya Medical Centre, 50603, Kuala Lumpur, Malaysia.
BMC Bioinformatics. 2019 Feb 4;19(Suppl 13):402. doi: 10.1186/s12859-018-2406-9.
Advances 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.
Quality 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.
The 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.
医学领域的进步导致临床数据的产生增加，这为临床研究领域提供了增强的机会。在本文中，我们建议通过使用不同的技术，扩展马来亚大学医学中心（UMMC）的电子病历范围，这些技术涉及建立多个临床科室之间的互操作性功能，包括乳腺癌的诊断、筛查和治疗，以及建立临床审核的自动系统和潜在的数据挖掘，以增强未来的临床乳腺癌研究。
采用质量实施框架（QIF）来开发乳腺癌模块，作为 UMMC 使用的内部电子病历系统 i-Pesakit©的一部分。完成 i-Pesakit©乳腺癌模块需要电子管理临床数据，整合来自多个内部临床科室的临床数据，以建立一个以研究为重点的患者数据治理模型。这 14 个 QIF 步骤在本研究的四个主要阶段中执行，包括：（i）关于主机设置的初步考虑；（ii）创建实施结构；（iii）实施开始后的持续结构；（iv）改进未来应用。该模块的架构框架结合了临床和研究需求，符合个人数据保护法。
UMMC i-Pesakit©乳腺癌模块的完成需要填充电子病历，包括管理临床数据访问、建立信息技术和研究为重点的治理模型，以及整合来自多个内部临床科室的临床数据。这种多学科合作提高了临床服务中数据采集的质量，使医院数据监测、质量保证、审核报告和研究数据管理受益，并为在典型中等收入国家环境中为临床和研究组织实施响应式电子病历提供了框架。未来的应用包括与国家注册局等外部组织建立整合，报告机构数据给国家癌症登记处，以及进行临床研究的数据挖掘。我们相信，整合多个临床就诊数据源可以提供更全面、准确和实时更新的临床数据，用于进行流行病学研究和审核。
