Evidence map›Paper›PMID 30717675›Full record

ArticleBMC bioinformatics2019

Development of electronic medical records for clinical and research purposes: the breast cancer module using an implementation framework in a middle income country- Malaysia.

Nurul Aqilah Mohd Nor, Nur Aishah Taib, Marniza Saad, Hana Salwani Zaini, Zahir Ahmad, Yamin Ahmad, Sarinder Kaur Dhillon

Abstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Digitalisation Medical Records: Improving Efficiency and Reducing Burnout in Healthcare.International journal of environmental research and public health · 2023
    Article
  5. Article
  6. Article
  7. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Nurul Aqilah Mohd NorData Science and Bioinformatics Laboratory, Institute of Biological Sciences, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia.
Nur Aishah TaibDepartment of Surgery, University Malaya Medical Centre, 50603, Kuala Lumpur, Malaysia. naisha@um.edu.my.
Marniza SaadDepartment of Oncology, University Malaya Medical Centre, 50603, Kuala Lumpur, Malaysia.
Hana Salwani ZainiDepartment of Information Technology, University Malaya Medical Centre, 50603, Kuala Lumpur, Malaysia.
Zahir AhmadDepartment of Information Technology, University Malaya Medical Centre, 50603, Kuala Lumpur, Malaysia.
Yamin AhmadDepartment of Information Technology, University Malaya Medical Centre, 50603, Kuala Lumpur, Malaysia.
Sarinder Kaur DhillonData Science and Bioinformatics Laboratory, Institute of Biological Sciences, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia. sarinder@um.edu.my.ORCID http://orcid.org/0000-0003-1922-2044

Funding

Institut Pengurusan dan Pemantauan Penyelidikan, Universiti Malaya PG130-2013AMinistry of Higher Education, Malaysia PR001-2017AMinistry of Higher Education, Malaysia UM.C/HIR/MOHE/06
6 · The paper itself

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.

Indexed as

Biomedical ResearchElectronic Health RecordsIncomeBreast NeoplasmsData AccuracyDeveloping CountriesFemaleHumansInformation Storage and RetrievalMalaysiaUser-Computer InterfaceBreast CancerDatabase mirroringElectronic medical recordMedical systemQuality implementation framework

Identifiers

PMID30717675
PMCPMC7394320

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.