Professional self-awareness and medical record data integrity: A phenomenological study among health information management personnel in indonesian primary care

Authors

DOI:

https://doi.org/10.61099/jih.v2i3.485

Keywords:

Electronic Health Records, Health Information Management, Medical Records, Primary Health Care, Self-Assessment

Abstract

Introduction: Accurate and consistent medical record data are essential for patient safety, continuity of care, service evaluation, and health-system decision-making. However, data-quality problems may persist despite electronic medical record implementation because documentation is also shaped by human behaviour and organisational conditions. This study aimed to explore how health information management personnel understand and practise professional self-awareness, its perceived role in maintaining medical record accuracy and consistency, and the conditions supporting or constraining reflective data-management practices in Indonesian primary care.

Research Methodology: A descriptive phenomenological study was conducted at Antang Primary Health Centre, Makassar, Indonesia, from April to June 2026. Twelve health information management personnel were recruited through purposive sampling. Data were collected through semi-structured in-depth interviews, non-participant observation, field notes, and document review. Interview data were transcribed verbatim and analysed using a phenomenological thematic procedure involving significant-statement identification, meaning-unit formulation, coding, categorisation, and theme development. Trustworthiness was supported through triangulation, member checking, peer debriefing, reflexive journaling, and an audit trail.

Results: Five major themes and ten subthemes were identified: professional responsibility for data integrity, reflective verification of medical record data, recognition and correction of documentation errors, organisational barriers to consistent documentation, and development of a collective data-quality culture. Participants had 1–12 years of professional experience, and interviews lasted 35–60 minutes. High workload, time pressure, incomplete documentation, and inconsistent recording practices constrained reflective verification.

Conclusion: Professional self-awareness supports medical record integrity through verification, error recognition, reflection, communication, and corrective action. Primary healthcare facilities should combine individual accountability with standardised checklists, routine audits, supportive supervision, non-punitive error reporting, and digital validation mechanisms

Downloads

Download data is not yet available.

References

1. Agrawal L, DaSouza RO, Mulgund P, Chaudhary P. Frequency of Electronic Personal Health Record Use in US Older Adults: Cross-Sectional Study of a National Survey. JMIR Aging. 2025;8. doi:https://doi.org/10.2196/71460

2. Alomar D, Almashmoum M, Eleftheriou I, Whelan P, Ainsworth J. The Impact of Patient Access to Electronic Health Records on Health Care Engagement: Systematic Review. J Med Internet Res. 2024;26. doi:https://doi.org/10.2196/56473

3. AlHussainan A, Alhuwail D. Bridging Global Frameworks and Local Practice: Quantitative Evaluation of Electronic Health Record Safety in Kuwait’s Public Hospitals. JMIR Med Informatics. 2025;13. doi:https://doi.org/10.2196/70782

4. Chimbo B, Motsi L. The Effects of Electronic Health Records on Medical Error Reduction: Extension of the DeLone and McLean Information System Success Model. JMIR Med Informatics. 2024;12. doi:https://doi.org/10.2196/54572

5. Cook N, Hoopes M, Biel FM, Cartwright N, Gordon M, Sills M. Early Results of an Initiative to Assess Exposure to Firearm Violence in Ambulatory Care: Descriptive Analysis of Electronic Health Record Data. JMIR Public Heal Surveill. 2024;10. doi:https://doi.org/10.2196/47444

6. Cooley ME, Lenert LA, Abrahm JL, Lobach DF. Using Data-driven Clinical Decision Support to Integrate Precision Cancer Symptom Management Into the Electronic Health Record. Semin Oncol Nurs. 2025;41(4):151937. doi:https://doi.org/10.1016/j.soncn.2025.151937

7. de Oliveira JMD, Mohr ETB, Scandolara DH, et al. Mapping the evaluation of Brazil’s national electronic health system for primary care (PEC e-SUS APS): a scoping review. Comput Biol Med. 2025;197:110983. doi:https://doi.org/10.1016/j.compbiomed.2025.110983

8. Font M, Davoody N. Optimizing an Electronic Health Record System Used to Help Health Care Professionals Comply With a Standardized Care Pathway for Heart Failure During the Transition From Hospital To Chronic Care: Qualitative Semistructured Interview Study. JMIR Med Informatics. 2025;13. doi:https://doi.org/10.2196/63665

9. Ghosh J, Gudzune KA, Schwartz JL. Electronic health records tools for treating obesity among adult patients in primary care: A scoping review. Obes Pillars. 2025;13:100161. doi:https://doi.org/10.1016/j.obpill.2025.100161

10. Goh KH, Yeow AYK, Wang L, et al. The Benefits of Integrating Electronic Medical Record Systems Between Primary and Specialist Care Institutions: Mixed Methods Cohort Study. J Med Internet Res. 2025;27. doi:https://doi.org/10.2196/49363

11. Jhamb M, Weltman MR, Yabes JG, et al. Electronic health record based population health management to optimize care in CKD: Design of the Kidney Coordinated HeAlth Management Partnership (K-CHAMP) trial. Contemp Clin Trials. 2023;131:107269. doi:https://doi.org/10.1016/j.cct.2023.107269

12. Kamdje Wabo G, Moorthy P, Siegel F, Seuchter SA, Ganslandt T. Evaluating and Enhancing the Fitness-for-Purpose of Electronic Health Record Data: Qualitative Study on Current Practices and Pathway to an Automated Approach Within the Medical Informatics for Research and Care in University Medicine Consortium. JMIR Med Informatics. 2024;12. doi:https://doi.org/10.2196/57153

13. Kariotis T, Prictor M, Gray K, Chang S. Service Users’ Perspectives on an Integrated Electronic Care Record in Mental Health Care: Qualitative Vignette and Interview Study. JMIR Med Informatics. 2025;13. doi:https://doi.org/10.2196/64162

14. Kariotis T, Prictor M, Gray K, Chang S. Patient-Accessible Electronic Health Records and Information Practices in Mental Health Care Contexts: Scoping Review. J Med Internet Res. 2025;27. doi:https://doi.org/10.2196/54973

15. Khairat S, Morelli J, Boynton MH, Bice T, Gold JA, Carson SS. Investigation of Information Overload in Electronic Health Records: Protocol for Usability Study. JMIR Res Protoc. 2025;14. doi:https://doi.org/10.2196/66127

16. Makaranga J, Moshi G, Sukums F. Exploring the nature, drivers and consequences of electronic medical record workarounds in Tanzanian public primary health care. Rec Manag J. 2025;35(3):341-355. doi:https://doi.org/10.1108/RMJ-05-2025-0049

17. Marceau M, Dulgarian S, Cambre J, et al. Clinician Attitudes and Perceptions of Point-of-Care Information Resources and Their Integration Into Electronic Health Records: Qualitative Interview Study. JMIR Med Informatics. 2025;13. doi:https://doi.org/10.2196/60191

18. Marfeo E, Sacco M, Maldonado JC, et al. Applying NLP methods to code functional performance in electronic health records using the international classification of functioning, disability, and health. Disabil Health J. 2025;18(4):101888. doi:https://doi.org/10.1016/j.dhjo.2025.101888

19. McFarlane ML, Morra A, Podgers D, Barber D, Lougheed MD. Impact of a Novel Electronic Medical Record–Integrated Electronic Form (Provider Asthma Assessment Form) and Severe Asthma Algorithm in Primary Care: Single-Center, Pre- and Postobservational Study. JMIR Form Res. 2025;9. doi:https://doi.org/10.2196/74043

20. Muli I, Cajander Å, Scandurra I, Hägglund M. Health Care Professionals’ Perspectives on Implementing Patient-Accessible Electronic Health Records in Primary Care: Qualitative Study. JMIR Med Informatics. 2025;13. doi:https://doi.org/10.2196/64982

21. Wu Y, Wu M, Wang C, Lin J, Liu J, Liu S. Evaluating the Prevalence of Burnout Among Health Care Professionals Related to Electronic Health Record Use: Systematic Review and Meta-Analysis. JMIR Med Informatics. 2024;12. doi:https://doi.org/10.2196/54811

22. Vithanage D, Yu P, Xie Q, Xu H, Wang L, Deng C. A comprehensive evaluation of large language models for information extraction from unstructured electronic health records in residential aged care. Comput Biol Med. 2025;197:111013. doi:https://doi.org/10.1016/j.compbiomed.2025.111013

23. Ose D, Adediran E, Owens R, et al. Electronic Health Record–Driven Approaches in Primary Care to Strengthen Hypertension Management Among Racial and Ethnic Minoritized Groups in the United States: Systematic Review. J Med Internet Res. 2023;25. doi:https://doi.org/10.2196/42409

24. Pradhan A, Wright EA, Hayduk VA, et al. Impact of an Electronic Health Record–Based Interruptive Alert Among Patients With Headaches Seen in Primary Care: Cluster Randomized Controlled Trial. JMIR Med Informatics. 2024;12. doi:https://doi.org/10.2196/58456

25. Shin J, Choi J, Kweon HJ, Han Y, Lee M. Hospital frailty risk score using electronic medical records and geriatric syndromes in an acute-care hospital. Geriatr Nurs (Minneap). 2025;62:175-180. doi:https://doi.org/10.1016/j.gerinurse.2025.01.016

Alternate text

Downloads

Published

2026-08-05

How to Cite

Nurfazirah, N., Ihsan Kamaruddin, M., & Andre Mangaya Takke, J. (2026). Professional self-awareness and medical record data integrity: A phenomenological study among health information management personnel in indonesian primary care. Journal Interdisciplinary Health, 2(3), 136–151. https://doi.org/10.61099/jih.v2i3.485

Similar Articles

1 2 3 4 > >> 

You may also start an advanced similarity search for this article.