Incomplete Medical Resumes: Unveiling the Critical Factors
DOI:
https://doi.org/10.51699/ijhsms.v2i3.1274Keywords:
incomplete medical resumes, factors, methodology, motivation, financial constraintsAbstract
This study aims to investigate the primary factors causing incomplete medical resume forms in inpatient settings. By analyzing medical resumes, the research identifies method, media, motivation, and financial factors as the main contributors to the observed deficiencies. The absence of a standard operational procedure (SOP) emerged as the top priority, followed by the lack of dedicated media for doctors and budgetary constraints impacting medical record availability. Lastly, the study highlights the absence of strict sanctions for personnel not completing medical resumes accurately. The findings of this research hold implications for improving the quality of medical resumes by addressing these identified factors, thereby enhancing patient care and treatment documentation.
Downloads
References
Al-Emran, M., Mezhuyev, V. and Kamaludin, A. (2018) ‘Technology Acceptance Model in M-learning context: A systematic review’, Computers & Education, 125, pp. 389– 412.
Aldosari, B. et al. (2018) ‘Assessment of factors influencing nurses acceptance of electronic medical record in a Saudi Arabia hospital’, Informatics in Medicine Unlocked, 10(September 2017), pp. 82–88. Available at: https://doi.org/10.1016/j.imu.2017.12.007.
Ammenwerth, E. (2019) ‘Technology Acceptance Models in ealth nformatics: TAM and UTAUT’, Studies in Health Technology and Informatics, 263, pp. 64–71. Available at: https://doi.org/10.3233/SHTI190111.
Asadi, S. et al. (2019) ‘An Integrated SEM-Neural Network Approach for Predicting Determinants of Adoption of Wearable Healthcare Devices’, Mobile Information Systems, 2019. Available at: https://doi.org/10.1155/2019/8026042.
Bayaga, A. and Ophoff, J. (2019) ‘Determinants of E- Government Use in Developing Countries: The Influence of Privacy and Security Concerns’, 2nd International Conference on Next Generation Computing Applications 2019, NextComp 2019 - Proceedings [Preprint]. Available at: https://doi.org/10.1109/NEXTCOMP.2019.8883653.
Bentley, C.L. et al. (2014) ‘Addressing design and suitability barriers to telecare use: has anything changed?’, Technology and Disability, 26(4), pp. 221–235.
Cajita, M.I. et al. (2017) ‘Intention to Use mHealth in Older Adults with Heart Failure’, J Cardiovasc Nurs, 32(6), pp. 1–13. Available at: https://doi.org/10.1097/JCN.0000000000000401.
Damayanti, N.A. et al. (2019) ‘Integrated information system for early detection of maternal risk factors based on continuum of care approach of mother and toddler cohorts’, Healthcare Informatics Research, 25(3), pp. 153–160.
Davis, F.D., Bagozzi, R.P. and Warshaw, P.R. (1989) ‘User acceptance of computer technology: A comparison of two theoretical models’, Management science, 35(8), pp. 982– 1003.
Deng, Z. et al. (2018) ‘What predicts patients’ adoption intention toward mhealth services in China: Empirical study’, JMIR mHealth and uHealth, 6(8), pp. 1–14. Available at: https://doi.org/10.2196/mhealth.9316.
Deng, Z., Liu, S. and Hinz, O. (2015) ‘The health information seeking and usage behavior intention of Chinese consumers through mobile phones’, Information Technology & People, 28(2), pp. 405–423. Available at: https://doi.org/DOI 10.1108/ITP-03-2014-0053.
Dishaw, M.T. and Strong, D.M. (1999) ‘Extending the technology acceptance model with task-technology fit constructs’, Information and Management, 36(1), pp. 9–21. Available at: https://doi.org/10.1016/S0378-7206(98)00101- 3.
Estriegana, R., Medina-Merodio, J.-A. and Barchino, R. (2019) ‘Student acceptance of virtual laboratory and practical work: An extension of the technology acceptance model’, Computers & Education, 135, pp. 1–14.
Faqih, K.M.S. and Jaradat, M.-I.R. (2015) ‘Mobile Healthcare Adoption among Patients in a Developing Country Environment: Exploring the Influence of Age and Gender Differences’, International Business Research, 8(9), pp. 142–174. Available at: https://doi.org/10.5539/ibr.v8n9p142.
Fenny, A.P., Crentsil, A.O. and Ackah, C. (2018) ‘The health MDGs in Ghana: lessons and implications for the implementation of the sustainable development goals’, Journal of Public Health, 26(2), pp. 225–234.
Gandhi, S. et al. (2021) ‘A systematic review of Demand- based & Supply-based Interventions on continuum of maternal and child healthcare in south Asian countries’, Journal of Public Health, 29(4), pp. 857–870.
Green, D.T. and Pearson, J.M. (2011) ‘Integrating website usability with the electronic commerce acceptance model’, Behaviour and Information Technology, 30(2), pp. 181–199. Available at: https://doi.org/10.1080/01449291003793785.
Greenhalgh, T. et al. (2015) ‘What is quality in assisted living technology? The ARCHIE framework for effective telehealth and telecare services’, BMC medicine, 13(1), pp. 1–15.
De Grood, C. et al. (2016) ‘Adoption of e-health technology by physicians: a scoping review’, Journal of multidisciplinary healthcare, 9, p. 335.
Gücin, N.Ö. and Berk, Ö.S. (2015) ‘Technology Acceptance in Health Care: An Integrative Review of Predictive Factors and Intervention Programs’, Procedia - Social and Behavioral Sciences, 195, pp. 1698–1704. Available at: https://doi.org/10.1016/j.sbspro.2015.06.263.
Kamal, S.A., Shafiq, M. and Kakria, P. (2020) ‘Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM)’, Technology in Society, 60(September 2019), p. 101212. Available at: https://doi.org/10.1016/j.techsoc.2019.101212.
Kim, H.M. et al. (2021) ‘GPS Tracking in Dementia Caregiving : Social Norm , Perceived Usefulness , and Behavioral Intent to Use Technology’, Proceedings of the 54th Hawaii International Conference on System Sciences, 0, pp. 3804–3817.
Lazard, A.J. et al. (2016) ‘Design simplicity influences patient portal use: The role of aesthetic evaluations for technology acceptance’, Journal of the American Medical Informatics Association, 23(e1), pp. e157–e161. Available at: https://doi.org/10.1093/jamia/ocv174.
Lin, C.C. (2013) ‘Exploring the relationship between technology acceptance model and usability test’, Information Technology and Management, 14(3), pp. 243–255. Available at: https://doi.org/10.1007/s10799-013-0162-0.
Mohamamad, A. and Yunus, A.M. (2017) ‘Technology Acceptance in Healthcare Service: A Case of Electronic Medical Records (ERM)’, International Journal of Academic Research in Business and Social Sciences, 7(11). Available at: https://doi.org/10.6007/ijarbss/v7-i11/3522.
Or, C.K.L. and Karsh, B.T. (2009) ‘A Systematic Review of Patient Acceptance of Consumer Health Information Technology’, Journal of the American Medical Informatics Association, 16(4), pp. 550–560. Available at: https://doi.org/10.1197/jamia.M2888.
Pai, F.Y. and Huang, K.I. (2011) ‘Applying the Technology Acceptance Model to the introduction of healthcare information systems’, Technological Forecasting and Social Change, 78(4), pp. 650–660. Available at: https://doi.org/10.1016/j.techfore.2010.11.007.
Peek, S.T.M. et al. (2014) ‘Factors influencing acceptance of technology for aging in place: A systematic review’, International Journal of Medical Informatics, 83(4), pp. 235–
Available at: https://doi.org/10.1016/j.ijmedinf.2014.01.004.
PERMENKES RI No 269/MENKES/PER/III/2008 (2008)
‘Permenkes RI 269/MENKES/PER/III/2008’, Permenkes Ri No 269/Menkes/Per/Iii/2008, p. 7.
Purwanto, E. and Budiman, V. (2020) ‘Applying the technology acceptance model to investigate the intention to use E-health: A conceptual framework’, Technology Reports of Kansai University, 62(05), pp. 2569–2580.
Rafique, H. et al. (2020) ‘Investigating the acceptance of mobile library applications with an extended technology acceptance model (TAM)’, Computers & Education, 145, p. 103732.
Rahimi, B. et al. (2018) ‘A systematic review of the technology acceptance model in health informatics’, Applied clinical informatics, 9(03), pp. 604–634.
Reicht, T. and Stocker, A. (2011) ‘Der Nutzen Sozialer Netzwerkplattformen im professionellen Bereich. Eine Befragung der Nutzer von Xing.’, (August), p. 104.
Rho, M.J., Choi, I. young and Lee, J. (2014) ‘Predictive factors of telemedicine service acceptance and behavioral intention of physicians’, International Journal of Medical Informatics, 83(8), pp. 559–571. Available at: https://doi.org/10.1016/j.ijmedinf.2014.05.005.
Salloum, S.A. et al. (2019) ‘Exploring students’ acceptance of e-learning through the development of a comprehensive technology acceptance model’, IEEE access, 7, pp. 128445– 128462.
Santi, M.W. and Deharja, A. (2019) ‘The Effect Of Information System Usability And Midwife Involvement Toward Perceived Usefulness Of Jember Safety Center (Jsc) With Fai In Jember Regency’, in Proceeding of the 1st International Conference on Food and Agriculture.
Scherer, R., Siddiq, F. and Tondeur, J. (2019) ‘The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining
Gaspersz, V. (2006). Vincent Gaspersz 1. 1–120.
Haqqi, A., Aini, N. N., & Wicaksono, A. P. (2020). J-REMI: Journal of Medical Records and Health Information 1(4), 492–501.
Ministry of Health (2008). Regulation of the Minister of Health of the Republic of Indonesia No. 269 concerning Medical Records. Minister of Health Regulation No. 269/Menkes/Per/III/2008, 2008, 7.
Ministry of Health. (2013). ORGANIZATION OF MEDICAL RECORDERS WORK. Universidade Federal Do Triângulo Mineiro, 53(9), 1689–1699.
/citations?view_op=view_citation&continue=/scholar%3Fhl
%3Dpt- BR%26as_sdt%3D0,5%26scilib%3D1&citilm=1&citation_ for_view=wS0xi2wAAAAJ:2osOgNQ5qMEC&hl=pt- BR&oi=p
Latifah, E., Agung, S., & Rinda, R. T. (2020). The Effect of Motivation and Job Satisfaction on Employee Performance. Manager: Journal of Management Science, 2(4), 566. https://doi.org/10.32832/manager.v2i4.3811
Lestari Wiji, Astuti Retno, & Isworo Slamet. (2020). Completeness of filling medical record documents on inpatient ward, Ungaran General Hospital-Semarang, Central Java -Indonesia. GSC Biological and Pharmaceutical Sciences, 12(1), 145–155. https://doi.org/10.30574/gscbps.2020.12.1.0209
Maharani, N., Deharja, A., Wijayanti, R. A., Setiawan, D., & Putra, H. (2022). J-REMI: Journal of Medical Records and Health Information ANALYSIS OF FACTORS RELATED TO MEDICAL RESUME COMPLETENESS –
LITERATURE REVIEW J-REMI: Journal of Medical Records and Health Information. 3(2), 119–130.
Notoadmojo, S. (2010). Health Research Methodology. Renika Cipta.
Putri, A. (2021). ANALYSIS OF INCOMPATIBILITY OF FILLING IN INpatient MEDICAL RESUME IN THE CASE
OF COVID-19 AT SOREANG Hospital Amalia Putri, Lisnawati and Meira Hidayati Piksi Ganesha Polytechnic Accepted: Abstract Revised: Approved: Analysis of Incomplete Filling of Medical Resume. 1, 734–741.
Sodik, M. A., & Widyastika, K. S. (2020). Analysis Completeness of Outpatient Medical Record Documents Completion Based on Motivation and Compliance with Basic Tasks and The Function of Officers. 5(1), 25–31.
Sri Sugiarsi, Rizqy Zumrotus Sholikhah, & Eka Novayanti. (2021). Factors Causing Delay in Returning Inpatient Medical Record Documents. Indonesian Journal of Health Information Management, 1(2), 23–28. https://doi.org/10.54877/ijhim.v1i2.26
Tini, H., & Maulana, D. (2018). Overview of the Incomplete Completion of Medical Resume of Inpatients at Setia Mitra Hospital in 2018. Medical Record, 5(01), 9. http://v2.eprints.ums.ac.id/archive/etd/32431
Virdiana, A. R. (2015). Procedure and Budget. 9–20.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Rossalina Adi Wijayanti, Siti Alifa Lufianti
This work is licensed under a Creative Commons Attribution 4.0 International License.
