Quality of Electronic Medical Record Information and Satisfaction of Electronic Medical Record Users at Pandan Arang Boyolali Regional Hospital

Sri  Sugiarsi; Sri  Mulyono; Trismianto Asmo  Sutrisno

doi:10.21070/pels.v6i0.1982

(1) * Sri Sugiarsi Health Information Management STIKes Mitra Husada Karanganyar
Indonesia
(2) Sri Mulyono Health Information Management STIKes Mitra Husada Karanganyar
Indonesia
(3) Trismianto Asmo Sutrisno Health Information Management STIKes Mitra Husada Karanganyar
Indonesia
(*) Corresponding Author

DOI: https://doi.org/10.21070/pels.v6i0.1982

Abstract

Information Quality can be defined as how well the function concerning the value of the output of information produced or managed by the application/ system for users can meet everyone’s expectations and will help complete their work. Information Quality measurement indicators (Riskinanto, 2016) are information quality based on accuracy value, information quality based on timeliness of delivery, and information quality based on relevance. This study aims to explaining the quality of information and user satisfaction of electronic medical records at the Pandan Arang Regional General Hospital. This study is descriptive with the aim of describing the quality of information and satisfaction of electronic medical record users. The sample was 77 people consisting of doctors, nurses and medical record officers. Primary data were collected using questionnaires. Data analysis using descriptive analysis. Results: of the information quality variable have a mean of 17.5. With a mean of 17.5, it can be concluded that the quality of information is included in the very high-quality category with an interval of 16.8-20. information satisfaction variable have a mean of 8.4. With a mean of 8.4, it can be concluded that information satisfaction falls into the satisfied category with an interval of 8.4-10. Although information satisfaction has an average value that falls into the satisfied criteria, there are still respondents who choose to be quite satisfied regarding the information satisfaction received by system users. Conclution: Electronic medical record (EMR) information quality and user satisfaction are closely related, impacting the effectiveness and adoption of EMR systems in healthcare settings. Research shows that while EMRs can improve perceived medical record quality

Downloads

Download data is not yet available.

References

[1] Kementerian Kesehatan RI, Peraturan Menteri Kesehatan Republik Indonesia Nomor 24 Tahun 2022 Tentang Rekam Medis. Jakarta, 2023.
[2] L. Min, Q. Tian, X. Lu, and H. Duan, "Modeling EHR with the openEHR approach: An exploratory study in China Philip Payne," BMC Med. Inform. Decis. Mak., vol. 18, no. 1, 2018, doi: 10.1186/s12911-018-0650-6.
[3] P. Taylor et al., "Critical Success Factors for Adoption of Electronic Health Record Systems: Literature Review and Prescriptive Analysis," J. Med. Syst., vol. 37, no. 1, pp. 37–41, 2014, doi: 10.1080/10580530.2014.958024.
[4] C. S. Kruse, C. Kristof, B. Jones, E. Mitchell, and A. Martinez, "Barriers to Electronic Health Record Adoption: A Systematic Literature Review," J. Med. Syst., 2016, doi: 10.1007/s10916-016-0628-9.
[5] E. C. Khoong, R. Cherian, G. Y. Matta, C. R. Lyles, D. Schillinger, and N. Ratanawongsa, "Perspectives of English, Chinese, and Spanish-speaking safety-net patients on clinician computer use: Qualitative analysis," J. Med. Internet Res., vol. 21, no. 5, pp. 1–7, 2019, doi: 10.2196/13131.
[6] B. H. Nelson, R. R. Todd, and P. A. Wixom, "Antecedents of Information and System Quality: An Empirical Examination Within the Context of Data Warehousing," J. Manag. Inf. Syst., vol. 21, no. 4, 2015.
[7] M. B. Hansen, K. Kidholm, C. Nøhr, T. Schmidt, and K. T. Elmholdt, "Model for Evaluating the Implementation of a Third Generation EHR System," Stud. Health Technol. Inform., vol. 265, 2019, doi: 10.3233/SHTI190153.
[8] P. Messeri et al., "An Information Systems Model of the Determinants of Electronic Health Record Use," Appl. Clin. Inform., vol. 4, no. 2, 2013, doi: 10.4338/ACI-2013-01-RA-0005.
[9] L. A. Baumann, J. Baker, and A. G. Elshaug, "The impact of electronic health record systems on clinical documentation times: A systematic review," Health Policy, vol. 122, no. 8, pp. 827–836, 2018, doi: 10.1016/j.healthpol.2018.05.014.
[10] N. Aouira et al., "Paper-based vs. electronic records for clinical audit: Evidence of documentation of medication safety monitoring in youth prescribed antipsychotics," Child. Youth Serv. Rev., vol. 109, p. 104666, 2020, doi: 10.1016/j.childyouth.2019.104666.
[11] M. Alwhaibi et al., "Measuring the quality and completeness of medication-related information derived from hospital electronic health records database," Saudi Pharm. J., vol. 27, no. 4, pp. 502–506, 2019, doi: 10.1016/j.jsps.2019.01.013.
[12] S. Khan, M. Millery, A. Campbell, J. Merrill, S. Shih, R. Kukafka, and P. Messeri, "An Information Systems Model of the Determinants of Electronic Health Record Use," Appl. Clin. Inform., vol. 4, no. 2, pp. 185–200, 2013.
[13] L. A. Baumann, J. Baker, and A. G. Elshaug, "The impact of electronic health record systems on clinical documentation times: A systematic review," Health Policy, vol. 122, no. 8, pp. 827–836, 2018.
[14] A. Roy, A. Lapi, D. Spergel, and C. Baccigalupi, "Observing patchy reionization with future CMB polarization experiments," J. Cosmol. Astropart. Phys., vol. 2018, no. 6, p. 014, Jun. 2018.
[15] N. Aouira, S. Khan, B. McDermott, H. Heussler, A. Haywood, A. Karaksha, and W. Bor, "Paper-based vs. electronic records for clinical audit: Evidence of documentation of medication safety monitoring in youth prescribed antipsychotics," Child. Youth Serv. Rev., vol. 117, p. 105272, 2020.