Abstract
Hospital information systems (HIS) have been applied on a massive scale; however, user evaluation of their effectiveness, efficiency, and service quality improvements remain rare. This study aimed to describe the utility of information systems from the users’ point of view by using the Technology Acceptance Model (TAM) in a maternity hospital in Lampung, Indonesia. The study provided an overview of the features of the information system and the workflow of the user through this information system. Screenshots were taken by using Camtasia Studio 2.0 Trial Version application software for one day (two shifts) in the outpatient service. The HIS generally supported the workflow, but not all application modules were fully applied. The obstacles appear to be at the registration unit/outpatient registration and queue dashboard, cashier unit, pharmacy unit, medicine storage/room, and poly unit/checking room. A TAM framework, which included perceived ease of use and perceived usefulness of the information system, revealed that the currently implemented HIS was not perceived as optimal. However, users are still optimistic and aware of the usefulness of the information system in supporting their jobs. Thus, leaders have committed to initiate the potential development of this information system in the inpatient polyclinic.
References
1. Ologeanu-Taddei R, Morquin D, Domingo H, Bourret R. Understanding the acceptance factors of an hospital information system: evidence from a French University Hospital. AMIA. Annu Symp Proceedings AMIA Symp. 2015: 1001–7.
2. AIHW. Review and evaluation of Australian information about primary health care. Melbourne: AIHW; 2011. p. 256.
3. Asyary A, Kusnanto H, Fuad A. Sistem peresepan elektronik pada keselamatan pengobatan pasien. Kesmas: National Public Health Journal. 2013; 8(3): 119–24.
4. Hwang JY, Kim KY, Lee KH. Factors that influence the acceptance of telemetry by emergency medical technicians in ambulances: an application of the extended technology acceptance model. Telemedicine Journal and e-Health. 2014; 20(12): 1127–34.
5. Garavand A, Mohseni M, Asadi H, Etemadi M, Moradi-Joo M, Moosavi A. Factors influencing the adoption of health information technologies: a systematic review. Electron Physician. 2016; 8(8): 2713–8.
6. Aggelidis VP, Chatzoglou PD. Using a modified technology acceptance model in hospitals. International Journal of Medical Informatics. 2009; 78(2): 115–26.
7. Gagnon MP, Orruno E, Asua J, Abdeljelil A Ben, Emparanza J. Using a modified technology acceptance model to evaluate healthcare professionals’ adoption of a new telemonitoring system. Telemedicine Journal and e-Health. 2012; 18(1): 54–9.
8. Gemala RH. Pedoman pengelolaan rekam medis rumah sakit di Indonesia. Jakarta: Direktor Jendral Pelayanan Medik Departemen Keehatan Republik Indonesia; 2010.
9. Veruswati M, Asyary A. Implementation of information system toward health system strengthening in Indonesia: a policy brief. Public Health Indonesia. 2017; 3(3): 73–6.
10. Kilsdonk E, Peute LW, Jaspers MWM. Factors influencing implementation success of guideline-based clinical decision support systems: a systematic review and gaps analysis. International Journal of Medical Informatics. 2017; 98: 56–64.
11. Sligo J, Gauld R, Roberts V, Villa L. A literature review for large-scale health information system project planning, implementation and evaluation. International Journal of Medical Informatics. 2017; 97: 86–97.
12. Cresswell KM, Mozaffar H, Lee L, Williams R, Sheikh A. Workarounds to hospital electronic prescribing systems: a qualitative study in English hospitals. BMJ Quality & Safety. 2017; 26(7): 542–51.
13. Handayani PW, Hidayanto AN, Pinem AA, Hapsari IC, Sandhyaduhita PI, Budi I. Acceptance model of a hospital information system. International Journal of Medical Informatics. 2017; 99: 11–28.
14. Michael GC, Aliyu I, Grema BA, Thacher TD. Impact of structural and interpersonal components of health care on user satisfaction with services of an outpatient clinic of a Nigerian tertiary hospital. Tropical Journal of Medical Research. 2017; 20(2): 139.
15. Lu C-C, Lin S-W, Chen H-J, Ying K-C. Optimal allocation of cashiers and pharmacists in large hospitals: a point-wise fluid-based dynamic queueing network approach. IEEE Access. 2017; 6: 2859–70.
16. Herman MJ, Handayani RS, Siahaan SA. Kajian praktik kefarmasian apoteker pada tatanan rumah sakit. Kesmas: National Public Health Journal. 2013; 7(8): 365–72.
17. Chana N, Porat T, Whittlesea C, Delaney B. Improving specialist drug prescribing in primary care using task and error analysis: an observational study. The British Journal of General Practice. 2017; 67(656): e157– 67.
18. Miller Jr DP, Latulipe C, Melius KA, Quandt SA, Arcury TA. Primary care providers’ views of patient portals: interview study of perceived benefits and consequences. Journal of Medical Internet Research. 2016; 18(1): e8.
19. Jin Y, Yan M. Computer literacy and the construct validity of a high-stakes computer-based writing assessment. Language Assessment Quarterly. 2017; 14(2): 101–19.
20. Tsai HS, Shillair R, Cotten SR. Social support and “playing around” an examination of how older adults acquire digital literacy with tablet computers. Journal of Applied Gerontology. 2017; 36(1): 29–55.
Recommended Citation
Asyary A , Prasetyo AK , Eryando T ,
et al.
Users’ Perception of the Hospital Information System in a Maternity Hospital in Lampung, Indonesia.
Kesmas.
2019;
14(2):
76-81
DOI: 10.21109/kesmas.v14i2.2574
Available at:
https://scholarhub.ui.ac.id/kesmas/vol14/iss2/5
Included in
Biostatistics Commons, Environmental Public Health Commons, Epidemiology Commons, Health Policy Commons, Health Services Research Commons, Nutrition Commons, Occupational Health and Industrial Hygiene Commons, Public Health Education and Promotion Commons, Women's Health Commons