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BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2020

Open Access 01-12-2020 | Research article

Implementation of a national electronic health information system in Gabon: a survey of healthcare providers’ perceptions

Authors: Cheick Oumar Bagayoko, Jack Tchuente, Diakaridia Traoré, Gaetan Moukoumbi Lipenguet, Raymond Ondzigue Mbenga, Aimé Patrice Koumamba, Myriam Corille Ondjani, Olive Lea Ndjeli, Marie-Pierre Gagnon

Published in: BMC Medical Informatics and Decision Making | Issue 1/2020

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Abstract

Background

The Health Information System (HIS) is a set of computerized tools for the collection, storage, management, and transmission of health data. The role of such tools in supporting the modernization of health systems, improving access to quality healthcare, and reducing costs in developing countries is unquestionable, but their implementation faces several challenges. In Gabon, a unique national electronic HIS has been launched. It will connect healthcare institutions and providers at all levels in the whole country.

Objective

This study aims to explore and identify the factors influencing healthcare providers’ perceptions of the national electronic HIS in Gabon.

Methods

A 44-item questionnaire based on the Information System Success Model (ISSM) was administered between February and April 2018 among 2600 healthcare providers across the country. The questions assessed the different aspects of the HIS that could influence its perceived impact on a 5-level Likert scale (from fully agree to totally disagree). The reliability and construct validity of the questionnaire were checked using Cronbach alpha and congeneric reliability coefficients. A logistic regression was used to identify the factors influencing healthcare providers’ perceptions of the system.

Results

A total of 2327 questionnaires were completed (i.e. 89.5% response rate). The logistic regression identified five elements that significantly influenced perceived system impact: System Quality (Odds Ratio–OR = 1.70), Information Quality (OR = 1.69), Actual Use (OR = 1.41), Support Quality (OR = 1.37), and Useful Functions (OR = 1.14). The model explained 30% of the variance in providers’ perception that the national HIS leads to positive impacts.

Discussion

The results show that healthcare providers’ perceptions regarding the positive impact of the national HIS in Gabon are influenced by their previous use of an HIS, the scope of their usage, and the quality of the system, information, and support provided to users. These results could inform the development of strategies to ensure adequate change of management and user experience for the implementation of the national HIS in Gabon, and eventually in other low resource environments.
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Literature
1.
Haux R. Health information systems – past, present, future. Int J Med Inform. 2006;75(3):268–81.PubMedCrossRef
2.
3.
Birkhead GS, Klompas M, Shah NR. Uses of electronic health Records for Public Health Surveillance to advance public health. Annu Rev Public Health. 2015;36(1):345–59.PubMedCrossRef
4.
Shehu I, Shamsudeen AS, Amaal KN. Acceptance of electronic health record for improving quality of health service delivery: case study of Aminu Kano teaching hospital, Nigeria. KIU J Human. 2018;2(2 B):195–210.
5.
6.
Hoque MR, Bao Y, Sorwar G. Investigating factors influencing the adoption of e-health in developing countries: a patient's perspective. Inform Health Soc Care. 2017;42(1):1–17.PubMedCrossRef
7.
Anwar F, Shamim A. Barriers in adoption of health information Technology in Developing Societies. Int J Adv Comput Sci Appl. 2011;2(8):40–5.
8.
Mukred A, Singh D, Safie N. Investigating the impact of information culture on the adoption of information system in public health sector of developing countries. Int J Bus Inf Syst. 2017;24(3):261.
9.
Hossain A, Quaresma R, Rahman H. Investigating factors influencing the physicians’ adoption of electronic health record (EHR) in healthcare system of Bangladesh: an empirical study. Int J Inf Manag. 2019;44:76–87.CrossRef
10.
Lorenzi N, Riley RT, Dewan NA. Barriers and resistance to informatics in behavioral health. Stud Health Technol Inform. 2001;2:1301–4.
11.
Lorenzi NM, Riley RT, Blyth AJC, Southon G, Dixon BJ. Antecedents of the people and organizational aspects of medical informatics: review of the literature. J Am Med Inform Assoc. 1997;4(2):79–93.PubMedPubMedCentralCrossRef
12.
Liang L, Wiens MO, Lubega P, Spillman I, Mugisha S. A locally developed electronic health platform in Uganda: development and implementation of Stre@ mline. JMIR Form Res. 2018;2(2):e20.PubMedPubMedCentralCrossRef
13.
Narattharaksa K, Speece M, Newton C, Bulyalert D. Key success factors behind electronic medical record adoption in Thailand. J Health Organ Manag. 2016;30(6):985–1008.PubMedCrossRef
14.
Heeks R. Health information systems: failure, success and improvisation. Int J Med Inform. 2006;75(2):125–37 1386-5056.PubMedCrossRef
15.
Venkatesh V, Sykes TA, Zhang X. ‘Just What the Doctor Ordered’: A Revised UTAUT for EMR System Adoption and Use by Doctors. In: 2011 44th Hawaii International Conference on System Sciences; 2011. p. 1–10.
16.
Lee YK, Kenneth A, Larsen KRT. The technology acceptance model: past, present, and future. Commun Assoc Inf Syst. 2003;12(1):752–80.
17.
Davis F, Bagozzi R, Warshaw PR. User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Manag Sci. 1989;35(8):982–1003.CrossRef
18.
Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: toward a unified view. MIS Q. 2003;27(3):425–78.CrossRef
19.
Bawack RE, Kala Kamdjoug JR. Adequacy of UTAUT in clinician adoption of health information systems in developing countries: the case of Cameroon. Int J Med Inform. 2018;109:15–22.PubMedCrossRef
20.
Alsharo M, Alnsour Y, Alabdallah M. How habit affects continuous use: evidence from Jordan’s national health information system. Inform Health Soc Care. 2018;45(3):1–14.
21.
Delone W, McLean E. The DeLone and McLean model of information systems success: a ten-year update. J Manag Inf Syst. 2003;19(4):9–30.CrossRef
22.
Ayebazibwe I, Kimaro HC, Kaasbøll JJ. System use and user satisfaction in the adoption of electronic medical records systems: a case of DHIS2 tracker implementation in Tanzania. Int Conf Soc Implications Comput Dev Ctries. 2019;551:63–75.
23.
Tilahun B, Fritz F. Modeling antecedents of electronic medical record system implementation success in low-resource setting hospitals. BMC Med Inform Decis Mak. 2015;15:61.PubMedPubMedCentralCrossRef
24.
Tubaishat A. Evaluation of electronic health record implementation in hospitals. Comput Inform Nurs. 2017;35(7):364–72.PubMedCrossRef
25.
26.
Monem H, Afrasiabi M, Rezvan P, AbediDehkordi S. The impact of user quality and information quality on the IS success in healthcare context. J Basic Appl Sci Res. 2013;3(10):40–51.
27.
Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate data analysis: Pearson education limited; 2013.
28.
Hoque R, Sorwar G. Understanding factors influencing the adoption of mHealth by the elderly: an extension of the UTAUT model. Int J Med Inform. 2017;101:75–84.PubMedCrossRef
29.
Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model Multidiscip J. 1999;6(1):1–55.CrossRef
30.
Abdelhamid M. Greater patient health information control to improve the sustainability of health information exchanges. J Biomed Inform. 2018;83:150–8.PubMedCrossRef
31.
Cilliers L, Viljoen KL, Chinyamurindi WT. A study on students’ acceptance of mobile phone use to seek health information in South Africa. Health Inf Manag. 2018;47(2):59–69.PubMed
32.
Studenmund AH. Using econometrics: a practical guide, 6th ed., international ed edn. Harlow: Pearson Education Limited; 2013.
33.
McLean ER, DeLone WH. Information systems success measurement. Foundations Trends® Inf Syst. 2016;2(1):1–116.CrossRef
34.
Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. N Engl J Med. 2010;363(6):501–4.PubMedCrossRef
35.
Petter S, DeLone W, McLean E. Measuring information systems success: models, dimensions, measures, and interrelationships. Eur J Inf Syst. 2008;17(3):236–63.CrossRef
36.
Alwan K, Awoke T, Tilahun B. Knowledge and utilization of computers among health professionals in a developing country: a cross-sectional study. JMIR Human Factors. 2015;2(1):e4.PubMedPubMedCentralCrossRef
37.
Miranda FJ, Gadelha NS. Hospital Information System Satisfaction in Brazil: Background and Moderating Effects, vol. 2; 2014.
38.
Merritt K, Smith D, Renzo JCD. An investigation of self-reported computer literacy: is it reliable. Issues Inf Syst. 2005;6(1):289–95.
39.
Odekunle FF, Odekunle RO, Shankar S. Why sub-Saharan Africa lags in electronic health record adoption and possible strategies to increase its adoption in this region. Int J Health Sci. 2017;11(4):59.
40.
Petter S, DeLone W, McLean ER. Information systems success: the quest for the independent variables. J Manag Inf Syst. 2013;29(4):7–62.CrossRef
Metadata
Title
Implementation of a national electronic health information system in Gabon: a survey of healthcare providers’ perceptions
Authors
Cheick Oumar Bagayoko
Jack Tchuente
Diakaridia Traoré
Gaetan Moukoumbi Lipenguet
Raymond Ondzigue Mbenga
Aimé Patrice Koumamba
Myriam Corille Ondjani
Olive Lea Ndjeli
Marie-Pierre Gagnon
Publication date
01-12-2020
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2020
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-020-01213-y

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