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Enferm Clin. 2020;30(S6):110---113
www.elsevier.es/enfermeriaclinica
An application of the Unied Theory of Acceptance
and Use of Technology (UTAUT) model
for understanding patient perceptions
on using hospital mobile application
Badra Al Aufaa,∗, Intan Syafra Renindraa, Julianti Siannita Putria,
Mochamad Iqbal Nurmansyahb
a Hospital Administration Department, Vocational Education Program, Universitas Indonesia, Indonesia
b Faculty of Health Science, Universitas Islam Negeri Syarif Hidayatullah Jakarta, Indonesia
Received
8 November 2019; accepted 2 June 2020
KEYWORDS Abstract
Hospital; Objective: This study to identify the determinants of patients’ intention to use mobile hospital
Mobile application; applications by applying the Unied Theory of Acceptance and Use of Technology (UTAUT)
Use of technology model.
Method: This cross-sectional study was conducted in two hospitals in Bekasi, Indonesia. A total
of 148 respondents took part in this study. The questionnaire has been developed based on the
UTAUT model.
Results: Several measured variables were associated with the hospital mobile app intention
use, including satised in using the app (OR: 2.21), perceived benet that the use of the app
can save time (OR: 2.62), easiness of the use of the app (OR: 4.07), easiness in learning the app
(OR: 2.95), perceived benet that the use of the app can speed up the administration process
(OR: 3.05) and the fast speed of the application (OR: 2.62).
Conclusion: The study implies that hospital managers should pay attention so that they enable
patients to use it properly.
˜
© 2020 Elsevier Espana, S.L.U. All rights reserved.
Peer-review under responsibility of the scientic committee of the 4th International Conference Hospital Administration (ICHA4). Full-text
and the content of it is under responsibility of authors of the article.
∗ Corresponding author.
E-mail address: badra@vokasi.ui.ac.id (B. Al Aufa).
https://doi.org/10.1016/j.enfcli.2020.06.025
˜
1130-8621/© 2020 Elsevier Espana, S.L.U. All rights reserved.
An application of the UTAUT model for understanding patient perceptions 111
Introduction Table 1 Demographic characteristics.
The fast development of information technology affects Characteristics N %
several industries, including a hospital. Its development Age
has a potency to improve the quality of healthcare.1 One <=25 25 16.9
study showed that health information technology improves 26---45 105 70.9
2
healthcare communications, efciency, and patient safety. =>46 18 12.2
The use of hospital mobile application has some benets Sex
in health care consultancy and accelerate the process of Female 116 78.4
appointment and registration.3
Male
Globally, in 2018, about 50% of mobile phone users have 32 21.6
at least one mobile health app on their mobile phones.4 Employment status
The software could be used to help the patient in reg- Housewife 50 33.8
istration and look for information regarding the doctor’s Private employee 37 25.0
schedule, nearest hospital, and service available in the hos- Self-employed 30 20.3
pital. Evidence has conrmed that patient experience can Government employee 8 5.4
be improved by mobile health apps through which reminders Army/Police 5 3.4
5
and diagnostic information are delivered to patients. In Others 18 12.2
Indonesia, several hospitals have used health technology,
particularly for online registration. One study in Surabaya
showed that more than 3000 patients in one month who analysis has been performed to determine a relationship
used mobile hospital application in one hospital.6 Although between independent and dependent variables.
the application has been widely used in Indonesia, the eval-
uation study of its use is still understudied. Therefore, Results
this study aimed to identify the determinants of patients’
intention to use mobile hospital application by applying the Based on the results of the study (Table 1), the majority of
Theory
Unied of Acceptance and Use of Technology (UTAUT) respondents aged 26---45 years with a percentage of 70.9%
model. Unied Theory of Acceptance and Use of Technology (n = 105). Based on the sex of the respondents, the major-
(UTAUT) is an integrative concept that has been used widely ity of respondents were women with a percentage of 78.4%
7
to measure IT adoption. (n = 116). The majority of respondents’ jobs were house-
wives with a percentage of 33.8% (n = 50).
The results from Table 2 indicates the patients who have
Method high intent to use the app, compared to those who have low
intended, more agreed that the use of the app can save time
This cross-sectional study performed in two private hospi- in the registration process (OR, 2.618; 95% CI, 1.310---5.233).
tals in Bekasi, Indonesia. The data were collected using The patients who satised in using the app 2.2 times to be
a self-administered questionnaire between April and May more likely to have high intention in using the app (OR,
2019. The population of the study is all outpatients who 2.209; 95% CI, 1.114---4.380). Patients who agree that the
used the mobile application. The sample was calculated app is easy to use and learn were 4.01 and 2.95 times more
by using the Slovin formula, and the result of the calcu- likely to have high intended to use the app. The patients
lation was 148 patients. The selection of the sample of who agree that the app can speed up the registration pro-
the respondents was using consecutive sampling method. cess were 3.04 times (AOR, 3.048; 95% CI, 1.510---6.152) to
The questionnaire has been developed based on UTAUT have high intended to use the app. Furthermore, no signif-
model.7 UTAUT model formulated four core determinants of icant differences were found between patients who intend
intention to use mobile application including performance and who do not intend to use the app concerning their social
expectation, effort expectation, social inuence, and facil- inuences.
itating conditions.8
Performance Expectancy is the level of individual con- Discussion
dence that the use of the existing system can help them
to get a benet that can help facilitate their work. Effort This study showed that more than half of the respondents
Expectancy is dened as the easiness level in using the have high intention in using the hospital mobile appli-
system.9 Social inuence is dened as the degree to which cation for hospital registration. Patients who perceived
an individual perceives that others believe he or she should that the use of the application can speed up the hos-
use the new system. Facilitating Conditions are the level of pital registration process were more likely to have high
individual condence in the infrastructure and supporting intention in using hospital mobile application. The results
facilities owned by a company or organization available to have been conrmed by other studies that revealed perfor-
support the use of the existing system. The questionnaire mance expectancy was a signicant factor in affecting the
comprised three parts: (1) Demographic characteristics, (2) patients’ intention and use of the mobile application in the
Behavior use toward the application (behavioral intention), hospital.10
(3) Perceptions toward the application (effort expectancy, This study also stated that the application that eases in
social inuence, and facilitating conditions). A bivariate using and learning the application became signicant factors
112 B. Al Aufa et al.
Table 2 Factor determines behavior intention in using mobile app.
Variables Low intend to use High intend to use OR (95% CI) p-value
n = 53 (%) n = 95 (%)
Performance expectancy
The app is helpful
Not helpful 24 (40.7) 35 (59.3) 1.419 (0.717---2.808) 0.406
Helpful 29 (32.6) 60 (67.4)
Satised in using the app
Not satisfy 31 (45.6) 37 (54.4) 2.209 (1.114---4.380) 0.034
Satisfy 22 (27.5) 58 (72.5)
The use of the app can save time
Not agree 29 (49.2) 30 (50.8) 2.618 (1.310---5.233) 0.010
Agree 24 (27.0) 65 (73.0)
Effort expectancy
Ease of operation
Not agree 42 (47.7) 46 (52.3) 4.067 (1.871---8.839) 0.000
Agree 11 (18.3) 49 (81.7)
Ease of learning
Not agree 41 (44.6) 51 (55.4) 2.948 (1.380---6.298) 0.008
Agree 12 (21.4) 44 (78.6)
The app speeds up the process
Not agree 35 (48.6) 37 (51.4) 3.048 (1.510---6.152) 0.003
Agree 18 (23.7) 58 (76.3)
Social inuence
Others used the app
No 42 (35.9) 75 (64.1) 1.018 (0.445---2.328) 1.000
Yes 11 (35.5) 20 (64.5)
Recommended by others
No 38 (37.6) 63 (62.4) 1.287 (0.618---2.680) 0.624
Yes 15 (31.9) 32 (68.1)
Facilitating condition
The app has an attractive display
Not agree 37 (36.3) 65 (63.7) 1.067 (0.515---2.212) 1.000
Agree 16 (34.8) 30 (65.2)
The
app is fast operated
Not agree 43 (42.4) 59 (57.8) 2.624 (1.175---5.859) 0.027
Agree 10 (21.7) 36 (78.3)
The app is easy operated
Not agree 41 (39.8) 62 (60.2) 1.819 (0.842---3.926) 0.178
Agree 12 (26.7) 33 (73.3)
that affect the intention of using the application. Another was only focused on one company of the private hospital
study revealed that that compatibility, perceived useful- in Indonesia.
ness, and perceived ease of use signicantly affected the
behavioral intention to use the mobile obesity-management Conclusion
app.11 Moreover, easiness is the key factor inuencing the
12 Hospital managers need to pay more attention to the
continuance intention of mobile application use. Another hospital mobile-application since the majority of patients
research showed that perceived ease of use of the soft- currently have an intention to use the application in the
ware application inuencing behavioral intention to use admission process during their hospital visit. The mobile
the software application.13 Another study revealed that
perceived ease of use positively correlated with mHealth application should be designed to be easier to be used and
14 has benecial for assisting patients in the hospital admission
service adoption. process.
This study did not explore individual characteristics that
may inuence the intention of the use of the mobile app. Conict of interest
This study should not be generalized to the entirety of the
hospital mobile application in Indonesia as this research The authors declare no conict of interest.
An application of the UTAUT model for understanding patient perceptions 113
References 8. Fuad A, Hsu CY. UTAUT for HSS: Initial framework to study
health IT adoption in the developing countries. F1000Research.
1. Wickramasinghe N, Goldberg S. How M = Ec2 in healthcare. Int 2018;23, http://dx.doi.org/10.12688/f esearch.13798.11000.
J Mob Commun. 2004;2:140---56, http://dx.doi.org/10.1109/ 9. Venkatesh V. Determinants of perceived ease of use: inte-
ITCC.2004.1286641. grating control, intrinsic motivation, and emotion into the
2. Prince SB, Herrin DM. The role of information technol- technology acceptance model. Inf Syst Res. 2000;11:342---65,
ogy in healthcare communications, efciency, and patient http://dx.doi.org/10.1287/isre.11.4.342. 21187.
safety: Aplication and results. J Nurs Adm. 2007;37:184---7, 10. Zhang Y, Liu C, Luo S, Xie Y, Liu F, Li X, et al. Factors inuencing
http://dx.doi.org/10.1097/01.NNA. 0000266841.46684.50. patients’ intentions to use diabetes management apps based
3. López MM, López MM, de la Torre Díez I, Jimeno JCP, López- on an extended unied theory of acceptance and use of tech-
Coronado M. mHealth App for iOS to help in diagnostic decision nology model: web-based survey. J Med Internet Res. 2019;21,
in ophthalmology to primary care physicians. J Med Syst. http://dx.doi.org/10.2196/31502.
2017;41, http://dx.doi.org/10.1007/s10916-017-0731-6. 11. Jeon E, Park HA. Factors affecting acceptance of smartphone
4. Fox S, Duggan M. Half of smartphone owners use their devices to application for management of obesity. Healthc Inform Res.
get health information and one-fth of smartphone owners have 2015;21:74---82, http://dx.doi.org/10.4258/hir. 21.2.742015.
12. Kang S. Factors inuencing intention of mobile application
health apps. Washington (DC): Pew Research Center’s Internet use. Int J Mob Commun. 2014;12:360---79, http://dx.doi.org/
& American Life Project; 2012. 10.1504/IJMC.2014.530636.
5. Center for Technology Innovation at Brookings. mHealth in China 13. Lee S-J, Choi MJ, Rho MJ, Kim D-J, Choi IY. Factors affecting user
and the United States: how mobile technology is transforming acceptance in overuse of smartphones in mobile health services:
healthcare; 2014. p. 1---36. an empirical study testing a modied integrated model in South
6. Sa’idah N. Analisis Penggunaan Sistem Pendaftaran Online Korea. Front Psychiatry. 2018;9, http://dx.doi.org/10.3389/
(E-Health) berdasarkan Unied Theory of Acceptance and fpsyt.2018.80065.
Use of Technology (UTAUT). J Adm Kesehat Indones. 2017;5: 14. Deng Z, Hong Z, Ren C, Zhang W, Xiang F. What predicts patients’
72---81. adoption intention toward mhealth services in China: empir-
7. Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of ical study. JMIR mHealth uHealth. 2018;6, http://dx.doi.org/
information technology: toward a unied view. MIS Q Manag Inf 10.2196/mhealth. 9316.
Syst. 2003;27:425---78.
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