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In the second stage of the Electronic Health Record Sharing System (eHRSS) development, a mobile app (eHealth app) was launched to further enhance collaborative care among the public sector, the private sector, the community, and the caregivers.
This study aims to investigate the factors associated with the downloading and utilization of the app, as well as the awareness, perception, and future improvement of the app.
We collected 2110 surveys; respondents were stratified into 3 groups according to their status of enrollment in the eHRSS. The primary outcome measure was the downloading and acceptance of the eHealth app. We collected the data on social economics factors, variables of the Technology Acceptance Model and Theory of Planned Behavior. Any factors identified as significant in the univariate analysis (
The respondents had an overall high satisfaction rate and a positive attitude toward continuing to adopt and recommend the app. However, the satisfaction rate among respondents who have downloaded but not adopted the app was relatively lower, and few of them perceived that the downloading and acceptance processes are difficult. A high proportion of current users expressed a positive attitude about continuing to adopt and recommend the app to friends, colleagues, and family members. The behavioral intention strongly predicted the acceptance of the eHealth app (β=.89;
Despite the high satisfaction rate among the respondents, privacy concerns and perceived difficulties in adopting the app were the major challenges of promoting eHealth. Further promotion could be made through doctors and publicity. For future improvement, comprehensive health records and tailored health information should be included.
In Hong Kong, a substantial proportion of hospital services is provided by the public sector (90% of all in-patient bed-days) and up to 70% of the outpatient services are offered by the private sector [
In stage 2 development, a mobile app, an “eHealth app,” was launched in January 2021 [
Across the world, similar mobile health apps were developed for people to upload and view health records, manage personal health care activities, share clinical information with doctors, and improve public health. Apps such as “Capzule PHR,” “Health and Family,” and “Health Notes” allow patients to view and get access to their medical information and record their data at any time and any place through the internet or by offline access [
To further promote quality and efficiency, as well as to recommend the future development of the mobile (eHealth) app, perceptions and views from users are required to inform a more system-friendly design. The objectives of this project are to evaluate the factors associated with the downloading and utilization of the eHealth app; to examine the awareness, use, and acceptability of the mobile eHealth app; to explore whether eHealth app use may be associated with the joining of the eHRSS; the reasons for nonuse among those who joined the eHRSS; the extent to which the app improves user experience and influences health service utilization; and to recommend a potential room for improvement of the eHealth apps.
A self-administered questionnaire was adopted in this study. Prospective study participants were based on a list of patients provided by the HA. A simple random sampling methodology was mainly used. Over 5.5 million existing eHRSS users were included in the population, and computer-generated numbers were listed correspondingly for participant recruitment. An invitational SMS was first sent by the HA to existing eHRSS users. This served to alert the participants that they would receive a subsequent survey invitation by Chinese University of Hong Kong via SMS [
Survey items focused on the awareness, use, and acceptability of the eHealth app; the association between the use of the eHealth app and the joining of the eHRSS; the reasons why some users did not use the eHealth app after joining the eHRSS; the extent to which the eHealth app improved user experience, modified health service access, and health management; and recommendations for possible improvement of the eHealth app. The surveys were designed by an academic physician with relevant experience in projects related to the eHRSS, and extensive expertise in both clinical and public health research studies. The questionnaire draft was face-validated by a panel of epidemiologists, biostatisticians, and professionals in the field of health care policy, public health, and primary care. It was subsequently pilot tested for feasibility and item comprehensiveness among 20 people. The completion rate was 65% (13/20), and the average response time was 7 minutes and 40 seconds (
The surveys were available in both Chinese and English versions. All surveys were anonymous, and written consent was provided by the participants at the start of the questionnaire. The study participants were informed that all information presented would be in the form of aggregated data that could not identify any individuals.
This study was approved by the Survey and Behavioral Research Ethics Committee of the Chinese University of Hong Kong (approval number SBRE-21-0184).
All surveys were checked for their completeness and the presence of participant consent. All data entry and analysis were conducted using SPSS version 26.0 (IBM, Inc.). As part of quality control, at least 20% (422/2110) of all surveys were randomly checked for the validity, quality, and accuracy. All items in the survey were analyzed as stratified according to the status of enrollment. The primary outcome measure was the downloading and acceptance of the eHealth app. We tested for the presence of statistical association by identifying potential associated factors using univariate and multivariate regression analyses. We included age, gender, educational level, job status, monthly household income, the types of mobile phone operating systems currently in use, the eHRSS enrollment status, perceived enablers of acceptance, and perceived barriers of the eHealth app use. Any factors identified as significant in univariate analysis (
To investigate the factors that could predict downloading and acceptance of the eHealth app, we used 2 internationally recognized models that have been widely adopted to examine the use of new technologies. These were the Technology Acceptance Model (TAM), which was first developed by Fred D Davis, Richard P Bagozzi, and Paul R Warshaw [
Furthermore, we employed the Theory of Planned Behavior (TPB), a commonly used psychological theory that links people’s beliefs and behaviors [
A total of 2110 completed surveys were collected (
Participant characteristics (N=2110).
Characteristics | Values, n (%) | |
|
|
|
|
16-30 | 136 (6.45) |
|
31-40 | 162 (7.68) |
|
41-50 | 343 (16.26) |
|
51-60 | 631 (29.91) |
|
61-70 | 636 (30.14) |
|
>70 | 202 (9.57) |
|
|
|
|
Male | 1184 (56.11) |
|
Female | 926 (43.89) |
|
|
|
|
Primary or below | 150 (7.12) |
|
Secondary | 1118 (53.06) |
|
Tertiary or above | 839 (39.82) |
|
Other | 3 (not counted)a |
|
|
|
|
Employed (Full-time/part-time) | 999 (49.36) |
|
Unemployed | 100 (4.94) |
|
Retired | 695 (34.34) |
|
Housewives | 138 (6.82) |
|
Students | 53 (2.62) |
|
Others | 39 (1.93) |
|
Refuse to answer | 86 (not counted)a |
|
|
|
|
<10,000 | 373 (21.54) |
|
10,000-19,999 | 458 (26.44) |
|
20,000-29,999 | 335 (19.34) |
|
30,000-39,999 | 154 (8.89) |
|
40,000-59,999 | 180 (10.39) |
|
≥60,000 | 232 (13.39) |
|
Refuse to answer | 378 (not counted)a |
|
|
|
|
Apple iOS | 700 (33.18) |
|
Android | 1110 (52.61) |
|
Huawei | 174 (8.25) |
|
Others | 126 (5.97) |
aAs these options are out of the original categories, the answers were “not counted” and thus not used in the analysis.
b1HK $=US $0.12.
Participants were classified into several groups according to downloading and acceptance of the eHealth app (
The COVID-19 vaccination program (649/2110, 30.76%), medical doctors (647/2110, 30.66%), publicity (posters, pamphlets, television, outdoor advertisements; 533/2110, 25.26%), and friends or family members (388/2110, 18.39%) were the 4 major sources of information about the eHealth app among respondents (
In group 1, the majority of participants agreed that the app can show their accurate vaccination records (1118/1242, 90.02%) and other health records (1081/1242, 87.04%). They also expressed that the app provides useful administrative functions, including giving consent to health care providers for sharing their data (1044/1242, 84.06%), easier management of eHealth accounts (1005/1242, 80.92%), and empowerment of their family members and own health (940/1242, 75.68%). A similar result was also noted in the other 2 groups (
Among the study participants in group 1 (
Perceived enablers of downloading the eHealth app.
Enablers of downloading | Downloaded and used eHealth app (n=1242) | Downloaded but not used eHealth app (n=399) | Not having downloaded and used eHealth app (n=469) |
|
Strongly agree or agree, n (%) | Strongly agree or agree, n (%) | Strongly agree or agree, n (%) |
It is convenient to get information about different government-subsidized medical programs | 920 (74.07) | 293 (73.43) | 332 (70.79) |
I can view my accurate health records | 1081 (87.04) | 309 (77.44) | 380 (81.02) |
I can manage my eHealth account easily (eg, update the communication means) | 1005 (80.92) | 281 (70.43) | 359 (76.55) |
I can give sharing consents to health care providers easily so that they can view my health records | 1044 (84.06) | 307 (76.94) | 378 (80.60) |
I can find the health care providers and doctors that are participating in different health programs with ease | 899 (72.38) | 269 (67.42) | 368 (78.46) |
I can check the remaining balance and record of the Elderly Health Care Voucher Scheme | 904 (72.79) | 270 (67.67) | 371 (79.10) |
I can show the vaccination record/QR code | 1118 (90.02) | 321 (80.45) | 383 (81.66) |
It helps to manage my health and my families’ health | 940 (75.68) | 274 (68.67) | 367 (78.25) |
My friend recommended me to use the “eHealth” app | 691 (55.64) | 202 (50.63) | 244 (52.03) |
My family recommended me to use the “eHealth” app | 777 (62.56) | 225 (56.39) | 282 (60.13) |
My doctor recommended me to use the “eHealth” app | 797 (64.17) | 240 (60.15) | 312 (66.52) |
Government’s advertisement of the “eHealth” app | 730 (58.78) | 216 (54.14) | 271 (57.78) |
I can get souvenirs | 466 (37.52) | 148 (37.09) | 201 (42.86) |
Perceived enablers of acceptance of the eHealth app.
Enablers of acceptance | Downloaded and used eHealth app (n=1242) | Downloaded but not used eHealth app (n=399) | Not having downloaded and used eHealth app (n=469) | |||||||||
|
n | Mean (SD) | 95% CI | n | Mean (SD) | 95% CI | n | Mean (SD) | 95% CI |
|
||
It is convenient to get information about different government-subsidized medical programs | 920 | 3.84 (0.78) | 3.80-3.89 | 293 | 3.75 (0.85) | 3.66-3.83 | 332 | 3.76 (0.75) | 3.69-3.82 |
|
||
I can view my accurate health records | 1081 | 4.15 (0.79) | 4.11-4.20 | 309 | 3.87 (0.87) | 3.78-3.96 | 380 | 3.96 (0.71) | 3.89-4.02 |
|
||
I can manage my eHealth account easily (eg, update the communication means) | 1005 | 3.99 (0.73) | 3.95-4.03 | 281 | 3.70 (0.86) | 3.62-3.79 | 359 | 3.86 (0.71) | 3.79-3.92 |
|
||
I can give sharing consents to health care providers easily so that they can view my health records | 1044 | 4.07 (0.73) | 4.03-4.11 | 307 | 3.84 (0.85) | 3.75-3.92 | 378 | 3.92 (0.71) | 3.86-3.99 |
|
||
I can find the health care providers and doctors that are participating different health programs with ease | 899 | 3.86 (0.75) | 3.82-3.90 | 269 | 3.68 (0.80) | 3.61-3.76 | 368 | 3.89 (0.69) | 3.82-3.95 |
|
||
I can check the remaining balance and record of the Elderly Health Care Voucher Scheme | 904 | 3.90 (0.81) | 3.86-3.95 | 270 | 3.71 (0.86) | 3.63-3.80 | 371 | 3.88 (0.72) | 3.82-3.95 |
|
||
I can show the vaccination record/QR code | 1118 | 4.22 (0.72) | 4.18-4.26 | 321 | 3.95 (0.86) | 3.86-4.03 | 383 | 4.00 (0.73) | 3.93-4.06 |
|
||
It helps to manage my health and my families’ health | 940 | 3.93 (0.79) | 3.89-3.98 | 274 | 3.73 (0.89) | 3.64-3.82 | 367 | 3.89 (0.72) | 3.83-3.96 |
|
||
My friend recommended me to use the “eHealth” app | 691 | 3.55 (0.91) | 3.50-3.60 | 202 | 3.41 (0.94) | 3.32-3.50 | 244 | 3.44 (0.86) | 3.37-3.52 |
|
||
My family recommended me to use the “eHealth” app | 777 | 3.68 (0.89) | 3.63-3.73 | 225 | 3.5 (0.95) | 3.40-3.59 | 282 | 3.56 (0.87) | 3.48-3.64 |
|
||
My doctor recommended me to use the “eHealth” app | 797 | 3.7 (0.88) | 3.65-3.75 | 240 | 3.58 (0.88) | 3.49-3.67 | 312 | 3.71 (0.77) | 3.64-3.78 |
|
||
Government’s advertisement of the “eHealth” app | 730 | 3.61 (0.88) | 3.56-3.66 | 216 | 3.49 (0.92) | 3.40-3.58 | 271 | 3.52 (0.86) | 3.44-3.59 |
|
||
m. I can get souvenirs | 466 | 3.21 (1.08) | 3.15-3.27 | 148 | 3.15 (1.05) | 3.05-3.25 | 201 | 3.24 (0.99) | 3.15-3.33 |
|
Perceived barriers to downloading of the eHealth app.
Barrier | Downloaded and used the eHealth app (n=1028-1222) | Downloaded but not used the eHealth app (n=301-391) | Not having downloaded and used the eHealth app (n=365-461) |
|
Strongly agree or agree, n (%) | Strongly agree or agree, n (%) | Strongly agree or agree, n (%) |
One’s physician has not joined | 505/1028 (49.12) | 133/310 (42.90) | 151/365 (41.37) |
Only see 1 doctor who is familiar with my health records | 392/1092 (35.90) | 144/347 (41.50) | 181/425 (42.59) |
No sickness | 295/1157 (25.50) | 97/358 (27.09) | 156/441 (35.37) |
Concerned about personal information and privacy | 408/1222 (33.39) | 168/388 (43.30) | 243/461 (52.71) |
My doctor did not mention about/recommend/think it is necessary to use the “eHealth” app | 417/1078 (38.68) | 136/333 (40.84) | 183/403 (45.41) |
I do not know how to use a smartphone/mobile app | 203/1167 (17.40) | 94/372 (25.27) | 119/441 (26.98) |
Not willing for others to read one’s own health records | 372/1216 (30.59) | 161/391 (41.18) | 209/455 (45.93) |
Uncertain about the benefits of the eHealth app | 266/1198 (22.20) | 134/374 (35.83) | 172/437 (39.36) |
Complicated downloading procedures | 321/1216 (26.40) | 172/382 (45.03) | 173/423 (40.90) |
Perceived barriers to acceptance of the eHealth app.
Barrier | Downloaded and used the eHealth app (n=1242) | Downloaded but not used the eHealth app (n=399) | Not having downloaded and used the eHealth app (n=469) | |||||||
|
n | Mean (SD) | 95% CI | n | Mean (SD) | 95% CI | n | Mean (SD) | 95% CI | |
One’s physician has not joined | 505 | 3.30 (1.08) | 3.23-3.37 | 133 | 3.30 (0.92) | 3.18-3.41 | 151 | 3.16 (0.95) | 3.05-3.26 | |
Only see 1 doctor who is familiar with my health records | 392 | 3.03 (1.02) | 2.96-3.09 | 144 | 3.09 (0.93) | 2.97-3.2 | 181 | 3.12 (0.92) | 3.02-3.23 | |
No sickness | 295 | 2.73 (1.02) | 2.66-2.80 | 97 | 2.83 (0.95) | 2.71-2.95 | 156 | 2.97 (0.97) | 2.86-3.08 | |
Concerned about personal information and privacy | 408 | 2.94 (1.14) | 2.86-3.02 | 168 | 3.09 (1.05) | 2.96-3.22 | 243 | 3.46 (1.06) | 3.34-3.58 | |
My doctor did not mention about/recommend/think it is necessary to use the “eHealth” app | 417 | 3.11 (0.98) | 3.05-3.18 | 136 | 3.22 (0.84) | 3.12-3.33 | 183 | 3.23 (0.86) | 3.14-3.33 | |
I do not know how to use a smartphone/mobile app | 203 | 2.43 (1.11) | 2.36-2.51 | 94 | 2.70 (1.07) | 2.57-2.83 | 119 | 2.78 (1.00) | 2.67-2.89 | |
Not willing for others to read one’s own health records | 372 | 2.89 (1.09) | 2.82-2.96 | 161 | 3.08 (0.99) | 2.95-3.2 | 209 | 3.28 (1.00) | 3.17-3.39 | |
Uncertain about the benefits of the eHealth app | 266 | 2.70 (1.04) | 2.63-2.77 | 134 | 3.06 (0.95) | 2.95-3.18 | 172 | 3.15 (0.93) | 3.05-3.26 | |
Complicated downloading procedures | 321 | 2.79 (1.05) | 2.73-2.86 | 172 | 3.20 (1.01) | 3.07-3.32 | 173 | 3.23 (0.88) | 3.13-3.33 |
The proportion of participants in group 1 who were positive about the downloading and acceptance processes was in general higher than those in group 2. Most respondents in group 1 were satisfied with the downloading processes (908/1242, 73.11%;
In terms of applicability, vaccine records (1108/1242, 89.21%), appointment records (1055/1242, 84.94%), medication records (1015/1242, 81.72%), allergy records (924/1242, 74.40%), and health management (786/1242, 63.29%) were the top 5 useful functions among the users (
Turning to the perception of the app (
A high proportion of group 1 respondents, current users, expressed a positive attitude about continuing to adopt (1105/1242, 88.97%) and recommend the app to friends, colleagues, and family members (1024/1242, 82.45%;
Respondents were more likely to download the app when they had joined the eHRSS (adjusted odds ratio [aOR] 9.2, 95% CI 6.35-13.32;
The independent factors associated with the acceptance of the eHealth app were similar to those associated with downloading, except that male participants (aOR 1.85, 95% CI 1.36-2.52;
Factors associated with downloading and acceptance of the eHealth app.
Factor | Users, n (n=1159) | Downloading | Acceptance | |||||||
|
|
Values, n (%) | aORa (95% CI) | Values, n (%) | aOR (95% CI) |
|
||||
|
|
|
|
.63 |
|
|
.53 |
|
||
|
16-40 | 150 | 105 (70) | 1 (reference) |
|
82 (54.7) | 1 (reference) |
|
|
|
|
41-60 | 571 | 440 (77.1) | 1.22 (0.70-2.11) | .48 | 347 (60.8) | 1.31 (0.81-2.13) | .27 |
|
|
|
>60 | 438 | 361 (82.4) | 1.40 (0.71-2.78) | .33 | 280 (63.9) | 1.35 (0.75-2.43) | .32 |
|
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|
|
|
|
|
|
|
|
|||
|
Male | 680 | 553 (81.3) | 1.19 (0.83-1.73) | .35 | 458 (67.4) | 1.85 (1.36-2.52) | <.001 |
|
|
|
Female | 479 | 353 (73.7) | 1 (reference) |
|
251 (52.4) | 1 (reference) |
|
|
|
|
|
|
|
.03 |
|
.04 |
|
|||
|
Primary or below | 73 | 50 (68.5) | 0.91 (0.44-1.91) | .81 | 32 (43.8) | 0.49 (0.25-0.94) | .03 |
|
|
|
Secondary | 617 | 491 (79.6) | 1.63 (1.08-2.46) | .02 | 373 (60.5) | 1.05 (0.75-1.48) | .76 |
|
|
|
Tertiary or above | 469 | 365 (77.8) | 1 (reference) |
|
304 (64.8) | 1 (reference) |
|
|
|
|
|
|
|
.01 |
|
.48 |
|
|||
|
Full-time/part-time | 642 | 504 (78.5) | 1 (reference) |
|
404 (62.9) | 1 (reference) |
|
|
|
|
Unemployed | 49 | 36 (73.5) | 1.38 (0.59-3.21) | .46 | 26 (53.1) | 1.21 (0.57-2.56) | .62 |
|
|
|
Retired | 352 | 297 (84.4) | 1.12 (0.67-1.88) | .67 | 230 (65.3) | 0.89 (0.58-1.35) | .58 |
|
|
|
Housewives | 74 | 45 (60.8) | 0.44 (0.23-0.84) | .01 | 29 (39.2) | 0.63 (0.34-1.15) | .13 |
|
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|
Students | 22 | 13 (59.1) | 0.49 (0.15-1.57) | .23 | 11 (50) | 0.82 (0.27-2.52) | .73 |
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Others | 20 | 11 (55) | 0.27 (0.09-0.82) | .02 | 9 (45) | 0.47 (0.16-1.38) | .17 |
|
|
|
|
|
|
.27 |
|
|
.82 |
|
||
|
<10,000 | 228 | 170 (74.6) | 1 (reference) |
|
118 (51.8) | 1 (reference) |
|
|
|
|
10,000-19,999 | 300 | 227 (75.7) | 0.91 (0.55-1.51) | .72 | 177 (59) | 1.20 (0.78-1.85) | .41 |
|
|
|
20,000-29,999 | 225 | 174 (77.3) | 0.74 (0.43-1.29) | .29 | 141 (62.7) | 1.07 (0.67-1.70) | .79 |
|
|
|
≥30,000 | 406 | 335 (82.5) | 1.22 (0.71-2.08) | .47 | 273 (67.2) | 1.18 (0.75-1.86) | .46 |
|
|
|
|
|
|
.05 |
|
|
.19 |
|
||
|
Apple iOS | 392 | 295 (75.3) | 1 (reference) |
|
239 (61) | 1 (reference) |
|
|
|
|
Android | 615 | 501 (81.5) | 1.22 (0.82-1.82) | .34 | 391 (63.6) | 0.93 (0.67-1.31) | .69 |
|
|
|
Huawei | 93 | 73 (78.5) | 1.24 (0.63-2.46) | .53 | 54 (58.1) | 0.83 (0.47-1.46) | .51 |
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Others | 59 | 37 (62.7) | 0.46 (0.22-0.97) | .04 | 25 (42.4) | 0.47 (0.24-0.94) | .03 |
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Yes | 924 | 807 (87.3) | 9.20 (6.35-13.32) | <.001 | 665 (72) | 9.77 (6.64-14.38) | <.001 |
|
|
|
No | 235 | 99 (42.1) | 1 (reference) |
|
44 (18.7) | 1 (reference) |
|
|
aaOR: adjusted odds ratio.
b1HK $=US $0.12.
ceHRSS: electronic Health Record Sharing System.
Factors associated with perceived enablers and barriers of the eHealth app.
Factors | aORa (95% CI) | aORa (95% CI) | |||||||
|
|||||||||
|
It is convenient to get information about different government-subsidized medical programs | 0.94 (0.69-1.28) | .70 | 0.95 (0.74-1.23) | .71 | ||||
|
I can view my accurate health records | 1.41 (1.02-1.95) | .04 | 1.40 (1.08-1.81) | .01 | ||||
|
I can manage my eHealth account easily (eg, update the communication means) | 0.82 (0.55-1.22) | .32 | 1.26 (0.90-1.75) | .18 | ||||
|
I can give sharing consents to health care providers easily so that they can view my health records | 1.14 (0.80-1.63) | .47 | 1.12 (0.84-1.50) | .44 | ||||
|
I can find the health care providers and doctors who participated in different health programs with ease | 0.49 (0.33-0.73) | .001 | 0.62 (0.45-0.85) | .003 | ||||
|
I can check the remaining balance and record of the Elderly Health Care Voucher Scheme | 0.99 (0.70-1.40) | .95 | 1.03 (0.78-1.37) | .82 | ||||
|
I can show the vaccination record/QR code | 1.43 (1.03-1.98) | .03 | 1.33 (1.02-1.75) | .03 | ||||
|
It helps to manage my health and my families’ health | 0.73 (0.51-1.06) | .09 | 0.76 (0.56-1.01) | .06 | ||||
|
My friend recommended me to use the “eHealth” app | 1.28 (0.88-1.86) | .20 | 0.98 (0.72-1.35) | .92 | ||||
|
My family recommended me to use the “eHealth” app | 1.10 (0.75-1.62) | .63 | 1.14 (0.82-1.59) | .42 | ||||
|
My doctor recommended me to use the “eHealth” app | 0.83 (0.60-1.13) | .23 | 0.85 (0.65-1.11) | .23 | ||||
|
Government’s advertisement of the “eHealth” app | 1.00 (0.76-1.32) | .97 | 1.01 (0.80-1.27) | .96 | ||||
|
I can get souvenirs | 1.14 (0.93-1.39) | .22 | 1.13 (0.95-1.34) | .17 | ||||
|
|||||||||
|
One’s physician has not joined | 1.45 (1.18-1.77) | <.001 | 1.18 (1.01-1.39) | .04 | ||||
|
Only see 1 doctor who is familiar with my health records | 1.01 (0.82-1.26) | .90 | 1.08 (0.90-1.29) | .42 | ||||
|
No sickness | 0.94 (0.76-1.16) | .58 | 0.97 (0.81-1.16) | .75 | ||||
|
Concerned about personal information and privacy | 0.74 (0.60-0.90) | .003 | 0.89 (0.75-1.05) | .16 | ||||
|
My doctor did not mention about/recommend/think it is necessary to use the “eHealth” app | 1.20 (0.95-1.51) | .12 | 1.05 (0.87-1.27) | .58 | ||||
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I do not know how to use a smartphone/mobile app | 0.97 (0.81-1.17) | .77 | 1.04 (0.89-1.22) | .62 | ||||
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Not willing for others to read one’s own health records | 1.05 (0.84-1.31) | .66 | 1.04 (0.87-1.24) | .68 | ||||
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Uncertain about the benefits of the eHealth app | 0.81 (0.64-1.01) | .06 | 0.80 (0.66-0.96) | .02 | ||||
|
Complicated downloading procedures | 0.88 (0.71-1.08) | .23 | 0.81 (0.68-0.96) | .02 |
aaOR: adjusted odds ratio.
In the TAM, perceived usefulness (β=.52;
Turning to the TPB, attitude (β=.30;
Factors predictive of downloading and acceptance of the eHealth app by the Technology Acceptance Model. *
Factors predictive of downloading and acceptance of the eHealth app by the Theory of Planned Behavior. *
Overall, the satisfaction rate among the respondents was high. The satisfaction rate among group 2 respondents was relatively lower, and few of them perceived the downloading process as complicated. The willingness to continue to use and recommend the app was strong among all respondents. The 3 major enablers of adopting the app were the viewing of health records, especially the vaccination record; managing their eHealth accounts and sharing consent; and managing their family members’ and their own health. However, respondents of the 3 groups had different perceived barriers. These include one’s physician had not joined the eHRSS or had not recommended the eHealth app to them, a complicated downloading process, and privacy concerns. Most of the respondents expected to access more health records in the app, such as laboratory results and radiographic images, and have more personalized health information and health tips based on their age groups and health condition.
This study has a few limitations. First, the survey was cross sectional, and so only the correlation could be measured instead of the causal relationship with the possibility of reverse causality. To corroborate the enablers and barriers, prospective longitudinal studies are required. In addition, face validity rather than construct validity was applied in the design of the questionnaire. The consistency reliability of the survey measurements has not yet been evaluated. Besides, some variables that could affect the downloading and acceptance of eHealth app may not be discussed in this study. Hence, there was a possibility of residual confounding. Finally, the study focused on acceptance of the app and examined individual factors affecting its use, which was based on a more individual level by using the TAM and TPB models in study design and analysis. Referring to Shachak et al’s [
eHealth app provides accurate and quick retrieval of clinical details for the citizens, as well as a platform for citizens to record self-monitoring health data. Thus, the app also facilitated the work of health care professionals with the integration and sharing of health records [
Similar to our previous studies in 2020, many participants learned about the eHRSS from others, including medical doctors, posters, television, and outdoor advertisement [
The participation of doctors was decisive to encourage the citizens to download and use the eHealth app. Our previous study in 2020 found that the actual use of the eHRSS among patients was also significantly associated with the enrollment among physicians [
Privacy was an important perceived barrier to the acceptability of the eHealth app. The respondents in group 3 were worried about their personal information and privacy. As supported by international studies, privacy was a common concern raised by the public about eHealth technologies [
More assistance and support should be provided regarding the perceived difficulties in using mobile apps. To enhance the acceptance rate among people who have not adopted or downloaded the app, the utility and benefit of the app should be emphasized among the public. We suggest further promoting the app through doctors by sharing the benefits of health management in using the app with the citizens. For future development, more sharable scope of the health record, such as laboratory results and radiographic images, and customized health information, including age-specific health care recommendations and tailored health tips, should be included.
Regarding the perception of difficulties in using mobile apps, the user interface and user experience should be further enhanced. The acceptance of the eHealth app requires a certain level of technology literacy and a fair understanding of digital technology [
Regarding the privacy issue, the security and privacy measures applied to the eHealth app should be reinforced. Further, it is an effective way to ensure widespread participation in the eHealth app by emphasizing the utility and benefits of the app [
In our findings, doctors had an important role in determining people’s acceptance of the app. Doctors could recommend citizens managing the eHealth account and sharing function, which were the top-rated perceived enablers. The app could also improve the workflow of the doctors by allowing them to access patients’ health records that have been shared in the eHRSS. Doctor was an important source for citizens to acknowledge the eHealth app. Therefore, it was also important to introduce the eHealth app to doctors and health care providers, encourage them to manage patients’ health, and facilitate comanagement by patients and their family with the assistance of the eHealth app.
For future improvement, personalized and age-specific health care recommendations should be provided to facilitate a more patient-centered eHealth app [
Overall, the respondents had a high satisfaction rate and a positive attitude toward continuing to adopt and recommend the app. The eHealth app seemed to empower citizens and their family members by enhancing their health information, self-management strategies, and experience with health services. However, privacy concerns and perceived difficulties in adopting were the major challenges of promoting eHealth. More comprehensive health records and tailored health information were recommended to be included for future improvement.
Factors predictive of downloading and adoption of the eHealth app by the Technology Acceptance Model (TAM).
Factors predictive of downloading and adoption of the eHealth app by the Technology Acceptance Model (TAM).
Factors predictive of downloading and acceptance of the eHealth app by the Theory of Planned Behavior (TPB).
Survey administered for the different respondents in this study.
Distribution of study participants according to downloading and acceptance of the eHealth app.
Sources where the study participants learnt about the eHealth app.
Perception on processes of current and future acceptance of the eHealth app.
Applicability of the eHealth app.
Perception of the eHealth app.
Expectations on future development of the eHealth app.
Electronic Health Record Sharing System
Hospital Authority
Technology Acceptance Model
Theory of Planned Behavior
Theory of Reasoned Action
The study was funded by Hospital Authority of Hong Kong Special Administrative Region (Ref.: (20) in HA 7052118).
The data used for the analyses are available upon reasonable request from the corresponding author.
JH and MCSW participated in the conception of the research ideas, study design, interpretation of the findings, and provided intellectual input to the translational aspects of the study. JH, WSP, YYW, and FYM contributed to the implementation of the study, statistical analysis, and writing of the first draft of the manuscript. MCSW, FSWC, CSKC, WNW, and NTC made critical revisions on the manuscripts and provided expert opinions on implications of the study findings.
FSWC, CSKC, WMW, and NTC are from the funding authority.