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BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2021

01-12-2021 | Computed Tomography | Research article

Factors of quality of care and their association with smartphone based PHR adoption in South Korean hospitals

Authors: Byung Kwan Choi, Young-Taek Park, Hyeoun-Ae Park, Chris Lane, Emmanuel C. Jo, Sunghong Kang

Published in: BMC Medical Informatics and Decision Making | Issue 1/2021

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Abstract

Background

Healthcare organizations have begun to adopt personal health records (PHR) systems to engage patients, but little is known about factors associated with the adoption of PHR systems at an organizational level. The objective of this study is to investigate factors associated with healthcare organizations’ adoption of PHR systems in South Korea.

Methods

The units of analysis were hospitals with more than 100 beds. Study data of 313 hospitals were collected from May 1 to June 30, 2020. The PHR adoption status for each hospital was collected from PHR vendors and online searches. Adoption was then confirmed by downloading the hospital’s PHR app and the PHR app was examined to ascertain its available functions. One major outcome variable was PHR adoption status at hospital level. Data were analysed by logistic regressions using SAS 9.4 version.

Results

Out of 313 hospitals, 103 (32.9%) hospitals adopted PHR systems. The nurse-patient ratio was significantly associated with PHR adoption (OR 0.758; 0.624 to 0.920, p = 0.005). The number of health information management staff was associated with PHR adoption (OR 1.622; 1.228 to 2.141, p = 0.001). The number of CTs was positively associated with PHR adoption (OR 5.346; 1.962 to 14.568, p = 0.001). Among the hospital characteristics, the number of beds was significantly related with PHR adoption in the model of standard of nursing care (OR 1.003; 1.001 to 1.005, p < 0.001), HIM staff (OR 1.004; 1.002 to 1.006, p < 0.001), and technological infrastructure (OR 1.050; 1.003 to 1.006, p < 0.001).

Conclusions

One-third of study hospitals had adopted PHR systems. Standard of nursing care as well as information technology infrastructure in terms of human resources for health information management and advanced technologies were significantly associated with adoption of PHR systems. A favourable environment for adopting new technologies in general may be associated with the adoption and use of PHR systems.
Literature
1.
Jung SY, Lee K, Hwang H, Yoo S, Baek HY, Kim J. Support for sustainable use of personal health records: understanding the needs of users as a first step towards patient-driven mobile health. JMIR Mhealth Uhealth. 2017;5(2):e19.CrossRefPubMedPubMedCentral
2.
Abd-alrazaq AA, Bewick BM, Farragher T, Gardner P. Factors that affect the use of electronic personal health records among patients: a systematic review. Int J Med Inform. 2019;126:164–75.CrossRefPubMed
3.
4.
Woollen J, Prey J, Wilcox L, Sackeim A, Restaino S, Raza ST, Bakken S, Feiner S, Hripcsak G, Vawdrey D. Patient experiences using an inpatient personal health record. Appl Clin Inform. 2016;7(2):446–60.CrossRefPubMedPubMedCentral
5.
6.
Park YR, Lee Y, Kim JY, Kim J, Kim HR, Kim YH, Kim WS, Lee JH. Managing patient-generated health data through mobile personal health records: analysis of usage data. JMIR Mhealth Uhealth. 2018;6(4):e89.CrossRefPubMedPubMedCentral
7.
Wyatt J, Hoogewerf J, Quinn N, Williams J, Clement C, Thimbleby H, Sathanandam S, Rastall P. Personal health record user insights: final report. London: Royal College of Physicians; 2017.
8.
9.
Vance B, Tomblin B, Studeny J, Coustasse A. Benefits and barriers for adoption of personal health records. In: 2015 Business and Health Administration Association Annual Conference at Chicago, IL; 2015.
10.
Peacock S, Reddy A, Leveille SG, Walker J, Payne TH, Oster NV, Elmore JG. Patient portals and personal health information online: perception, access, and use by US adults. J Am Med Inform Assoc. 2017;24(1):e173–7.CrossRefPubMed
11.
Zhao JY, Song B, Anand E, Schwartz D, Panesar M, Jackson GP, Elkin PL. Barriers, facilitators, and solutions to optimal patient portal and personal health record use: a systematic review of the literature. AMIA Annu Symp Proc. 2018;2017:1913–22.PubMedPubMedCentral
12.
Perzynski AT, Roach MJ, Shick S, Callahan B, Gunzler D, Cebul R, Kaelber DC, Huml A, Thornton JD, Einstadter D. Patient portals and broadband internet inequality. J Am Med Inform Assoc. 2017;24(5):927–32.CrossRefPubMedPubMedCentral
13.
Song YJ. The South Korean health care system. Jpn Med Assoc J. 2009;52(3):206–9.
14.
15.
16.
17.
18.
19.
Price M, Bellwood P, Kitson N, Davies I, Weber J, Lau F. Conditions potentially sensitive to a personal health record (PHR) intervention, a systematic review. BMC Med Inform Decis Mak. 2015;15:32.CrossRefPubMedPubMedCentral
20.
21.
Henderson J. Research in health information management: an expanding field of enquiry. Health Inf Manag J. 2017;46(3):103–4.
22.
Wells S, Rozenblum R, Park A, Dunn M, Bates DW. Organizational strategies for promoting patient and provider uptake of personal health records. J Am Med Inform Assoc. 2015;22(1):213–22.CrossRefPubMed
23.
Institute of Medicine (US) Committee on Quality of Health Care in America. To Err is Human: Building a Safer Health System. Kohn LT, Corrigan JM, Donaldson MS, editors. Washington (DC): National Academies Press (US); 2000.
24.
Hughes RG. Tools and Strategies for Quality Improvement and Patient Safety. In: Hughes RG, editor. Patient Safety and Quality: An Evidence-Based Handbook for Nurses. Rockville (MD): Agency for Healthcare Research and Quality (US); 2008 Chapter 44.
25.
Feldman SS, Buchalter S, Hayes LW. Health information technology in healthcare quality and patient safety: literature review. JMIR Med Inform. 2018;6(2):e10264. https://​doi.​org/​10.​2196/​10264. Erratum in: JMIR Med Inform. 2019;7(1):e11320.
26.
27.
Menachemi N, Chukmaitov A, Saunders C, Brooks RG. Hospital quality of care: does information technology matter? The relationship between information technology adoption and quality of care. Health Care Manage Rev. 2008;33(1):51–9.CrossRefPubMed
28.
29.
Lee YT, Park YT, Park JS, Yi BK. Association between electronic medical record system adoption and healthcare information technology infrastructure. Healthc Inform Res. 2018;24(4):327–34.CrossRefPubMedPubMedCentral
30.
Detmer D, Bloomrosen M, Raymond B, Tang P. Integrated personal health records: transformative tools for consumer-centric care. BMC Med Inform Decis Mak. 2008;8:45.CrossRefPubMedPubMedCentral
31.
Assadi V, Hassanein K. Consumer adoption of personal health record systems: a self-determination theory perspective. J Med Internet Res. 2017;19(7):e270.CrossRefPubMedPubMedCentral
32.
Taha J, Czaja SJ, Sharit J, Morrow DG. Factors affecting usage of a personal health record (PHR) to manage health. Psychol Aging. 2013;28(4):1124–39.CrossRefPubMedPubMedCentral
33.
Day K, Gu Y. Influencing factors for adopting personal health record (PHR). Stud Health Technol Inform. 2012;178:39–44.PubMed
34.
Lee G, Park JY, Shin SY, Hwang JS, Ryu HJ, Lee JH, Bates DW. Which users should be the focus of mobile personal health records? Analysis of user characteristics influencing usage of a tethered mobile personal health record. Telemed J E Health. 2016;22(5):419–28.CrossRefPubMedPubMedCentral
35.
Jung SY, Kim JW, Hwang H, Lee K, Baek RM, Lee HY, Yoo S, Song W, Han JS. Development of comprehensive personal health records integrating patient-generated health data directly from Samsung s-health and apple health apps: retrospective cross-sectional observational study. JMIR Mhealth Uhealth. 2019;7(5):e12691.CrossRefPubMedPubMedCentral
36.
Choi BK, Park YT, Kwon LS, Kim YS. Analysis of platforms and functions of mobile-based personal health record systems. Healthc Inform Res. 2020;26(4):311–20.CrossRefPubMedPubMedCentral
37.
38.
39.
Jamoom E, Beatty P, Bercovitz A, Woodwell D, Palso K, Rechtsteiner E. Physician adoption of electronic health record systems: United States, 2011. NCHS Data Brief. 2012;98:1–8.
40.
Lupiáñez-Villanueva F, Devaux A, Valverde-Albacete J, Folkvord F, Fauli C, Altenhofer M, et al. Benchmarking deployment of eHealth among general practitioners. Publications Office of the European Union; 2018.
41.
Hersh W, Wright A. What workforce is needed to implement the health information technology agenda? Analysis from the HIMSS analytics database. AMIA Annu Symp Proc. 2008;2008:303–7.PubMedCentral
Metadata
Title
Factors of quality of care and their association with smartphone based PHR adoption in South Korean hospitals
Authors
Byung Kwan Choi
Young-Taek Park
Hyeoun-Ae Park
Chris Lane
Emmanuel C. Jo
Sunghong Kang
Publication date
01-12-2021
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2021
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-021-01666-9

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