Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2021

Open Access 01-12-2021 | Care | Research

Exploring the perspectives of primary care providers on use of the electronic Patient Reported Outcomes tool to support goal-oriented care: a qualitative study

Authors: Hardeep Singh, Farah Tahsin, Jason Xin Nie, Brian McKinstry, Kednapa Thavorn, Ross Upshur, Sarah Harvey, Walter P. Wodchis, Carolyn Steele Gray

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

Login to get access

Abstract

Background

Digital health technologies can support primary care delivery, but clinical uptake in primary care is limited. This study explores enablers and barriers experienced by primary care providers when adopting new digital health technologies, using the example of the electronic Patient Reported Outcome (ePRO) tool; a mobile application and web portal designed to support goal-oriented care. To better understand implementation drivers and barriers primary care providers’ usage behaviours are compared to their perspectives on ePRO utility and fit to support care for patients with complex care needs.

Methods

This qualitative sub-analysis was part of a larger trial evaluating the use of the ePRO tool in primary care. Qualitative interviews were conducted with providers at the midpoint (i.e. 4.5–6 months after ePRO implementation) and end-point (i.e. 9–12 months after ePRO implementation) of the trial. Interviews explored providers’ experiences and perceptions of integrating the tool within their clinical practice. Interview data were analyzed using a hybrid thematic analysis and guided by the Technology Acceptance Model. Data from thirteen providers from three distinct primary care sites were included in the presented study.

Results

Three core themes were identified: (1) Perceived usefulness: perceptions of the tool’s alignment with providers’ typical approach to care, impact and value and fit with existing workflows influenced providers’ intention to use the tool and usage behaviour; (2) Behavioural intention: providers had a high or low behavioural intention, and for some, it changed over time; and (3) Improving usage behaviour: enabling external factors and enhancing the tool’s perceived ease of use may improve usage behaviour.

Conclusions

Multiple refinements/iterations of the ePRO tool (e.g. enhancing the tool’s alignment with provider workflows and functions) may be needed to enhance providers’ usage behaviour, perceived usefulness and behavioural intention. Enabling external factors, such as organizational and IT support, are also necessary to increase providers’ usage behaviour. Lessons from this study advance knowledge of technology implementation in primary care.

Trial registration

Clinicaltrials.gov Identified NCT02917954. Registered September 2016, https://​www.​clinicaltrials.​gov/​ct2/​show/​study/​NCT02917954
Appendix
Available only for authorised users
Literature
1.
Grant RW, Ashburner JM, Hong CS, Chang Y, Barry MJ, Atlas SJ. Defining patient complexity from the primary care physician’s perspective: a cohort study. Ann Intern Med. 2011;155(12):797–804.PubMedCrossRef
2.
Kingston A, Comas-Herrera A, Jagger C. Forecasting the care needs of the older population in England over the next 20 years: estimates from the Population Ageing and Care Simulation (PACSim) modelling study. Lancet Public Health. 2018;3(9):e447–55.PubMedPubMedCentralCrossRef
3.
Grant RW, Adams AS, Bayliss EA, Heisler M. Establishing visit priorities for complex patients: a summary of the literature and conceptual model to guide innovative interventions. Healthc (Amst). 2013;1(3–4):117–22.CrossRef
4.
Peek CJ, Baird MA, Coleman E. Primary care for patient complexity, not only disease. Fam Syst Health. 2009;27(4):287–302.PubMedCrossRef
5.
Grant RW, Wexler DJ, Ashburner JM, Hong CS, Atlas SJ. Characteristics of “complex” patients with type 2 diabetes mellitus according to their primary care physicians. Arch Intern Med. 2012;172(10):821–3.PubMedCrossRef
6.
Reuben DB, Tinetti ME. Goal-oriented patient care–an alternative health outcomes paradigm. N Engl J Med. 2012;366(9):777–9.PubMedCrossRef
7.
Loeb DF, Bayliss EA, Candrian C, deGruy FV, Binswanger IA. Primary care providers’ experiences caring for complex patients in primary care: a qualitative study. BMC Fam Pract. 2016;17(1):34.PubMedPubMedCentralCrossRef
8.
Østbye T, Yarnall KSH, Krause KM, Pollak KI, Gradison M, Michener JL. Is there time for management of patients with chronic diseases in primary care? Ann Fam Med. 2005;3(3):209–14.PubMedPubMedCentralCrossRef
9.
10.
Steele Gray C, Mercer S, Palen T, McKinstry B, Hendry A. ehealth advances in support of people with complex care needs: case examples from Canada. Scotland and the US. Healthc Q. 2016;19(2):29–37.CrossRef
11.
12.
Shaw J, Agarwal P, Desveaux L, Palma DC, Stamenova V, Jamieson T, Yang R, Bhatia RS, Bhattacharyya O. Beyond “implementation”: digital health innovation and service design. npj Digit Med. 2018;1(1):48.PubMedPubMedCentralCrossRef
13.
Whitelaw S, Pellegrini D, Van Spall HGC. Barriers to and facilitators of the uptake of digital health technology in cardiology: a systematic review. Eur Heart J. 2020;41(Supplement_2):26.CrossRef
14.
Seto E, Leonard KJ, Cafazzo JA, Barnsley J, Masino C, Ross HJ. Mobile phone-based telemonitoring for heart failure management: a randomized controlled trial. J Med Internet Res. 2012;14(1):e31.PubMedPubMedCentralCrossRef
15.
Becker S, Miron-Shatz T, Schumacher N, Krocza J, Diamantidis C, Albrecht U-V. Experiences, possibilities, and perspectives. JMIR mHealth uHealth. 2014;2(2):e24.PubMedPubMedCentralCrossRef
16.
McLean S, Sheikh A. Does telehealthcare offer a patient-centred way forward for the community-based management of long-term respiratory disease? Prim Care Respir J. 2009;18:125–6.PubMedPubMedCentralCrossRef
17.
Lau R, Stevenson F, Ong BN, Dziedzic K, Treweek S, Eldridge S, Everitt H, Kennedy A, Qureshi N, Rogers A, et al. Achieving change in primary care—causes of the evidence to practice gap: systematic reviews of reviews. Implement Sci. 2016;11(1):40.PubMedPubMedCentralCrossRef
18.
Hans PK, Gray CS, Gill A, Tiessen J. The provider perspective: investigating the effect of the Electronic Patient-Reported Outcome (ePRO) mobile application and portal on primary care provider workflow. Prim Health Care Res Dev. 2018;19(2):151–64.PubMedCrossRef
19.
Salmon P, Peters S, Rogers A, Gask L, Clifford R, Iredale W, Dowrick C, Morriss R. Peering through the barriers in GPs’ explanations for declining to participate in research: the role of professional autonomy and the economy of time. Fam Pract. 2007;24(3):269–75.PubMedCrossRef
20.
Granström E, Wannheden C, Brommels M, Hvitfeldt H, Nyström ME. Digital tools as promoters for person-centered care practices in chronic care? Healthcare professionals’ experiences from rheumatology care. BMC Health Serv Res. 2020;20(1):1108.PubMedPubMedCentralCrossRef
21.
Wildevuur SE, Simonse LW. Information and communication technology-enabled person-centered care for the “big five” chronic conditions: scoping review. J Med Internet Res. 2015;17(3):e77.PubMedPubMedCentralCrossRef
22.
Mohammed HT, Hyseni L, Bui V, Gerritsen B, Fuller K, Sung J, Alarakhia M. Exploring the use and challenges of implementing virtual visits during COVID-19 in primary care and lessons for sustained use. PLoS ONE. 2021;16(6):e0253665.PubMedPubMedCentralCrossRef
23.
Steele Gray C, Wodchis WP, Upshur R, Cott C, McKinstry B, Mercer S, Palen TE, Ramsay T, Thavorn K. Supporting goal-oriented primary health care for seniors with complex care needs using mobile technology: evaluation and implementation of the health system performance research network, bridgepoint electronic patient reported outcome Tool. JMIR Res Protoc. 2016;5(2):e126.PubMedPubMedCentralCrossRef
24.
Steele Gray C, Gill A, Khan AI, Hans PK, Kuluski K, Cott C. The electronic patient reported outcome tool: testing usability and feasibility of a mobile app and portal to support care for patients with complex chronic disease and disability in primary care settings. JMIR Mhealth Uhealth. 2016;4(2):e58–e58.PubMedPubMedCentralCrossRef
25.
Marangunić N, Granić A. Technology acceptance model: a literature review from 1986 to 2013. Univers Access Inf Soc. 2015;14(1):81–95.CrossRef
26.
Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci. 2000;46(2):186–204.CrossRef
27.
Rahimi B, Nadri H, Lotfnezhad Afshar H, Timpka T. A systematic review of the technology acceptance model in health informatics. Appl Clin Inform. 2018;9(3):604–34.PubMedPubMedCentralCrossRef
28.
Steele Gray C, Chau E, Tahsin F, Harvey S, Loganathan M, McKinstry B, Mercer SW, Nie JX, Palen TE, Ramsay T, Thavorn K, Upshur R, Wodchis WP. Assessing the implementation and effectiveness of the electronic patient-reported outcome tool for older adults with complex care needs: mixed methods study. JMIR. 2021;23(11):896.
29.
Tahsin F, Tracy S, Chau E, Harvey S, Loganathan M, McKinstry B, Mercer S, Nie J, Thavorn K, Ramsay T, Sritharan J, SteeleGray C. Exploring the relationship between the usability of a goal oriented mobile health application and non-usage attrition in patients with multimorbidity: a blended data analysis approach. Digit Health. 2021;7:2055.
30.
Thorne S, Kirkham SR, MacDonald-Emes J. Interpretive description: a noncategorical qualitative alternative for developing nursing knowledge. Res Nurs Health. 1997;20(2):169–77.PubMedCrossRef
31.
Thorne S, Kirkham SR, O’Flynn-Magee K. The analytic challenge in interpretive description. Int J Qual Methods. 2004;3(1):1–11.CrossRef
32.
Sharp J. Development, extension, and application: a review of the technology acceptance model. Inf Sys Educ J. 2006;5(9).
33.
Palinkas LA, Horwitz SM, Green CA, Wisdom JP, Duan N, Hoagwood K. Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Adm Policy Ment Health. 2015;42(5):533–44.PubMedPubMedCentralCrossRef
34.
Glazier RH, Redelmeier DA. Building the patient-centered medical home in Ontario. JAMA. 2010;303(21):2186–7.PubMedCrossRef
35.
Steele Gray CBR, Kee, K, Minkman M, Shaw J, Tietschert MV, Wankah P, Wodchis WP, Zonneveld N, Nies H. Will the “new” become the “normal”? Exploring Sustainability of Rapid Health System Transformations. Organ Behav Hum Decis Process (submitted).
36.
Fereday J, Muir-Cochrane E. Demonstrating rigor using thematic analysis: a hybrid approach of inductive and deductive coding and theme development. Int J Qual Methods. 2006;5(1):80–92.CrossRef
37.
Davis FD, Bagozzi RP, Warshaw PR. User acceptance of computer technology: a comparison of two theoretical models. Manag Sci. 1989;35(8):982–1003.CrossRef
38.
Morse JM. Myth #93: reliability and validity are not relevant to qualitative inquiry. Qual Health Res. 1999;9(6):717–8.CrossRef
39.
Morse JM, Barrett M, Mayan M, Olson K, Spiers J. Verification strategies for establishing reliability and validity in qualitative research. Int J Qual Methods. 2002;1(2):13–22.CrossRef
40.
41.
Patton MQ. Qualitative Research. In Everitt B, Howell D, editors. Encyclopedia of Statistics in Behavioral Science. London (UK): John Wiley & Sons Inc; 2005.
42.
Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007;19(6):349–57.PubMedCrossRef
43.
Kogan AC, Wilber K, Mosqueda L. Person-centered care for older adults with chronic conditions and functional impairment: a systematic literature review. J Am Ger Soc. 2016;64(1):e1–7.CrossRef
44.
Rosewilliam S, Roskell CA, Pandyan AD. A systematic review and synthesis of the quantitative and qualitative evidence behind patient-centred goal setting in stroke rehabilitation. Clin Rehabil. 2011;25(6):501–14.PubMedCrossRef
45.
Ross J, Stevenson FA, Dack C, Pal K, May CR, Michie S, Yardley L, Murray E. Health care professionals’ views towards self-management and self-management education for people with type 2 diabetes. BMJ Open. 2019;9(7):e029961.PubMedPubMedCentralCrossRef
46.
Hutchinson A, Becker LA. How the philosophies, styles, and methods of family medicine affect the research agenda. Ann Fam Med. 2004;2 Suppl 2(Suppl 2):S41–4.PubMedCrossRef
47.
Jacob C, Sanchez-Vazquez A, Ivory C. Social, organizational, and technological factors impacting clinicians’ adoption of mobile health tools: systematic literature review. JMIR Mhealth Uhealth. 2020;8(2):e15935.PubMedPubMedCentralCrossRef
48.
Bally ELS, Cesuroglu T. Toward integration of mhealth in primary care in the netherlands: a qualitative analysis of stakeholder perspectives. Front Public Health. 2020;7:407–407.PubMedPubMedCentralCrossRef
49.
Mold J. Goal-directed health care: redefining health and health care in the era of value-based care. Cureus. 2017;9(2):e1043–e1043.PubMedPubMedCentral
50.
Bodenheimer TGK. Self-management support for people with chronic illness. 1st ed. New York: MacGraw-Hill; 2007.
51.
Reuben DB, Jennings LA. Putting goal-oriented patient care into practice. J Am Geriatr Soc. 2019;67(7):1342–4.PubMedCrossRef
52.
Irfan Khan A, Gill A, Cott C, Hans PK, Steele Gray C. mHealth tools for the self-management of patients with multimorbidity in primary care settings: pilot study to explore user experience. JMIR mHealth uHealth. 2018;6(8):e171–e171.PubMedPubMedCentralCrossRef
53.
Hsiao J-L, Chen R-F. Critical factors influencing physicians’ intention to use computerized clinical practice guidelines: an integrative model of activity theory and the technology acceptance model. BMC Med Inform Decis Mak. 2016;16:3–3.PubMedPubMedCentralCrossRef
54.
Taj F, Klein MCA, van Halteren A. Digital health behavior change technology: bibliometric and scoping review of two decades of research. JMIR Mhealth Uhealth. 2019;7(12):e13311.PubMedPubMedCentralCrossRef
55.
Lorgelly PK, Adler A. Impact of a global pandemic on health technology assessment. Appl Health Econ. 2020;18(3):339–43.CrossRef
56.
Golinelli D, Boetto E, Carullo G, Nuzzolese AG, Landini MP, Fantini MP. Adoption of digital technologies in health care during the COVID-19 pandemic: systematic review of early scientific literature. J Med Internet Res. 2020;22(11):e22280.PubMedPubMedCentralCrossRef
57.
Jimenez G, Matchar D, Koh CHG, van der Kleij R, Chavannes NH, Car J. The role of health technologies in multicomponent primary care interventions: systematic review. J Med Internet Res. 2021;23(1):e20195.PubMedPubMedCentralCrossRef
58.
Gagnon M-P, Desmartis M, Labrecque M, Car J, Pagliari C, Pluye P, Frémont P, Gagnon J, Tremblay N, Légaré F. Systematic review of factors influencing the adoption of information and communication technologies by healthcare professionals. J Med Syst. 2012;36(1):241–77.PubMedCrossRef
59.
Institute of Medicine Committee on Quality of Health Care in A. In: Crossing the Quality Chasm: A New Health System for the 21st Century. Washington (DC): National Academies Press (US); 2001.
60.
61.
Christodoulakis C, Asgarian A, Easterbrook S. Barriers to adoption of information technology in healthcare. In: Proceedings of the 27th annual international conference on computer science and software engineering. Markham, Ontario, Canada: IBM Corp.; 2017: 66–75.
62.
Steele Gray C, Khan A, McKillop I, Sharpe S, Cott C. User-centred co-design with multiple user groups: the case of the electronic Patient Reported Outcome (ePRO) mobile application and portal. Int J Integr Care. 2019;19:439.CrossRef
Metadata
Title
Exploring the perspectives of primary care providers on use of the electronic Patient Reported Outcomes tool to support goal-oriented care: a qualitative study
Authors
Hardeep Singh
Farah Tahsin
Jason Xin Nie
Brian McKinstry
Kednapa Thavorn
Ross Upshur
Sarah Harvey
Walter P. Wodchis
Carolyn Steele Gray
Publication date
01-12-2021
Publisher
BioMed Central
Keyword
Care
Published in
BMC Medical Informatics and Decision Making / Issue 1/2021
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-021-01734-0

Other articles of this Issue 1/2021

BMC Medical Informatics and Decision Making 1/2021 Go to the issue

Research article

Investigating the interpretability of fetal status assessment using antepartum cardiotocographic records

Research article

Isotypes of autoantibodies against novel differential 4-hydroxy-2-nonenal-modified peptide adducts in serum is associated with rheumatoid arthritis in Taiwanese women

Research article

A hybrid cost-sensitive ensemble for heart disease prediction

Study protocol

Development and field testing of a patient decision aid for management of acute Achilles tendon rupture: a study protocol

Research

A graph-based gene selection method for medical diagnosis problems using a many-objective PSO algorithm

Research article

Primary care practices’ ability to predict future risk of expenditures and hospitalization using risk stratification and segmentation