Experiences of Complex Patients With Telemonitoring in a Nurse-Led Model of Care: Multimethod Feasibility Study

Kayleigh Gordon, Katie N Dainty, Carolyn Steele Gray, Jane DeLacy, Amika Shah, Myles Resnick, Emily Seto, Kayleigh Gordon, Katie N Dainty, Carolyn Steele Gray, Jane DeLacy, Amika Shah, Myles Resnick, Emily Seto

Abstract

Background: Telemonitoring (TM) interventions have been designed to support care delivery and engage patients in their care at home, but little research exists on TM of complex chronic conditions (CCCs). Given the growing prevalence of complex patients, an evaluation of multi-condition TM is needed to expand TM interventions and tailor opportunities to manage complex chronic care needs.

Objective: This study aims to evaluate the feasibility and patients' perceived usefulness of a multi-condition TM platform in a nurse-led model of care.

Methods: A pragmatic, multimethod feasibility study was conducted with patients with heart failure (HF), hypertension (HTN), and/or diabetes. Patients were asked to take physiological readings at home via a smartphone-based TM app for 6 months. The recommended frequency of taking readings was dependent on the condition, and adherence data were obtained through the TM system database. Patient questionnaires were administered, and patient interviews were conducted at the end of the study. An inductive analysis was performed, and codes were then mapped to the normalization process theory and Implementation Outcomes constructs by Proctor.

Results: In total, 26 participants were recruited, 17 of whom used the TM app for 6 months. Qualitative interviews were conducted with 14 patients, and 8 patients were interviewed with their informal caregiver present. Patient adherence was high, with patients with HF taking readings on average 76.6% (141/184) of the days they were asked to use the system and patients with diabetes taking readings on average 72% (19/26) of the days. The HTN adherence rate was 55% (29/52) of the days they were asked to use the system. The qualitative findings of the patient experience can be grouped into 4 main themes and 13 subthemes. The main themes were (1) making sense of the purpose of TM, (2) engaging and investing in TM, (3) implementing and adopting TM, and (4) perceived usefulness and the perceived benefits of TM in CCCs.

Conclusions: Multi-condition TM in nurse-led care was found to be feasible and was perceived as useful. Patients accepted and adopted the technology by demonstrating a moderate to high level of adherence across conditions. These results demonstrate how TM can address the needs of patients with CCCs through virtual TM assessments in a nurse-led care model by supporting patient self-care and keeping patients connected to their clinical team.

Keywords: adherence; complex patients; implementation; mobile phone; normalization process theory; patient experience; telemonitoring.

Conflict of interest statement

Conflicts of Interest: None declared.

©Kayleigh Gordon, Katie N Dainty, Carolyn Steele Gray, Jane DeLacy, Amika Shah, Myles Resnick, Emily Seto. Originally published in JMIR Nursing Informatics (https://nursing.jmir.org), 29.09.2020.

Figures

Figure 1
Figure 1
Screenshots of the Medly app for patients with a complex chronic condition.
Figure 2
Figure 2
Total number of blood pressure readings on the hypertension modules. BP: blood pressure.
Figure 3
Figure 3
Total number of blood glucose readings on the diabetes mellitus modules. BG: blood glucose.
Figure 4
Figure 4
Mapping normalization process theory to Proctor’s Implementation Outcomes in a feasibility study to evaluate multi-condition in nurse-led care.

References

    1. Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, Meinow B, Fratiglioni L. Aging with multimorbidity: A systematic review of the literature. Ageing Research Reviews. 2011 Sep;10(4):430–439. doi: 10.1016/j.arr.2011.03.003.
    1. Sakib MN, Shooshtari S, St John P, Menec V. The prevalence of multimorbidity and associations with lifestyle factors among middle-aged Canadians: an analysis of Canadian Longitudinal Study on Aging data. BMC Public Health. 2019 Feb 28;19(1):243. doi: 10.1186/s12889-019-6567-x.
    1. Gruneir A, Bronskill SE, Maxwell CJ, Bai YQ, Kone AJ, Thavorn K, Petrosyan Y, Calzavara A, Wodchis WP. The association between multimorbidity and hospitalization is modified by individual demographics and physician continuity of care: a retrospective cohort study. BMC Health Serv Res. 2016 Apr 27;16:154. doi: 10.1186/s12913-016-1415-5.
    1. Mondor L, Maxwell CJ, Hogan DB, Bronskill SE, Gruneir A, Lane NE, Wodchis WP. Multimorbidity and healthcare utilization among home care clients with dementia in Ontario, Canada: A retrospective analysis of a population-based cohort. PLoS Med. 2017 Mar;14(3):e1002249. doi: 10.1371/journal.pmed.1002249.
    1. Skinner HG, Coffey R, Jones J, Heslin KC, Moy E. The effects of multiple chronic conditions on hospitalization costs and utilization for ambulatory care sensitive conditions in the United States: a nationally representative cross-sectional study. BMC Health Serv Res. 2016 Mar 1;16(1):1–8. doi: 10.1186/s12913-016-1304-y.
    1. O'Brien R, Wyke S, Guthrie B, Watt G, Mercer S. An 'endless struggle': a qualitative study of general practitioners' and practice nurses' experiences of managing multimorbidity in socio-economically deprived areas of Scotland. Chronic Illn. 2011 Mar;7(1):45–59. doi: 10.1177/1742395310382461.
    1. Aoki T, Yamamoto Y, Ikenoue T, Onishi Y, Fukuhara S. Multimorbidity patterns in relation to polypharmacy and dosage frequency: a nationwide, cross-sectional study in a Japanese population. Sci Rep. 2018 Feb 28;8(1):-. doi: 10.1038/s41598-018-21917-6.
    1. Gallacher K, May CR, Montori VM, Mair FS. Understanding patients' experiences of treatment burden in chronic heart failure using normalization process theory. Ann Fam Med. 2011;9(3):235–43. doi: 10.1370/afm.1249.
    1. Violan C, Foguet-Boreu Q, Flores-Mateo G, Salisbury C, Blom J, Freitag M, Glynn L, Muth C, Valderas JM. Prevalence, determinants and patterns of multimorbidity in primary care: a systematic review of observational studies. PLoS One. 2014;9(7):e102149. doi: 10.1371/journal.pone.0102149.
    1. Heale R, James S, Garceau M. A multiple-case study in nurse practitioner-led clinics: an exploration of the quality of care for patients with multimorbidity. Nurs Leadersh (Tor Ont) 2016;29(3):37–45. doi: 10.12927/cjnl.2016.24891.
    1. Young J, Eley D, Patterson E, Turner C. A nurse-led model of chronic disease management in general practice: Patients' perspectives. Aust Fam Physician. 2016 Dec;45(12):912–916.
    1. Gordon K, Gray C, Dainty K, deLacy J, Seto E. Nurse-Led Models of Care for Patients with Complex Chronic Conditions: A Scoping Review. Nurs Leadersh (Tor Ont) 2019 Sep;32(3):57–76. doi: 10.12927/cjnl.2019.25972.
    1. Heale R, Wenghofer E, James S, Garceau M. Quality of Care for Patients With Diabetes and Mulitmorbidity Registered at Nurse Practitioner-Led Clinics. Can J Nurs Res. 2018 Mar;50(1):20–27. doi: 10.1177/0844562117744137.
    1. Hansen K, McDonald C, O'Hara S, Post L, Silcox S, Gutmanis I. A formative evaluation of a nurse practitioner-led interprofessional geriatric outpatient clinic. J Interprof Care Internet. 2017 Apr 06;:546. doi: 10.1080/13561820.2017.1303463. doi: 10.1080/13561820.2017.1303463.
    1. Gordon K, Steele Gray C, Dainty KN, DeLacy J, Ware P, Seto E. Exploring an Innovative Care Model and Telemonitoring for the Management of Patients With Complex Chronic Needs: Qualitative Description Study. JMIR Nursing. 2020 Mar 6;3(1):e15691. doi: 10.2196/15691.
    1. Heale R, James S, Wenghofer E, Garceau M. Nurse practitioner’s perceptions of the impact of the nurse practitioner-led clinic model on the quality of care of complex patients. Prim Health Care Res Dev. 2018 Jan 9;19(6):553–560. doi: 10.1017/s1463423617000913.
    1. Steele GC, Khan A, Kuluski K, McKillop I, Sharpe S, Bierman A. Improving Patient Experience and Primary Care Quality for Patients With Complex Chronic Disease Using the Electronic Patient-Reported Outcomes Tool: Adopting Qualitative Methods Into a User-Centered Design Approach. JMIR Res Protoc Internet. 2016;5(1):e28. doi: 10.2196/resprot.5204.
    1. Paré G, Jaana M, Sicotte C. Systematic Review of Home Telemonitoring for Chronic Diseases?: The Evidence Base Home Telemonitoring?: A Definition. Journal of American Medical Informatics Association. 2007;14(3):269–277. doi: 10.1197/jamia.M2270.
    1. Kitsiou S, Paré G, Jaana M. Effects of home telemonitoring interventions on patients with chronic heart failure: an overview of systematic reviews. J Med Internet Res. 2015 Mar 12;17(3):e63. doi: 10.2196/jmir.4174.
    1. Kitsiou S, Paré G, Jaana M, Gerber B. Effectiveness of mHealth interventions for patients with diabetes: an overview of systematic reviews. PLoS One. 2017;12(3):e0173160. doi: 10.1371/journal.pone.0173160.
    1. Queirós A, Alvarelhão J, Cerqueira M, Silva A, Santos M, Pacheco Rocha N. Remote Care Technology: A Systematic Review of Reviews and Meta-Analyses. Technologies. 2018 Feb 10;6(1):22. doi: 10.3390/technologies6010022.
    1. Pekmezaris R, Tortez L, Williams M, Patel V, Makaryus A, Zeltser R, Sinvani L, Wolf-Klein G, Lester J, Sison C, Lesser M, Kozikowski A. Home Telemonitoring In Heart Failure: A Systematic Review And Meta-Analysis. Health Aff (Millwood) 2018 Dec;37(12):1983–1989. doi: 10.1377/hlthaff.2018.05087.
    1. Yun J, Park J, Park H, Lee H, Park D. Comparative Effectiveness of Telemonitoring Versus Usual Care for Heart Failure: A Systematic Review and Meta-analysis. J Card Fail. 2018 Jan;24(1):19–28. doi: 10.1016/j.cardfail.2017.09.006.
    1. Cruz J, Brooks D, Marques A. Home telemonitoring effectiveness in COPD: a systematic review. Int J Clin Pract. 2014 Mar;68(3):369–78. doi: 10.1111/ijcp.12345.
    1. He T, Liu X, Li Y, Wu Q, Liu M, Yuan H. Remote home management for chronic kidney disease: A systematic review. J Telemed Telecare. 2016 Jul 09;23(1):3–13. doi: 10.1177/1357633x15626855.
    1. Achelrod D, Schreyögg J, Stargardt T. Health-economic evaluation of home telemonitoring for COPD in Germany: evidence from a large population-based cohort. Eur J Health Econ. 2017 Sep;18(7):869–882. doi: 10.1007/s10198-016-0834-x.
    1. 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 Feb 16;14(1):e31. doi: 10.2196/jmir.1909.
    1. Paré Guy, Moqadem K, Pineau G, St-Hilaire C. Clinical effects of home telemonitoring in the context of diabetes, asthma, heart failure and hypertension: a systematic review. J Med Internet Res. 2010 Jun 16;12(2):e21. doi: 10.2196/jmir.1357.
    1. Mochari-Greenberger H, Vue L, Luka A, Peters A, Pande RL. A Tele-Behavioral Health Intervention to Reduce Depression, Anxiety, and Stress and Improve Diabetes Self-Management. Telemed J E Health. 2016 Aug;22(8):624–30. doi: 10.1089/tmj.2015.0231.
    1. Lee JY, Chan CKY, Chua SS, Ng CJ, Paraidathathu T, Lee KKC, Lee SWH. Telemonitoring and Team-Based Management of Glycemic Control on People with Type 2 Diabetes: a Cluster-Randomized Controlled Trial. J Gen Intern Med. 2020 Jan;35(1):87–94. doi: 10.1007/s11606-019-05316-9.
    1. Kim Y, Park J, Lee B, Jung C, Park D. Comparative effectiveness of telemonitoring versus usual care for type 2 diabetes: A systematic review and meta-analysis. J Telemed Telecare. 2018 Jul 17;25(10):587–601. doi: 10.1177/1357633x18782599.
    1. Margolis KL, Asche SE, Dehmer SP, Bergdall AR, Green BB, Sperl-Hillen JM, Nyboer RA, Pawloski PA, Maciosek MV, Trower NK, O'Connor PJ. Long-term Outcomes of the Effects of Home Blood Pressure Telemonitoring and Pharmacist Management on Blood Pressure Among Adults With Uncontrolled Hypertension: Follow-up of a Cluster Randomized Clinical Trial. JAMA Netw Open. 2018 Sep 7;1(5):e181617. doi: 10.1001/jamanetworkopen.2018.1617.
    1. Duan Y, Xie Z, Dong F, Wu Z, Lin Z, Sun N, Xu J. Effectiveness of home blood pressure telemonitoring: a systematic review and meta-analysis of randomised controlled studies. J Hum Hypertens. 2017 Jul;31(7):427–437. doi: 10.1038/jhh.2016.99.
    1. Sicotte C, Paré G, Morin S, Potvin J, Moreault M. Effects of home telemonitoring to support improved care for chronic obstructive pulmonary diseases. Telemed J E Health. 2011 Mar;17(2):95–103. doi: 10.1089/tmj.2010.0142.
    1. Seto E, Leonard KJ, Cafazzo JA, Barnsley J, Masino C, Ross HJ. Perceptions and experiences of heart failure patients and clinicians on the use of mobile phone-based telemonitoring. J Med Internet Res. 2012 Feb 10;14(1):e25. doi: 10.2196/jmir.1912.
    1. Walker R, Tong A, Howard K, Palmer S. Patient expectations and experiences of remote monitoring for chronic diseases: Systematic review and thematic synthesis of qualitative studies. Int J Med Inform. 2019 Apr;124:78–85. doi: 10.1016/j.ijmedinf.2019.01.013.
    1. Ong MK, Romano PS, Edgington S, Aronow HU, Auerbach AD, Black JT, De Marco T, Escarce JJ, Evangelista LS, Hanna B, Ganiats TG, Greenberg BH, Greenfield S, Kaplan SH, Kimchi A, Liu H, Lombardo D, Mangione CM, Sadeghi B, Sadeghi B, Sarrafzadeh M, Tong K, Fonarow GC, Better Effectiveness After Transition–Heart Failure (BEAT-HF) Research Group Effectiveness of Remote Patient Monitoring After Discharge of Hospitalized Patients With Heart Failure: The Better Effectiveness After Transition -- Heart Failure (BEAT-HF) Randomized Clinical Trial. JAMA Intern Med. 2016 Mar;176(3):310–8. doi: 10.1001/jamainternmed.2015.7712.
    1. Koehler F, Koehler K, Deckwart O, Prescher S, Wegscheider K, Kirwan B, Winkler S, Vettorazzi E, Bruch L, Oeff M, Zugck C, Doerr G, Naegele H, Störk S, Butter C, Sechtem U, Angermann C, Gola G, Prondzinsky R, Edelmann F, Spethmann S, Schellong SM, Schulze PC, Bauersachs J, Wellge B, Schoebel C, Tajsic M, Dreger H, Anker SD, Stangl K. Efficacy of telemedical interventional management in patients with heart failure (TIM-HF2): a randomised, controlled, parallel-group, unmasked trial. Lancet. 2018 Sep;392(10152):1047–57. doi: 10.1016/s0140-6736(18)31880-4.
    1. Kruse C, Pesek B, Anderson M, Brennan K, Comfort H. Telemonitoring to Manage Chronic Obstructive Pulmonary Disease: Systematic Literature Review. JMIR Med Inform. 2019 Mar 20;7(1):e11496. doi: 10.2196/11496.
    1. Sul A, Lyu D, Park D. Effectiveness of telemonitoring versus usual care for chronic obstructive pulmonary disease: A systematic review and meta-analysis. J Telemed Telecare. 2018 Dec 12;26(4):189–199. doi: 10.1177/1357633x18811757.
    1. Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, Griffey R, Hensley M. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health. 2011 Mar;38(2):65–76. doi: 10.1007/s10488-010-0319-7.
    1. van Walraven C, Dhalla IA, Bell C, Etchells E, Stiell IG, Zarnke K, Austin PC, Forster AJ. Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community. Can Med Assoc J. 2010 Apr 6;182(6):551–7. doi: 10.1503/cmaj.091117.
    1. May C, Mair F, Finch T, MacFarlane A, Dowrick C, Treweek S. Development of a theory of implementation and integration: Normalization Process Theory. Implement Science. 2009;(1):29. doi: 10.1186/1748-5908-4-29. doi: 10.1186/1748-5908-4-29.
    1. May C, Finch T. Implementing, Embedding, and Integrating Practices: An Outline of Normalization Process Theory. Sociology. 2009 Jun 15;43(3):535–554. doi: 10.1177/0038038509103208.
    1. Murray E, Treweek S, Pope C, MacFarlane A, Ballini L, Dowrick C, Finch T, Kennedy A, Mair F, O'Donnell C, Ong BN, Rapley T, Rogers A, May C. Normalisation process theory: a framework for developing, evaluating and implementing complex interventions. BMC Med. 2010 Oct 20;8:63. doi: 10.1186/1741-7015-8-63.
    1. May C. Towards a general theory of implementation. Implement Sci. 2013 Feb 13;8:18. doi: 10.1186/1748-5908-8-18.
    1. Ware P, Dorai M, Ross H, Cafazzo J, Laporte A, Boodoo C. Patient adherence to a mobile phone?based heart failure telemonitoring program: A longitudinal mixed-methods study. Journal of Medical Internet Research. 2019;21(2):1–18. doi: 10.2196/13259.
    1. Seto E, Leonard KJ, Cafazzo JA, Masino C, Barnsley J, Ross HJ. Mobile phone-based remote patient monitoring improves heart failure management and outcomes: a randomized controlled trial. Journal of the American College of Cardiology. 2011 Apr;57(14):E1260. doi: 10.1016/s0735-1097(11)61260-6.
    1. Seto E, Leonard KJ, Cafazzo JA, Barnsley J, Masino C, Ross HJ. Developing healthcare rule-based expert systems: case study of a heart failure telemonitoring system. Int J Med Inform. 2012 Aug;81(8):556–65. doi: 10.1016/j.ijmedinf.2012.03.001.
    1. Billingham SAM, Whitehead AL, Julious SA. An audit of sample sizes for pilot and feasibility trials being undertaken in the United Kingdom registered in the United Kingdom Clinical Research Network database. BMC Med Res Methodol. 2013;13:104. doi: 10.1186/1471-2288-13-104.
    1. Julious SA. Sample size of 12 per group rule of thumb for a pilot study. Pharmaceut. Statist. 2005 Oct;4(4):287–291. doi: 10.1002/pst.185.
    1. Ware JE, Sherbourne CD. The MOS 36-ltem Short-Form Health Survey (SF-36) Medical Care. 1992;30(6):473–483. doi: 10.1097/00005650-199206000-00002.
    1. May C. Agency and implementation: Understanding the embedding of healthcare innovations in practice. 2013 Feb;78:26–33. doi: 10.1016/j.socscimed.2012.11.021.
    1. Thorne S, Kirkham SR, MacDonald-Emes J. Interpretive description: A noncategorical qualitative alternative for developing nursing knowledge. Research in Nursing and Health. 1997 Apr;20(2):169–177. doi: 10.1002/(sici)1098-240x(199704)20:2<169::aid-nur9>;2-i.
    1. Thorne S, Kirkham Sr, MacDonald-Emes J. Interpretive description: a noncategorical qualitative alternative for developing nursing knowledge. Res Nurs Health. 1997 Apr;20(2):169–77. doi: 10.1002/(sici)1098-240x(199704)20:2<169::aid-nur9>;2-i.
    1. Hunt MR. Strengths and Challenges in the Use of Interpretive Description: Reflections Arising From a Study of the Moral Experience of Health Professionals in Humanitarian Work. Qual Health Res. 2009 Aug 18;19(9):1284–1292. doi: 10.1177/1049732309344612.
    1. Hennink MM, Kaiser BN, Marconi VC. Code Saturation Versus Meaning Saturation. Qual Health Res. 2016 Sep 26;27(4):591–608. doi: 10.1177/1049732316665344.
    1. Saunders B, Sim J, Kingstone T, Baker S, Waterfield J, Bartlam B, Burroughs H, Jinks C. Saturation in qualitative research: exploring its conceptualization and operationalization. Qual Quant. 2017 Sep 14;52(4):1893–1907. doi: 10.1007/s11135-017-0574-8.
    1. Census Profile. Brampton, Ontario. 2016. [2018-01-01]. .
    1. Maeder A, Poultney N, Morgan G, Lippiatt R. Patient Compliance in Home-Based Self-Care Telehealth Projects. J Telemed Telecare. 2015 Nov 10;21(8):439–442. doi: 10.1177/1357633x15612382.
    1. Celler B, Argha A, Varnfield M, Jayasena R. Patient Adherence to Scheduled Vital Sign Measurements During Home Telemonitoring: Analysis of the Intervention Arm in a Before and After Trial. JMIR Med Info. 2018;6(2):e15. doi: 10.2196/preprints.9200.
    1. Lee C. Adoption of Smart Technology Among Older Adults: Challenges and Issues. Publ Pol Aging Rep. 2013 Dec 17;24(1):14–17. doi: 10.1093/ppar/prt005.
    1. Kuluski K, Peckham A, Gill A, Gagnon D, Dumas S, Sheridan N, McKillop A, Wong-Cornall C, Parsons J. What is important to people with multimorbidity and their caregivers? Identifying attributes of person centred primary health care from the user perspective. Int J Integr Care. 2019 Aug 08;19(4):271. doi: 10.5334/ijic.s3271.
    1. Bayliss EA, Edwards AE, Steiner JF, Main DS. Processes of care desired by elderly patients with multimorbidities. Fam Pract. 2008 Aug;25(4):287–93. doi: 10.1093/fampra/cmn040.
    1. 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 Jun 02;4(2):e58. doi: 10.2196/mhealth.5331.

Source: PubMed

3
Subscribe