Tailoring Remote Patient Management in Cardiovascular Risk Management for Healthcare Professionals Using Panel Management: a Qualitative Study

Overview

Journal BMC Prim Care

Specialties Health Services
Public Health

Date 2024 Apr 20

PMID 38643103

Authors

Margot Rakers

Nicoline van Hattem

Iris Simic

Niels Chavannes

Petra van Peet

Tobias Bonten

Rimke Vos

Hendrikus van Os

Affiliations

Soon will be listed here.

Abstract

Background: While remote patient management (RPM) has the potential to assist in achieving treatment targets for cardiovascular risk factors in primary care, its effectiveness may vary among different patient subgroups. Panel management, which involves proactive care for specific patient risk groups, could offer a promising approach to tailor RPM to these groups. This study aims to (i) assess the perception of healthcare professionals and other stakeholders regarding the adoption and (ii) identify the barriers and facilitators for successfully implementing such a panel management approach.

Methods: In total, nineteen semi-structured interviews and two focus groups were conducted in the Netherlands. Three authors reviewed the audited transcripts. The Consolidated Framework for Implementation Strategies (CFIR) domains were used for the thematic analysis.

Results: A total of 24 participants (GPs, nurses, health insurers, project managers, and IT consultants) participated. Overall, a panel management approach to RPM in primary care was considered valuable by various stakeholders. Implementation barriers encompassed concerns about missing necessary risk factors for patient stratification, additional clinical and technical tasks for nurses, and reimbursement agreements. Facilitators included tailoring consultation frequency and early detection of at-risk patients, an implementation manager accountable for supervising project procedures and establishing agreements on assessing implementation metrics, and ambassador roles.

Conclusion: Panel management could enhance proactive care and accurately identify which patients could benefit most from RPM to mitigate CVD risk. For successful implementation, we recommend having clear agreements on technical support, financial infrastructure and the criteria for measuring evaluation outcomes.

References

Treskes R, van Winden L, van Keulen N, van der Velde E, Beeres S, Atsma D . Effect of Smartphone-Enabled Health Monitoring Devices vs Regular Follow-up on Blood Pressure Control Among Patients After Myocardial Infarction: A Randomized Clinical Trial. JAMA Netw Open. 2020; 3(4):e202165. PMC: 7163406. DOI: 10.1001/jamanetworkopen.2020.2165. View

Smeets H, Kortekaas M, Rutten F, Bots M, van der Kraan W, Daggelders G . Routine primary care data for scientific research, quality of care programs and educational purposes: the Julius General Practitioners' Network (JGPN). BMC Health Serv Res. 2018; 18(1):735. PMC: 6156960. DOI: 10.1186/s12913-018-3528-5. View

Mantena S, Keshavjee S . Strengthening healthcare delivery with remote patient monitoring in the time of COVID-19. BMJ Health Care Inform. 2021; 28(1). PMC: 8300556. DOI: 10.1136/bmjhci-2020-100302. View

Vonken L, Hussein H, Crutzen R, Vluggen S . Perceptions of Dutch general practitioners towards eHealth for patients with type-2 diabetes: a qualitative study. Fam Pract. 2022; 40(1):91-97. PMC: 9384395. DOI: 10.1093/fampra/cmac066. View

van der Ende M, Sijtsma A, Snieder H, van der Harst P . Letter to editor: Reply on question of Marques JR et al. regarding the paper entitled: "The LifeLines cohort study: Prevalence and treatment of cardiovascular disease and risk factors". Int J Cardiol. 2019; 294:57. DOI: 10.1016/j.ijcard.2019.06.026. View

van Hattem N, Silven A, Bonten T, Chavannes N . COVID-19's impact on the future of digital health technology in primary care. Fam Pract. 2021; 38(6):845-847. PMC: 8344716. DOI: 10.1093/fampra/cmab081. View

Gannamani R, Castela Forte J, Folkertsma P, Hermans S, Kumaraswamy S, van Dam S . A Digitally Enabled Combined Lifestyle Intervention for Weight Loss: Pilot Study in a Dutch General Population Cohort. JMIR Form Res. 2024; 8:e38891. PMC: 10884913. DOI: 10.2196/38891. View

Corrrigan M, Cupples M, Smith S, Byrne M, Leathem C, Clerkin P . The contribution of qualitative research in designing a complex intervention for secondary prevention of coronary heart disease in two different healthcare systems. BMC Health Serv Res. 2006; 6:90. PMC: 1543625. DOI: 10.1186/1472-6963-6-90. View

Kaminetzky C, Nelson K . In the Office and In-Between: The Role of Panel Management in Primary Care. J Gen Intern Med. 2015; 30(7):876-7. PMC: 4471035. DOI: 10.1007/s11606-015-3310-x. View

10.

Hallensleben C, van Luenen S, Rolink E, Ossebaard H, Chavannes N . eHealth for people with COPD in the Netherlands: a scoping review. Int J Chron Obstruct Pulmon Dis. 2019; 14:1681-1690. PMC: 6668016. DOI: 10.2147/COPD.S207187. View

11.

Clark A, Briffa T, Thirsk L, Neubeck L, Redfern J . What football teaches us about researching complex health interventions. BMJ. 2012; 345:e8316. DOI: 10.1136/bmj.e8316. View

12.

Roth G, Mensah G, Johnson C, Addolorato G, Ammirati E, Baddour L . Global Burden of Cardiovascular Diseases and Risk Factors, 1990-2019: Update From the GBD 2019 Study. J Am Coll Cardiol. 2020; 76(25):2982-3021. PMC: 7755038. DOI: 10.1016/j.jacc.2020.11.010. View

13.

Kotseva K, De Backer G, De Bacquer D, Ryden L, Hoes A, Grobbee D . Lifestyle and impact on cardiovascular risk factor control in coronary patients across 27 countries: Results from the European Society of Cardiology ESC-EORP EUROASPIRE V registry. Eur J Prev Cardiol. 2019; 26(8):824-835. DOI: 10.1177/2047487318825350. View

14.

Holbrook A, Thabane L, Keshavjee K, Dolovich L, Bernstein B, Chan D . Individualized electronic decision support and reminders to improve diabetes care in the community: COMPETE II randomized trial. CMAJ. 2009; 181(1-2):37-44. PMC: 2704409. DOI: 10.1503/cmaj.081272. View

15.

Gale N, Heath G, Cameron E, Rashid S, Redwood S . Using the framework method for the analysis of qualitative data in multi-disciplinary health research. BMC Med Res Methodol. 2013; 13:117. PMC: 3848812. DOI: 10.1186/1471-2288-13-117. View

16.

Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M . Developing and evaluating complex interventions: the new Medical Research Council guidance. BMJ. 2008; 337:a1655. PMC: 2769032. DOI: 10.1136/bmj.a1655. View

17.

Feldstein A, Schneider J, Unitan R, Perrin N, Smith D, Nichols G . Health care worker perspectives inform optimization of patient panel-support tools: a qualitative study. Popul Health Manag. 2012; 16(2):107-19. DOI: 10.1089/pop.2012.0065. View

18.

Hammerton M, Benson T, Sibley A . Readiness for five digital technologies in general practice: perceptions of staff in one part of southern England. BMJ Open Qual. 2022; 11(2). PMC: 9244720. DOI: 10.1136/bmjoq-2022-001865. View

19.

Ross J, Stevenson F, Lau R, Murray E . Factors that influence the implementation of e-health: a systematic review of systematic reviews (an update). Implement Sci. 2016; 11(1):146. PMC: 5080780. DOI: 10.1186/s13012-016-0510-7. View

20.

Shahmoradi L, Safdari R, Ahmadi H, Zahmatkeshan M . Clinical decision support systems-based interventions to improve medication outcomes: A systematic literature review on features and effects. Med J Islam Repub Iran. 2021; 35:27. PMC: 8214039. DOI: 10.47176/mjiri.35.27. View