“Everyone Has a Role in This”: Evaluating Organizational Readiness for a Digital Solution to Support Hypertension Care Teams and Patients

Abstract

Background

Hypertension is a significant contributor to cardiovascular disease, yet evidence-based blood pressure (BP) control practices are inconsistently applied. The Collaboration Oriented Approach to Controlling High Blood Pressure (COACH) is a digital clinical decision support tool designed to improve BP self-management and support clinician workflows. While the patient perspective on COACH has been evaluated in a separate study, this study evaluates organizational readiness for COACH implementation across three health systems using the Consolidated Framework for Implementation Research (CFIR).

Objectives

This study aimed to assess preimplementation facilitators and barriers for COACH, focusing on organizational readiness and modifiable factors influencing scalability.

Methods

Qualitative interviews were conducted with 72 care team members from nine primary care clinics across three health systems using Epic or Oracle electronic health records. Data were analyzed using CFIR domains: innovation, inner setting, outer setting, individuals, and implementation process. Subdomains were rated from −2 (barrier) to +2 (facilitator).

Results

Overall, 79% of CFIR domain scores were positive, suggesting strong readiness for COACH implementation. The innovation domain scored 80% positive, highlighting COACH's user-friendly design, robust evidence base, and perceived advantages over current workflows. The inner setting domain showed 85% positive scores, driven by strong leadership, established infrastructures for patient-centered care, and high motivation for quality improvement. The outer setting domain scored 70% positive, reflecting barriers such as reimbursement policies, resource limitations, and staffing shortages. Participants noted the importance of continued leadership engagement, team-based support, and addressing workload challenges for sustainable implementation.

Conclusion

The study demonstrates high organizational readiness for COACH, with critical barriers in reimbursement and resources that must be addressed for successful adoption. Findings underscore COACH's potential to enhance clinical decision-making and patient engagement. Future research should explore long-term impacts on care delivery and outcomes, informing broader adoption of digital health interventions in clinical practice.

Keywords

hypertension - clinical decision support systems - implementation science - electronic health records - health disparities

• References

• 1 Heart Disease Facts. Accessed May 3, 2024 at: https://www.cdc.gov/heartdisease/facts.htm
• 2 Wu J, Napoleone J, Linke S. et al. Long-term results of a digital hypertension self-management program: retrospective cohort study. JMIR Cardio 2023; 7: e43489
• 3 Price JD, Jayaprakash M, McKay CM. et al. Evidence-based interventions for high blood pressure and glycemic control among Illinois health systems. Prev Chronic Dis 2020; 17: E08
• 4 Sekkarie A, Fang J, Hayes D, Loustalot F. . Prevalence of self-reported hypertension and antihypertensive medication use among adults—United States, 2017–2021; 2024. Morbidity and Mortality Weekly Report. Accessed at: https://www.cdc.gov/mmwr/volumes/73/wr/mm7309a1.htm
• 5 Bobrie G, Chatellier G, Genes N. et al. Cardiovascular prognosis of “masked hypertension” detected by blood pressure self-measurement in elderly treated hypertensive patients. JAMA 2004; 291 (11) 1342-1349
• 6 United States Preventive Services Task Force. Final recommendation statement: high blood pressure in adults: screening. 2017
• 7 Fagard RH, Van Den Broeke C, De Cort P. Prognostic significance of blood pressure measured in the office, at home and during ambulatory monitoring in older patients in general practice. J Hum Hypertens 2005; 19 (10) 801-807
• 8 Crabtree MM, Stuart-Shor E, McAllister M. Home blood pressure monitoring: an integrated review of the literature. Jnp-J Nurse Pract 2013; 9 (06) 356-361
• 9 Kerr EA, Zikmund-Fisher BJ, Klamerus ML, Subramanian U, Hogan MM, Hofer TP. The role of clinical uncertainty in treatment decisions for diabetic patients with uncontrolled blood pressure. Ann Intern Med 2008; 148 (10) 717-727
• 10 Canfield SM, Koopman RJ. Implementing patient-generated home blood pressure data into primary care EHR workflow in a large health system: facilitators, adoption considerations, and next steps. Ann Fam Med 2023
• 11 Gentili A, Failla G, Melnyk A. et al. The cost-effectiveness of digital health interventions: a systematic review of the literature. Front Public Health 2022; 10: 787135
• 12 Hamine S, Gerth-Guyette E, Faulx D, Green BB, Ginsburg AS. Impact of mHealth chronic disease management on treatment adherence and patient outcomes: a systematic review. J Med Internet Res 2015; 17 (02) e52
• 13 Canfield SM, Koopman RJ. Facilitators and barriers to integrating patient-generated blood pressure data into primary care EHR workflows. Appl Clin Inform 2024; 15 (05) 942-951
• 14 Dorr DA, Richardson JE, Bobo M. et al. Provider perspectives on patient-and provider-facing high blood pressure clinical decision support. Appl Clin Inform 2022; 13 (05) 1131-1140
• 15 Cohen DJ, Keller SR, Hayes GR, Dorr DA, Ash JS, Sittig DF. Integrating patient-generated health data into clinical care settings or clinical decision-making: lessons learned from project healthdesign. JMIR Hum Factors 2016; 3 (02) e26
• 16 Koirala T, Burger CD, Chaudhry R. et al. Impact of a disease-focused electronic health record dashboard on clinical staff efficiency in previsit patient review in an ambulatory pulmonary hypertension care clinic. Appl Clin Inform 2024; 15 (05) 928-938
• 17 Koopman RJ, Canfield SM, Belden JL. et al. Home blood pressure data visualization for the management of hypertension: designing for patient and physician information needs. BMC Med Inform Decis Mak 2020; 20 (01) 195
• 18 Campbell R. The five “rights” of clinical decision support. J AHIMA 2013; 84 (10) 42-47 , quiz 48
• 19 Moja L, Kwag KH, Lytras T. et al. Effectiveness of computerized decision support systems linked to electronic health records: a systematic review and meta-analysis. Am J Public Health 2014; 104 (12) e12-e22
• 20 Dorr DA, D'Autremont C, Pizzimenti C. et al. Assessing data adequacy for high blood pressure clinical decision support: a quantitative analysis. Appl Clin Inform 2021; 12 (04) 710-720
• 21 Damschroder LJ, Reardon CM, Opra Widerquist MA, Lowery J. Conceptualizing outcomes for use with the Consolidated Framework for Implementation Research (CFIR): the CFIR Outcomes Addendum. Implement Sci 2022; 17 (01) 7
• 22 Ghosh P, Canfield S, Dorr D. et al. Features facilitating patients' acceptance of Collaboration Oriented Application for Controlling High Blood Pressure (COACH). Ann Fam Med 2023; 21 (Suppl. 03) 4901
• 23 Archibald MM, Ambagtsheer RC, Casey MG, Lawless M. Using zoom videoconferencing for qualitative data collection: perceptions and experiences of researchers and participants. Int J Qual Methods 2019; 18: 1609406919874596
• 24 Saunders B, Sim J, Kingstone T. et al. Saturation in qualitative research: exploring its conceptualization and operationalization. Qual Quant 2018; 52 (04) 1893-1907
• 25 Dedoose. Version 8.0. Web application for managing, analyzing, and presenting qualitative and mixed method research data Los Angeles: SocioCultural Research Consultants, LLC. 2018;
• 26 Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci 2009; 4 (01) 50
• 27 CFIR Rating Rules. Accessed at: https://cfirguide.org/wp-content/uploads/2019/08/ratingrules10-29-14.pdf
• 28 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 (06) 349-357
• 29 Eyles H, Jull A, Dobson R. et al. Co-design of mHealth delivered interventions: a systematic review to assess key methods and processes. Curr Nutr Rep 2016; 5: 160-167
• 30 Stowell E, Lyson MC, Saksono H. et al. Designing and evaluating mHealth interventions for vulnerable populations: a systematic review. CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems Paper No.: 15, 2018:1–17
• 31 Persell SD, Petito LC, Anthony L. et al. Prospective cohort study of remote patient monitoring with and without care coordination for hypertension in primary care. Appl Clin Inform 2023; 14 (03) 428-438
• 32 Borges do Nascimento IJ, Abdulazeem H, Vasanthan LT. et al. Barriers and facilitators to utilizing digital health technologies by healthcare professionals. NPJ Digit Med 2023; 6 (01) 161
• 33 Pickering TG, Miller NH, Ogedegbe G, Krakoff LR, Artinian NT, Goff D. American Heart Association, American Society of Hypertension, Preventive Cardiovascular Nurses Association. Call to action on use and reimbursement for home blood pressure monitoring: a joint scientific statement from the American Heart Association, American Society Of Hypertension, and Preventive Cardiovascular Nurses Association. Hypertension 2008; 52 (01) 10-29
• 34 Whitelaw S, Pellegrini DM, Mamas MA, Cowie M, Van Spall HGC. Barriers and facilitators of the uptake of digital health technology in cardiovascular care: a systematic scoping review. Eur Heart J Digit Health 2021; 2 (01) 62-74
• 35 Kronish IM, Hughes C, Quispe K, Viera AJ. Implementing ambulatory blood pressure monitoring in primary care practice. Fam Pract Manag 2020; 27 (03) 19-25
• 36 Shimbo D, Artinian NT, Basile JN. et al; American Heart Association and the American Medical Association. Self-measured blood pressure monitoring at home: a joint policy statement from the American Heart Association and American Medical Association. Circulation 2020; 142 (04) e42-e63
• 37 Proia KK, Thota AB, Njie GJ. et al; Community Preventive Services Task Force. Team-based care and improved blood pressure control: a community guide systematic review. Am J Prev Med 2014; 47 (01) 86-99
• 38 Kim KK, McGrath SP, Solorza JL, Lindeman D. The ACTIVATE Digital Health Pilot Program for diabetes and hypertension in an underserved and rural community. Appl Clin Inform 2023; 14 (04) 644-653
• 39 Department of Health and Human Services. Think Cultural Health. Department of Health and Human Services. Accessed August 29, 2024 at: https://thinkculturalhealth.hhs.gov/clas/standards