Addressing low-value pharmacological prescribing in primary prevention of CVD through a structured evidence-based and theory-informed process for the design and testing of de-implementation strategies: the DE-imFAR study

Alvaro Sanchez, Jose Ignacio Pijoan, Susana Pablo, Marta Mediavilla, Rita Sainz de Rozas, Itxasne Lekue, Susana Gonzalez-Larragan, Gaspar Lantaron, Jon Argote, Arturo García-Álvarez, Pedro Maria Latorre, Christian D Helfrich, Gonzalo Grandes, Alvaro Sanchez, Jose Ignacio Pijoan, Susana Pablo, Marta Mediavilla, Rita Sainz de Rozas, Itxasne Lekue, Susana Gonzalez-Larragan, Gaspar Lantaron, Jon Argote, Arturo García-Álvarez, Pedro Maria Latorre, Christian D Helfrich, Gonzalo Grandes

Abstract

Background: De-implementation or abandonment of ineffective or low-value healthcare is becoming a priority research field globally due to the growing empirical evidence of the high prevalence of such care and its impact in terms of patient safety and social inefficiency. Little is known, however, about the factors, barriers, and facilitators involved or about interventions that are effective in promoting and accelerating the de-implementation of low-value healthcare. The De-imFAR study seeks to carry out a structured, evidence-based, and theory-informed process involving the main stakeholders (clinicians, managers, patients, and researchers) for the design, deployment, and assessment of de-implementation strategies for reducing low-value pharmacological prescribing.

Methods: A phase I formative study using a systematic and comprehensive framework based on theory and evidence for the design of implementation strategies-specifically, the Behavior Change Wheel (BCW)-will be conducted to design and model de-implementation strategies to favor reductions in low-value pharmacological prescribing of statins in primary prevention of cardiovascular disease (CVD) by main stakeholders (clinicians, managers, patients, and researchers) in a collegiate way. Subsequently, a phase II comparative hybrid trial will be conducted to assess the feasibility and potential effectiveness of at least one active de-implementation strategy to reduce low-value pharmacological prescribing of statins in primary prevention of CVD compared to the usual procedures for dissemination of clinical practice guidelines ("what-not-to-do" recommendations). A mixed-methods evaluation will be used: quantitative for the results of the implementation at the professional level (e.g., adoption, reach and implementation or execution of the recommended clinical practice); and qualitative to determine the feasibility and perceived impact of the de-implementation strategies from the clinicians' perspective, and patients' experiences related to the clinical care received.

Discussion: The DE-imFAR study aims to generate valid scientific knowledge about the design and development of de-implementation strategies using theory- and evidence-based methodologies suggested by implementation science. It will explore the effectiveness of these strategies and their acceptability among clinicians, policymakers, and patients. Its ultimate goal is to maximize the quality and efficiency of our health system by abandoning low-value pharmacological prescribing.

Trial registration: Clinicaltrials.gov identifier: NCT04022850. Registered 17 July 2019.

Keywords: Cardiovascular disease prevention; De-implementation; Low-value care.

Conflict of interest statement

The authors declare that they have no competing interests.

References

    1. Committee on Quality of Health Care in America; Institute of Medicine . Crossing the quality chasm: a new health system for the 21st Century. Washington, DC: National Academy Press; 2001.
    1. Chassin MR, Galvin RW. The urgent need to improve health care quality. Institute of medicine national roundtable on health care quality. JAMA. 1998;280:1000–1005. doi: 10.1001/jama.280.11.1000.
    1. Niven DJ, Mrklas KJ, Holodinsky JK, Straus SE, Hemmelgarn BR, Jeffs LP, Stelfox HT. Towards understanding the de-adoption of low-value clinical practices: a scoping review. BMC Med. 2015;13:255. doi: 10.1186/s12916-015-0488-z.
    1. Morgan DJ, Dhruva SS, Wright SM, Korenstein D. 2016 Update on medical overuse: A systematic review. JAMA Intern Med. 2016;176(11):1687–1692. doi: 10.1001/jamainternmed.2016.5381.
    1. Morgan DJ, Dhruva SS, Coon ER, Wright SM, Korenstein D. 2017 Update on medical overuse: A systematic review. JAMA Intern Med. 2018;178(1):110–115. doi: 10.1001/jamainternmed.2017.4361.
    1. Scott IA. Cognitive challenges to minimising low value care. Intern Med J. 2017;47(9):1079–1083. doi: 10.1111/imj.13536.
    1. Morgan DJ, Brownlee S, Leppin AL, Kressin N, Dhruva SS, Levin L, Landon BE, Zezza MA, Schmidt H, Saini V, Elshaug AG. Setting a research agenda for medical overuse. BMJ. 2015;351:h4534. doi: 10.1136/bmj.h4534.
    1. Bokhof B, Junius-Walker U. Reducing polypharmacy from the perspectives of general practitioners and older patients: A synthesis of qualitative studies. Drugs Aging. 2016;33(4):249–266. doi: 10.1007/s40266-016-0354-5.
    1. Stryczek Krysttel, Lea Colby, Gillespie Chris, Sayre George, Wanner Scott, Rinne Seppo T., Wiener Renda Soylemez, Feemster Laura, Udris Edmunds, Au David H., Helfrich Christian D. De-implementing Inhaled Corticosteroids to Improve Care and Safety in COPD Treatment: Primary Care Providers’ Perspectives. Journal of General Internal Medicine. 2019;35(1):51–56. doi: 10.1007/s11606-019-05193-2.
    1. Colla CH, Mainor AJ, Hargreaves C, Sequist T, Morden N. Interventions aimed at reducing use of low-value health services: a systematic review. Med Care Res Rev. 2017;74(5):507–550. doi: 10.1177/1077558716656970.
    1. WHO . The World Health Report. Reducing risks, promoting healthy life. Geneva: WHO; 2002.
    1. Los lípidos como factor de riesgo cardiovascular: tratamiento farmacológico. INFAC 2014; 22 (7):1-7. Available at: (accessed October 2019)
    1. San Vicente Blanco R., Pérez Irazusta I., Ibarra Amarica J., Berraondo Zabalegui I., Uribe Oyarbide F., Urraca Garcia de Madinabeitia J., Samper Otxotorena R., Aizpurua Imaz I., Almagro Mugica F., Andrés Novales J., Ugarte Libano R. Guía de Práctica Clínica sobre el manejo de los lípidos como factor de riesgo cardiovascular. Osakidetza. Vitoria-Gasteiz.
    1. Byrne P, Cullinan J, Smith A, et al. Statins for the primary prevention of cardiovascular disease: an overview of systematic reviews. BMJ Open. 2019;9:e023085. doi: 10.1136/bmjopen-2018-023085.
    1. Thompson PD, Panza G, Zaleski A, Taylor B. Statin-associated side effects. J Am Coll Cardiol. 2016;67(20):2395–2410. doi: 10.1016/j.jacc.2016.02.071.
    1. Keller H, Krones T, Becker A, Hirsch O, Sönnichsen AC, Popert U, Kaufmann-Kolle P, Rochon J, Wegscheider K, Baum E, Donner-Banzhoff N. Arriba: effects of an educational intervention on prescribing behaviour in prevention of CVD in general practice. Eur J Prev Cardiol. 2012;19(3):322–329. doi: 10.1177/1741826711404502.
    1. Zillich AJ, Ackermann RT, Stump TE, Ambuehl RJ, Downs SM, Holmes AM, Katz B, Inui TS. An evaluation of educational outreach to improve evidence-based prescribing in Medicaid: a cautionary tale. J Eval Clin Pract. 2008;14(5):854–860. doi: 10.1111/j.1365-2753.2008.01035.x.
    1. Arcoraci V, Santoni L, Ferrara R, Furneri G, Cannata A, Sultana J, Moretti S, Di Luccio A, Tari DU, Pagliaro C, Corrao S, Tari M. Effect of an educational program in primary care: the case of lipid control in cardio-cerebrovascular prevention. Int J Immunopathol Pharmacol. 2014;27(3):351–363. doi: 10.1177/039463201402700305.
    1. Dormuth CR, Carney G, Taylor S, Bassett K, Maclure M. A randomized trial assessing the impact of a personal printed feedback portrait on statin prescribing in primary care. J Contin Educ Health Prof. 2012;32(3):153–162. doi: 10.1002/chp.21140.
    1. Harris MF, Parker SM, Litt J, van Driel M, Russell G, Mazza D, Jayasinghe UW, Del Mar C, Lloyd J, Smith J, Zwar N, Taylor R, Powell Davies G, Preventive Evidence into Practice Partnership Group Implementing guidelines to routinely prevent chronic vascular disease in primary care: the Preventive Evidence into Practice cluster randomised controlled trial. BMJ Open. 2015;5(12):e009397. doi: 10.1136/bmjopen-2015-009397.
    1. Liddy C, Hogg W, Singh J, Taljaard M, Russell G, Deri Armstrong C, Akbari A, Dahrouge S, Grimshaw JM. A real-world stepped wedge cluster randomized trial of practice facilitation to improve cardiovascular care. Implement Sci. 2015;10:150. doi: 10.1186/s13012-015-0341-y.
    1. Peiris D, Usherwood T, Panaretto K, Harris M, Hunt J, Redfern J, Zwar N, Colagiuri S, Hayman N, Lo S, Patel B, Lyford M, MacMahon S, Neal B, Sullivan D, Cass A, Jackson R, Patel A. Effect of a computer-guided, quality improvement program for cardiovascular disease risk management in primary health care: the treatment of cardiovascular risk using electronic decision support cluster-randomized trial. Circ Cardiovasc Qual Outcomes. 2015;8(1):87–95. doi: 10.1161/CIRCOUTCOMES.114.001235.
    1. Bertoni AG, Bonds DE, Chen H, Hogan P, Crago L, Rosenberger E, Barham AH, Clinch CR, Goff DC., Jr Impact of a multifaceted intervention on cholesterol management in primary care practices: guideline adherence for heart health randomized trial. Arch Intern Med. 2009;169(7):678–686. doi: 10.1001/archinternmed.2009.44.
    1. Hasson H, Nilsen P, Augustsson H, von Thiele Schwarz U. Empirical and conceptual investigation of de-implementation of low-value care from professional and health care system perspectives: a study protocol. Implement Sci. 2018;13(1):67. doi: 10.1186/s13012-018-0760-7.
    1. Grimshaw JM, Thomas RE, MacLennan G, et al. Effectiveness and efficiency of guideline dissemination and implementation strategies. Health Technol Assess. 2004;8(6):iii–iiv. doi: 10.3310/hta8060.
    1. Durlak JA, DuPre EP. Implementation matters: a review of research on the influence of implementation on program outcomes and the factors affecting implementation. Am J Community Psychol. 2008;41(3-4):327–350. doi: 10.1007/s10464-008-9165-0.
    1. Flottorp SA, Oxman AD, Krause J, Musila NR, Wensing M, Godycki-Cwirko M, Baker R, Eccles MP. A checklist for identifying determinants of practice: a systematic review and synthesis of frameworks and taxonomies of factors that prevent or enable improvements in healthcare professional practice. Implement Sci. 2013;8:35. doi: 10.1186/1748-5908-8-35.
    1. Powell BJ, McMillen JC, Proctor EK, Carpenter CR, Griffey RT, Bunger AC, Glass JE, York JL. A compilation of strategies for implementing clinical innovations in health and mental health. Med Care Res Rev. 2012;69(2):123–157. doi: 10.1177/1077558711430690.
    1. Coombs CR, Hislop D, Holland J, Bosley SLC, Manful E. Exploring types of individual unlearning by local health-care managers: an original empirical approach. Southampton: NIHR Journals Library; 2013.
    1. Helfrich CD, Rose AJ, Hartmann CW, van Bodegom-Vos L, Graham ID, Wood SJ, Majerczyk BR, Good CB, Pogach LM, Ball SL, Au DH, Aron DC. How the dual process model of human cognition can inform efforts to de-implement ineffective and harmful clinical practices: A preliminary model of unlearning and substitution. J Eval Clin Pract. 2018; [Epub ahead of print] PubMed PMID: 29314508.
    1. Ubel PA, Asch DA. Creating value in health by understanding and overcoming resistance to de-innovation. Health Aff (Millwood). 2015;34(2):239–244. doi: 10.1377/hlthaff.2014.0983.
    1. Nilsen P, Roback K, Broström A, Ellström PE. Creatures of habit: accounting for the role of habit in implementation research on clinical behaviour change. Implement Sci. 2012;7(1):53. doi: 10.1186/1748-5908-7-53.
    1. Presseau J, Johnston M, Heponiemi T, Elovainio M, Francis JJ, Eccles MP, Steen N, Hrisos S, Stamp E, Grimshaw JM, Hawthorne G. Reflective and automatic processes in health care professional behaviour: a dual process model tested across multiple behaviours. Ann Behav Med. 2014;48(3):347–358. doi: 10.1007/s12160-014-9609-8.
    1. Wang V, Maciejewski ML, Helfrich CD, Weiner BJ. Working smarter not harder: Coupling implementation to de-implementation. Healthc (Amst). 2018;6(2):104–107. doi: 10.1016/j.hjdsi.2017.12.004.
    1. Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. 2011;6:42. doi: 10.1186/1748-5908-6-42.
    1. Michie S, Richardson M, Johnston M, et al. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013;46:81–95. doi: 10.1007/s12160-013-9486-6.
    1. Atkins L, Francis J, Islam R, et al. A guide to using the Theoretical Domains Framework of behaviour change investigate implementation problems. Implement Sci. 2017;12:77. doi: 10.1186/s13012-017-0605-9.
    1. Birken SA, Powell BJ, Presseau J, et al. Combined use of the Consolidated Framework for Implementation Research (CFIR) and the Theoretical Domains Framework (TDF): a systematic review. Implement Sci. 2017;12:2. doi: 10.1186/s13012-016-0534-z.
    1. 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;4:50. doi: 10.1186/1748-5908-4-50.
    1. Waltz TJ, Powell BJ, Fernández ME, Abadie B, Damschroder LJ. Choosing implementation strategies to address contextual barriers: diversity in recommendations and future directions. Implement Sci. 2019;14(1):42. doi: 10.1186/s13012-019-0892-4.
    1. Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999;89(9):1322–1327. doi: 10.2105/AJPH.89.9.1322.
    1. López-de-Munain J, Torcal J, López V, Garay J. Prevention in routine general practice: activity patterns and potential promoting factors. Prev Med. 2001;32(1):13–22. doi: 10.1006/pmed.2000.0777.
    1. Bully P, Sanchez A, Grandes G, Pombo H, Arietalenizbeaskoa MS, Arce V, Martinez C, PVS Group Metric properties of the “prescribe healthy life” screening questionnaire to detect healthy behaviors: a cross-sectional pilot study. BMC Public Health. 2016;16(1):1228. doi: 10.1186/s12889-016-3898-8.

Source: PubMed

3
Tilaa