Optimizing the development and evaluation of complex interventions: lessons learned from the BetterBirth Program and associated trial

Dale A Barnhart, Katherine E A Semrau, Corwin M Zigler, Rose L Molina, Megan Marx Delaney, Lisa R Hirschhorn, Donna Spiegelman, Dale A Barnhart, Katherine E A Semrau, Corwin M Zigler, Rose L Molina, Megan Marx Delaney, Lisa R Hirschhorn, Donna Spiegelman

Abstract

Background: Despite extensive efforts to develop and refine intervention packages, complex interventions often fail to produce the desired health impacts in full-scale evaluations. A recent example of this phenomenon is BetterBirth, a complex intervention designed to implement the World Health Organization's Safe Childbirth Checklist and improve maternal and neonatal health. Using data from the BetterBirth Program and its associated trial as a case study, we identified lessons to assist in the development and evaluation of future complex interventions.

Methods: BetterBirth was refined across three sequential development phases prior to being tested in a matched-pair, cluster randomized trial in Uttar Pradesh, India. We reviewed published and internal materials from all three development phases to identify barriers hindering the identification of an optimal intervention package and identified corresponding lessons learned. For each lesson, we describe its importance and provide an example motivated by the BetterBirth Program's development to illustrate how it could be applied to future studies.

Results: We identified three lessons: (1) develop a robust theory of change (TOC); (2) define optimization outcomes, which are used to assess the effectiveness of the intervention across development phases, and corresponding criteria for success, which determine whether the intervention has been sufficiently optimized to warrant full-scale evaluation; and (3) create and capture variation in the implementation intensity of components. When applying these lessons to the BetterBirth intervention, we demonstrate how a TOC could have promoted more complete data collection. We propose an optimization outcome and related criteria for success and illustrate how they could have resulted in additional development phases prior to the full-scale trial. Finally, we show how variation in components' implementation intensities could have been used to identify effective intervention components.

Conclusion: These lessons learned can be applied during both early and advanced stages of complex intervention development and evaluation. By using examples from a real-world study to demonstrate the relevance of these lessons and illustrating how they can be applied in practice, we hope to encourage future researchers to collect and analyze data in a way that promotes more effective complex intervention development and evaluation.

Trial registration: ClinicalTrials.gov, NCT02148952; registered on May 29, 2014.

Keywords: Childbirth; Complex intervention; India; Intervention development; WHO Safe Childbirth Checklist.

Conflict of interest statement

Competing interestsThe authors declare that they have no competing interests.

© The Author(s) 2020.

Figures

Fig. 1
Fig. 1
Implementation strategies and theories of change used during the development of the BetterBirth intervention
Fig. 2
Fig. 2
Robust theory of change for the BetterBirth intervention
Fig. 3
Fig. 3
Dose-response relationship between coaching intensity and EBP adherence

References

    1. Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M, et al. Developing and evaluating complex interventions: the new Medical Research Council guidance. BMJ. 2008;337:a1655.
    1. Moore GF, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, et al. Process evaluation of complex interventions: Medical Research Council guidance. BMJ. 2015;350:h1258.
    1. Proctor EK, Powell BJ, McMillen JC. Implementation strategies: recommendations for specifying and reporting. Implement Sci. 2013;8:139.
    1. Cori A, Ayles H, Beyers N, Schaap A, Floyd S, Sabapathy K, et al. HPTN 071 (PopART): a cluster-randomized trial of the population impact of an HIV combination prevention intervention including universal testing and treatment: mathematical model. PLoS One. 2014;9(1):e84511.
    1. Piper ME, Cook JW, Schlam TR, Jorenby DE, Smith SS, Collins LM, et al. A randomized controlled trial of an optimized smoking treatment delivered in primary care. Ann Behav Med. 2018;52:854–864.
    1. Lloyd J, Creanor S, Logan S, Green C, Dean SG, Hillsdon M, et al. Effectiveness of the Healthy Lifestyles Programme (HeLP) to prevent obesity in UK primary-school children: a cluster randomised controlled trial. Lancet Child Adolescent Health. 2018;2(1):35–45.
    1. Collins LM, Nahum-Shani I, Almirall D. Optimization of behavioral dynamic treatment regimens based on the sequential, multiple assignment, randomized trial (SMART) Clin Trials. 2014;11(4):426–434.
    1. Collins LM, Dziak JJ, Kugler KC, Trail JB. Factorial experiments: efficient tools for evaluation of intervention components. Am J Prev Med. 2014;47(4):498–504.
    1. Dziak JJ, Nahum-Shani I, Collins LM. Multilevel factorial experiments for developing behavioral interventions: power, sample size, and resource considerations. Psychol Methods. 2012;17(2):153–175.
    1. Collins LM, Chakraborty B, Murphy SA, Strecher V. Comparison of a phased experimental approach and a single randomized clinical trial for developing multicomponent behavioral interventions. Clin Trials. 2009;6(1):5–15.
    1. Nevo D, Lok J, Spiegelman D. Analysis of “Learn-As-You-Go” (LAGO) studies. 2019. Preprint available at .
    1. Kingston B, Bacallao M, Smokowski P, Sullivan T, Sutherland K. Constructing “packages” of evidence-based programs to prevent youth violence: processes and illustrative examples from the CDC’s youth violence prevention centers. J Prim Prev. 2016;37(2):141–163.
    1. Pettifor A, Nguyen NL, Celum C, Cowan FM, Go V, Hightow-Weidman L. Tailored combination prevention packages and PrEP for young key populations. J Int AIDS Soc. 2015;18(2 Suppl 1):19434.
    1. Grant A, Dreischulte T, Guthrie B. Process evaluation of the data-driven quality improvement in primary care (DQIP) trial: active and less active ingredients of a multi-component complex intervention to reduce high-risk primary care prescribing. Implement Sci. 2017;12(1):4.
    1. Winder R, Richards SH, Campbell JL, Richards DA, Dickens C, Gandhi M, et al. Development and refinement of a complex intervention within cardiac rehabilitation services: experiences from the CADENCE feasibility study. Pilot Feasibility Stud. 2017;3:9.
    1. Shojania KG. Conventional evaluations of improvement interventions: more trials or just more tribulations? BMJ Qual Saf. 2013;22(11):881–884.
    1. Hirschhorn LR, Semrau K, Kodkany B, Churchill R, Kapoor A, Spector J, et al. Learning before leaping: integration of an adaptive study design process prior to initiation of BetterBirth, a large-scale randomized controlled trial in Uttar Pradesh, India. Implement Sci. 2015;10:117.
    1. Semrau KEA, Hirschhorn LR, Marx Delaney M, Singh VP, Saurastri R, Sharma N, et al. Outcomes of a coaching-based WHO Safe Childbirth Checklist program in India. N Engl J Med. 2017;377(24):2313–24.
    1. Spector JM, Lashoher A, Agrawal P, Lemer C, Dziekan G, Bahl R, et al. Designing the WHO Safe Childbirth Checklist program to improve quality of care at childbirth. Int J Gynaecol Obstet. 2013;122(2):164–168.
    1. Haynes AB, Berry WR, Gawande AA. What do we know about the safe surgery checklist now? Ann Surg. 2015;261(5):829–830.
    1. Haynes AB, Weiser TG, Berry WR, Lipsitz SR, Breizat AH, Dellinger EP, et al. A surgical safety checklist to reduce morbidity and mortality in a global population. N Engl J Med. 2009;360(5):491–499.
    1. Spector JM, Agrawal P, Kodkany B, Lipsitz S, Lashoher A, Dziekan G, et al. Improving quality of care for maternal and newborn health: prospective pilot study of the WHO safe childbirth checklist program. PLoS One. 2012;7(5):e35151.
    1. Semrau KEA, Hirschhorn LR, Kodkany B, Spector JM, Tuller DE, King G, et al. Effectiveness of the WHO Safe Childbirth Checklist program in reducing severe maternal, fetal, and newborn harm in Uttar Pradesh, India: study protocol for a matched-pair, cluster-randomized controlled trial. Trials. 2016;17(1):576.
    1. Fitzmaurice G, Laird N, Ware J. Applied longitudinal analysis. 2. Hoboken: Wiley; 2011.
    1. Weiss CH. Nothing as practical as good theory: exploring theory-based evaluation for comprehensive community initiatives for children and families. In: Connell J, Kubisch A, Schorr L, Weiss C, editors. New approaches to evaluating community initiatives: concepts, methods, and contexts. Washington DC: Aspen Institute; 1995. pp. 65–92.
    1. De Silva MJ, Breuer E, Lee L, Asher L, Chowdhary N, Lund C, et al. Theory of change: a theory-driven approach to enhance the Medical Research Council’s framework for complex interventions. Trials. 2014;15:267.
    1. Breuer E, Lee L, De Silva M, Lund C. Using theory of change to design and evaluate public health interventions: a systematic review. Implement Sci. 2016;11:63.
    1. Liang L, Bernhardsson S, Vernooij RW, Armstrong MJ, Bussieres A, Brouwers MC, et al. Use of theory to plan or evaluate guideline implementation among physicians: a scoping review. Implement Sci. 2017;12(1):26.
    1. Ajzen Icek. The theory of planned behavior. Organizational Behavior and Human Decision Processes. 1991;50(2):179–211.
    1. Atkins L, Francis J, Islam R, O’Connor D, Patey A, Ivers N, et al. A guide to using the Theoretical Domains Framework of behaviour change to investigate implementation problems. Implement Sci. 2017;12(1):77.
    1. Hallinan CM. Program logic: a framework for health program design and evaluation - the Pap nurse in general practice program. Aust J Prim Health. 2010;16(4):319–325.
    1. Tremblay MC, Brousselle A, Richard L, Beaudet N. Defining, illustrating and reflecting on logic analysis with an example from a professional development program. Eval Program Plann. 2013;40:64–73.
    1. Mackenzie M, Blamey A. The practice and the theory. Evaluation. 2016;11(2):151–168.
    1. Chandani Y, Noel M, Pomeroy A, Andersson S, Pahl MK, Williams T. Factors affecting availability of essential medicines among community health workers in Ethiopia, Malawi, and Rwanda: solving the last mile puzzle. Am J Trop Med Hyg. 2012;87(5 Suppl):120–126.
    1. de Wit EE, Adithy CC, JFG B-A, Regeer BJ. Learning about parenting together: a programme to support parents with inter-generational concerns in Pune, India. Contemp Fam Ther. 2018;40(1):68–83.
    1. Victora CG, Black RE, Boerma JT, Bryce J. Measuring impact in the Millennium Development Goal era and beyond: a new approach to large-scale effectiveness evaluations. Lancet. 2011;377(9759):85–95.
    1. Gooding K, Makwinja R, Nyirenda D, Vincent R, Sambakunsi R. Using theories of change to design monitoring and evaluation of community engagement in research: experiences from a research institute in Malawi. Wellcome Open Res. 2018;3:8.
    1. Gilissen J, Pivodic L, Gastmans C, Vander Stichele R, Deliens L, Breuer E, et al. How to achieve the desired outcomes of advance care planning in nursing homes: a theory of change. BMC Geriatr. 2018;18(1):47.
    1. Pronovost PJ, Berenholtz SM, Needham DM. Translating evidence into practice: a model for large scale knowledge translation. BMJ. 2008;337:a1714.
    1. Molina RL, Bobay L, Semrau KEA. Historical perspectives: lessons from the BetterBirth trial: a practical roadmap for complex intervention studies. NeoReviews. 2019;20(2):e62–ee6.
    1. Breuer E, De Silva MJ, Fekadu A, Luitel NP, Murhar V, Nakku J, et al. Using workshops to develop theories of change in five low and middle income countries: lessons from the programme for improving mental health care (PRIME) Int J Ment Health Syst. 2014;8:15.
    1. Sullivan H, Stewart M. Who owns the theory of change? Evaluation. 2016;12(2):179–199.
    1. Goldenberg RL, McClure EM. Improving birth outcomes in low- and middle-income countries. N Engl J Med. 2017;377(24):2387–2388.
    1. Molina RL, Neal BJ, Bobanski L, Singh VP, Neville BA, Delaney MM, et al. Nurses’ and auxiliary nurse midwives’ adherence to essential birth practices with peer coaching in Uttar Pradesh, India: a secondary analysis of the BetterBirth trial. Implement Sci. 2020;15(1):1.
    1. Thabane L, Ma J, Chu R, Cheng J, Ismaila A, Rios LP, et al. A tutorial on pilot studies: the what, why and how. BMC Med Res Methodol. 2010;10:1.
    1. Lee EC, Whitehead AL, Jacques RM, Julious SA. The statistical interpretation of pilot trials: should significance thresholds be reconsidered? BMC Med Res Methodol. 2014;14:41.
    1. Prentice RL. Surrogate endpoints in clinical trials: definition and operational criteria. Stat Med. 1989;8(4):431–440.
    1. Vanderweele TJ. Surrogate measures and consistent surrogates. Biometrics. 2013;69(3):561–569.
    1. Chen H, Geng Z, Jia J. Criteria for surrogate end points. J R Stat Soc Series B Stat Methodology. 2007;69(5):919–932.
    1. Ciani O, Buyse M, Garside R, Pavey T, Stein K, Sterne JA, et al. Comparison of treatment effect sizes associated with surrogate and final patient relevant outcomes in randomised controlled trials: meta-epidemiological study. BMJ. 2013;346:f457.
    1. Fleming TR, DeMets DL. Surrogate end points in clinical trials: are we being misled? Ann Intern Med. 1996;125(7):605.
    1. Packer M, Pitt B, Rouleau JL, Swedberg K, DeMets DL, Fisher L. Long-term effects of flosequinan on the morbidity and mortality of patients with severe chronic heart failure: primary results of the PROFILE trial after 24 years. JACC Heart Fail. 2017;5(6):399–407.
    1. Concorde Coordinating Committee Preliminary analysis of the Concorde trial. Lancet. 1993;341:889–890.
    1. Packer M, Carver JR, Rodeheffer RJ, Ivanhoe RJ, DiBianco R, Zeldis SM, et al. Effect of oral milrinone on mortality in severe chronic heart failure. The PROMISE Study Research Group. N Engl J Med. 1991;325(21):1468–1475.
    1. Ensor H, Lee RJ, Sudlow C, Weir CJ. Statistical approaches for evaluating surrogate outcomes in clinical trials: a systematic review. J Biopharm Stat. 2016;26(5):859–879.
    1. Chuang-Stein C, Kirby S, Hirsch I, Atkinson G. The role of the minimum clinically important difference and its impact on designing a trial. Pharm Stat. 2011;10(3):250–256.
    1. Arnold DM, Burns KE, Adhikari NK, Kho ME, Meade MO, Cook DJ, et al. The design and interpretation of pilot trials in clinical research in critical care. Crit Care Med. 2009;37(1 Suppl):S69–S74.
    1. Semrau KEA, Miller K, Lipsitz S, Fisher-Bowman J, Karlage A, Neville BA, et al. Association of adherence to essential birth practices and perinatal mortality in Uttar Pradesh, India. Oral presentation (Number 766) Rio de Janeiro: Federation of International Gynecologists & Obstetricians (FIGO) 22nd World Congress; 2018.
    1. Hargreaves JR, Goodman C, Davey C, Willey BA, Avan BI, Schellenberg JR. Measuring implementation strength: lessons from the evaluation of public health strategies in low- and middle-income settings. Health Policy Plan. 2016;31(7):860–867.
    1. Warren SF, Fey ME, Yoder PJ. Differential treatment intensity research: a missing link to creating optimally effective communication interventions. Ment Retard Dev Disabil Res Rev. 2007;13(1):70–77.
    1. Fletcher A, Jamal F, Moore G, Evans RE, Murphy S, Bonell C. Realist complex intervention science: applying realist principles across all phases of the Medical Research Council framework for developing and evaluating complex interventions. Evaluation (Lond) 2016;22(3):286–303.
    1. Hemming K, Haines TP, Chilton PJ, Girling AJ, Lilford RJ. The stepped wedge cluster randomised trial: rationale, design, analysis, and reporting. BMJ. 2015;350:h391.
    1. Nelson MC, Cordray DS, Hulleman CS, Darrow CL, Sommer EC. A procedure for assessing intervention fidelity in experiments testing educational and behavioral interventions. J Behav Health Serv Res. 2012;39(4):374–396.
    1. Carroll C, Patterson M, Wood S, Booth A, Rick J, Balain S. A conceptual framework for implementation fidelity. Implement Sci. 2007;2:40.
    1. Hasson H. Systematic evaluation of implementation fidelity of complex interventions in health and social care. Implement Sci. 2010;5:67.
    1. Breitenstein SM, Gross D, Garvey CA, Hill C, Fogg L, Resnick B. Implementation fidelity in community-based interventions. Res Nurs Health. 2010;33(2):164–173.
    1. Greenland S. Randomization, statistics, and causal inference. Epidemiology. 1990;1(6):421–429.
    1. Greenland S, Robins JM. Identifiability, exchangeability, and epidemiological confounding. Int J Epidemiol. 1986;15(3):413–419.
    1. Spiegelman D, Zhou X. Evaluating public health interventions: 8. Causal inference for time-invariant interventions. Am J Public Health. 2018;108:e1–e4.
    1. Piper ME, Fiore MC, Smith SS, Fraser D, Bolt DM, Collins LM, et al. Identifying effective intervention components for smoking cessation: a factorial screening experiment. Addiction. 2016;111(1):129–141.
    1. Hermens RP, Hak E, Hulscher ME, Braspenning JC, Grol RP. Adherence to guidelines on cervical cancer screening in general practice: programme elements of successful implementation. Br J Gen Pract. 2001;51(472):897–903.
    1. Pellecchia M, Connell JE, Beidas RS, Xie M, Marcus SC, Mandell DS. Dismantling the active ingredients of an intervention for children with autism. J Autism Dev Disord. 2015;45(9):2917–2927.
    1. Abry T, Hulleman CS, Rimm-Kaufman SE. Using indices of fidelity to intervention core components to identify program active ingredients. Am J Eval. 2015;36(3):320–338.
    1. Abry T, Rimm-Kaufman SE, Curby TW. Are all program elements created equal? Relations between specific social and emotional learning components and teacher-student classroom interaction quality. Prev Sci. 2017;18(2):193–203.
    1. Bernet AC, Willens DE, Bauer MS. Effectiveness-implementation hybrid designs: implications for quality improvement science. Implement Sci. 2013;8(Suppl 1):S2.
    1. Prins A, Oulmette P, Kimerling R, Cameron RP, Hugelshofer DS, Shaw-Hegwer J, et al. The primary care PTSD screen (PD-PTSD): development and operating characteristics. Prim Care Psychiatry. 2003;9(1):9–14.
    1. Kabongo L, Gass J, Kivondo B, Kara N, Semrau K, Hirschhorn LR. Implementing the WHO Safe Childbirth Checklist: lessons learnt on a quality improvement initiative to improve mother and newborn care at Gobabis District Hospital, Namibia. BMJ Open Qual. 2017;6(2):e000145.
    1. Varghese B, Copas A, Kumari S, Bandyopadhyay S, Sharma J, Saha S, et al. Does the safe childbirth checklist (SCC) program save newborn lives? Evidence from a realistic quasi-experimental study, Rajasthan, India. Matern Health Neonatol Perinatol. 2019;5:3.
    1. Kumar S, Yadav V, Balasubramaniam S, Jain Y, Joshi CS, Saran K, et al. Effectiveness of the WHO SCC on improving adherence to essential practices during childbirth, in resource constrained settings. BMC Pregnancy Childbirth. 2016;16(1):345.
    1. Nababan HY, Islam R, Mostari S, Tariqujjaman M, Sarker M, Islam MT, et al. Improving quality of care for maternal and newborn health: a pre-post evaluation of the Safe Childbirth Checklist at a hospital in Bangladesh. BMC Pregnancy Childbirth. 2017;17(1):402.
    1. Tuyishime E, Park PH, Rouleau D, Livingston P, Banguti PR, Wong R. Implementing the World Health Organization safe childbirth checklist in a district Hospital in Rwanda: a pre- and post-intervention study. Matern Health Neonatol Perinatol. 2018;4:7.
    1. Molina RL, Villar J, Reyes A, Elliott J, Begley M, Johnson M, et al. Delivery practices and care experience during implementation of an adapted safe childbirth checklist and respectful care program in Chiapas, Mexico. Int J Gynaecol Obstet. 2019;145(1):101–109.
    1. Marx Delaney M, Miller KA, Bobanski L, Singh S, Kumar V, Karlage A, et al. Unpacking the null: a post-hoc analysis of a cluster-randomised controlled trial of the WHO Safe Childbirth Checklist in Uttar Pradesh, India (BetterBirth) Lancet Glob Health. 2019;7(8):e1088–e1e96.
    1. Werdenberg J, Biziyaremye F, Nyishime M, Nahimana E, Mutaganzwa C, Tugizimana D, et al. Successful implementation of a combined learning collaborative and mentoring intervention to improve neonatal quality of care in rural Rwanda. BMC Health Serv Res. 2018;18(1):941.
    1. Semrau KEA, Herlihy J, Grogan C, Musokotwane K, Yeboah-Antwi K, Mbewe R, et al. Effectiveness of 4% chlorhexidine umbilical cord care on neonatal mortality in Southern Province, Zambia (ZamCAT): a cluster-randomised controlled trial. Lancet Glob Health. 2016;4(11):e827–ee36.
    1. Wyatt KM, Lloyd JJ, Creanor S, Logan S. The development, feasibility and acceptability of a school-based obesity prevention programme: results from three phases of piloting. BMJ Open. 2011;1(1):e000026.
    1. Richards SH, Dickens C, Anderson R, Richards DA, Taylor RS, Ukoumunne OC, et al. Assessing the effectiveness of Enhanced Psychological Care for patients with depressive symptoms attending cardiac rehabilitation compared with treatment as usual (CADENCE): a pilot cluster randomised controlled trial. Trials. 2018;19(1):211.

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