Resumen
Introduction: Public health interventions seem to contribute to the improvement of the conditions of individual or communal health in real scenarios, however, the different evaluation models that currently exist are focused in getting to know their effectiveness, impact or results, leaving an empty space for the comprehension of what works within the intervention, for who and under what circumstances. In this way, it is necessary to use an evaluation model that allows to generate evidence regarding causal explanations and results associated to the activation of mechanisms in complex situations, both in the context and in the development. Objective: To adapt an evaluation model for complex interventions in public health, that incorporates the categories of the realistic evaluation of context, mechanism, and results in this type of interventions. Methodology: A qualitative exploratory study was done with a formal consensus, with a Nominal Group Technique (NGT), linking 15 technicians in public health and 10 experts in evaluation and evaluative investigation within 3 discussion workshops, following an iterative process of three participative encounters until reaching a consensus for the consolidation of the evaluation model in public health. Results: This evaluation model incorporates characteristics of the interventions of public health and integrates elements of context, mechanism, and results, to facilitate the comprehension of the effectiveness of an intervention identifying what works (or not), for who and under what circumstances. Conclusions: This adaptation of an evaluation model brings relevant information to make informed decisions from an evaluation of interventions in real contexts.
Referencias
Campbell M, Fitzpatrick R, Haines A, Kinmonth AL, Sandercock P, Spiegelhalter D, et al. Framework for design and evaluation of complex interventions to improve health. BMJ. 2000; 321: 6946. doi: https://doi.org/10.1136/bmj.321.7262.694
Maldonado C, Mendoza L, Mendieta Ramírez V, Cruz Olvera J, Ruvalcaba Ledezma J. La trascendencia de los determinantes sociales de la salud “Un análisis comparativo entre los modelos JONNPR. 2019; 4(11): 1051-1063. doi: 10.19230/jonnpr.3065
Tarride M. Hacia la constitución de una salud pública compleja. RCSP. 2005; 9: 169-174.
Cassetti Viola, Paredes-Carbonell JJ. La teoría del cambio: una herramienta para la planificación y la evaluación participativa en salud comunitaria. Gac Sanit [online]. 2020; 34(3): 305-307. doi: https://dx.doi.org/10.1016/j.gaceta.2019.06.002
Greenhalgh T, Plsek P, Wilson T, Fraser S, Holt T. Response to the appropriation of complexity theory in health care. J Health Serv Res Policy. 2010; 2: 115-117. doi: http://dx.doi.org/10.1258/jhsrp.2010.009158
Paley J. The appropriation of complexity theory in health care. J Health Serv Res Policy. 2010; 1: 59-61. doi: https://doi.org/10.1258/jhsrp.2009.009072
De Salazar L. Reflexiones y posiciones alrededor de la evaluación de intervenciones complejas: salud pública y promoción de la salud. Cali: Universidad del Valle; 2011. Disponible en: https://www2.congreso.gob.pe/sicr/cendocbib/con4_uibd.nsf/526C2BD3A550CC0805257CB600590276/$FILE/reflexiones_posiciones_alrededor_salud_publica.pdf
Tenbensel T. Complexity in health and health care systems. Soc Sci Med. 2013; 93: 181-184. doi: https://doi.org/10.1016/j.socscimed.2013.06.017
Martínez N, Díaz Z, Martínez Y, Chao M, Dandicourt C, Vera E, et al. Modelo de Enfermería Salubrista para las prácticas de cuidado interdisciplinar. Rev Cuba Enferm. 2020; 36(3): e3490.
Hernández AR, Hurtig AK, Dahlblom K, San Sebastián M. More than a checklist: a realist evaluation of supervision of mid-level health workers in rural Guatemala. BMC Health Serv Res. 2014; 14: 112. doi: https://doi.org/10.1186/1472-6963-14-112
Jagosh J, Bush PL, Salsberg J, Macaulay AC, Greenhalgh T, Wong G, et al. A realist evaluation of community-based participatory research: partnership synergy, trust building and related ripple effects. BMC Public Health. 2015; 15: 725 doi: https://doi.org/10.1186/s12889-015-1949-1
Tyler I, Pauly B, Wang J, Patterson T, Bourgeault I, Manson H. Evidence use in equity focused health impact assessment: a realist evaluation. BMC Public Health. 2019; 19: 230. doi: https://doi.org/10.1186/s12889-019-6534-6
Norris SL, Rehfuess EA, Smith H, Tunçalp Ö, Grimshaw JM, Ford NP, et al. Complex health interventions in complex systems: improving the process and methods for evidence-informed health decisions. BMJ Glob Health. 2019; doi: http://dx.doi.org/10.1136/bmjgh-2018-000963
García LM. Modelos evaluativos para intervenciones complejas en salud. Rev Salud Pública. 2021; 22: 1-7. doi: https://doi.org/10.15446/rsap.v22n4.77864
Skivington K, Matthews L, Simpson SA, Craig P, Baird J, Blazeby JM et al. A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance. BMJ. 2021; 374: 2061. doi: https://doi.org/10.1136/bmj.n2061
Fridrich A, Jenny GJ, Bauer GF. The context, process, and outcome evaluation model for organisational health interventions. Biomed Res Int. 2015; 2015: 414832. doi: https://doi.org/10.1155/2015/414832
Pawson R, Tilley N. What works in evaluation research? Br J Criminol. 1994; 34(3): 291–306. doi: https://doi.org/10.1093/oxfordjournals.bjc.a048424
Almeida G, Artaza O, Donoso N, Fábrega R. La atención primaria de salud en la Región de las Américas a 40 años de Alma-Ata. Rev Panam Salud Publica. 2018; 42: e104. doi: https://doi.org/10.26633/RPSP.2018.104
García LM. Efectividad de la estrategia “Salud al Campo” Enfoque de Evaluación Realista. Tesis Doctoral. Cali: Universidad del Valle; 2020.
Delbecq AL, Van de Ven AH. “A Group Process Model for Problem Identification and Program Planning”. J Applied Behav Sci. 1971; 7(4): 466-492. doi: https://doi.org/10.1177/002188637100700404
Olsen, J. The nominal group technique (NGT) as a tool for facilitating pan-disability focus groups and as a new method for quantifying changes in qualitative data. Int J Qual Methods. 2019; 18: 160940691986604. doi: https://doi.org/10.1177/1609406919866049
Hoffmann C, Glasziou P, Boutron I, Milne R, Perera R, Moher D et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ. 2014; 348: g1687. doi: https://doi.org/10.1136/bmj.g1687
Gilmore B. Realist evaluations in low- and middle-income countries: reflections and recommendations from the experiences of a foreign researcher. BMJ Glob Health. 2019; 4: e001638. doi: http://dx.doi.org/10.1136/bmjgh-2019-001638
Mark MM, Henry GT. Logic models and content analyses for the explication of evaluation theories: the case of emergent realist evaluation. Eval Program Plann. 2013; 38: 74-76. doi: https://doi.org/10.1016/j.evalprogplan.2012.03.018
Glasgow RE, Harden SM, Gaglio B, Rabin B, Smith ML, Porter GC, et al. RE-AIM Planning and Evaluation Framework: Adapting to New Science and Practice With a 20-Year Review. Front Public Health. 2019; 7: 64. doi: https://doi.org/10.3389/fpubh.2019.00064
Pawson R, Tilley N. An introduction to scientific realist evaluation. In: E Chelimsky, WR Shadish. Evaluation for the 21st century. SAGE Publications. A handbook. 1997; 405-418. doi: https://dx.doi.org/10.4135/9781483348896.n29
Rycroft-Malone J, Burton C, Wilkinson J, Harvey G, McCormack B, Baker R, et al. Collective action for knowledge mobilisation: a realist evaluation of the collaborations for leadership in applied health research and care. NIHR J Library. 2015. doi: https://doi.org/10.3310/hsdr03440
Soura BD, Fallu JS, Bastien R, Frédéric N, Brière. El estudio de la evaluabilidad. En: Ridde V, Dagenais C. Evaluación de las intervenciones sanitarias en salud global. Marseille: Éditions science et bien commun; 2020. Availaible from: https://scienceetbiencommun.pressbooks.pub/evalsalud/chapter/evaluabilidad/
Jagosh J. Retroductive theorizing in Pawson and Tilley’s applied scientific realism. JCR.2020; 9: 121-130. https://doi.org/10.1080/14767430.2020.1723301
Linsley P, Howard D, Owen S. The construction of context-mechanisms-outcomes in realistic evaluation. Nurse Res. 2015; 3: 28-34. doi: http://doi: 10.7748/nr.22.3.28.e1306
Westhorp G. Realist impact evaluation: an introduction. methods lab: overseas development Institute, the Australian department of foreign affairs and trade (DFAT) and Better Evaluation. London: Better Evaluation; 2014. Available from: https://www.betterevaluation.org/en/resources/realist-impact-evaluation-introduction
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; 337–655. doi: 10.1136/bmj.a1655
Moore GF, Evans RE. ¿What theory, for whom and in which context? Reflections on the application of theory in the development and evaluation of complex population health interventions. SSM-Salud de la población. 2017; 3: 132-135.
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. doi: 10.1136/bmj.h1258
Craig P, Dieppe P, Macintyre S, Health P, Unit S, Michie S, et al. Developing and evaluating complex interventions: new guidance. 2000. Available from: https://www.betterevaluation.org/sites/default/files/Complex_interventions_guidance.pdf
Gómez ARD, González ER. Evaluación de la prevención de la enfermedad y la promoción de la salud: factores que deben considerar Rev Fac Nac Salud Pública. 2004; 22(1): 87-106.
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Derechos de autor 2024 Mercy Soto-Chaquir, Lina María García-Zapata , Ana Milena Galarza-Iglesias, Liliana Cristina Morales-Viana