Interpretation of guidance on the use of complex systems models for economic evaluations of public health interventions_Chinese Journal of Evidence-Based Medicine

Authors：

WANG Ziyi ^1,2,3 , LU Cuncun ⁴ , LIU Wendi ^1,2,3 , LIANG Shanshan ^1,2,3 , CUI Lu ^1,2,3 , SHANG Wenru ^1,2,3 , HU Xiaoye ^1,2,3 , WANG Zhifei ⁴ ,  LI Xiuxia ^1,2,3 ,  YANG Kehu ^2,3

1. Evidence Based Social Science Research Center/Health Technology Assessment Center, School of Public Health, Lanzhou University, Lanzhou 730000, P. R. China;
2. Evidence Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, P. R. China;
3. Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou University, Lanzhou 730000, P. R. China;
4. Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, P. R. China;

Corresponding author：

LI Xiuxia, Email: lixiuxia@lzu.edu.cn; YANG Kehu, Email: yangkh-ebm@lzu.edu.cn

Keywords：

Complex systems; Economic evaluation; Public health; Guideline

DOI：

10.7507/1672-2531.202305113

Video：

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In response to the need for health economics modelers to apply more appropriate complex systems models to address complex challenges in public health, an international team of more than 40 experts in the field of complex systems models and economic evaluation has developed and recently published a guideline on the application of complex systems models to the economic evaluation of public health interventions. This paper introduces the development process and main content of the guidelines, which can provide references to facilitate the application of the guidelines by domestic researchers, aiming to ultimately improve the overall quality of public health research and services and improve the health of the population in China.

Citation： WANG Ziyi, LU Cuncun, LIU Wendi, LIANG Shanshan, CUI Lu, SHANG Wenru, HU Xiaoye, WANG Zhifei, LI Xiuxia, YANG Kehu. Interpretation of guidance on the use of complex systems models for economic evaluations of public health interventions. Chinese Journal of Evidence-Based Medicine, 2023, 23(12): 1365-1372. doi: 10.7507/1672-2531.202305113 Copy

1.	Meier P, Purshouse R, Bain M, et al. The SIPHER Consortium: introducing the new UK hub for systems science in public health and health economic research. Wellcome Open Res, 2019, 4: 174.
2.	赵燕利, 李莹莹, 李秋芳, 等. 复杂干预的开发与评价: 2021年英国医学研究委员会框架更新解读. 中国循证医学杂志, 2023, 23(2): 125-32.
3.	Skivington K, Matthews L, Simpson SA, et al. A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance. BMJ, 2021, 374: n2061.
4.	Squires H, Boyd K. The use of modelling approaches for the economic evaluation of public health interventions. Oxford: Oxford Academic, 2019.
5.	毕兆峰, 李亚飞, 卫飞雪, 等. 人乳头瘤病毒疫苗建模与经济学评估快速界面模型介绍及中国实例分析. 中华预防医学杂志, 2019, 53(7): 744-751.
6.	沈月红, 郭晓君, 仲亚琴. 主体建模在慢性非传染性疾病及健康行为研究中的应用. 中国卫生统计, 2021, 38(4): 628-630, 635.
7.	Breeze PR, Squires H, Ennis K, et al. Guidance on the use of complex systems models for economic evaluations of public health interventions. Health Econ, 2023, 32(7): 1603-1625.
8.	Shiell A, Hawe P, Gold L. Complex interventions or complex systems. Implications for health economic evaluation. BMJ, 2008, 336(7656): 1281-1283.
9.	Brailsford SC, Harper PR, Sykes J. Incorporating human behaviour in simulation models of screening for breast cancer. Eur J Oper Res, 2012, 219(3): 491-507.
10.	Dodd PJ, Garnett GP, Hallett TB. Examining the promise of HIV elimination by 'test and treat' in hyperendemic settings. AIDS, 2010, 24(5): 729-735.
11.	Keogh-Brown MR, Jensen HT, Basu S, et al. Evidence on the magnitude of the economic, health and population effects of palm cooking oil consumption: an integrated modelling approach with Thailand as a case study. Popul Health Metr, 2019, 17(1): 12.
12.	Occhipinti JA, Skinner A, Iorfino F, et al. Reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants. BMC Med, 2021, 19(1): 61.
13.	Probst C, Vu TM, Epstein JM, et al. The normative underpinnings of population-level alcohol use: an individual-level simulation model. Health Educ Behav, 2020, 47(2): 224-234.
14.	Stankov I, Yang Y, Langellier BA, et al. Depression and alcohol misuse among older adults: exploring mechanisms and policy impacts using agent-based modelling. Soc Psychiatry Psychiatr Epidemiol, 2019, 54(10): 1243-1253.
15.	Tobias MI, Cavana RY, Bloomfield A. Application of a system dynamics model to inform investment in smoking cessation services in New Zealand. Am J Public Health, 2010, 100(7): 1274-1281.
16.	Viana J, Brailsford SC, Harindra V, et al. Combining discrete-event simulation and system dynamics in a healthcare setting: a composite model for Chlamydia infection. Eur J Oper Res, 2014, 237(1): 196-206.
17.	Whitty CJ. What makes an academic paper useful for health policy. BMC Med, 2015, 13: 301.
18.	Basu S, Andrews J. Complexity in mathematical models of public health policies: a guide for consumers of models. PLoS Med, 2013, 10(10): e1001540.
19.	Jin H, Robinson S, Shang W, et al. Overview and use of tools for selecting modelling techniques in health economic studies. Pharmacoeconomics, 2021, 39(7): 757-770.
20.	Morshed AB, Kasman M, Heuberger B, et al. A systematic review of system dynamics and agent-based obesity models: evaluating obesity as part of the global syndemic. Obes Rev, 2019, 20 (Suppl 2): 161-178.
21.	Mykoniatis K, Angelopoulou A. A modeling framework for the application of multi-paradigm simulation methods. Simulation, 2019, 96(1): 55-73.
22.	Brailsford SC, Eldabi T, Kunc M, et al. Hybrid simulation modelling in operational research: a state-of-the-art review. Eur J Oper Res, 2019, 278(3): 721-737.
23.	Freebairn L, Atkinson JA, Qin Y, et al. 'Turning the tide' on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling. BMJ Open Diabetes Res Care, 2020, 8(1): e000975.
24.	Squires H, Chilcott J, Akehurst R, et al. A framework for developing the structure of public health economic models. Value Health, 2016, 19(5): 588-601.
25.	Freebairn L, Atkinson JA, Kelly PM, et al. Decision makers' experience of participatory dynamic simulation modelling: methods for public health policy. BMC Med Inform Decis Mak, 2018, 18(1): 131.
26.	Staniszewska S, Hill EM, Grant R, et al. Developing a framework for public involvement in mathematical and economic modelling: bringing new dynamism to vaccination policy recommendations. Patient, 2021, 14(4): 435-445.
27.	Robinson S. Conceptual modelling for simulation Part I: definition and requirements. JORS, 2008, 59(3): 278-290.
28.	McGrath S, Lin V, Zhang Z, et al. gfoRmula: an r package for estimating the effects of sustained treatment strategies via the parametric g-formula. Patterns (NY), 2020, 1(3): 100008.
29.	卢存存, 陈子佳, 张强等. 基于真实世界数据的目标试验模拟研究: 现状与展望. 中国循证医学杂志, 2023, 23(4): 492-496.
30.	Chrysanthopoulou SA, Rutter CM, Gatsonis CA. Bayesian versus empirical calibration of microsimulation models: a comparative analysis. Med Decis Making, 2021, 41(6): 714-726.
31.	Vanni T, Karnon J, Madan J, et al. Calibrating models in economic evaluation: a seven-step approach. Pharmacoeconomics, 2011, 29(1): 35-49.
32.	Rothery C, Strong M, Koffijberg HE, et al. Value of information analytical methods: report 2 of the ISPOR Value of Information Analysis Emerging Good Practices Task Force. Value Health, 2020, 23(3): 277-286.
33.	Vu TM, Buckley C, Bai H, et al. Multiobjective genetic programming can improve the explanatory capabilities of mechanism-based models of social systems. Complexity, 2020, 2020: 8923197.
34.	Dion A, Carini-Gutierrez A, Jimenez V, et al. Weight of evidence: participatory methods and Bayesian updating to contextualize evidence synthesis in stakeholders' knowledge. J Mix Methods Res, 2022, 16(3): 281-306.
35.	Balci O. Validation, verification, and testing techniques throughout the life cycle of a simulation study. Ann Oper Res, 1994, 53(1): 121-173.
36.	徐俪筝, 陈鸣声, 司磊. 骨质疏松症卫生经济学评价研究的现状、挑战及建议. 中华内分泌代谢杂志, 2021, 37(9): 859-862.
37.	董淑英. 复杂系统的认识与系统模型. 系统仿真学报, 2006, (z2): 5.
38.	李青, 谭卫华, 郑立羽. 大健康背景下公共卫生社会工作的发展. 华东理工大学学报(社会科学版), 2020, 35(1): 57-69.

1. Meier P, Purshouse R, Bain M, et al. The SIPHER Consortium: introducing the new UK hub for systems science in public health and health economic research. Wellcome Open Res, 2019, 4: 174.
2. 赵燕利, 李莹莹, 李秋芳, 等. 复杂干预的开发与评价: 2021年英国医学研究委员会框架更新解读. 中国循证医学杂志, 2023, 23(2): 125-32.
3. Skivington K, Matthews L, Simpson SA, et al. A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance. BMJ, 2021, 374: n2061.
4. Squires H, Boyd K. The use of modelling approaches for the economic evaluation of public health interventions. Oxford: Oxford Academic, 2019.
5. 毕兆峰, 李亚飞, 卫飞雪, 等. 人乳头瘤病毒疫苗建模与经济学评估快速界面模型介绍及中国实例分析. 中华预防医学杂志, 2019, 53(7): 744-751.
6. 沈月红, 郭晓君, 仲亚琴. 主体建模在慢性非传染性疾病及健康行为研究中的应用. 中国卫生统计, 2021, 38(4): 628-630, 635.
7. Breeze PR, Squires H, Ennis K, et al. Guidance on the use of complex systems models for economic evaluations of public health interventions. Health Econ, 2023, 32(7): 1603-1625.
8. Shiell A, Hawe P, Gold L. Complex interventions or complex systems. Implications for health economic evaluation. BMJ, 2008, 336(7656): 1281-1283.
9. Brailsford SC, Harper PR, Sykes J. Incorporating human behaviour in simulation models of screening for breast cancer. Eur J Oper Res, 2012, 219(3): 491-507.
10. Dodd PJ, Garnett GP, Hallett TB. Examining the promise of HIV elimination by 'test and treat' in hyperendemic settings. AIDS, 2010, 24(5): 729-735.
11. Keogh-Brown MR, Jensen HT, Basu S, et al. Evidence on the magnitude of the economic, health and population effects of palm cooking oil consumption: an integrated modelling approach with Thailand as a case study. Popul Health Metr, 2019, 17(1): 12.
12. Occhipinti JA, Skinner A, Iorfino F, et al. Reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants. BMC Med, 2021, 19(1): 61.
13. Probst C, Vu TM, Epstein JM, et al. The normative underpinnings of population-level alcohol use: an individual-level simulation model. Health Educ Behav, 2020, 47(2): 224-234.
14. Stankov I, Yang Y, Langellier BA, et al. Depression and alcohol misuse among older adults: exploring mechanisms and policy impacts using agent-based modelling. Soc Psychiatry Psychiatr Epidemiol, 2019, 54(10): 1243-1253.
15. Tobias MI, Cavana RY, Bloomfield A. Application of a system dynamics model to inform investment in smoking cessation services in New Zealand. Am J Public Health, 2010, 100(7): 1274-1281.
16. Viana J, Brailsford SC, Harindra V, et al. Combining discrete-event simulation and system dynamics in a healthcare setting: a composite model for Chlamydia infection. Eur J Oper Res, 2014, 237(1): 196-206.
17. Whitty CJ. What makes an academic paper useful for health policy. BMC Med, 2015, 13: 301.
18. Basu S, Andrews J. Complexity in mathematical models of public health policies: a guide for consumers of models. PLoS Med, 2013, 10(10): e1001540.
19. Jin H, Robinson S, Shang W, et al. Overview and use of tools for selecting modelling techniques in health economic studies. Pharmacoeconomics, 2021, 39(7): 757-770.
20. Morshed AB, Kasman M, Heuberger B, et al. A systematic review of system dynamics and agent-based obesity models: evaluating obesity as part of the global syndemic. Obes Rev, 2019, 20 (Suppl 2): 161-178.
21. Mykoniatis K, Angelopoulou A. A modeling framework for the application of multi-paradigm simulation methods. Simulation, 2019, 96(1): 55-73.
22. Brailsford SC, Eldabi T, Kunc M, et al. Hybrid simulation modelling in operational research: a state-of-the-art review. Eur J Oper Res, 2019, 278(3): 721-737.
23. Freebairn L, Atkinson JA, Qin Y, et al. 'Turning the tide' on hyperglycemia in pregnancy: insights from multiscale dynamic simulation modeling. BMJ Open Diabetes Res Care, 2020, 8(1): e000975.
24. Squires H, Chilcott J, Akehurst R, et al. A framework for developing the structure of public health economic models. Value Health, 2016, 19(5): 588-601.
25. Freebairn L, Atkinson JA, Kelly PM, et al. Decision makers' experience of participatory dynamic simulation modelling: methods for public health policy. BMC Med Inform Decis Mak, 2018, 18(1): 131.
26. Staniszewska S, Hill EM, Grant R, et al. Developing a framework for public involvement in mathematical and economic modelling: bringing new dynamism to vaccination policy recommendations. Patient, 2021, 14(4): 435-445.
27. Robinson S. Conceptual modelling for simulation Part I: definition and requirements. JORS, 2008, 59(3): 278-290.
28. McGrath S, Lin V, Zhang Z, et al. gfoRmula: an r package for estimating the effects of sustained treatment strategies via the parametric g-formula. Patterns (NY), 2020, 1(3): 100008.
29. 卢存存, 陈子佳, 张强等. 基于真实世界数据的目标试验模拟研究: 现状与展望. 中国循证医学杂志, 2023, 23(4): 492-496.
30. Chrysanthopoulou SA, Rutter CM, Gatsonis CA. Bayesian versus empirical calibration of microsimulation models: a comparative analysis. Med Decis Making, 2021, 41(6): 714-726.
31. Vanni T, Karnon J, Madan J, et al. Calibrating models in economic evaluation: a seven-step approach. Pharmacoeconomics, 2011, 29(1): 35-49.
32. Rothery C, Strong M, Koffijberg HE, et al. Value of information analytical methods: report 2 of the ISPOR Value of Information Analysis Emerging Good Practices Task Force. Value Health, 2020, 23(3): 277-286.
33. Vu TM, Buckley C, Bai H, et al. Multiobjective genetic programming can improve the explanatory capabilities of mechanism-based models of social systems. Complexity, 2020, 2020: 8923197.
34. Dion A, Carini-Gutierrez A, Jimenez V, et al. Weight of evidence: participatory methods and Bayesian updating to contextualize evidence synthesis in stakeholders' knowledge. J Mix Methods Res, 2022, 16(3): 281-306.
35. Balci O. Validation, verification, and testing techniques throughout the life cycle of a simulation study. Ann Oper Res, 1994, 53(1): 121-173.
36. 徐俪筝, 陈鸣声, 司磊. 骨质疏松症卫生经济学评价研究的现状、挑战及建议. 中华内分泌代谢杂志, 2021, 37(9): 859-862.
37. 董淑英. 复杂系统的认识与系统模型. 系统仿真学报, 2006, (z2): 5.
38. 李青, 谭卫华, 郑立羽. 大健康背景下公共卫生社会工作的发展. 华东理工大学学报(社会科学版), 2020, 35(1): 57-69.

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