Using Group Model Building to Capture the Complex Dynamics of Scaling Up District-Level Surgery in Arusha Region, Tanzania

Document Type : Original Article

Authors

1 Department of Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands

2 Department of Business Administration, Institute for Management Research, Radboud University, Nijmegen, The Netherlands

3 Institute of Global Surgery, Royal College of Surgeons Ireland, Dublin 2, Ireland

4 Division of Population Health Sciences, Royal College of Surgeons in Ireland, Dublin 2, Ireland

5 East Central and Southern Africa Health Community, Arusha, Tanzania

6 Tanzania Surgical Association, Dar Es Salaam, Tanzania

7 Kilimanjaro Christian Medical Centre, Moshi, Tanzania

Abstract

Background
Scaling up surgery at district hospitals (DHs) is the critical challenge if the Tanzanian national Surgical, Obstetric, and Anesthesia Plan (NSOAP) objectives are to be achieved. Our study aims to address this challenge by taking a dynamic view of surgical scale-up at the district level using a participatory research approach.
 
Methods
A group model building (GMB) workshop was held with 18 professionals from three hospitals in the Arusha region. They built a graphical representation of the local system of surgical services delivery through a facilitated discussion that employed the nominal group technique. This resulted in a causal loop diagram (CLD) from which the participants identified the requirements for scaling-up surgery and the stakeholders who could satisfy these. After the GMB sessions, we identified clusters of related variables using inductive thematic analysis and the main feedback loops driving the model.
 
Results
The CLD consists of 57 variables. These include the 48 variables that were obtained through the nominal group technique and those that participants added later. We identified 6 themes: patient benefits, financing of surgery, cost sharing, staff motivation, communication, and effects on referral hospital. There are 5 self-reinforcing feedback loops: training, learning, meeting demand, revenues, and willingness to work in a good hospital. There are four self-correcting feedback loops or ‘resistors to change:’ recurrent costs, income lost, staff stress, and brain drain.
 
Conclusion
This study provides a systems view on the scaling up of surgery from a district level perspective. Its results enable a critical appraisal of the feasibility of implementing the NSOAP. Our results suggest that policy-makers should be wary of ‘quick fixes’ that have short term gains only. Long term policy that considers the complex dynamics of surgical systems and that allows for periodic evaluation and adaption is needed to scale up surgery in a sustainable manner.

Keywords

References

  1. Institute for Health Metrics and Evaluation (IHME). Global Burden of Disease Study. http://www.healthdata.org/briefs/global-burden-disease-2015-factsheet.  Published 2015.
  2. National Surgical, Obstetric and Anaesthesia Plan (Nsoap) 2018-2025 the United Republic of Tanzania. Dodoma; 2018. https://www.pgssc.org/national-surgical-planning.
  3. Bijlmakers L, Cornelissen D, Cheelo M, et al. The cost of providing and scaling up surgery: a comparison of a district hospital and a referral hospital in Zambia. Health Policy Plan. 2018;33(10):1055-1064. doi:10.1093/heapol/czy086
  4. Nyberger K, Jumbam DT, Dahm J, et al. The situation of safe surgery and anaesthesia in Tanzania: a systematic review. World J Surg. 2019;43(1):24-35. doi:10.1007/s00268-018-4767-7
  5. Gajewski J, Mwapasa G, Cheelo M, et al. Participatory action research to design a surgical training and supervision intervention for district level hospitals in Malawi, Tanzania and Zambia. In: International Society of Surgery; 2019: Abstract 126.09.
  6. Paina L, Peters DH. Understanding pathways for scaling up health services through the lens of complex adaptive systems. Health Policy Plan. 2012;27(5):365-373. doi:10.1093/heapol/czr054
  7. Northridge ME, Metcalf SS. Enhancing implementation science by applying best principles of systems science. Health Res Policy Syst. 2016;14(1):74. doi:10.1186/s12961-016-0146-8
  8. Sterman JD. Systems Thinking and Modeling for a Complex World. Vol 6. Boston: Irwin McGraw-Hill; 2000. doi:10.1108/13673270210417646
  9. Marshall D a, Burgos-liz L, Eng I, et al. Applying Dynamic Simulation Modeling Methods in Health Care Delivery Research — The SIMULATE Checklist : Report of the ISPOR Simulation Modeling Emerging Good Practices Task Force. Value Health. 2015;18:5-16. doi:10.1016/j.jval.2014.12.001
  10. Pittalis C, Brugha R, Crispino G, et al. Evaluation of a surgical supervision model in three African countries—protocol for a prospective mixed-methods controlled pilot trial. Pilot Feasibility Stud. 2019;5(1):25. doi:10.1186/s40814-019-0409-6
  11. Vennix JAM. Group Model Building: Facilitating Team Learning Using System Dynamics. Nijmegen: John Wiley & Sons Inc; 1996.
  12. Harvey N, Holmes CA. Nominal group technique: An effective method for obtaining group consensus. Int J Nurs Pract. 2012;18(2):188-194. doi:10.1111/j.1440-172X.2012.02017.x
  13. Citron I, Jumbam D, Dahm J, et al. Towards equitable surgical systems: development and outcomes of a national surgical, obstetric and anaesthesia plan in Tanzania. BMJ Glob Health. 2019;4(2):e001282. doi:10.1136/bmjgh-2018-001282
  14. Pereira C, Mbaruku G, Nzabuhakwa C, Bergström S, McCord C. Emergency obstetric surgery by non-physician clinicians in Tanzania. Int J Gynaecol Obstet. 2011;114(2):180-183. doi:10.1016/j.ijgo.2011.05.004
  15. Beard JH, Oresanya LB, Akoko L, Mwanga A, Mkony CA, Dicker RA. Surgical task-shifting in a low-resource setting: outcomes after major surgery performed by nonphysician clinicians in Tanzania. World J Surg. 2014;38(6):1398-1404. doi:10.1007/s00268-013-2446-2
  16. Gajewski J, Mweemba C, Cheelo M, et al. Non-physician clinicians in rural Africa: lessons from the Medical Licentiate programme in Zambia. Hum Resour Health. 2017;15(1):53. doi:10.1186/s12960-017-0233-0
  17. Ozgediz D, Galukande M, Mabweijano J, et al. The neglect of the global surgical workforce: Experience and evidence from Uganda. World J Surg. 2008;32(6):1208-1215. doi:10.1007/s00268-008-9473-4
  18. Gajewski J, Borgstein E, Bijlmakers L, et al. Evaluation of a surgical training programme for clinical officers in Malawi. BJS. 2019;106(2):e156-e165. doi:10.1002/bjs.11065
  19. Meara JG, Leather AJM, Hagander L, et al. Global Surgery 2030: evidence and solutions for achieving health, welfare, and economic development. Lancet. 2015;386(9993):569-624. doi:10.1016/S0140-6736(15)60160-X
  20. van Heemskerken P, Broekhuizen H, Gajewski J, Brugha R, Bijlmakers L. Barriers to surgery performed by non-physician clinicians in sub-Saharan Africa-a scoping review. Hum Resour Health. 2020;18(1):51. doi:10.1186/s12960-020-00490-y
  21. Gajewski J, Bijlmakers L, Brugha R. Global Surgery – Informing National Strategies for Scaling Up Surgery in Sub-Saharan Africa. Int J Health Policy Manag. 2018;7(6):481-484. doi:10.15171/ijhpm.2018.27
  22. Peck GL, Hanna JS. The National Surgical, Obstetric, and Anesthesia Plan (NSOAP): recognition and definition of an empirically evolving global surgery systems science: Comment on “Global surgery – informing national strategies for scaling up surgery in sub-Saharan Africa.” Int J Health Policy Manag. 2018;7(12):1151-1154. doi:10.15171/ijhpm.2018.87
  23. DeVries CR, Rosenberg JS. Global Surgical Ecosystems: A Need for Systems Strengthening. Ann Glob Health. 2016;82(4):605. doi:10.1016/j.aogh.2016.09.011
  24. Kim D. System archetypes as dynamic theories. Syst Think. 2013;24(1):7-10.
  25. de Gooyert V, Rouwette E, van Kranenburg H, Freeman E. Reviewing the role of stakeholders in Operational Research: A stakeholder theory perspective. Eur J Oper Res. 2017;262(2):402-410. doi:10.1016/j.ejor.2017.03.079
  26. Scott RJ, Cavana RY, Cameron D. Recent evidence on the effectiveness of group model building. Eur J Oper Res. 2016;249(3):908-918. doi:10.1016/j.ejor.2015.06.078
  27. Cassidy R, Singh NS, Schiratti P-R, et al. Mathematical modelling for health systems research: a systematic review of system dynamics and agent-based models. BMC Health Serv Res. 2019;19(1):845. doi:10.1186/s12913-019-4627-7
  28. Peters DH, Bhuiya A, Ghaffar A. Engaging stakeholders in implementation research: lessons from the Future Health Systems Research Programme experience. Health Res Policy Syst. 2017;15(S2):104. doi:10.1186/s12961-017-0269-6
  29. Jumbam DT, Reddy CL, Roa L, Meara JG. How much does it cost to scale up surgical systems in low-income and middle-income countries? BMJ Glob Health. 2019;4(4):e001779. doi:10.1136/bmjgh-2019-001779
International Journal of Health Policy and Management
Volume 11, Issue 7
July 2022
Pages 981-989

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History

  • Receive Date: 15 February 2020
  • Revise Date: 30 November 2020
  • Accept Date: 01 December 2020
  • First Publish Date: 14 December 2020

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