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Using system dynamics modelling to estimate the costs of relaxing health system constraints

A case study of tuberculosis prevention and control interventions in South Africa

Bibliographic Data

ID15127273
AuthorsFiammetta Bozzani (0000-0002-9518-6885, London School of Hygiene & Tropical Medicine, corresponding author), Karin Diaconu (0000-0002-5810-9725, Institute for Global Health and Development, Queen Margaret University , Queen Margaret University Way, Musselburgh EH21 6UU, UK), Gabriela B Gomez (0000-0002-7409-798X, London School of Hygiene & Tropical Medicine), Aaron S Karat (0000-0001-9643-664X, Institute for Global Health and Development, Queen Margaret University , Queen Margaret University Way, Musselburgh EH21 6UU, UK), Karina Kielmann (0000-0001-5519-1658, Institute for Global Health and Development, Queen Margaret University , Queen Margaret University Way, Musselburgh EH21 6UU, UK), Anne D Grant (0000-0002-2437-5195, London School of Hygiene & Tropical Medicine), Anna Vassall (0000-0002-2911-1375, London School of Hygiene & Tropical Medicine)
Year2022
Volume37
Issue3
Pages369-375
Publication date2022-03-04
Open AccessYes
TypeARTICLE
VenueHealth Policy and Planning (JOURNAL)
Journal identifiersISSN: 0268-1080 • E-ISSN: 1460-2237
PublisherOxford University Press (PUBLISHER • GB)
DOI10.1093/heapol/czab155
PMID34951631
OpenAlexW4200480756
LanguageEN
Citations received3
References cited22

Health system constraints are increasingly recognized as an important addition to model-based analyses of disease control interventions, as they affect achievable impact and scale. Enabling activities implemented alongside interventions to relax constraints and reach the intended coverage may incur additional costs, which should be considered in priority setting decisions. We explore the use of group model building, a participatory system dynamics modelling technique, for eliciting information from key stakeholders on the constraints that apply to tuberculosis infection prevention and control processes within primary healthcare clinics in South Africa. This information was used to design feasible interventions, including the necessary enablers to relax existing constraints. Intervention and enabler costs were then calculated at two clinics in KwaZulu-Natal using input prices and quantities from the published literature and local suppliers. Among the proposed interventions, the most inexpensive was retrofitting buildings to improve ventilation (US$1644 per year), followed by maximizing the use of community sites for medication collection among stable patients on antiretroviral therapy (ART; US$3753) and introducing appointments systems to reduce crowding (US$9302). Enablers identified included enhanced staff training, supervision and patient engagement activities to support behaviour change and local ownership. Several of the enablers identified by the stakeholders, such as obtaining building permissions or improving information flow between levels of the health systems, were not amenable to costing. Despite this limitation, an approach to costing rooted in system dynamics modelling can be successfully applied in economic evaluations to more accurately estimate the ‘real world’ opportunity cost of intervention options. Further empirical research applying this approach to different intervention types (e.g. new preventive technologies or diagnostics) may identify interventions that are not cost-effective in specific contexts based on the size of the required investment in enablers

Activity-based costing · Business · Causal loop diagram · Economic growth · Economics · Health care · Operations management · Psychological intervention · Risk analysis (engineering) · System dynamics · Community Health and Development · Complex Systems and Decision Making · Computer Science · Health Policy Implementation Science · Marketing · Medicine · Nursing

  • Cost-effectiveness of tuberculosis infection prevention and control interventions in South African clinics

    Open Access•Fiammetta Bozzani, Nicky McCreesh et al.•BMJ Global Health•2023

  • A systems approach to understanding injury care in LMICs using causal loop diagrams

    Open Access•Justine Ina Davies, Kathryn Chu et al.•BMJ Global Health•2026

  • Qualitative system dynamics modelling to support the design and implementation of tuberculosis infection prevention and control measures in South African primary healthcare facilities

    Open Access•Karin Diaconu, Aaron S Karat et al.•Health Policy and Planning•2024

  • Health Care Systems in Low- and Middle-Income Countries

    Antonia Mills, Anne Mills•New England Journal of Medicine•2014

  • Building the Field of Health Policy and Systems Research

    Open Access•Kay Sheikh, Kabir Sheikh et al.•PLoS Medicine•2011

  • It has become everybody’s business and nobody’s business’

    Open Access•C J Colvin, Idriss Ibrahim Kallon et al.•Global Public Health•2020

  • Dynamic modeling approaches to characterize the functioning of health systems

    Open Access•Alenda Y Chang, Osondu Ogbuoji et al.•Social Science & Medicine•2017

  • Understanding pathways for scaling up health services through the lens of complex adaptive systems

    Open Access•Ligia Paina, David H Peters•Health Policy and Planning•2012

Citations per year1
Citation span2023 - 2026 (4)
Highly citedNo
Open DOIOpen Access
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