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A systems thinking approach to prospective planning of interventions for chronic kidney disease care

Research output: Contribution to journalArticlepeer-review

Abstract

Chronic kidney disease (CKD) is a growing health problem. Previous approaches to improve CKD care tend to focus on the linear relationships between a specific intervention and its effects on the target CKD population. The objective of this paper is to investigate how a systems thinking approach can support decision making on system-level interventions for chronic disease management. Our research team conducted a case study at an academic health-care organization. To support prospective planning of interventions at the study institution, we adopted a systems thinking approach in three phases: intervention structuring, causal loop modeling, and implementation planning. In the first phase, four potential interventions were proposed to address gaps in the current system. In the second phase, a causal loop diagram was developed to identify feedback loops and evaluate potential impacts of the interventions on patients and care providers. In the last phase, the analysis was linked to decision making on intervention implementation. Overall, this whole process based on systems thinking helped the health-care organization to holistically understand the impact of various components of their CKD care system. Furthermore, the findings from the qualitative modeling and analysis provided the leadership with insights into gaps in care and a way forward for implementing interventions more successfully and effectively.

Original languageEnglish (US)
Pages (from-to)130-147
Number of pages18
JournalHealth Systems
Volume6
Issue number2
DOIs
StatePublished - Jul 1 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Human-Computer Interaction
  • Health Policy
  • Health Informatics
  • Management Science and Operations Research

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