These models and simulations have been tagged “Medicines”.
Major stocks and flows of Erythropoiesis and Erythropoiesis Stimulating Agents (ESA) Dosing in Anemia due to Renal Failure from Jim Rogers. See Simulation Insight
Addition of Incident Reporting and Prevention Interventions to a simple error chain of medication errors for patients in hospital IM-10113
A simple error chain of medication errors for patients in hospital. Serious medication errors in inpatients with drug orders sometimes result in Adverse Drug Events (ADE) and Deaths. See next IM-646
Causal loop diagram patient centric version of Insight 691, unfolding the complexity of medication management.
This model shows the Pharmaceutical New Drug Pipeline based on drug release, approval and patent expiry. This pipeline is then linked to patients switching from older drugs to newer drugs based on proven indications and marketing (indication creep). Based on work by Mark Heffernan on the Australian Pharmaceutical Benefits Scheme for drug subsidy.Conference paper and Larger ithink model
The dynamics of methadone treatment for intravenous opioid users. The major flows in this study were people cycling between being on methadone and off treatment. This is a minimal model of the insights from the more detailed modelling project described in Monograph pdf
From p592 Doyle F et al.(2007) Journal of Process Control 17 571-594
Rich picture version of causal loop diagram for medication errors, showing the importance of reporting, analyzing and fixing knowledge and process errors. Medication errors will tend to grow due to the use of more medications in more complex patients. This is exacerbated by the loss of staff knowledge by turnover and goal erosion in places with harmful errors.
Mind map example of a medication management project.
See also IM-692 for CLD