Microsimulation Modeling for Health Decision Sciences Using R: A Tutorial

Krijkamp, Eline M.; Alarid‐Escudero, Fernando; Enns, Eva A.; Jalal, Hawre; Hunink, M. G. Myriam; Pechlivanoglou, Petros

doi:10.1177/0272989x18754513

Cited by 107 publications

(107 citation statements)

References 37 publications

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“…However, the NRI is not without problems and may be misleading in certain conditions [32]. We thus built a microsimulation model based on real-world data to better estimate the cost and effectiveness in the real-world [21]. Our analytic framework, combining traditional measures, NRI, and a microsimulation model, would be particularly useful in implementing prediction models in clinical practice.…”

Section: Discussionmentioning

confidence: 99%

“…Microsimulation is a technique used to model complex real-life events by simulating the impact of policy change on the individual units (micro units) that make up the system where the events occur [21,22]. We constructed a microsimulation model to evaluate the cost-effectiveness of the LACE index and HOSPITAL score when applied to hospitalizations of the current study cohort.…”

Section: Microsimulation Modelmentioning

confidence: 99%

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Assess the Performance and Cost-Effectiveness of LACE and HOSPITAL Re-Admission Prediction Models as a Risk Management Tool for Home Care Patients: An Evaluation Study of a Medical Center Affiliated Home Care Unit in Taiwan

Wang

Chen

et al. 2020

IJERPH

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The LACE index and HOSPITAL score models are the two most commonly used prediction models identifying patients at high risk of readmission with limited information for home care patients. This study compares the effectiveness of these two models in predicting 30-day readmission following acute hospitalization of such patients in Taiwan. A cohort of 57 home care patients were enrolled and followed-up for one year. We compared calibration, discrimination (area under the receiver operating curve, AUC), and net reclassification improvement (NRI) to identify patients at risk of 30-day readmission for both models. Moreover, the cost-effectiveness of the models was evaluated using microsimulation analysis. A total of 22 readmissions occurred after 87 acute hospitalizations during the study period (readmission rate = 25.2%). While the LACE score had poor discrimination (AUC = 0.598, 95% confidence interval (CI) = 0.488-0.702), the HOSPITAL score achieved helpful discrimination (AUC = 0.691, 95% CI = 0.582-0.785). Moreover, the HOSPITAL score had improved the risk prediction in 38.3% of the patients, compared with the LACE index (NRI = 0.383, 95% CI = 0.068-0.697, p = 0.017). Both prediction models effectively reduced readmission rates compared to an attending physician's model (readmission rate reduction: LACE, 39.2%; HOSPITAL, 43.4%; physician, 10.1%; p < 0.001). The HOSPITAL score provides a better prediction of readmission and has potential as a risk management tool for home care patients.

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Section: Discussionmentioning

confidence: 99%

Section: Microsimulation Modelmentioning

confidence: 99%

Assess the Performance and Cost-Effectiveness of LACE and HOSPITAL Re-Admission Prediction Models as a Risk Management Tool for Home Care Patients: An Evaluation Study of a Medical Center Affiliated Home Care Unit in Taiwan

Wang

Chen

et al. 2020

IJERPH

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“…The following outcomes are considered: total costs (incurred by treatment with FVIII, bleed management, and other medical costs), total number of FVIII infusions, total number of bleeding events (joint and nonjoint), life-years gained, and quality-adjusted life-years (QALYs) gained. The analysis simulates 10,000 individual patient experiences using R version 3.3.3 based on a template for microsimulation modeling provided by Krijkamp et al 21 . This generates a distribution with a mean and variance: the mean is interpreted as the average effect for a single patient.…”

Section: Decision Modelmentioning

confidence: 99%

Assessing the potential cost-effectiveness of a gene therapy for the treatment of hemophilia A

Cook

Forbes

Adamski

et al. 2020

Journal of Medical Economics

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Aim: Hemophilia A is a genetic, chronic disorder classified by deficient or defective coagulation factor VIII (FVIII) that puts those affected at risk for spontaneous bleeding episodes, which lead to joint damage and chronic pain over time. Currently, most severe hemophilia A patients are treated with prophylactic FVIII, which requires costly and frequent infusions and lifelong adherence to medication. A gene therapy (valoctocogene roxaparvovec) is currently in development for the treatment of severe hemophilia A. This model assessed the potential cost-effectiveness of treating patients with valoctocogene roxaparvovec rather than prophylactic therapy. Materials and methods: We developed an individual-based, state-transition microsimulation model for assessing the likely cost-effectiveness of valoctocogene roxaparvovec compared to prophylactic FVIII. Men aged 30 with severe hemophilia A were modeled over a lifetime horizon, and costs were reported from the perspective of the United States health care system. Through microsimulation, patient-level heterogeneity was captured in starting weight, starting Pettersson score (PS), durability of valoctocogene roxaparvovec, and annual bleed rate (ABR). Results: The model projects that treatment with single-administration valoctocogene roxaparvovec would be cost-saving to people with hemophilia A at a price point comparable to other currently available gene therapy products due to its potential to reduce FVIII utilization, direct medical costs, lifetime bleeds, and accumulated joint damage. Limitations: The model relies upon evidence-based assumptions for clinical inputs due to limited data availability. Such uncertainty was mitigated by modeling heterogeneity across the population, specifically with regards to long-term gene therapy durability, lifetime bleed rates, and joint damage progression. Conclusion: Valoctocogene roxaparvovec was found to be cost-saving-on average by about $6.8 million per patient-and more effective than prophylactic therapy for treatment of hemophilia A. The comparative benefit of gene therapy was observed across a broad range of simulated patients that were representative of the real-world severe hemophilia A population.

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“…All interventions in one cost‐effectiveness plane (produced with functions provided by the DARTH group . NSP, needles and syringes programme; OST, opioid substitution therapy; screen, screen at; screenGP, screen at GP offices; treat, treat all infected…”

Section: Resultsmentioning

confidence: 99%

Feasibility of reaching world health organization targets for hepatitis C and the cost‐effectiveness of alternative strategies

Wisløff

White

Dalgård

et al. 2018

Journal of Viral Hepatitis

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Summary New drugs for treating hepatitis C have considerably increased the probability of being cured. Treatment uptake, however, is still low. The objectives of this study were to analyse the impact of initiatives that may increase the proportion of infected people on treatment and interventions aimed at reducing the incidence of new infection among people who inject drugs. A compartmental model for Norway was used to simulate hepatitis C and related complications. We analysed 2 different screening initiatives aimed to increase the proportion of infected people on treatment. Interventions aiming at reducing the hepatitis C incidence analysed were opioid substitution therapy (OST), a clean needle and syringe programme and a combination of both. The most cost‐effective strategy for increasing hepatitis C treatment uptake was screening by general practitioners while simultaneously allowing for all infected people to be treated. We estimated that this intervention reduces the incidence of hepatitis C by 2030 by 63% compared with the current incidence. The 2 harm reduction strategies both reduced the incidence of hepatitis C by about 70%. Combining an increase in the current clean needles and syringe programme with OST was clearly the most cost‐effective option. This strategy would reduce the incidence of hepatitis C by 80% compared with the current incidence by 2030. Thus, interventions to reduce the burden and spread of hepatitis C are cost‐effective. Reaching the WHO target of a 90% reduction in hepatitis C incidence by 2030 may be difficult without combining different initiatives.

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Microsimulation Modeling for Health Decision Sciences Using R: A Tutorial

Cited by 107 publications

References 37 publications

Assess the Performance and Cost-Effectiveness of LACE and HOSPITAL Re-Admission Prediction Models as a Risk Management Tool for Home Care Patients: An Evaluation Study of a Medical Center Affiliated Home Care Unit in Taiwan

Assess the Performance and Cost-Effectiveness of LACE and HOSPITAL Re-Admission Prediction Models as a Risk Management Tool for Home Care Patients: An Evaluation Study of a Medical Center Affiliated Home Care Unit in Taiwan

Assessing the potential cost-effectiveness of a gene therapy for the treatment of hemophilia A

Feasibility of reaching world health organization targets for hepatitis C and the cost‐effectiveness of alternative strategies

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