Evidence map›Paper›PMID 36567380›Full record

ArticleHealth economics review2022

A decision support tool with health economic modelling for better management of DVT patients.

Reda Lebcir, Usame Yakutcan, Eren Demir

Abstract read
In one paragraph

Article in Health economics review, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Reda LebcirUniversity of Hertfordshire, Hatfield, AL10 9AB, UK.ORCID http://orcid.org/0000-0003-0500-7861
Usame YakutcanUniversity of Hertfordshire, Hatfield, AL10 9AB, UK. U.Yakutcan@herts.ac.uk.ORCID http://orcid.org/0000-0002-9648-5529
Eren DemirUniversity of Hertfordshire, Hatfield, AL10 9AB, UK.ORCID http://orcid.org/0000-0002-9087-7169

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundResponding to the increasing demand for Deep Vein Thrombosis (DVT) treatment in the United Kingdom (UK) at times of limited budgets and resources is a great challenge for decision-makers. Therefore, there is a need to find innovative policies, which improve operational efficiency and achieve the best value for money for patients. This study aims to develop a Decision Support Tool (DST) that assesses the impact of implementing new DVT patients' management and care policies aiming at improving efficiency, reducing costs, and enhancing value for money.

methodsWith the involvement of stakeholders from a number of DVT services in the UK, we developed a DST combining discrete event simulation (DES) for DVT pathways and the Socio Technical Allocation of Resources (STAR) approach, an agile health economics technique. The model was inputted with data from the literature, local datasets from DVT services, and interviews conducted with DVT specialists. The tool was validated and verified by various stakeholders and two policies, namely shifting more patients to community services (CSs) and increasing the usage of the Novel Oral Anticoagulant (NOAC) drug were selected for testing on the model.

resultsSixteen possible scenarios were run on the model for a period of 5 years and generated treatment activity, human resources, costing, and value for money outputs. The results indicated that hospital visits can be reduced by up to 50%. Human resources' usage can be greatly lowered driven mainly by offering NOAC treatment to more patients. Also, combining both policies can lead to cost savings of up to 50%. The STAR method, which considers both service and patient perspectives, produced findings that implementing both policies provide a significantly higher value for money compared to the situation when neither is applied.

conclusionsThe combination of DES and STAR can help decision-makers determine the interventions that have the highest benefits from service providers' and patients' perspectives. This is important given the mismatch between care demand and resources and the resulting need for improving operational and economic outcomes. The DST tool has the potential to inform policymaking in DVT services in the UK to improve performance.

Indexed as

Community servicesDecision support toolDeep vein thrombosisDiscrete event simulationNational health servicePatient flow modellingSTARUnited Kingdom

Identifiers

PMID36567380
PMCPMC9790817

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.