Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna Avda. Astrofísico Fco. Sánchez s/n, 38200, AP 456. La Laguna, Canary Islands, Spain.
Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna Avda. Astrofísico Fco. Sánchez s/n, 38200, AP 456. La Laguna, Canary Islands, Spain; Spanish Network of Health Services Research for Chronic Diseases (REDISSEC), Tenerife, Spain.
J Biomed Inform. 2020 Oct;110:103563. doi: 10.1016/j.jbi.2020.103563. Epub 2020 Sep 12.
The development of decision models to assess interventions for rare diseases require huge efforts from research groups, especially regarding collecting and synthesizing the knowledge to parameterize the model. This article presents a method to reuse the knowledge collected in an ontology to automatically generate decision tree models for different contexts and interventions.
We updated the reference ontology (RaDiOS) to include more knowledge required to generate a model. We implemented a transformation tool (RaDiOS-MTT) that uses the knowledge stored in RaDiOS to automatically generate decision trees for the economic assessment of interventions on rare diseases.
We used a case study to illustrate the potential of the tool, and automatically generate a decision tree that reproduces an actual study on newborn screening for profound biotinidase deficiency.
RaDiOS-MTT allows research groups to reuse the evidence collected, and thus speeding up the development of health economics assessments for interventions on rare diseases.
开发用于评估罕见病干预措施的决策模型需要研究小组付出巨大努力，特别是在收集和综合知识以对模型进行参数化方面。本文提出了一种方法，可重复使用在本体中收集的知识，自动为不同的情境和干预措施生成决策树模型。
我们更新了参考本体（RaDiOS），以纳入生成模型所需的更多知识。我们实现了一个转换工具（RaDiOS-MTT），该工具使用 RaDiOS 中存储的知识自动为罕见病干预措施的经济评估生成决策树。
我们使用一个案例研究来说明该工具的潜力，并自动生成一个决策树，该决策树再现了针对新生儿严重生物素酶缺乏症筛查的实际研究。
RaDiOS-MTT 允许研究小组重复使用已收集的证据，从而加快了罕见病干预措施的卫生经济学评估的开发。
