Developing an algorithm to identify individuals with psychosis in secondary care in England: application using the Mental Health Services Data Set.

IF 3.9 3区 医学 Q1 PSYCHIATRY
BJPsych Open Pub Date : 2025-02-27 DOI:10.1192/bjo.2024.853
Claire de Oliveira, Maria Ana Matias, María José Aragon Aragon, Misael Anaya Montes, David Osborn, Rowena Jacobs
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Abstract

Background: There is currently no definitive method for identifying individuals with psychosis in secondary care on a population-level using administrative healthcare data from England.

Aims: To develop various algorithms to identify individuals with psychosis in the Mental Health Services Data Set (MHSDS), guided by national estimates of the prevalence of psychosis.

Method: Using a combination of data elements in the MHSDS for financial years 2017-2018 and 2018-2019 (mental health cluster (a way to describe and classify a group of individuals with similar characteristics), Health of the Nation Outcome Scale (HoNOS) scores, reason for referral, primary diagnosis, first-episode psychosis flag, early intervention in psychosis team flag), we developed 12 unique algorithms to detect individuals with psychosis seen in secondary care. The resulting numbers were then compared with national estimates of the prevalence of psychosis to ascertain whether they were reasonable or not.

Results: The 12 algorithms produced 99 204-138 516 and 107 545-134 954 cases of psychosis for financial years 2017-2018 and 2018-2019, respectively, in line with national prevalence estimates. The numbers of cases of psychosis identified by the different algorithms differed according to the type and number (3-6) of data elements used. Most algorithms identified the same core of patients.

Conclusions: The MHSDS can be used to identify individuals with psychosis in secondary care in England. Users can employ several algorithms to do so, depending on the objective of their analysis and their preference regarding the data elements employed. These algorithms could be used for surveillance, research and/or policy purposes.

开发一种算法来识别在英国二级护理精神病患者:使用精神卫生服务数据集的应用。
背景:目前还没有明确的方法来识别个体精神病患者在二级保健在人口水平上使用来自英格兰的行政保健数据。目的:以国家精神病患病率估计为指导,开发各种算法来识别精神卫生服务数据集(MHSDS)中的精神病患者。方法:结合2017-2018财政年度和2018-2019财政年度MHSDS中的数据元素(心理健康集群(一种描述和分类具有相似特征的个体的方法),国家健康结果量表(HoNOS)评分,转诊原因,初级诊断,首次发作精神病标志,精神病团队早期干预标志),我们开发了12种独特的算法来检测二级保健中看到的精神病个体。然后将所得的数字与全国精神病患病率的估计进行比较,以确定它们是否合理。结果:12种算法在2017-2018财政年度和2018-2019财政年度分别产生了99 204-138 516例和107 545-134 954例精神病病例,与国家患病率估计相符。根据所使用的数据元素的类型和数量(3-6),不同算法识别的精神病病例数有所不同。大多数算法识别的都是相同的核心患者。结论:MHSDS可用于识别英国二级护理精神病患者。用户可以使用多种算法来实现这一点,这取决于他们的分析目标和他们对所使用的数据元素的偏好。这些算法可用于监测、研究和/或政策目的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BJPsych Open
BJPsych Open Medicine-Psychiatry and Mental Health
CiteScore
6.30
自引率
3.70%
发文量
610
审稿时长
16 weeks
期刊介绍: Announcing the launch of BJPsych Open, an exciting new open access online journal for the publication of all methodologically sound research in all fields of psychiatry and disciplines related to mental health. BJPsych Open will maintain the highest scientific, peer review, and ethical standards of the BJPsych, ensure rapid publication for authors whilst sharing research with no cost to the reader in the spirit of maximising dissemination and public engagement. Cascade submission from BJPsych to BJPsych Open is a new option for authors whose first priority is rapid online publication with the prestigious BJPsych brand. Authors will also retain copyright to their works under a creative commons license.
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