Lorenzoni Giulia, Baldi Ileana, Soattin Marta, Gregori Dario, Buja Alessandra
Department of Cardio-Thoraco-Vascular Sciences and Public Health, University of Padua, Padua (Italy).
Hygiene and Public Health Unit, Department of Cardio-Thoraco-Vascular Sciences and Public Health, University of Padua, Padua (Italy).
Epidemiol Prev. 2019 Jul-Aug;43(4 Suppl 2):51-61. doi: 10.19191/EP19.4.S2.P051.092.
to identify and describe all hypertension, heart failure (HF), and congenital heart disease case-identification algorithms by means of Italian Healthcare Administrative Databases (HADs), through the review of papers published in the past 10 years.
this study is part of a project that systematically reviewed case-identification algorithms for 18 acute and chronic conditions by means of HADs in Italy. PubMed was searched for original articles, published between 2007 and 2017, in Italian or English. The search string consisted of a combination of free text and MeSH terms with a common part that focused on HADs and a disease-specific part. All identified papers were screened by two independent reviewers. Pertinent papers were classified according to the objective for which the algorithm had been used, and only articles that used algorithms for primary objectives (I disease occurrence; II population/cohort selection; III outcome identification) were considered for algorithm extraction. The HADs used (hospital discharge records, drug prescriptions, etc.), ICD-9 and ICD-10 codes, ATC classification of drugs, follow-back periods, and age ranges applied by the algorithms have been reported. Further information on specific objective(s), accuracy measures, sensitivity analyses, and the contribution of each HAD have also been recorded.
the search strategy identified 429 papers for hypertension, 479 for HF, and 138 for congenital heart diseases. After title/abstract and full-text screening, the review led to the inclusion of 21 articles for hypertension, 24 for HF, and only 1 for congenital heart diseases. Eighteen algorithms had a primary objective (5 hypertension, 12 HF, 1 congenital heart diseases). All the hypertension algorithms were based on the drug prescription database, except for one algorithm that also used the hospital discharge records and the exemption from co-payment database. As for HF, all the algorithms employed the hospital discharge record database and only two algorithms used another information source. The only algorithm identified for congenital heart diseases was based on the hospital discharge database. The algorithm identified for congenital heart diseases was validated, showing excellent performance. Conversely, only one hypertension algorithm was validated, and none of the HF algorithms were validated - even though 5 out of 12 algorithms were based on previous algorithms used at both national and international level.
the findings of the present study showed wide use of Italian administrative databases for the detection of hypertension and heart failure cases. However, the validity of the algorithms in most cases has not been tested, highlighting the need for introducing stricter requirements to enforce the assessment of the validity of the algorithms used.
通过回顾过去10年发表的论文，利用意大利医疗保健管理数据库（HADs）识别并描述所有高血压、心力衰竭（HF）和先天性心脏病的病例识别算法。
本研究是一个项目的一部分，该项目通过意大利的HADs系统回顾了18种急慢性疾病的病例识别算法。在PubMed中检索2007年至2017年间发表的意大利语或英语原创文章。检索词由自由文本和医学主题词组合而成，有一个共同部分聚焦于HADs，还有一个疾病特定部分。所有识别出的论文由两名独立评审员进行筛选。相关论文根据算法使用的目的进行分类，仅考虑将算法用于主要目的（I疾病发生；II人群/队列选择；III结局识别）的文章进行算法提取。已报告所使用的HADs（医院出院记录、药物处方等）、ICD - 9和ICD - 10编码、药物的ATC分类、追溯期以及算法应用的年龄范围。还记录了关于特定目的、准确性测量、敏感性分析以及每个HAD贡献的进一步信息。
检索策略识别出429篇关于高血压的论文、479篇关于HF的论文和138篇关于先天性心脏病的论文。经过标题/摘要和全文筛选，该综述纳入了21篇关于高血压的文章、24篇关于HF的文章，而关于先天性心脏病的仅1篇。18种算法有主要目的（5种用于高血压，12种用于HF，1种用于先天性心脏病）。所有高血压算法均基于药物处方数据库，只有一种算法还使用了医院出院记录和免付共付费用数据库。至于HF，所有算法都采用了医院出院记录数据库，只有两种算法使用了另一个信息源。识别出的唯一一种先天性心脏病算法基于医院出院数据库。识别出的先天性心脏病算法经过验证，表现出色。相反，只有一种高血压算法经过验证，而HF算法均未经验证——尽管12种算法中有5种基于国内外先前使用的算法。
本研究结果表明意大利行政数据库在检测高血压和心力衰竭病例方面得到广泛应用。然而，大多数情况下算法的有效性尚未得到检验，这凸显了需要引入更严格的要求来加强对所用算法有效性的评估。
