Generation of a Dataset of Problems Related to Hypertension (HTN) in the Electronic Health Information System of Buenos Aires City

Abstract

Arterial hypertension (HTN) is one of the most prevalent noncommunicable chronic diseases and the most common cardiovascular risk factor in the global population. The Ministry of Health of the Government of the City of Buenos Aires is carrying out a continuous improvement process for the identification, follow-up, and control of patients with HTN in public healthcare facilities, with the aim of optimizing care and managing resources more efficiently. Within the Ministry, the Operational Management of Information and Statistics is responsible for identifying patients based on electronic health records (EHR) of the information system used in public facilities, and for building monitoring and control indicators. The identification process began with a set of simple rules, prioritizing sensitivity over specificity. Over time, improvements were applied to increase the positive predictive value and specificity. The aim of this work is to describe the progress made in generating new rules for the identification of people with HTN, and the establishment of a periodic monitoring and evaluation circuit. The new version of the process incorporates reasons for referral related to HTN that were initially excluded, and also includes a periodic update to validate new expressions entered in the information system. Text processing tools and quantitative techniques were used to evaluate the results. False positives were eliminated and terms associated with the disease were incorporated.