{"id":6806,"date":"2018-11-02T12:22:19","date_gmt":"2018-11-02T17:22:19","guid":{"rendered":"https:\/\/www.bu.edu\/gdp\/?p=6806"},"modified":"2023-03-27T16:20:37","modified_gmt":"2023-03-27T20:20:37","slug":"building-a-national-hiv-cohort-from-routine-laboratory-data-probabilistic-record-linkage-with-graphs","status":"publish","type":"post","link":"https:\/\/www.bu.edu\/gdp\/2018\/11\/02\/building-a-national-hiv-cohort-from-routine-laboratory-data-probabilistic-record-linkage-with-graphs\/","title":{"rendered":"Building a National HIV Cohort from Routine Laboratory Data: Probabilistic Record-Linkage with Graphs"},"content":{"rendered":"
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Photo by Irwan iwe via Unsplash.<\/figcaption><\/figure>\n

The management of chronic diseases such as HIV requires healthcare providers to link patient records across multiple interactions with the health system. South Africa\u2019s National Health Laboratory Service (NHLS) conducts all routine laboratory monitoring for the country\u2019s national public sector HIV program but does not use identifiers to track individual patients as they seek care. As a result, the lack of patient identifiers has limited the potential uses of the NHLS database for epidemiological research, policy evaluation and holistic patient care.<\/span><\/p>\n

In a <\/span>new working<\/i> paper<\/b><\/a> published in bioRxiv<\/em>,\u00a0Jacob Bor<\/span><\/a> and colleagues describe the algorithm they developed to give HIV patients in South Africa unique identifiers, therefore enabling analysis of the NHLS database as a national HIV cohort. They linked data on all CD4 glycoprotein counts, HIV viral loads and antiretroviral therapy workup laboratory tests from 2004-2016 to the patient\u2019s name, sex, date of birth, gender and treatment facility.\u00a0<\/span><\/p>\n

Main findings<\/b>:<\/span><\/p>\n