English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Background To assess the performance of various coding algorithms for identifying people with hepatitis B virus (HBV) and hepatitis C virus (HCV) using claims data according to different reference standards (RSs) and study periods (SPs). Methods A proportional random sampling of 10,000 patients aged ≥ 20 years in a health care system in Southern Taiwan were enrolled as study participants. We used three hierarchical RSs (RS1: having positive results of laboratory tests; R2: having RS1 or having prescriptions of anti-HBV or anti-HCV medications; R3: having R1 or R2 or having textual diagnosis recorded in electrical medical records) with three SPs (4-, 8-, and 12-years) to calculate positive predictive value (PPV) and sensitivity (Sen) of 6 coding algorithms using HBV- and HCV-related  International Classification of Disease Tenth Revision Clinical Modification  ( ICD-10-CM ) codes in Taiwan National Health Insurance claims data for years 2016–2019. Results Of 10,000 enrolled participants, the number of participants had confirmed HBV and HCV was 146 and 165, respectively according to RS1 with 4-years SP and increased to 729 and 525, respectively according to RS3 with 12-years SP. For both HBV and HCV, the PPV was lowest according to RS1 and highest according to RS3. The longer the SP, the higher the PPV. However, the Sen was highest according to RS2 with 4-years SP. For both HBV and HCV, the coding algorithm with highest PPV and Sen was “ ≥ 3 outpatient codes” and “ ≥ 2 outpatient or ≥ 1 inpatients codes,” respectively. Conclusions In conclusion, using different RSs with different SPs would result in different estimation of PPV and Sen. To achieve the best yield of both PPV and Sen, the optimal coding algorithm is “ ≥ 2 outpatients or ≥ 1 inpatients codes” for identifying people with HBV or HCV.

Validation of coding algorithms for identifying people with viral hepatitis using claims data according to different standard references