Dan Li, Dawei Gao, Masaaki Yamada, Chuangbin Chen, Liuchun Xiang, Haisong Nie
Healthcare-seeking behavior and spatial variation of internal migrants with chronic diseases: a nationwide empirical study in China
Geospatial health
automated surveillance methods increasingly replace support conventional manual surveillance latter labor intensive vulnerable subjective interpretation sought validate 2 previously developed semiautomated surveillance algorithms identify deep surgical site infections ssis patients undergoing colorectal surgeries dutch hospitals multicenter retrospective cohort study 4 hospitals selected colorectal surgery patients 2018 2019 based procedure codes extracted routine care data electronic health records per hospital classification model regression model applied independently classify patients low high probability developed deep ssi highprobability patients need manual ssi confirmation lowprobability records classified deep ssi sensitivity positive predictive value ppv workload reduction calculated compared conventional surveillance total 672 colorectal surgery patients included 28 41 developed deep ssi surveillance models achieved good performance adaptation clinical practice classification model 100 sensitivity ppv ranged 111 458 hospitals regression model 100 sensitivity 90149 ppv models 25 records needed review confirm ssi regression model requires complex data management skills partly due incomplete data independent external validation surveillance models performed well classification model preferred regression model sourcedata availability less complex datamanagement requirements next step implementation infection prevention practices workflow processes