Matches in SemOpenAlex for { <https://semopenalex.org/work/W3114808547> ?p ?o ?g. }
- W3114808547 endingPage "107416" @default.
- W3114808547 startingPage "107416" @default.
- W3114808547 abstract "Medical errors constitute a significant challenge affecting patient and staff safety in complex and dynamic healthcare systems. While various organizational factors may contribute to such errors, limited studies have addressed patient and staff safety issues simultaneously in the same study setting. To evaluate this, we conduct an exploratory analysis using two types of tree-based machine learning algorithms, random forests and gradient boosting, and the hospital-level aggregate staff experience survey data from UK hospitals. Based on staff views and priorities, the results from both algorithms suggest that “health and wellbeing” is the leading theme associated with the number of reported errors and near misses harming patient and staff safety. Specifically, “work-related stress” is the most important survey item associated with safety outcomes. With respect to prediction accuracy, both algorithms provide similar results with comparable values in error metrics. Based on the analytical results, healthcare risk managers and decision-makers can develop and implement policies and practices that address staff experience and prioritize resources effectively to improve patient and staff safety." @default.
- W3114808547 created "2021-01-05" @default.
- W3114808547 creator A5054604298 @default.
- W3114808547 creator A5062430416 @default.
- W3114808547 creator A5074455285 @default.
- W3114808547 creator A5082357489 @default.
- W3114808547 creator A5084847550 @default.
- W3114808547 date "2021-04-01" @default.
- W3114808547 modified "2023-10-16" @default.
- W3114808547 title "A comparative study of patient and staff safety evaluation using tree-based machine learning algorithms" @default.
- W3114808547 cites W1487727533 @default.
- W3114808547 cites W1536315814 @default.
- W3114808547 cites W1641431478 @default.
- W3114808547 cites W1678356000 @default.
- W3114808547 cites W1714083232 @default.
- W3114808547 cites W1969885422 @default.
- W3114808547 cites W1970588955 @default.
- W3114808547 cites W1978237455 @default.
- W3114808547 cites W1995793930 @default.
- W3114808547 cites W1998025025 @default.
- W3114808547 cites W2003015733 @default.
- W3114808547 cites W2006353560 @default.
- W3114808547 cites W2013373955 @default.
- W3114808547 cites W2026587832 @default.
- W3114808547 cites W2052867931 @default.
- W3114808547 cites W2062612702 @default.
- W3114808547 cites W2065775831 @default.
- W3114808547 cites W2070370095 @default.
- W3114808547 cites W2070493638 @default.
- W3114808547 cites W2092505366 @default.
- W3114808547 cites W2106082968 @default.
- W3114808547 cites W2143481518 @default.
- W3114808547 cites W2154741265 @default.
- W3114808547 cites W2159113688 @default.
- W3114808547 cites W2171184561 @default.
- W3114808547 cites W2204197063 @default.
- W3114808547 cites W221430152 @default.
- W3114808547 cites W2262790950 @default.
- W3114808547 cites W2296558069 @default.
- W3114808547 cites W2319748385 @default.
- W3114808547 cites W2344072891 @default.
- W3114808547 cites W2346834216 @default.
- W3114808547 cites W2397224336 @default.
- W3114808547 cites W2398094216 @default.
- W3114808547 cites W2415905670 @default.
- W3114808547 cites W2568932432 @default.
- W3114808547 cites W2593192889 @default.
- W3114808547 cites W2736964911 @default.
- W3114808547 cites W2741099223 @default.
- W3114808547 cites W2773309836 @default.
- W3114808547 cites W2782846081 @default.
- W3114808547 cites W2786275068 @default.
- W3114808547 cites W2789519695 @default.
- W3114808547 cites W2801837099 @default.
- W3114808547 cites W2802643674 @default.
- W3114808547 cites W2804877181 @default.
- W3114808547 cites W2857887762 @default.
- W3114808547 cites W2889418550 @default.
- W3114808547 cites W2893026898 @default.
- W3114808547 cites W2901106616 @default.
- W3114808547 cites W2902660003 @default.
- W3114808547 cites W2906245976 @default.
- W3114808547 cites W2921124928 @default.
- W3114808547 cites W2948678706 @default.
- W3114808547 cites W2950419939 @default.
- W3114808547 cites W2951323722 @default.
- W3114808547 cites W2952539326 @default.
- W3114808547 cites W2960050274 @default.
- W3114808547 cites W2981915020 @default.
- W3114808547 cites W2983579676 @default.
- W3114808547 cites W2999477184 @default.
- W3114808547 cites W3003049325 @default.
- W3114808547 cites W3004500195 @default.
- W3114808547 cites W3005828492 @default.
- W3114808547 cites W3006902195 @default.
- W3114808547 cites W3033073186 @default.
- W3114808547 cites W3033308296 @default.
- W3114808547 cites W3035443326 @default.
- W3114808547 cites W3046400528 @default.
- W3114808547 cites W3049586794 @default.
- W3114808547 cites W3080572068 @default.
- W3114808547 cites W3093232111 @default.
- W3114808547 cites W3103897629 @default.
- W3114808547 doi "https://doi.org/10.1016/j.ress.2020.107416" @default.
- W3114808547 hasPublicationYear "2021" @default.
- W3114808547 type Work @default.
- W3114808547 sameAs 3114808547 @default.
- W3114808547 citedByCount "13" @default.
- W3114808547 countsByYear W31148085472021 @default.
- W3114808547 countsByYear W31148085472022 @default.
- W3114808547 countsByYear W31148085472023 @default.
- W3114808547 crossrefType "journal-article" @default.
- W3114808547 hasAuthorship W3114808547A5054604298 @default.
- W3114808547 hasAuthorship W3114808547A5062430416 @default.
- W3114808547 hasAuthorship W3114808547A5074455285 @default.
- W3114808547 hasAuthorship W3114808547A5082357489 @default.
- W3114808547 hasAuthorship W3114808547A5084847550 @default.
- W3114808547 hasConcept C11413529 @default.