Performance of machine learning algorithms for surgical site infection case detection and prediction: A systematic review and meta-analysis.

Background: Medical researchers and clinicians have shown much interest in developing machine learning (ML) algorithms to detect/predict surgical site infections (SSIs). However, little is known about the overall performance of ML algorithms in predicting SSIs and how to improve the algorithm's robustness. We conducted a systematic review and meta-analysis to summarize the performance of ML algorithms in SSIs case detection and prediction and to describe the impact of using unstructured and textual data in the development of ML algorithms.

Field testing a new ICD coding system: methods and early experiences with ICD-11 Beta Version 2018.

Objective: A beta version (2018) of International Classification of Diseases, 11th Revision for MMS (ICD-11), needed testing. Field-testing involves real-world application of the new codes to examine usability. We describe creating a dataset and characterizing the usability of ICD-11 code set by coders.

Decision algorithm for when to use the ICD-11 3-part model for healthcare harms.

Accurate data collection of healthcare-related adverse events provides a foundation for quality and health system improvement. The International Classification of Diseases for Mortality and Morbidity Statistics, 11th revision (ICD-11 MMS) includes new codes to identify harm or injury and the events or actions leading to the adverse events. However, it is difficult to choose the correct codes without in-depth understanding of which event may be classified as an injury or harm.

Validated algorithms for identifying timing of second event of oropharyngeal squamous cell carcinoma using real-world data.

Background: Understanding occurrence and timing of second events (recurrence and second primary cancer) is essential for cancer specific survival analysis. However, this information is not readily available in administrative data.

Methods: Alberta Cancer Registry, physician claims, and other administrative data were used.

Supervised consumption site enables cost savings by avoiding emergency services: a cost analysis study.

Background And Aims: We report on a cost analysis study, using population level data to determine the emergency service costs avoided from emergency overdose management at supervised consumption services (SCS).

Design: We completed a cost analysis from a payer's perspective. In this setting, there is a single-payer model of service delivery.

Training and experience of coding with the World Health Organization's International Classification of Diseases, Eleventh Revision.

Background: The new International Classification of Diseases, Eleventh Revision for Mortality and Morbidity Statistics (ICD-11) was developed and released by the World Health Organization (WHO) in June 2018. Because ICD-11 incorporates new codes and features, training materials for coding with ICD-11 are urgently needed prior to its implementation.

Objective: This study outlines the development of ICD-11 training materials, training processes and experiences of clinical coders while learning to code using ICD-11.