Electronic Health Records Role in Predicting Outcomes to Work-Related Musculoskeletal Disorders: A Study Protocol.

Work-related musculoskeletal disorders are increasing in cost and time lost from work. Electronic health records have the potential to provide rich data to help inform and predict outcomes to WMSDs. The objective is to compare an EHR dataset from an occupational health service to comparative data, to help determine if the EHR dataset can be used in future studies to predict outcomes to care.

Understanding Clinician EHR Data Quality for Reuse in Predictive Modelling.

It is imperative to build clinician trust to reuse ever-growing amounts of rich clinical data. Utilising a proprietary, structured electronic health record, we address data quality by assessing the plausibility of chiropractors, physical therapists and osteopaths' data entry to help determine if the data is fit for use in predicting outcomes of work-related musculoskeletal disorders using machine learning. For most variables assessed, individual clinician data entry positively correlated to the clinician group's data entry, indicating data is fit for reuse. However, from the clinician's perspective, there were inconsistencies, which could lead to data mistrust. When assessing data quality in EHR studies, it is crucial to engage clinicians with their deep understanding of EHR use, as improvement suggestions could be made. Clinicians should be considered local knowledge experts.