Generalizability of a Musculoskeletal Therapist Electronic Health Record for Modelling Outcomes to Work-Related Musculoskeletal Disorders.

PURPOSE: Electronic Health Records (EHRs) can contain vast amounts of clinical information that could be reused in modelling outcomes of work-related musculoskeletal disorders (WMSDs). Determining the generalizability of an EHR dataset is an important step in determining the appropriateness of its reuse. The study aims to describe the EHR dataset used by occupational musculoskeletal therapists and determine whether the EHR dataset is generalizable to the Australian workers' population and injury characteristics seen in workers' compensation claims. METHODS: Variables were considered if they were associated with outcomes of WMSDs and variables data were available. Completeness and external validity assessment analysed frequency distributions, percentage of records and confidence intervals. RESULTS: There were 48,434 patient care plans across 10 industries from 2014 to 2021. The EHR collects information related to clinical interventions, health and psychosocial factors, job demands, work accommodations as well as workplace culture, which have all been shown to be valuable variables in determining outcomes to WMSDs. Distributions of age, duration of employment, gender and region of birth were mostly similar to the Australian workforce. Upper limb WMSDs were higher in the EHR compared to workers' compensation claims and diagnoses were similar. CONCLUSION: The study shows the EHR has strong potential to be used for further research into WMSDs as it has a similar population to the Australian workforce, manufacturing industry and workers' compensation claims. It contains many variables that may be relevant in modelling outcomes to WMSDs that are not typically available in existing datasets.

Electronic Health Records for Predicting Outcomes to Work-Related Musculoskeletal Disorders: A Scoping Review.

PURPOSE: Through electronic health records (EHRs), musculoskeletal (MSK) therapists such as chiropractors and physical therapists, as well as occupational medicine physicians could collect data on many variables that can be traditionally challenging to collect in managing work-related musculoskeletal disorders (WMSDs). The review's objectives were to explore the extent of research using EHRs in predicting outcomes of WMSDs by MSK therapists. METHOD: A systematic search was conducted in Medline, PubMed, CINAHL, and Embase. Grey literature was searched. 2156 unique papers were retrieved, of which 38 were included. Three themes were explored, the use of EHRs to predict outcomes to WMSDs, data sources for predicting outcomes to WMSDs, and adoption of standardised information for managing WMSDs. RESULTS: Predicting outcomes of all MSK disorders using EHRs has been researched in 6 studies, with only 3 focusing on MSK therapists and 4 addressing WMSDs. Similar to all secondary data source research, the challenges include data quality, missing data and unstructured data. There is not yet a standardised or minimum set of data that has been defined for MSK therapists to collect when managing WMSD. Further work based on existing frameworks is required to reduce the documentation burden and increase usability. CONCLUSION: The review outlines the limited research on using EHRs to predict outcomes of WMSDs. It highlights the need for EHR design to address data quality issues and develop a standardised data set in occupational healthcare that includes known factors that potentially predict outcomes to help regulators, research efforts, and practitioners make better informed clinical decisions.

A meta-synthesis of competency standards suggest allied health are not preparing for a digital health future.

OBJECTIVE: This study reviewed the competency and threshold standards for allied health professionals to identify the inclusion of digital health competencies. MATERIALS AND METHODS: A nine-stage, sequential meta-synthesis of professional standards was undertaken. Statements relevant to digital health were extracted, categorised by discipline, and coded to the level in the standards, skills or knowledge and level of learning. RESULTS: Eighteen standards were analysed. Of these, fourteen standards contained a total of thirty-five statements related to digital health in the themes of data governance and technologies, but not data translation. Only four disciplines included more than two statements related to digital health. DISCUSSION: The study highlighted four key gaps in the Standards. Statements in competency and threshold standards for allied health professionals lack reference to digital health, with predominantly information management statements. The statements are ambiguously worded, and could be interpreted to only refer to paper records management, and when there is a reference to digital health, it is more likely to be a skill as opposed to knowledge, typically at the indicator or cue level, and largely a lower level of learning (Bloom's). The lack of digital health in standards may result in limited instruction in already full tertiary education curriculum. CONCLUSION: Digital health represents a major gap in competency statements for all allied health disciplines, signifying the need for a national approach to developing quality and specific digital health competencies, to support allied health graduates being prepared to work in the digital health age.

Health Information Management: Changing with Time.

Objective: With the evolution of patient medical records from paper to electronic media and the changes to the way data is sourced, used, and managed, there is an opportunity for health information management (HIM) to learn and facilitate the increasing expanse of available patient data. Methods: This paper discusses the emerging trends and lessons learnt in relation with the following four areas: 1) data and information governance, 2) terminology standards certification, 3) International Classification of Diseases, 11th edition (ICD-11), and 4) data analytics and HIM. Results: The governance of patient data and information increasingly requires the HIM profession to incorporate the roles of data scientists and data stewards into its portfolio to ensure data analytics and digital transformation is appropriately managed. Not only are terminology standards required to facilitate the structure and primary use of this data, developments in Canada in relation with the standards, role descriptions, framework and curricula in the form of certification provide one prime example of ensuring the quality of the secondary use of patient data. The impending introduction of ICD-11 brings with it the need for the HIM profession to manage the transition between ICD versions and country modifications incorporating changes to standards and tools, and the availability and type of patient data available for secondary use. Conclusions: In summary, the health information management profession now requires abilities in leadership, data, and informatics in addition to health information science and coding skills to facilitate the expanding secondary use of patient data.

18F-fluorodeoxyglucose positron emission tomography imaging in brain tumours: the Western Australia positron emission tomography/cyclotron service experience.

(18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) scans in the first 49 patients referred with either possible brain tumour or brain tumour recurrence were reviewed. FDG-PET imaging was reported with reference to anatomical imaging. Based on the report the FDG study was classified as either positive or negative for the presence of tumour. Thirty-eight cases were included in the analysis, 21 having pathological data and 17 with diagnostic clinical follow up. Eleven were excluded, as they had inadequate follow-up data. Of the 21 cases with pathology, 18 were shown to have tumour. In this group there were five false-negative scans and two false-positive PET scans. Seventeen cases were assessed by clinical follow up, nine were considered to have been tumour. There were two false negatives with one false positive. The overall sensitivity, specificity and positive and negative predictive values were 74, 73, 87 and 53% respectively. This is similar to figures previously quoted in published work. Despite relatively limited numbers, the utility of FDG PET imaging in our hands is similar to published reports. With a positive predictive value of 87%, a positive FDG study indicates a high likelihood that there is brain tumour present. A negative study does not exclude the presence of tumour.