The Rhabdomyolysis Evaluation in the Emergency Department (REED) Score - a Risk Prediction Model for Older Adults in the Emergency Department With Rhabdomyolysis After Prolonged Immobilisation ("Long Lie")

There is no RPM in existence to understand which older adult patients who fall and develop rhabdomyolysis secondary to a "long lie" will have a poor outcome (AKI, KRT, death). Therefore, it will be beneficial to understand which patients need admission for in-patient care to reduce sequelae [bad outcomes] and which patients can avoid hospital associated issues (e.g. deconditioning, infections) and be safely discharged home. This will be achieved with a retrospective longitudinal cohort study, specifically a retrospective chart review where electronic medical/health records will be reviewed by one researcher (the Principal Investigator [PI]) to abstract key data to identify the risk factors associated with poor outcomes after having a fall and a long lie. The medical/health records are what the PI would use in their normal clinical and non-clinical role when working for the NHS Trust. The main electronic patient records that will be utilised is the 'Acute Care Portal' which has emergency department, prehospital ambulance data, community/primary care and in patient speciality teams/departments records available. This is likely where the majority of the data required will be abstracted from but other clinical systems such as 'SystmOne' may be utilised to check if a patient died since being back in the community (outside the acute hospital Trust). Additionally, the medical/health records for patients who attend the critical care unit (CCU) are within a system called 'Metavision', this will be reviewed for patients that attended the CCU.

The data will be input into a data abstraction tool (DAT) which is an Excel Spreadsheet (XLS). This will include a study ID (a number ascending from 1) and not patient identifiable information such as the NHS number. This ensures that the DAT will be a pseudonymised dataset. This will be saved on the University of Salford (UoS) password protected and two factor authenticated OneDrive of the PI. The participants will be identified through a dataset produced by the NHS laboratory data team which shall be emailed to the NHSMail account of the PI. This will be provided to the NHS Trust Healthcare Analytics team who will upload the dataset to the NHS England Digital Message Exchange for Social Care and Health (MESH) portal to assess for any patients who has opted out using the National Data Opt Out (NDOO). Once this is returned to the PI via NHSMail this will act as the data linkage file (DLF). The pseudonymised dataset can be viewed (but not edited) by the three co-investigators (research supervisors) via UoS OneDrive. The DLF can only be accessed by the PI via the password protected, two factor authenticated NHSMail OneDrive.

Once the study has completed (defined as when the study is published in a peer reviewed journal) the DLF will be permanently deleted by the NHS IT team at which point the pseudonymised DAT dataset becomes anonymised as it can no longer be linked back to individual patients. The anonymised dataset will be changed to a comma-separated values (CSV) format for data preservation and uploaded to the UoS Research Repository, Figshare for 10 years. After the 10 years it will be permanently deleted by the UoS IT Team. Once the anonymised dataset is uploaded to Figshare the version on UoS OneDrive will be permanently deleted by the UoS IT team.

A waiver of consent is being requested to the Confidentiality Advisory Group (CAG) to minimise any harm/distress to the participants or their families. This is because the data is routinely collected and will not negatively affect the participants through the access of routinely collected data being utilised for another purpose (research). Additionally, some of the participants will have subsequently died or may have cognitive issues which are important participants to include so the research is representative of the real world. Excluding these vulnerable groups or avoiding recruiting these would not represent the real-world issues and could disadvantage future patients with similar conditions. Participants that have opted out of their data being used for research purposes will not be included but other participants will be included to ensure that future patients can be managed appropriately, safely and based on contemporaneous evidence.

Direct risk to patients is minimised by seeking CAG approval opposed to directly seeking consent from every individual patient/family member. Indirect harm from data breaches will be minimised by having a robust data management plan (DMP) in place. This clearly sates how the DAT and DLF will be stored, on what platform and how it will be shared as previously stated.