The Akrivia Health Secure Data Access Service
Akrivia Heath curates a dataset of 5.1 million patients’ electronic health records (EHRs) from secondary care psychiatric healthcare organisations (HCOs) in England and Wales, available for research access. DOWNLOAD now by filling out the form below.
Treatment resistant depression: A comparative study of access, pathways, and outcomes between Caucasian and ethnic minority individuals
Background Treatment resistant depression (TRD) is considered when an individual fails to respond to two or more different antidepressants in adequate doses, duration and with adequate adherence within the same major depressive episode. Aim To examine the clinical profiles of TRD patients through data from electronic healthcare records and compare characteristics and treatment pathways of…
Using Electronic Health Records to Recruit Patients with Mild Cognitive Impairment for Clinical Trials
Clinical trials for psychotropic medication typically involve an elaborate screening process, where patients are required to meet complex inclusion and exclusion criteria to qualify for research participation. Screening criteria are usually envisaged with the aim to identify people who have a clear-cut diagnosis without many otherwise frequent comorbidities. However, psychiatric patients often exhibit traits present…
A data-driven approach to clinical trial patient samples
Ana Todorovic, Sophie Gibbons, Philip Craig, Benjamin Fell MQDataMind2023_Poster_ATDownload IntroductionPsychotropic drug trials often involve a substantial period of patient recruitment. Psychiatrists typically use their own judgment to sequentially approach patients who might fulfill complex inclusion and exclusion criteria. However, information already present in patient records can also be used to constrain who is approached for…
Patient and Public Involvement Co-Development of a Route to Record-Level Data Access to Akrivia Health’s Secondary Healthcare Dataset
PPI_Poster_SG_PK_v2-1-CopyDownload Names: Panagiota Kontari, Sophie Gibbons, Simon Pilinger, Elizabeth Ford, Benjamin Fell Background Using electronic health records (EHRs) as a source of real-world health data in research has vast potential for public good. Record-level data access (RLDA) provides further analysis utility beyond that of aggregate data, however, often raises concerns among patients and the public,…
Identifying Predictors of Suicide in Severe Mental Illness: A Feasibility Study of a Clinical Prediction Rule (Oxford Mental Illness and Suicide Tool or OxMIS)
Background: Oxford Mental Illness and Suicide tool (OxMIS) is a brief, scalable, freely available, structured risk assessment tool to assess suicide risk in patients with severe mental illness (schizophrenia-spectrum disorders or bipolar disorder). OxMIS requires further external validation, but a lack of large-scale cohorts with relevant variables makes this challenging. Electronic health records provide possible data sources for…