Development and evaluation of a de-identification procedure for a case register sourced from mental health electronic records.

BACKGROUND: Electronic health records (EHRs) provide enormous potential for health research but also present data governance challenges. Ensuring de-identification is a pre-requisite for use of EHR data without prior consent. The South London and Maudsley NHS Trust (SLaM), one of the largest secondary mental healthcare providers in Europe, has developed, from its EHRs, a de-identified psychiatric case register, the Clinical Record Interactive Search (CRIS), for secondary research. METHODS: We describe development, implementation and evaluation of a bespoke de-identification algorithm used to create the register. It is designed to create dictionaries using patient identifiers (PIs) entered into dedicated source fields and then identify, match and mask them (with ZZZZZ) when they appear in medical texts. We deemed this approach would be effective, given high coverage of PI in the dedicated fields and the effectiveness of the masking combined with elements of a security model. We conducted two separate performance tests i) to test performance of the algorithm in masking individual true PIs entered in dedicated fields and then found in text (using 500 patient notes) and ii) to compare the performance of the CRIS pattern matching algorithm with a machine learning algorithm, called the MITRE Identification Scrubber Toolkit - MIST (using 70 patient notes - 50 notes to train, 20 notes to test on). We also report any incidences of potential breaches, defined by occurrences of 3 or more true or apparent PIs in the same patient's notes (and in an additional set of longitudinal notes for 50 patients); and we consider the possibility of inferring information despite de-identification. RESULTS: True PIs were masked with 98.8% precision and 97.6% recall. As anticipated, potential PIs did appear, owing to misspellings entered within the EHRs. We found one potential breach. In a separate performance test, with a different set of notes, CRIS yielded 100% precision and 88.5% recall, while MIST yielded a 95.1% and 78.1%, respectively. We discuss how we overcome the realistic possibility - albeit of low probability - of potential breaches through implementation of the security model. CONCLUSION: CRIS is a de-identified psychiatric database sourced from EHRs, which protects patient anonymity and maximises data available for research. CRIS demonstrates the advantage of combining an effective de-identification algorithm with a carefully designed security model. The paper advances much needed discussion of EHR de-identification - particularly in relation to criteria to assess de-identification, and considering the contexts of de-identified research databases when assessing the risk of breaches of confidential patient information.

Acute hospital service utilization by inpatients in psychiatric hospitals.

OBJECTIVE: Standardized mortality ratios are twice the population average in the year following a mental health admission, yet there is a relative paucity of research on uptake of general medical care in psychiatric inpatients. METHODS: A retrospective database analysis was performed to ascertain the frequency of acute medical care usage by psychiatric inpatients. Data were gathered through a static linkage between anonymized clinical records in a large UK mental health provider and the national hospital activity database (Hospital Episode Statistics) over 1year from 2010 to 2011. RESULTS: Over the year, 10.4% of the 8023 psychiatric admission episodes included at least one night in a general hospital during that psychiatric inpatient stay, while 12.0% of psychiatry admission episodes entailed an emergency department (ED) visit. Over the course of the full year, of the 4674 people admitted to the mental health provider at least once, 16.0% were admitted to a general hospital while registered as a mental health inpatient and 18.0% were seen in the ED. Patients were simultaneously registered as occupying beds in both general and psychiatric hospitals for a total of 5163 bed days at a cost of £2.4 million over the year. CONCLUSION: This large population-based linkage study indicates a high rate of general hospital utilization by psychiatric inpatients in an independent mental health provider. The need for combined, flexible and practical approaches to the medical care of psychiatric inpatients is highlighted to reduce unplanned care and provide treatment in the site best suited to the patient's needs.

A cohort study on mental disorders, stage of cancer at diagnosis and subsequent survival.

OBJECTIVES: To assess the stage at cancer diagnosis and survival after cancer diagnosis among people served by secondary mental health services, compared with other local people. SETTING: Using the anonymised linkage between a regional monopoly secondary mental health service provider in southeast London of four London boroughs, Croydon, Lambeth, Lewisham and Southwark, and a population-based cancer register, a historical cohort study was constructed. PARTICIPANTS: A total of 28 477 cancer cases aged 15+ years with stage of cancer recorded at diagnosis were identified. Among these, 2206 participants had been previously assessed or treated in secondary mental healthcare before their cancer diagnosis and 125 for severe mental illness (schizophrenia, schizoaffective or bipolar disorders). PRIMARY AND SECONDARY OUTCOME MEASURES: Stage when cancer was diagnosed and all-cause mortality after cancer diagnosis among cancer cases registered in the geographical area of southeast London. RESULTS: Comparisons between people with and without specific psychiatric diagnosis in the same residence area for risks of advanced stage of cancer at diagnosis and general survival after cancer diagnosed were analysed using logistic and Cox models. No associations were found between specific mental disorder diagnoses and beyond local spread of cancer at presentation. However, people with severe mental disorders, depression, dementia and substance use disorders had significantly worse survival after cancer diagnosis, independent of cancer stage at diagnosis and other potential confounders. CONCLUSIONS: Previous findings of associations between mental disorders and cancer mortality are more likely to be accounted for by differences in survival after cancer diagnosis rather than by delayed diagnosis.