Identifying Veterans Using Electronic Health Records in the United Kingdom: A Feasibility Study

Abstract

There is a lack of quantitative evidence concerning UK (United Kingdom) Armed Forces (AF) veterans who access secondary mental health care services—specialist care often delivered in high intensity therapeutic clinics or hospitals—for their mental health difficulties. The current study aimed to investigate the utility and feasibility of identifying veterans accessing secondary mental health care services using National Health Service (NHS) electronic health records (EHRs) in the UK. Veterans were manually identified using the Clinical Record Interactive Search (CRIS) system—a database holding secondary mental health care EHRs for an NHS Trust in the UK. We systematically and manually searched CRIS for veterans, by applying a military-related key word search strategy to the free-text clinical notes completed by clinicians. Relevant data on veterans’ socio-demographic characteristics, mental disorder diagnoses and treatment pathways through care were extracted for analysis. This study showed that it is feasible, although time consuming, to identify veterans through CRIS. Using the military-related key word search strategy identified 1600 potential veteran records. Following manual review, 693 (43.3%) of these records were verified as “probable” veterans and used for analysis. They had a median age of 74 years (interquartile range (IQR): 53–86); the majority were male (90.8%) and lived alone (38.0%). The most common mental diagnoses overall were depressive disorders (22.9%), followed by alcohol use disorders (10.5%). Differences in care pathways were observed between pre and post national service (NS) era veterans. This feasibility study represents a first step in showing that it is possible to identify veterans through free-text clinical notes. It is also the first to compare veterans from pre and post NS era.

Rates and Associated Factors of Secondary Mental Health Care Utilisation among Ex-Military Personnel in the United States: A Narrative Review

“…These registers are advantageous in providing rich material and numerous measurement points for large numbers of participants [44]. On the other hand, limitations of electronic systems include the large amounts of missing data often present [45,46], non-standardised clinical free-text notes [46,47], and a lack of information regarding undiagnosed mentally ill individuals [48].…”

Military veterans and civilians’ mental health diagnoses: an analysis of secondary mental health services

“…As there is no marker to identify veterans in EHRs, this study employed the Military Service Identification Tool (MSIT) [ 15 ], a machine learning computer tool, to identify military veterans using probabilistic modelling of free-text clinical notes. The MSIT was found to have high precision and accuracy for correctly detecting veterans in EHRs, with an overall accuracy rating of 97% [ 15 , 16 ].…”

Identification/Non-Identification Among U.K. Veterans in Scotland

“…Forty-seven percent were referred from the NHS 5 and 16% were referred from other veterans, findings which point to the importance of raising visibility in the health sector and establishing social networks amongst the veteran community. The role of the NHS as a means by which to identify veterans has been highlighted (Mark et al, 2020) and greater use of the NHS as a frontline means of identification has been urged (Finnigan et al, 2018).…”

“…Perhaps one of the biggest barriers to identifying veterans, or having veterans self-identify, is the lack of a formal centralised veteran database in the U.K. itself. It is currently the case that the number of veterans within U.K. society remains a projection (Ministry of Defence, 2019) and numbers range up to 2.5 million individuals (Mark, et al, 2020). The same applies to Scotland, the focus of our work, and the number here is even less specific.…”