Suicide Information Database-Cymru: a protocol for a population-based, routinely collected data linkage study to explore risks and patterns of healthcare contact prior to suicide to identify opportunities for intervention

Police and hospital data linkage for traffic injury surveillance: A systematic review

This systematic review examines studies of traffic injury that involved linkage of police crash data and hospital data and were published from 1994 to 2023 worldwide in English. Inclusion and exclusion criteria were the basis for selecting papers from PubMed, Web of Science, and Scopus, and for identifying additional relevant papers using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and supplementary snowballing (n = 60). The selected papers were reviewed in terms of research objectives, data items and sample size included, temporal and spatial coverage, linkage methods and software tools, as well as linkage rates and most significant findings. Many studies found that the number of clinically significant road injury cases was much higher according to hospital data than crash data. Under-estimation of cases in crash data differs by road user type, pedestrian cases commonly being highly under-counted. A limited number of the papers were from low- and middle-income countries. The papers reviewed lack consistency in what was reported and how, which limited comparability.

Alcohol-Specific Mortality in People With Epilepsy: Cohort Studies in Two Independent Population-Based Datasets

Objectives: The risk of dying by alcohol-specific causes in people with epilepsy has seldom been reported from population-based studies. We aimed to estimate the relative risk of alcohol-specific mortality in people with epilepsy, and the extent to which problematic alcohol use was previously identified in the patients' medical records.

Method: We delineated cohort studies in two population-based datasets, the Clinical Practice Research Datalink (CPRD GOLD) in England (January 01, 2001–December 31, 2014) and the Secure Anonymised Information Linkage (SAIL) Databank in Wales (January 01, 2001–December 31, 2014), linked to hospitalization and mortality records. People with epilepsy were matched to up to 20 persons without epilepsy on gender, age (±2 years) and registered general practice. We identified alcohol-specific death from Office for National Statistics (ONS) records using specified ICD-10 codes. We further identified prescriptions, interventions and hospitalisations related to alcohol use.

Results: In the CPRD GOLD, we identified 9,871 individuals in the incident epilepsy cohort and 185,800 in the comparison cohort and, in the SAIL Databank, these numbers were 5,569 and 110,021, respectively. We identified a five-fold increased risk of alcohol-specific mortality in people with epilepsy vs. those without the condition in our pooled estimate across the two datasets (deprivation-adjusted HR 4.85, 95%CI 3.46–6.79).

Conclusions: People with epilepsy are at increased risk of dying by an alcohol-specific cause than those without the disorder. It is plausible that serious alcohol misuse could either contribute to the development of epilepsy or it could commence subsequent to epilepsy being diagnosed. Regardless of the direction of the association, it is important that the risk of dying as a consequence of alcohol misuse is accurately quantified in people affected by epilepsy. Systematically-applied, sensitive assessment of alcohol consumption by healthcare professionals, at opportunistic, clinical contacts, with rapid access to quality treatment services, should be mandatory and play a key role in reduction of health harms and mortality.

Contacts with primary and secondary healthcare prior to suicide: case-control whole-population-based study using person-level linked routine data in Wales, UK, 2000-2017

BACKGROUND

Longitudinal studies of patterns of healthcare contacts in those who die by suicide to identify those at risk are scarce.

AIMS

To examine type and timing of healthcare contacts in those who die by suicide.

METHOD

A population-based electronic case-control study of all who died by suicide in Wales, 2001-2017, linking individuals' electronic healthcare records from general practices, emergency departments and hospitals. We used conditional logistic regression to calculate odds ratios, adjusted for deprivation. We performed a retrospective continuous longitudinal analysis comparing cases' and controls' contacts with health services.

RESULTS

We matched 5130 cases with 25 650 controls (5 per case). A representative cohort of 1721 cases (8605 controls) were eligible for the fully linked analysis. In the week before their death, 31.4% of cases and 15.6% of controls contacted health services. The last point of contact was most commonly associated with mental health and most often occurred in general practices. In the month before their death, 16.6 and 13.0% of cases had an emergency department contact and a hospital admission respectively, compared with 5.5 and 4.2% of controls. At any week in the year before their death, cases were more likely to contact healthcare services than controls. Self-harm, mental health and substance misuse contacts were strongly linked with suicide risk, more so when they occurred in emergency departments or as emergency admissions.

CONCLUSIONS

Help-seeking occurs in those at risk of suicide and escalates in the weeks before their death. There is an opportunity to identify and intervene through these contacts.

Risk of Unnatural Mortality in People With Epilepsy

Importance

People with epilepsy are at increased risk of mortality, but, to date, the cause-specific risks of all unnatural causes have not been reported.

Objective

To estimate cause-specific unnatural mortality risks in people with epilepsy and to identify the medication types involved in poisoning deaths.

Design, Setting, and Participants

This population-based cohort study used 2 electronic primary care data sets linked to hospitalization and mortality records, the Clinical Practice Research Datalink (CPRD) in England (from January 1, 1998, to March 31, 2014) and the Secure Anonymised Information Linkage (SAIL) Databank in Wales (from January 1, 2001, to December 31, 2014). Each person with epilepsy was matched on age (within 2 years), sex, and general practice with up to 20 individuals without epilepsy. Unnatural mortality was determined using International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes V01 through Y98 in the Office for National Statistics mortality records. Hazard ratios (HRs) were estimated in each data set using a stratified Cox proportional hazards model, and meta-analyses were conducted using DerSimonian and Laird random-effects models. The analysis was performed from January 5, 2016, to November 16, 2017.

Exposures

People with epilepsy were identified using primary care epilepsy diagnoses and associated antiepileptic drug prescriptions.

Main Outcomes and Measures

Hazard ratios (HRs) for unnatural mortality and the frequency of each involved medication type estimated as a percentage of all medication poisoning deaths.

Results

In total, 44 678 individuals in the CPRD and 14 051 individuals in the SAIL Databank were identified in the prevalent epilepsy cohorts, and 891 429 (CPRD) and 279 365 (SAIL) individuals were identified in the comparison cohorts. In both data sets, 51% of the epilepsy and comparison cohorts were male, and the median age at entry was 40 years (interquartile range, 25-60 years) in the CPRD cohorts and 43 years (interquartile range, 24-64 years) in the SAIL cohorts. People with epilepsy were significantly more likely to die of any unnatural cause (HR, 2.77; 95% CI, 2.43-3.16), unintentional injury or poisoning (HR, 2.97; 95% CI, 2.54-3.48) or suicide (HR, 2.15; 95% CI, 1.51-3.07) than people in the comparison cohort. Particularly large risk increases were observed in the epilepsy cohorts for unintentional medication poisoning (HR, 4.99; 95% CI, 3.22-7.74) and intentional self-poisoning with medication (HR, 3.55; 95% CI, 1.01-12.53). Opioids (56.5% [95% CI, 43.3%-69.0%]) and psychotropic medication (32.3% [95% CI, 20.9%-45.3%)] were more commonly involved than antiepileptic drugs (9.7% [95% CI, 3.6%-19.9%]) in poisoning deaths in people with epilepsy.

Conclusions and Relevance

Compared with people without epilepsy, people with epilepsy are at increased risk of unnatural death and thus should be adequately advised about unintentional injury prevention and monitored for suicidal ideation, thoughts, and behaviors. The suitability and toxicity of concomitant medication should be considered when prescribing for comorbid conditions.

The case for case-control studies in the field of suicide prevention

Much of our knowledge about the risk factors for suicide comes from case-control studies that either use a psychological autopsy approach or are nested within large register-based cohort studies. We would argue that case-control studies are appropriate in the context of a rare outcome like suicide, but there are issues with using this design. Some of these issues are common in psychological autopsy studies and relate to the selection of controls (e.g. selection bias caused by the use of controls who have died by other causes, rather than live controls) and the reliance on interviewing informants (e.g. recall bias caused by the loved ones of cases having thought about the events leading up to the suicide in considerable detail). Register-based studies can overcome some of these problems because they draw upon contain information that is routinely collected for administrative purposes and gathered in the same way for cases and controls. However, they face issues that mean that psychological autopsy studies will still sometimes be the study design of choice for investigating risk factors for suicide. Some countries, particularly low and middle income countries, don't have sophisticated population-based registers. Even where they do exist, there will be variable of interest that are not captured by them (e.g. acute stressful life events that may immediately precede a suicide death), or not captured in a comprehensive way (e.g. suicide attempts and mental illness that do not result in hospital admissions). Future studies of risk factors should be designed to progress knowledge in the field and overcome the problems with the existing studies, particularly those using a case-control design. The priority should be pinning down the risk factors that are amenable to modification or mitigation through interventions that can successfully be rolled out at scale.

Childhood adversity, mental health and suicide (CHASE): a methods protocol for a longitudinal case-control linked data study

Introduction

Suicide is a tragic outcome with devastating consequences. In 2018, Scotland experienced a 15% increase in suicide from 680 to 784 deaths. This was marked among young people, with an increase of 53% in those aged 15-24, the highest since 2007. Early intervention in those most at risk is key, but identification of individuals at risk is complex, and efforts remain largely targeted towards universal suicide prevention strategies with little evidence of effectiveness.

Recent evidence suggests childhood adversity is a predictor of subsequent poor social and health outcomes, including suicide. This protocol reports on methodology for harmonising lifespan hospital contacts for childhood adversity, mental health, and suicidal behaviour. This will inform where to 1) focus interventions, 2) prioritise trauma-informed approaches, and 3) adapt support avenues earlier in life for those most at risk.

Methods

This study will follow a case-control design. Scottish hospital data (physical health SMR01; mental health SMR04; maternity/birth record SMR02; mother’s linked data SMR01, SMR04, death records) from 1981 to as recent as available will be extracted for people who died by suicide aged 10-34, and linked on Community Health Index unique identifier. A randomly selected control population matched on age and geography at death will be extracted in a 1:10 ratio. International Classification of Disease (ICD) codes will be harmonised between ICD9-CM, ICD9, ICD10-CM and ICD10 for childhood adversity, mental health, and suicidal behaviour.

Results

ICD codes for childhood adversity from four key studies are reported in two categories, 1) Maltreatment or violence-related codes, and 2) Codes suggestive of maltreatment. ‘Clinical Classifications Software’ ICD codes to operationalise mental health codes are also reported. Harmonised lifespan ICD categories were achieved semi-automatically, but required labour-intensive supplementary manual coding. Cross-mapped codes are reported.

Conclusion

There is a dearth of evidence about touchpoints prior to suicide. This study reports methods and harmonised ICD codes along the lifespan to understand hospital contact patterns for childhood adversity, which come to the attention of hospital practitioners.

Key words

Childhood Adversity, Adverse Childhood Experiences, Mental Health, Self-harm, Suicide, Suicidality, Violence, Hospital episodes, Routine Data, Data Linkage, Study Protocol

Individual, programmatic and systemic indicators of the quality of mental health care using a large health administrative database: an avenue for preventing suicide mortality

Suicide is a major public health issue in Canada. The quality of health care services, in addition to other individual and population factors, has been shown to affect suicide rates. In publicly managed care systems, such as systems in Canada and the United Kingdom, the quality of health care is manifested at the individual, program and system levels. Suicide audits are used to assess health care services in relation to the deaths by suicide at individual level and when aggregated at the program and system levels. Large health administrative databases comprise another data source used to inform population-based decisions at the system, program and individual levels regarding mental health services that may affect the risk of suicide. This status report paper describes a project we are conducting at the Institut national de santé publique du Québec (INSPQ) with the Quebec Integrated Chronic Disease Surveillance System (QICDSS) in collaboration with colleagues from Wales (United Kingdom) and the Norwegian Institute of Public Health. This study describes the development of quality of care indicators at three levels and the corresponding statistical analysis strategies designed. We propose 13 quality of care indicators, including system-level and several population-level determinants, primary care treatment, specialist care, the balance between care sectors, emergency room utilization, and mental health and addiction budgets, that may be drawn from a chronic disease surveillance system.

Using Neural Networks with Routine Health Records to Identify Suicide Risk: Feasibility Study

BACKGROUND

Each year, approximately 800,000 people die by suicide worldwide, accounting for 1-2 in every 100 deaths. It is always a tragic event with a huge impact on family, friends, the community and health professionals. Unfortunately, suicide prevention and the development of risk assessment tools have been hindered by the complexity of the underlying mechanisms and the dynamic nature of a person's motivation and intent. Many of those who die by suicide had contact with health services in the preceding year but identifying those most at risk remains a challenge.

OBJECTIVE

To explore the feasibility of using artificial neural networks with routinely collected electronic health records to support the identification of those at high risk of suicide when in contact with health services.

METHODS

Using the Secure Anonymised Information Linkage Databank UK, we extracted the data of those who died by suicide between 2001 and 2015 and paired controls. Looking at primary (general practice) and secondary (hospital admissions) electronic health records, we built a binary feature vector coding the presence of risk factors at different times prior to death. Risk factors included: general practice contact and hospital admission; diagnosis of mental health issues; injury and poisoning; substance misuse; maltreatment; sleep disorders; and the prescription of opiates and psychotropics. Basic artificial neural networks were trained to differentiate between the suicide cases and paired controls. We interpreted the output score as the estimated suicide risk. System performance was assessed with 10x10-fold repeated cross-validation, and its behavior was studied by representing the distribution of estimated risk across the cases and controls, and the distribution of factors across estimated risks.

RESULTS

We extracted a total of 2604 suicide cases and 20 paired controls per case. Our best system attained a mean error rate of 26.78% (SD 1.46; 64.57% of sensitivity and 81.86% of specificity). While the distribution of controls was concentrated around estimated risks < 0.5, cases were almost uniformly distributed between 0 and 1. Prescription of psychotropics, depression and anxiety, and self-harm increased the estimated risk by ~0.4. At least 95% of those presenting these factors were identified as suicide cases.

CONCLUSIONS

Despite the simplicity of the implemented system, the proposed methodology obtained an accuracy like other published methods based on specialized questionnaire generated data. Most of the errors came from the heterogeneity of patterns shown by suicide cases, some of which were identical to those of the paired controls. Prescription of psychotropics, depression and anxiety, and self-harm were strongly linked with higher estimated risk scores, followed by hospital admission and long-term drug and alcohol misuse. Other risk factors like sleep disorders and maltreatment had more complex effects.

Risk of suicide following an alcohol-related emergency hospital admission: An electronic cohort study of 2.8 million people

Objective

Alcohol misuse is a well-known risk factor for suicide however, the relationship between alcohol-related hospital admission and subsequent risk of death from suicide is unknown. We aimed to determine the risk of death from suicide following emergency admission to hospital with an alcohol-related cause.

Methods

We established an electronic cohort study of all 2,803,457 residents of Wales, UK, aged from 10 to under 100 years on 1 January 2006 with six years’ follow-up. The outcome event was death from suicide defined as intentional self-harm (ICD-10 X60-84) or undetermined intent (Y10-34). The main exposure was an alcohol-related admission defined as a ‘wholly attributable’ ICD-10 alcohol code in the admission record. Admissions were coded for the presence or absence of co-existing psychiatric morbidity. The analysis was by Cox regression with adjustments for confounding variables within the dataset.

Results

During the study follow-up period, there were 15,546,355 person years at risk with 28,425 alcohol-related emergency admissions and 1562 suicides. 125 suicides followed an admission (144.6 per 100,000 person years), of which 11 (9%) occurred within 4 weeks of discharge. The overall adjusted hazard ratio (HR) for suicide following admission was 26.8 (95% confidence interval (CI) 18.8 to 38.3), in men HR 9.83 (95% CI 7.91 to 12.2) and women HR 28.5 (95% CI 19.9 to 41.0). The risk of suicide remained substantial in subjects without known co-existing psychiatric morbidity: HR men 8.11 (95% CI 6.30 to 10.4) and women HR 24.0 (95% CI 15.5 to 37.3). The analysis was limited by the absence in datasets of potentially important confounding variables and the lack of information on alcohol-related harm and psychiatric morbidity in subjects not admitted to hospital.

Conclusion

Emergency alcohol-related hospital admission is associated with an increased risk of suicide. Identifying individuals in hospital provides an opportunity for psychosocial assessment and suicide prevention of a targeted at-risk group before their discharge to the community.

Comparison of Vital Statistics Definitions of Suicide against a Coroner Reference Standard: A Population-Based Linkage Study

OBJECTIVE

We sought to determine the utility of health administrative databases for population-based suicide surveillance, as these data are generally more accessible and more integrated with other data sources compared to coroners' records.

METHOD

In this retrospective validation study, we identified all coroner-confirmed suicides between 2003 and 2012 in Ontario residents aged 21 and over and linked this information to Statistics Canada's vital statistics data set. We examined the overlap between the underlying cause of death field and secondary causes of death using ICD-9 and ICD-10 codes for deliberate self-harm (i.e., suicide) and examined the sociodemographic and clinical characteristics of misclassified records.

RESULTS

Among 10,153 linked deaths, there was a very high degree of overlap between records coded as deliberate self-harm in the vital statistics data set and coroner-confirmed suicides using both ICD-9 and ICD-10 definitions (96.88% and 96.84% sensitivity, respectively). This alignment steadily increased throughout the study period (from 95.9% to 98.8%). Other vital statistics diagnoses in primary fields included uncategorised signs and symptoms. Vital statistics records that were misclassified did not differ from valid records in terms of sociodemographic characteristics but were more likely to have had an unspecified place of injury on the death certificate ( P < 0.001), more likely to have died at a health care facility ( P < 0.001), to have had an autopsy ( P = 0.002), and to have been admitted to a psychiatric hospital in the year preceding death ( P = 0.03).

CONCLUSIONS

A high degree of concordance between vital statistics and coroner classification of suicide deaths suggests that health administrative data can reliably be used to identify suicide deaths.

Integrating electronic healthcare records of armed forces personnel: Developing a framework for evaluating health outcomes in England, Scotland and Wales

•

A framework which integration national Electronic Healthcare Record datasets from England, Scotland and Wales is proposed.

•

Variable similarity is used to develop a schema which allows for variables to be linked and combined across the nations.

•

Evaluation of integration shows that it is possibly to perform data linkage across the nations.

Background

Electronic Healthcare Records (EHRs) are created to capture summaries of care and contact made to healthcare services. EHRs offer a means to analyse admissions to hospitals for epidemiological research. In the United Kingdom (UK), England, Scotland and Wales maintain separate data stores, which are administered and managed exclusively by devolved Government. This independence results in harmonisation challenges, not least lack of uniformity, making it difficult to evaluate care, diagnoses and treatment across the UK. To overcome this lack of uniformity, it is important to develop methods to integrate EHRs to provide a multi-nation dataset of health.

Objective

To develop and describe a method which integrates the EHRs of Armed Forces personnel in England, Scotland and Wales based on variable commonality to produce a multi-nation dataset of secondary health care.

Methods

An Armed Forces cohort was used to extract and integrate three EHR datasets, using commonality as the linkage point. This was achieved by evaluating and combining variables which shared the same characteristics. EHRs representing Accident and Emergency (A&E), Admitted Patient Care (APC) and Outpatient care were combined to create a patient-level history spanning three nations. Patient-level EHRs were examined to ascertain admission differences, common diagnoses and record completeness.

Results

A total of 6,336 Armed Forces personnel were matched, of which 5,460 personnel had 7,510 A&E visits, 9,316 APC episodes and 45,005 Outpatient appointments. We observed full completeness for diagnoses in APC, whereas Outpatient admissions were sparsely coded; with 88% of diagnoses coded as “Unknown/unspecified cause of morbidity”. In addition, A&E records were sporadically coded; we found five coding systems for identifying reason for admission.

Conclusion

At present, EHRs are designed to monitor the cost of treatment, enable administrative oversight, and are not currently suited to epidemiological research. However, only small changes may be needed to take advantage of what should be a highly cost-effective means of delivering important research for the benefit of the NHS.

Predicting suicide with the SAD PERSONS scale

BACKGROUND

Suicide is a major public health issue, and a priority requirement is accurately identifying high-risk individuals. The SAD PERSONS suicide risk assessment scale is widely implemented in clinical settings despite limited supporting evidence. This article aims to determine the ability of the SAD PERSONS scale (SPS) to predict future suicide in the emergency department.

METHODS

Five thousand four hundred sixty-two consecutive adults were seen by psychiatry consultation teams in two tertiary emergency departments with linkage to population-based administrative data to determine suicide deaths within 6 months, 1, and 5 years.

RESULTS

Seventy-seven (1.4%) individuals died by suicide during the study period. When predicting suicide at 12 months, medium- and high-risk scores on SPS had a sensitivity of 49% and a specificity of 60%; the positive and negative predictive values were 0.9 and 99%, respectively. Half of the suicides at both 6- and 12-month intervals were classified as low risk by SPS at index visit. The area under the curve at 12 months for the Modified SPS was 0.59 (95% confidence interval [CI] range 0.51-0.67). High-risk scores (compared to low risk) were significantly associated with death by suicide over the 5-year study period using the SPS (hazard ratio 2.49; 95% CI 1.34-4.61) and modified version (hazard ratio 2.29; 95% CI 1.24-2.29).

CONCLUSIONS

Although widely used in educational and clinical settings, these findings do not support the use of the SPS and Modified SPS to predict suicide in adults seen by psychiatric services in the emergency department.

Information for mental health systems: an instrument for policy-making and system service quality

AIMS

Information is crucial in mental healthcare, yet it remains undervalued by stakeholders. Its absence undermines rationality in planning, makes it difficult to monitor service quality improvement, impedes accountability and human rights monitoring. For international organizations (e.g., WHO, OECD), information is indispensable for achieving better outcomes in mental health policies, services and programs. This article reviews the importance of developing system level information with reference to inputs, processes and outputs, analyzes available tools for collecting and summarizing information, highlights the various goals of information gathering, discusses implementation issues and charts the way forward.

METHODS

Relevant publications and research were consulted, including WHO studies that purport to promote the use of information systems to upgrade mental health care in high- and low-middle income countries.

RESULTS

Studies have shown that once information has been collected by relevant systems and analyzed through indicator schemes, it can be put to many uses. Monitoring mental health services, represents a first step in using information. In addition, studies have noted that information is a prime resource in many other areas such as evaluation of quality of care against evidence based standards of care. Services data may support health services research where it is possible to link mental health data with other health and non-health databases. Information systems are required to carefully monitor involuntary admissions, restrain and seclusion, to reduce human rights violations in care facilities. Information has been also found useful for policy makers, to monitor the implementation of policies, to evaluate their impact, to rationally allocate funding and to create new financing models.

CONCLUSIONS

Despite its manifold applications, Information systems currently face many problems such as incomplete recording, poor data quality, lack of timely reporting and feedback, and limited application of information. Corrective action is needed to upgrade data collection in outpatient facilities, to improve data quality, to establish clear rules and norms, to access adequate information technology equipment and to train health care personnel in data collection. Moreover, it is necessary to shift from mere administrative data collection to analysis, dissemination and use by relevant stakeholders and to develop a "culture of information" to dismantle the culture of intuition and mere tradition. Clinical directors, mental health managers, patient and family representatives, as well as politicians should be educated to operate with information and not just intuition.

The Prevalence of Electroconvulsive Therapy Use Since 1973: A Meta-analysis

OBJECTIVES

A formal meta-analysis of the use of electroconvulsive therapy (ECT) has never been conducted before in literature reviews or syntheses. Such a study would be hampered by heterogeneity and potential reporting biases. However, it would provide a single comparable measure to allow an analysis of statistical key dimensions such as trends across time and psychiatric resources available. It would also help planners and decision makers to set standards and benchmarks for national and regional guidelines for quality assurance and research in health services.

METHODS

We surveyed different databases for relevant studies, limited from 1973 to October 2013. Data were extracted independently by 4 reviewers. The articles retrieved were peerreviewed studies (data-based studies or surveys) presenting ECT population rates (annual patient rates calculated from the general population) or number of patients receiving ECT during or after 1973 and attending a psychiatric establishment (either hospitals or approved ECT delivery centers for inpatients and outpatients in well-defined geographic areas).

RESULTS

This meta-analysis includes a total of 18 studies from 12 countries. A composite event rate of 16.9/100,000 inhabitants emerged, characterized by high heterogeneity. Across the countries assessed, the prevalence of ECT was higher in older studies.

CONCLUSIONS

By its prevalence, ECT remains rare to exceptional as a specialist treatment for mental disorders. Heterogeneity across regions or countries could best be explained by insufficient standardization of ECT procedures and practices. Linked health databases and audits could help strengthen the effectiveness of ECT in relation to primary outcomes such as suicide and help determine the gap in ECT provision, if any.

Population-based analysis of health care contacts among suicide decedents: identifying opportunities for more targeted suicide prevention strategies

The objective of this study was to detail the nature and correlates of mental health and non-mental health care contacts prior to suicide death. We conducted a systematic extraction of data from records at the Office of the Chief Coroner of Ontario of each person who died by suicide in the city of Toronto from 1998 to 2011. Data on 2,835 suicide deaths were linked with provincial health administrative data to identify health care contacts during the 12 months prior to suicide. Sub-populations of suicide decedents based on the presence and type of mental health care contact were described and compared across socio-demographic, clinical and suicide-specific variables. Time periods from last mental health contact to date of death were calculated and a Cox proportional hazards model examined covariates. Among suicide decedents, 91.7% had some type of past-year health care contact prior to death, 66.4% had a mental health care contact, and 25.3% had only non-mental health contacts. The most common type of mental health contact was an outpatient primary care visit (54.0%), followed by an outpatient psychiatric visit (39.8%), an emergency department visit (31.1%), and a psychiatric hospitalization (21.0%). The median time from last mental health contact to death was 18 days (interquartile range 5-63). Mental health contact was significantly associated with female gender, age 25-64, absence of a psychosocial stressor, diagnosis of schizophrenia or bipolar disorder, past suicide attempt, self-poisoning method and absence of a suicide note. Significant differences between sub-populations of suicide decedents based on the presence and nature of their health care contacts suggest the need for targeting of community and clinical-based suicide prevention strategies. The predominance of ambulatory mental health care contacts, often close to the time of death, reinforce the importance of concentrating efforts on embedding risk assessment and care pathways into all routine primary and specialty clinical care, and not only acute care settings.

Case-finding for common mental disorders of anxiety and depression in primary care: an external validation of routinely collected data

Background

The robustness of epidemiological research using routinely collected primary care electronic data to support policy and practice for common mental disorders (CMD) anxiety and depression would be greatly enhanced by appropriate validation of diagnostic codes and algorithms for data extraction. We aimed to create a robust research platform for CMD using population-based, routinely collected primary care electronic data.

Methods

We developed a set of Read code lists (diagnosis, symptoms, treatments) for the identification of anxiety and depression in the General Practice Database (GPD) within the Secure Anonymised Information Linkage Databank at Swansea University, and assessed 12 algorithms for Read codes to define cases according to various criteria. Annual incidence rates were calculated per 1000 person years at risk (PYAR) to assess recording practice for these CMD between January 1^st 2000 and December 31^st 2009. We anonymously linked the 2799 MHI-5 Caerphilly Health and Social Needs Survey (CHSNS) respondents aged 18 to 74 years to their routinely collected GP data in SAIL. We estimated the sensitivity, specificity and positive predictive value of the various algorithms using the MHI-5 as the gold standard.

Results

The incidence of combined depression/anxiety diagnoses remained stable over the ten-year period in a population of over 500,000 but symptoms increased from 6.5 to 20.7 per 1000 PYAR. A ‘historical’ GP diagnosis for depression/anxiety currently treated plus a current diagnosis (treated or untreated) resulted in a specificity of 0.96, sensitivity 0.29 and PPV 0.76. Adding current symptom codes improved sensitivity (0.32) with a marginal effect on specificity (0.95) and PPV (0.74).

Conclusions

We have developed an algorithm with a high specificity and PPV of detecting cases of anxiety and depression from routine GP data that incorporates symptom codes to reflect GP coding behaviour. We have demonstrated that using diagnosis and current treatment alone to identify cases for depression and anxiety using routinely collected primary care data will miss a number of true cases given changes in GP recording behaviour. The Read code lists plus the developed algorithms will be applicable to other routinely collected primary care datasets, creating a platform for future e-cohort research into these conditions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12911-016-0274-7) contains supplementary material, which is available to authorized users.