Excess mortality among individuals who have undergone addiction treatment: a study from Greenland.

In Greenland, where addiction-related concerns significantly affect well-being, research has explored alcohol's impact on health and mortality. However, no studies have focused on mortality among those who received addiction treatment. This study investigates whether individuals treated for addiction in Greenland experience elevated mortality rates compared to the general population. The study encompassed individuals receiving addiction treatment through the national system between 2012 and December 31, 2022. Data on treatment were sourced from the National Addiction Database, and Statistics Greenland. Person-years at risk were calculated and used to estimate crude mortality rates (CMRs). Adjusted standardized mortality rates (SMRs), accounting for age, sex, and calendar year, were estimated using an indirect method based on observed and expected deaths. Of the 3286 in treatment, 53.9% were women, with a median age of 37. About a third had undergone multiple treatment episodes, and 60.1% received treatment in 2019 or later. The cohort was followed for a median of 2.89 years, yielding 12,068 person-years. The overall CMR was 7.79 deaths per 1000 person-years, with a SMR of 1.42 (95% confidence interval: 1.15; 1.74). Significantly, SMRs differed by age at treatment entry, with younger groups exhibiting higher SMRs (p value = .021). This study found that individuals seeking treatment for addiction problems in Greenland had a higher mortality rate than the general population. Importantly, these SMRs were substantially lower than those observed in clinical populations in other countries.

Augmenting maternal clinical cohort data with administrative laboratory dataset linkages: a validation study.

Background: The use of big data and large language models in healthcare can play a key role in improving patient treatment and healthcare management, especially when applied to large-scale administrative data. A major challenge to achieving this is ensuring that patient confidentiality and personal information is protected. One way to overcome this is by augmenting clinical data with administrative laboratory dataset linkages in order to avoid the use of demographic information. Methods: We explored an alternative method to examine patient files from a large administrative dataset in South Africa (the National Health Laboratory Services, or NHLS), by linking external data to the NHLS database using specimen barcodes associated with laboratory tests. This offers us with a deterministic way of performing data linkages without accessing demographic information. In this paper, we quantify the performance metrics of this approach. Results: The linkage of the large NHLS data to external hospital data using specimen barcodes achieved a 95% success. Out of the 1200 records in the validation sample, 87% were exact matches and 9% were matches with typographic correction. The remaining 5% were either complete mismatches or were due to duplicates in the administrative data. Conclusions: The high success rate indicates the reliability of using barcodes for linking data without demographic identifiers. Specimen barcodes are an effective tool for deterministic linking in health data, and may provide a method of creating large, linked data sets without compromising patient confidentiality.

Adoption of high-sensitivity cardiac troponin for risk stratification of patients with suspected myocardial infarction: a multicentre cohort study.

Background: Guidelines recommend high-sensitivity cardiac troponin to risk stratify patients with possible myocardial infarction and identify those eligible for discharge. Our aim was to evaluate adoption of this approach in practice and to determine whether effectiveness and safety varies by age, sex, ethnicity, or socioeconomic deprivation status. Methods: A multi-centre cohort study was conducted in 13 hospitals across the United Kingdom from November 1st, 2021, to October 31st, 2022. Routinely collected data including high-sensitivity cardiac troponin I or T measurements were linked to outcomes. The primary effectiveness and safety outcomes were the proportion discharged from the Emergency Department, and the proportion dead or with a subsequent myocardial infarction at 30 days, respectively. Patients were stratified using peak troponin concentration as low (<5 ng/L), intermediate (5 ng/L to sex-specific 99th percentile), or high-risk (>sex-specific 99th percentile). Findings: In total 137,881 patients (49% [67,709/137,881] female) were included of whom 60,707 (44%), 42,727 (31%), and 34,447 (25%) were stratified as low-, intermediate- and high-risk, respectively. Overall, 65.8% (39,918/60,707) of low-risk patients were discharged from the Emergency Department, but this varied from 26.8% [2200/8216] to 93.5% [918/982] by site. The safety outcome occurred in 0.5% (277/60,707) and 11.4% (3917/34,447) of patients classified as low- or high-risk, of whom 0.03% (18/60,707) and 1% (304/34,447) had a subsequent myocardial infarction at 30 days, respectively. A similar proportion of male and female patients were discharged (52% [36,838/70,759] versus 54% [36,113/67,109]), but discharge was more likely if patients were <70 years old (61% [58,533/95,227] versus 34% [14,428/42,654]), from areas of low socioeconomic deprivation (48% [6697/14,087] versus 43% [12,090/28,116]) or were black or asian compared to caucasian (62% [5458/8877] and 55% [10,026/18,231] versus 46% [35,138/75,820]). Interpretation: Despite high-sensitivity cardiac troponin correctly identifying half of all patients with possible myocardial infarction as being at low risk, only two-thirds of these patients were discharged. Substantial variation in the discharge of patients by age, ethnicity, socioeconomic deprivation, and site was observed identifying important opportunities to improve care. Funding: UK Research and Innovation.

Prior emergency medical services utilization is a risk factor for in-hospital death among patients with substance misuse: a retrospective cohort study.

BACKGROUND: Substance misuse poses a significant public health challenge, characterized by premature morbidity and mortality, and heightened healthcare utilization. While studies have demonstrated that previous hospitalizations and emergency department visits are associated with increased mortality in patients with substance misuse, it is unknown whether prior utilization of emergency medical service (EMS) is similarly associated with poor outcomes among this population. The objective of this study is to determine the association between EMS utilization in the 30 days before a hospitalization or emergency department visit and in-hospital outcomes among patients with substance misuse. METHODS: We conducted a retrospective analysis of adult emergency department visits and hospitalizations (referred to as a hospital encounter) between 2017 and 2021 within the Substance Misuse Data Commons, which maintains electronic health records from substance misuse patients seen at two University of Wisconsin hospitals, linked with state agency, claims, and socioeconomic datasets. Using regression models, we examined the association between EMS use and the outcomes of in-hospital death, hospital length of stay, intensive care unit (ICU) admission, and critical illness events, defined by invasive mechanical ventilation or vasoactive drug administration. Models were adjusted for age, comorbidities, initial severity of illness, substance misuse type, and socioeconomic status. RESULTS: Among 19,402 encounters, individuals with substance misuse who had at least one EMS incident within 30 days of a hospital encounter experienced a higher likelihood of in-hospital mortality (OR 1.52, 95% CI [1.05 - 2.14]) compared to those without prior EMS use, after adjusting for confounders. Using EMS in the 30 days prior to an encounter was associated with a small increase in hospital length of stay but was not associated with ICU admission or critical illness events. CONCLUSIONS: Individuals with substance misuse who have used EMS in the month preceding a hospital encounter are at an increased risk of in-hospital mortality. Enhanced monitoring of EMS users in this population could improve overall patient outcomes.

Corrigendum: Estimating the prevalence of alcohol-related disorders and treatment utilization in Bremen 2016/2017 through routine data linkage.

[This corrects the article DOI: 10.3389/fpsyt.2023.1002526.].

Factors associated with SARS-CoV-2 testing, diagnosis and COVID-19 disease among individuals prescribed opioid-agonist treatment: a nationwide retrospective cohort study.

OBJECTIVES: Among people receiving opioid-agonist treatment (OAT), the risk of COVID-19 infection and disease may be higher owing to underlying health problems and vulnerable social circumstances. We aimed to determine whether recent OAT, compared to past exposure, affected risk of (i) testing for SARS-CoV-2, (ii) testing positive for SARS-CoV-2 and (iii) being hospitalized/dying with COVID-19 disease. METHODS: We included individuals prescribed OAT in Scotland between 2015 and 2020. We performed record linkage to SARS-CoV-2 PCR testing, vaccination, hospitalization, and mortality data, and followed up from March-2020 to December-2021. We used proportional hazards analysis and multivariate logistic regression to estimate associations between recent OAT prescription (in the previous two months), compared to past exposure (off treatment for over a year), and COVID-19 outcomes. Models were adjusted for confounders. RESULTS: Among 36,093 individuals prescribed OAT, 19,071 (52.9%) were tested for SARS-CoV-2, 2,896 (8.3%) tested positive and 552 (1.5%) were hospitalized/died with COVID-19. Recent OAT, compared to past exposure, was associated with lower odds of testing positive among those tested (aOR, 0.63; 95% CI, 0.57, 0.69). However, among those testing positive, recent OAT was associated with two-fold higher odds of hospitalization/death (aOR, 2.04; 95% CI, 1.60, 2.59). CONCLUSION: We found that recent OAT was associated with lower odds of SARS-CoV-2 infection, but with higher odds of disease once diagnosed. Clinical studies are needed to unravel the role of OAT in these associations. Enhanced effort is warranted to increase vaccine coverage among OAT patients to mitigate severe consequences of COVID-19.

Cancer Registry Enrichment via Linkage with Hospital-Based Electronic Medical Records: A Pilot Investigation.

Background: Hospital electronic medical record (EMR) systems are becoming increasingly integrated for management of patient data, especially given recent policy changes issued by the Centers for Medicaid and Medicare Services. In addition to data management, these data provide evidence for patient-centered outcomes research for a range of diseases, including cancer. Integrating EMR patient data with existing disease registries strengthens all essential components for assuring optimal health outcomes. Objectives: To identify the mechanisms for extracting, linking, and processing hospital EMR data with the Florida Cancer Data System (FCDS); and to assess the completeness of existing registry treatment data as well as the potential for data enhancement. Methods: A partnership among the Florida Department of Health, FCDS, and a large Florida hospital system was established to develop methods for hospital EMR extraction and transmission. Records for admission years between 2007 and 2010 were extracted using ICD-9-CM codes as the trigger and were linked with the cancer registry for patients with invasive cancers of the breast. Results: A total of 11,506 unique patients were linked with a total of 12,804 unique breast tumors. Evaluation of existing registry treatment data against the hospital EMR produced a total of 5% of registry records with updated surgery information, 1% of records with updated radiation information, and 7% of records updated with chemotherapy information. Enhancement of registry treatment information was particularly affected by the availability of chemotherapy medications data. Conclusion: Hospital EMR linkages to cancer disease registries is feasible but challenged by lack of standards for data collection, coding and transmission, comprehensive description of available data, and the exclusion of certain hospital datasets. The FCDS standard treatment data variables are highly robust and complete but can be enhanced by the addition of detailed chemotherapy regimens that are commonly used in patient centered outcomes research.

Subgroup analyses and patterns of multiple sclerosis health service utilisation: A cluster analysis.

Background: Previous investigations of multiple sclerosis (MS)-related healthcare have focused on utilisation of specific individual health services (e.g. hospital care, office-based neurologists) by people with MS (PwMS). Meanwhile, little is known about possible patterns of utilisation across health services and their potential differences across patient characteristics. Objective: To comprehensively analyse and identify patterns of MS-related health service utilisation and detect patient characteristics explaining such patterns. Methods: In 2021, we invited all PwMS insured by the largest insurance company in Lower Saxony, Germany, to take part in an online survey. We merged respondents' survey and health insurance claims data. We analysed MS-related health service utilisation and defined individual characteristics for subgroup analyses based on Andersen's Behavioural Model. We executed non-parametric missing value imputation and conducted hierarchical clustering to find patterns in health service utilisation. Results: Of 6928 PwMS, 1935 responded to our survey and 1803 were included in the cluster analysis. We identified four distinct health service utilisation clusters: (1) regular users (n = 1130), (2) assistive care users (n = 443), (3) low users (n = 195) and (4) special services users (n = 35). Clusters differ by patient characteristics (e.g. age, impairment). Conclusion: Our findings highlight the complexity of MS-related health service utilisation and provide relevant stakeholders with information allowing them to tailor healthcare planning according to utilisation patterns.

How to Elucidate Consent-Free Research Use of Medical Data: A Case for "Health Data Literacy".

Unlabelled: The extensive utilization of personal health data is one of the key success factors of modern medical research. Obtaining consent to the use of such data during clinical care, however, bears the risk of low and unequal approval rates and risk of consequent methodological problems in the scientific use of the data. In view of these shortcomings, and of the proven willingness of people to contribute to medical research by sharing personal health data, the paradigm of informed consent needs to be reconsidered. The European General Data Protection Regulation gives the European member states considerable leeway with regard to permitting the research use of health data without consent. Following this approach would however require alternative offers of information that compensate for the lack of direct communication with experts during medical care. We therefore introduce the concept of "health data literacy," defined as the capacity to find, understand, and evaluate information about the risks and benefits of the research use of personal health data and to act accordingly. Specifically, health data literacy includes basic knowledge about the goals and methods of data-rich medical research and about the possibilities and limits of data protection. Although the responsibility for developing the necessary resources lies primarily with those directly involved in data-rich medical research, improving health data literacy should ultimately be of concern to everyone interested in the success of this type of research.

Cohort profile: understanding health service system needs for people with intellectual disability using linked data in New South Wales, Australia.

This cohort profile describes one of the largest linked datasets in the world concerning the health of people with intellectual disability. The cohort comprises a retrospective group of 100,089 individuals with intellectual disability who received disability and/or health services in New South Wales, Australia. Of these participants, 34% were female, with a median age at cohort entry of 3 years (interquartile range, 0 to 19 years). A separate comparator cohort included 455,677 individuals, matched by 5-year age group, sex, and residential postcode at a 5:1 ratio. Initial results indicate that between 2001 and 2018, people with intellectual disability experienced more than double the rate of hospitalisations (538 versus 235 per 1000 person-years), as well as markedly higher rates of emergency department presentations (707 versus 379 per 1000 person-years) and use of ambulatory mental health services (1012 versus 157 per 1000 person-years), relative to the comparator cohort. The largest disparities in hospital admissions were for mental disorders, dialysis, and diseases of the nervous system and sense organs. Furthermore, individuals with intellectual disability had more than double the rate of dispensed medications found in the comparator cohort. Of these medications, 46.6% were for the treatment of nervous system conditions, as opposed to 24.7% for the comparator cohort. The mean age at death was 52 years (standard deviation [SD], 19 years) for people with intellectual disability and 64 years (SD, 22 years) for the comparator participants.

Comparison of outcomes of the 50-year follow-up of a randomized trial assessed by study questionnaire and by data linkage: The CONCUR study.

BACKGROUND/AIMS: Self-reported questionnaires on health status after randomized trials can be time-consuming, costly, and potentially unreliable. Administrative data sets may provide cost-effective, less biased information, but it is uncertain how administrative and self-reported data compare to identify chronic conditions in a New Zealand cohort. This study aimed to determine whether record linkage could replace self-reported questionnaires to identify chronic conditions that were the outcomes of interest for trial follow-up. METHODS: Participants in 50-year follow-up of a randomized trial were asked to complete a questionnaire and to consent to accessing administrative data. The proportion of participants with diabetes, pre-diabetes, hyperlipidaemia, hypertension, mental health disorders, and asthma was calculated using each data source and agreement between data sources assessed. RESULTS: Participants were aged 49 years (SD = 1, n = 424, 50% male). Agreement between questionnaire and administrative data was slight for pre-diabetes (kappa = 0.10), fair for hyperlipidaemia (kappa = 0.27), substantial for diabetes (kappa = 0.65), and moderate for other conditions (all kappa >0.42). Administrative data alone identified two to three times more cases than the questionnaire for all outcomes except hypertension and mental health disorders, where the questionnaire alone identified one to two times more cases than administrative data. Combining all sources increased case detection for all outcomes. CONCLUSIONS: A combination of questionnaire, pharmaceutical, and laboratory data with expert panel review were required to identify participants with chronic conditions of interest in this follow-up of a clinical trial.

Ascertainment of Aboriginal and Torres Strait Islander status for assessment of perinatal health outcomes: Reported versus derived maternal ethnicity in Western Australian pregnancy data.

BACKGROUND: Under-identification of Aboriginal and Torres Strait Islander (hereafter referred to as Aboriginal) people can result in inaccurate estimation of health outcomes. Data linkage has improved identification of Aboriginal people in administrative datasets. AIM: To compare three methods of ascertainment of Aboriginal status using only pregnancy data from the Western Australian Midwives Notification System (MNS), to the linked Indigenous Status Flag (ISF) derived by the Department of Health. MATERIALS AND METHODS: This retrospective population-based cohort study utilised logistic regression to determine which demographic characteristics were associated with under-identification, and the effect of ascertainment method on perinatal adverse outcomes. RESULTS: All methods identified a core group of 19 017 (83.0%) Aboriginal women and the ISF identified 2298 (10.0%) women who were not identified using any other method. Under-ascertainment was lowest when a woman's Aboriginal status was determined by ever being recorded as Aboriginal in the MNS data, and highest when taken as it had been recorded for the birth in question. Maternal age <20 years, smoking during pregnancy, pre-existing diabetes, a history of singleton preterm birth and being in the lowest 20% of Socio-Economic Indexes for Areas score were all associated with a higher chance of being identified by the methods using only the MNS. These methods were less likely to identify nulliparous women, and those with maternal age ≥35 years. The method of ascertainment of Aboriginality did not make a significant difference to the adjusted predicted marginal probabilities of adverse perinatal outcomes. CONCLUSION: Unlinked pregnancy data can be used for epidemiological research in Aboriginal obstetric populations.

The risk of repeated suicidal presentations following residential treatment for substance use disorders: A recurrent event analysis using linked administrative data.

BACKGROUND: Individuals seeking alcohol and other drug (AOD) treatment consistently experience higher rates of suicidal behaviours and death by suicide when compared to the general population. By linking residential AOD treatment data to administrative healthcare and death datasets, we aimed to examine suicide-related behaviours and identify risk and protective factors for these events following discharge from residential treatment. METHODS: Participants included 1056 individuals aged 18-69 (M = 32.06, SD = 9.55, male = 696,65.9 %) admitted to three residential treatment facilities in Queensland, Australia from January 1, 2014 to December 31, 2016. Treatment data was linked to administrative hospital, emergency department (ED), mental health service, and Registry of Deaths data 2-years post-discharge. ICD-10 codes were used to identify and analyse suicide-related events. RESULTS: Within 2-years post-discharge, 175 (16.6 %) individuals had a suicide-related event (n = 298 episodes). The highest proportion of episodes (11.1 %) occurred within 1-month of discharge. Higher risk of a recurrent suicide-related event was associated with receiving a Disability Support Pension (aHR = 1.69 (95%CI:1.10,2.59), two or more previous episodes of residential AOD treatment (aHR = 1.49 (95%CI:1.30,2.15). Completing residential treatment was associated with a lower risk of suicide-related events (aHR = 0.54 (95%CI:0.35,0.83). LIMITATIONS: The amalgamation of suicidal ideation, attempts, and death into a single outcome oversimplifies their complex nature and interplay. The exclusive focus on one service provider limits generalisability, and data constraints and missingness preclude many analyses. CONCLUSIONS: Understanding suicidal behaviours and critical risk periods following discharge from residential treatment is crucial for improving continuing care, developing effective suicide prevention, and implementing targeted interventions among this high-risk population.

Clustering care pathways of people with alcohol dependence using a data linkage of routine data in Bremen, Germany.

BACKGROUND: Although many individuals with alcohol dependence (AD) are recognized in the German healthcare system, only a few utilize addiction-specific treatment services. Those who enter treatment are not well characterized regarding their prospective pathways through the highly fragmented German healthcare system. This paper aims to (1) identify typical care pathways of patients with AD and their adherence to treatment guidelines and (2) explore the characteristics of these patients using routine data from different healthcare sectors. METHODS: We linked routinely collected register data of individuals with a documented alcohol-related diagnosis in the federal state of Bremen, Germany, in 2016/2017 and their addiction-specific health care: two statutory health insurance funds (outpatient pharmacotherapy for relapse prevention and inpatient episodes due to AD with and without qualified withdrawal treatment (QWT)), the German Pension Insurance (rehabilitation treatment) and a group of communal hospitals (outpatient addiction care). Individual care pathways of five different daily states of utilized addiction-specific treatment following an index inpatient admission due to AD were analyzed using state sequence analysis and cluster analysis. The follow-up time was 307 days (10 months). Individuals of the clustered pathways were compared concerning current treatment recommendations (1: QWT followed by postacute treatment; 2: time between QWT and rehabilitation). Patients' characteristics not considered during the cluster analysis (sex, age, nationality, comorbidity, and outpatient addiction care) were then compared using a multinomial logistic regression. RESULTS: The analysis of 518 individual sequences resulted in the identification of four pathway clusters differing in their utilization of acute and postacute treatment. Most did not utilize subsequent addiction-specific treatment after their index inpatient episode (n = 276) or had several inpatient episodes or QWT without postacute treatment (n = 205). Two small clusters contained pathways either starting rehabilitation (n = 26) or pharmacotherapy after the index episode (n = 11). Overall, only 9.3% utilized postacute treatment as recommended. CONCLUSIONS: A concern besides the generally low utilization of addiction-specific treatment is the implementation of postacute treatments for individuals after QWT.

Developing evaluation measures for health departments sharing and linking HIV and STI surveillance data.

Enhancing data sharing, quality, and use across siloed HIV and STI programs is critical for national and global initiatives to reduce new HIV infections and improve the health of people with HIV. As part of the Enhancing Linkage of STI and HIV Surveillance Data in the Ryan White HIV/AIDS Program initiative, four health departments (HDs) in the U.S. received technical assistance to better share and link their HIV and STI surveillance data. The process used to develop evaluation measures assessing implementation and outcomes of linking HIV and STI data systems involved six steps: 1) measure selection and development, 2) review and refinement, 3) testing, 4) implementation and data collection, 5) data quality review and feedback, and 6) dissemination. Findings from pilot testing warranted slight adaptations, including starting with a core set of measures and progressively scaling up. Early findings showed improvements in data quality over time. Lessons learned included identifying and engaging key stakeholders early; developing resources to assist HDs; and considering measure development as iterative processes requiring periodic review and reassessment to ensure continued utility. These findings can guide programs and evaluations, especially those linking data across multiple systems, in developing measures to track implementation and outcomes over time.

Evaluating data quality for blended data using a data quality framework.

In 2020 the U.S. Federal Committee on Statistical Methodology (FCSM) released "A Framework for Data Quality", organized by 11 dimensions of data quality grouped among three domains of quality (utility, objectivity, integrity). This paper addresses the use of the FCSM Framework for data quality assessments of blended data. The FCSM Framework applies to all types of data, however best practices for implementation have not been documented. We applied the FCSM Framework for three health-research related case studies. For each case study, assessments of data quality dimensions were performed to identify threats to quality, possible mitigations of those threats, and trade-offs among them. From these assessments the authors concluded: 1) data quality assessments are more complex in practice than anticipated and expert guidance and documentation are important; 2) each dimension may not be equally important for different data uses; 3) data quality assessments can be subjective and having a quantitative tool could help explain the results, however, quantitative assessments may be closely tied to the intended use of the dataset; 4) there are common trade-offs and mitigations for some threats to quality among dimensions. This paper is one of the first to apply the FCSM Framework to specific use-cases and illustrates a process for similar data uses.

Linkage of routinely collected NHS data to evaluate liaison mental health services: challenges and lessons learned.

Background: Liaison mental health services provide mental health care to patients in acute hospital settings. Evaluation of liaison services is challenging due to their heterogeneous organisation and delivery, high case throughput and varied patient case mix. We aimed to link routinely collected National Health Service data from secondary care settings, chosen for their service characteristics, to data from primary care to evaluate hospital-based liaison mental health services in England. Methods: We planned to compare patients referred to hospital-based liaison services with comparable patients in the same hospital not referred to liaison services and comparable patients in hospitals without any liaison services. We designed and enacted a methodology to link data from: (1) Hospital Episode Statistics, a database controlled by the National Health Service Digital and (2) ResearchOne, a primary care database controlled by The Phoenix Partnership. Results: Obtaining approvals for the steps prespecified in the methodological protocol took 907 days. Enactment following approvals took 385 days. Data supplied from Hospital Episode Statistics contained 181,063 patients from 6 hospitals (mean = 30,177, standard deviation = 28,875.86) who matched the inclusion and exclusion criteria. Data supplied from ResearchOne contained 33,666 (18.6%) of these patients from the 6 hospitals (mean = 5611, standard deviation = 5206.59). Discussion: Time required for approvals and enactment was attributable to slowness of data handling processes within each data holder and to resolution of technical and organisational queries between them. Variation in number of patients for which data was supplied between databases and between hospitals was attributable to coding inconsistencies and to the limited intersection of patient populations between databases and variation in recording practices between hospitals. Conclusion: Although it is technically feasible to link primary and secondary care data, the current system is challenging, complicated, unnecessarily bureaucratic, time consuming and costly. This limits the number of studies that could be conducted with these rich data sources. Funding: This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme as award number 13/58/08.

Liaison mental health services are based in acute general hospitals and provide assessment and treatment for people who have both physical and mental health problems. Our aim was to use routinely collected National Health Service data to find out whether general hospital patients referred to liaison mental health services have improved outcomes, compared with patients not referred to liaison services, and comparable patients in hospitals where there are no liaison services. The main outcomes were less time spent in hospital and fewer re-admissions to hospital following discharge. We tried to link data from routine National Health Service sources for hospital and primary care, to compare patients referred to liaison mental health services with similar people in each hospital who had not been referred, and similar people in hospitals without any liaison services at all. We planned to find out how long these people stayed in hospital, whether they were re-admitted and how much was their healthcare cost was. We experienced significant difficulties in being able to link the National Health Service data from the different organisations we approached. The whole process was extremely complex, and a delay in one part of the process resulted delays in other parts. We eventually had to abandon the research without obtaining any meaningful data, although the lessons we learnt will be useful for other researchers, so they can avoid experiencing similar problems. Routinely collected National Health Service data from primary care and secondary care can be linked using the approaches we tried, but we were unable to complete the process within the time frame of the research programme, even with time extensions. Current processes need to be streamlined and standardised with designated clear response times for the different organisations.

The relationship between gambling behaviour and gambling-related harm: A data fusion approach using open banking data.

BACKGROUND AND AIMS: UK-based gambling policymakers have proposed affordability checks starting at monthly losses of £125. The present study combines open banking data with self-reports of the Problem Gambling Severity Index (PGSI) and other relevant information to explore the harm profiles of people who gamble at different levels of electronic gambling behaviour. DESIGN, SETTING AND PARTICIPANTS: This was a data fusion study in which participants consented to share their bank data via an open banking application programming interface (API) and who also completed relevant self-report items. Hierarchical hurdle models were used to predict being an at-risk gambler (PGSI > 0) and being a 'higher-risk' gambler (higher PGSI scores among those with non-zero scores) using four specifications of electronic gambling behaviour (net-spend, outgoing expenditure, incoming withdrawals, interaction model combining expenditure and withdrawals), and by adding self-reported data across two additional steps. The study took place in the United Kingdom. Participants were past-year people who gamble (n = 424), recruited via Prolific. MEASUREMENTS: Self-report measures were used of gambling-related harm (PGSI), depression [Patient Health Questionnaire 9 (PHQ-9)], age and gender; bank-recorded measures of income and electronic gambling behaviour. FINDINGS: Unharmed gamblers had an average monthly gambling net-spend of £16.41, compared with £208.91 among highest-risk gamblers (PGSI ≥ 5). Being an at-risk gambler (PGSI > 0) was predicted significantly by all four types of gambling behaviour throughout all three steps [1.08 ≤ odds ratios (ORs) ≤ 2.92; Ps < 0.001), with only outgoing expenditure being significant in the interaction model (2.26 ≤ ORs ≤ 2.81; Ps < 0.001). Higher PHQ-9 scores also predicted at-risk gambling in steps 2-3 (1.09 ≤ ORs ≤ 1.10; Ps < 0.001), as did lower age (0.95 ≤ ORs ≤ 0.96; Ps < 0.001) and male gender identity in step 3 (2.51 ≤ ORs ≤ 2.95; Ps < 0.001). Being a higher-risk gambler was predicted significantly by gambling behaviour only in the expenditure-only (1.16 ≤ ORs ≤ 1.17; Ps ≤ 0.048) and withdrawal-only (1.08 ≤ ORs ≤ 1.09; Ps ≤ 0.004) models, and was not predicted by income (0.98 ≤ ORs ≤ 1.14; Ps ≥ 0.601), age (0.98 ≤ ORs ≤ 0.99; Ps ≥ 0.143) or male gender identity (1.07 ≤ ORs ≤ 1.15; Ps ≥ 0.472). CONCLUSION: The UK government's proposed affordability checks for gamblers should rarely affect people who are not experiencing gambling-related harm. At-risk gambling is predicted well by different types of gambling behaviour. Novel insights about gambling can be generated by fusing self-reported and objective data.

Cardiovascular and Noncardiovascular Prescribing and Mortality After Takotsubo Comparison With Myocardial Infarction and General Population.

Background: Takotsubo syndrome is an increasingly common cardiac emergency with no known evidence-based treatment. Objectives: The purpose of this study was to investigate cardiovascular mortality and medication use after takotsubo syndrome. Methods: In a case-control study, all patients with takotsubo syndrome in Scotland between 2010 and 2017 (n = 620) were age, sex, and geographically matched to individuals in the general population (1:4, n = 2,480) and contemporaneous patients with acute myocardial infarction (1:1, n = 620). Electronic health record data linkage of mortality outcomes and drug prescribing were analyzed using Cox proportional hazard regression models. Results: Of the 3,720 study participants (mean age, 66 years; 91% women), 153 (25%) patients with takotsubo syndrome died over the median of 5.5 years follow-up. This exceeded mortality rates in the general population (N = 374 [15%]; HR: 1.78 [95% CI: 1.48-2.15], P < 0.0001), especially for cardiovascular (HR: 2.47 [95% CI: 1.81-3.39], P < 0.001) but also noncardiovascular (HR: 1.48 [95% CI: 1.16-1.87], P = 0.002) deaths. Mortality rates were lower for patients with takotsubo syndrome than those with myocardial infarction (31%, 195/620; HR: 0.76 [95% CI: 0.62-0.94], P = 0.012), which was attributable to lower rates of cardiovascular (HR: 0.61 [95% CI: 0.44-0.84], P = 0.002) but not non-cardiovascular (HR: 0.92 [95% CI: 0.69-1.23], P = 0.59) deaths. Despite comparable medications use, cardiovascular therapies were consistently associated with better survival in patients with myocardial infarction but not in those with takotsubo syndrome. Diuretic (P = 0.01), anti-inflammatory (P = 0.002), and psychotropic (P < 0.001) therapies were all associated with worse outcomes in patients with takotsubo syndrome. Conclusions: In patients with takotsubo syndrome, cardiovascular mortality is the leading cause of death, and this is not associated with cardiovascular therapy use.