Emergency Medical Services Compliance With Prehospital Stroke Quality Metrics Is Associated With Faster Stroke Evaluation and Treatment.

BACKGROUND: Emergency medical services (EMS) is an important link in the stroke chain of recovery. Various prehospital quality metrics have been proposed for prehospital stroke care, but their individual impact is uncertain. We sought to measure associations between EMS quality metrics and downstream stroke care. METHODS: This is a retrospective analysis of a cohort of EMS-transported stroke patients assembled through a linkage between Michigan's EMS and stroke registries. We used multivariable regression to quantify the independent associations between EMS quality metric compliance (dispatch within 90 seconds of 911 call, prehospital stroke screen documentation [Prehospital stroke scale], glucose check, last known well time, maintenance of scene times ≤15 minutes, hospital prenotification, and intravenous line placement) and shorter door-to-CT times (door-to-CT ≤25), accounting for EMS recognition, age, sex, race, stroke subtype, severity, and duration of symptoms. We then developed a simple EMS quality score based on metrics associated with early CT and examined its associations with hospital stroke evaluation times, treatment, and patient outcomes. RESULTS: Five thousand seven hundred seven EMS-transported stroke cases were linked to prehospital records from January 2018 through June 2019. In multivariable analysis, prehospital stroke scale documentation (adjusted odds ratio, 1.4 [1.2-1.6]), glucose check (1.3 [1.1-1.6]), on-scene time ≤15 minutes (1.6 [1.4-1.9]), hospital prenotification ([2.0 [1.4-2.9]), and intravenous line placement (1.8 [1.5-2.1]) were independently associated with a door-to-CT ≤25 minutes. A 5-point quality score (1 point for each element) was therefore developed. In multivariable analysis, a 1-point higher EMS quality score was associated with a shorter time from EMS contact to CT (-9.2 [-10.6 to -7.8] minutes; P<0.001) and thrombolysis (-4.3 [-6.4 to -2.2] minutes; P<0.001), and higher odds of discharge to home (adjusted odds ratio, 1.1 [1.0-1.2]; P=0.002). CONCLUSIONS: Five EMS actions recommended by national guidelines were associated with rapid CT imaging. A simple quality score derived from these measures was also associated with faster stroke evaluation, greater odds of reperfusion treatment, and discharge to home.

Cancer risk among people living with Human Immuodeficiency Virus (HIV) in Rwanda from 2007 to 2018.

Assessing the risk of cancer among people living with HIV (PLHIV) in the current era of antiretroviral therapy (ART) is crucial, given their increased susceptibility to many types of cancer and prolonged survival due to ART exposure. Our study aims to compare the association between HIV infection and specific cancer sites in Rwanda. Population-based cancer registry data were used to identify cancer cases in both PLHIV and HIV-negative persons. A probabilistic record linkage approach between the HIV and cancer registries was used to supplement HIV status ascertainment in the cancer registry. Associations between HIV infection and different cancer types were evaluated using unconditional logistic regression models. We performed several sensitivity analyses to assess the robustness of our findings and to evaluate the potential impact of different assumptions on our results. From 2007 to 2018, the cancer registry recorded 17,679 cases, of which 7% were diagnosed among PLHIV. We found significant associations between HIV infection and Kaposi's Sarcoma (KS) (adjusted odds ratio [OR]: 29.1, 95% CI: 23.2-36.6), non-Hodgkin lymphoma (NHL) (1.6, 1.3-2.0), Hodgkin lymphoma (HL) (1.6, 1.1-2.4), cervical (2.3, 2.0-2.7), vulvar (4.0, 2.5-6.5), penile (3.0, 2.0-4.5), and eye cancers (2.2, 1.6-3.0). Men living with HIV had a higher risk of anal cancer (3.1, 1.0-9.5) than men without HIV, but women living with HIV did not have higher risk than women without HIV (1.0, 0.2-4.3). Our study found that in an era of expanded ART coverage in Rwanda, HIV is associated with a broad range of cancers, particularly those linked to viral infections.

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.

Healthcare costs attributable to diabetes in pregnancy: A cost of illness study in Tasmania, Australia.

AIMS: To estimate the direct costs during the prenatal, delivery and postpartum periods in mothers with diabetes in pregnancy, compared to those without. METHODS: This study used a population-based dataset from 2004 to 2017, including 57,090 people with diabetes and 114,179 people without diabetes in Tasmania, Australia. Based on diagnostic codes, delivery episodes with gestational diabetes mellitus (GDM) were identified and matched with delivery episodes without diabetes in pregnancy. A group of delivery episodes with pre-existing diabetes was identified for comparison. Hospitalisation, emergency department and pathology costs of these groups were calculated and adjusted to 2020-2021 Australian dollars. RESULTS: There were 2774 delivery episodes with GDM, 2774 delivery episodes without diabetes and 237 delivery episodes with pre-existing diabetes identified. Across the 24-month period, the pre-existing diabetes group required the highest costs, totalling $23,536/person. This was followed by the GDM ($13,210/person), and the no diabetes group ($11,167/person). The incremental costs of GDM over the no diabetes group were $890 (95% CI 635; 1160) in the year preceding delivery; $812 (616; 1031) within the delivery period and $341 (110; 582) in the year following delivery (p < 0.05). Within the year preceding delivery, the incremental costs in the prenatal period were $803 (579; 1058) (p < 0.05). Within the year following delivery, the incremental costs in the postpartum period were $137 (55; 238) (p < 0.05). CONCLUSIONS: Our results emphasised the importance of proper management of diabetes in pregnancy in the prenatal and postpartum periods and highlighted the significance of screening and preventative strategies for diabetes in pregnancy.

Exploring the relationships between pathogen-specific prenatal infections requiring inpatient admission and domains of offspring behaviour at age 5.

BACKGROUND: Research exploring the relationship between prenatal infection and child behavioural outcomes would benefit from further studies utilising full-population samples with the scale to investigate specific infections and to employ robust designs. We tested the association among several common infections requiring inpatient admission during and after pregnancy with a range of childhood behavioural outcomes, to determine whether any negative impact was specific to the period of foetal development. METHODS: The sample included all mother-offspring pairs from the Australian state of New South Wales (NSW) for whom the child commenced their first year of full-time schooling in 2009 (~age 5 years; n = 77,302 offspring), with records linked across four health administrative data sets including the NSW perinatal data collection (PDC), the NSW admitted patient data collection (APDC) and the NSW component of the 2009 Australian Early Development Census (AEDC). Multivariable linear regression was used to test associations between a number of infections requiring inpatient admission during and after pregnancy with a range of teacher assessed behavioural outcomes. RESULTS: Associations specific to the prenatal period were only found for streptococcus A although this would need to be reproduced in external samples given the low prevalence. Otherwise, 12 out of 15 selected infections either showed no association prenatally or also demonstrated associations in the 12 months after pregnancy. For example, prenatal hepatitis C, influenza and urinary E. coli infections were associated with lower scores of several domains of childhood behaviour, but even stronger associations were found when these same maternal infections occurred after pregnancy. CONCLUSIONS: The prenatal infections we tested appeared not to impact childhood behaviour by altering foetal neurodevelopment. Rather, the strong associations we found among infections occurring during and after pregnancy point to either residual socioeconomic/lifestyle factors or a shared familial/genetic liability between infections and behavioural problems.

Identifying overlaps and disconnects between media reports and official records of nonfatal firearm injuries in Indianapolis, Indiana, 2021-2022.

OBJECTIVE: Open-source data systems, largely drawn from media sources, are commonly used by scholars due to the lack of a comprehensive national data system. It is unclear if these data provide an accurate and complete representation of firearm injuries and their context. The study objectives were to compare firearm injuries in official police records with media reports to better identify the characteristics associated with media reporting. METHODS: Firearm injuries were identified in open-source media reports and compared to nonfatal firearm injury (n = 1642) data from official police records between January 1, 2021 to December 31, 2022 in Indianapolis, Indiana. Events were matched on date, location, and event circumstances. Four multivariate, multi-level mixed effects logistic regression models were conducted to assess which survivor, event, and community characteristics were associated with media reporting. Data were analyzed 2023 - January 2024. RESULTS: Media reported 41% of nonfatal shootings in 2021 and 45% in 2022(p < 0.05), which is approximately two out of every five shootings. Shootings involving multiple survivors, children, and self-defense were more likely to be reported, whereas unintentional shootings and shootings that occurred in structurally disadvantaged communities were less likely to be reported. CONCLUSIONS: Findings suggest that relying on media reports of firearm injuries alone may misrepresent the numbers and contexts of shootings. Public health interventions that educate journalists about these important issues may be an impactful firearm violence prevention strategy. Also, it is critical to link data systems at the local level to ensure interventions are designed and evaluated using accurate data.

Novel linkage approach to join community-acquired and national data.

BACKGROUND: Community optometrists in Scotland have performed regular free-at-point-of-care eye examinations for all, for over 15 years. Eye examinations include retinal imaging but image storage is fragmented and they are not used for research. The Scottish Collaborative Optometry-Ophthalmology Network e-research project aimed to collect these images and create a repository linked to routinely collected healthcare data, supporting the development of pre-symptomatic diagnostic tools. METHODS: As the image record was usually separate from the patient record and contained minimal patient information, we developed an efficient matching algorithm using a combination of deterministic and probabilistic steps which minimised the risk of false positives, to facilitate national health record linkage. We visited two practices and assessed the data contained in their image device and Practice Management Systems. Practice activities were explored to understand the context of data collection processes. Iteratively, we tested a series of matching rules which captured a high proportion of true positive records compared to manual matches. The approach was validated by testing manual matching against automated steps in three further practices. RESULTS: A sequence of deterministic rules successfully matched 95% of records in the three test practices compared to manual matching. Adding two probabilistic rules to the algorithm successfully matched 99% of records. CONCLUSIONS: The potential value of community-acquired retinal images can be harnessed only if they are linked to centrally-held healthcare care data. Despite the lack of interoperability between systems within optometry practices and inconsistent use of unique identifiers, data linkage is possible using robust, almost entirely automated processes.

Impact of the COVID-19 Pandemic on HIV Test Uptake Among People Who Inject Drugs in the Context of an HIV Outbreak.

Glasgow, Scotland's largest city, has been experiencing an HIV outbreak among people who inject drugs (PWID) since 2015. A key focus of the public health response has been to increase HIV testing among those at risk of infection. Our aim was to assess the impact of COVID-19 on HIV testing among PWID in Glasgow. HIV test uptake in the last 12 months was quantified among: (1) PWID recruited in six Needle Exchange Surveillance Initiative (NESI) surveys (n = 6110); linked laboratory data for (2) people prescribed opioid agonist therapy (OAT) (n = 14,527) and (3) people hospitalised for an injecting-related hospital admission (IRHA) (n = 12,621) across four time periods: pre-outbreak (2010-2014); early-outbreak (2015-2016); ongoing-outbreak (2017-2019); and COVID-19 (2020-June 21). From the pre to ongoing period, HIV testing increased: the highest among people recruited in NESI (from 28% to 56%) and on OAT (from 17% to 54%) while the lowest was among people with an IRHA (from 15% to 42%). From the ongoing to the COVID-19 period, HIV testing decreased markedly among people prescribed OAT, from 54% to 37% (aOR 0.50, 95% CI 0.48-0.53), but increased marginally among people with an IRHA from 42% to 47% (aOR 1.19, 95% CI 1.08-1.31). In conclusion, progress in increasing testing in response to the HIV outbreak has been eroded by COVID-19. Adoption of a linked data approach could be warranted in other settings to inform efforts to eliminate HIV transmission.

A comparison of cohorts of children with cerebral palsy from a population register and hospital admission data: A data linkage study.

BACKGROUND: Administrative health data, such as hospital admission data, are often used in research to identify children/young people with cerebral palsy (CP). OBJECTIVES: To compare sociodemographic, clinical details and mortality of children/young people identified as having CP in either a CP population registry or hospital admission data. METHODS: We identified two cohorts of children/young people (birth years 2001-2010, age at study end or death 2 months to 19 years 6 months) with a diagnosis of CP from either (i) the New South Wales (NSW)/Australian Capital Territory (ACT) CP Register or (ii) NSW hospital admission data (2001-2020). Using record linkage, these data sources were linked to each other and NSW Death, Perinatal, and Disability datasets. We determined the sensitivity and positive predictive value (PPV) of CP diagnosis in hospital admission data compared with the NSW/ACT CP Register (gold standard). We then compared the sociodemographic and clinical characteristics and mortality of the two cohorts available through record linkage using standardised mean difference (SMD). RESULTS: There were 1598 children/young people with CP in the NSW/ACT CP Register and 732-2439 children/young people with CP in hospital admission data, depending on the case definition used. The sensitivity of hospital admission data for diagnosis of CP ranged from 0.40-0.74 and PPV 0.47-0.73. Compared with children/young people with CP identified in the NSW/ACT CP Register, a greater proportion of those identified in hospital admission data (one or more admissions with G80 case definition) were older, lived in major cities, had comorbidities including epilepsy, gastrostomy use, intellectual disability and autism, and died during the study period (SMD > 0.1). CONCLUSIONS: Sociodemographic and clinical characteristics differ between cohorts of children/young people with CP identified using a CP register or hospital admission data. Those identified in hospital admission data have higher rates of comorbidities and death, suggesting some may have progressive conditions and not CP. These differences should be considered when planning and interpreting research using various data sources.

The Medicines Intelligence Data Platform: A Population-Based Data Resource From New South Wales, Australia.

BACKGROUND: The Medicines Intelligence (MedIntel) Data Platform is an anonymised linked data resource designed to generate real-world evidence on prescribed medicine use, effectiveness, safety, costs and cost-effectiveness in Australia. RESULTS: The platform comprises Medicare-eligible people who are ≥18 years and residing in New South Wales (NSW), Australia, any time during 2005-2020, with linked administrative data on dispensed prescription medicines (Pharmaceutical Benefits Scheme), health service use (Medicare Benefits Schedule), emergency department visits (NSW Emergency Department Data Collection), hospitalisations (NSW Admitted Patient Data Collection) plus death (National Death Index) and cancer registrations (NSW Cancer Registry). Data are currently available to 2022, with approval to update the cohort and data collections annually. The platform includes 7.4 million unique people across all years, covering 36.9% of the Australian adult population; the overall population increased from 4.8 M in 2005 to 6.0 M in 2020. As of 1 January 2019 (the last pre-pandemic year), the cohort had a mean age of 48.7 years (51.1% female), with most people (4.4 M, 74.7%) residing in a major city. In 2019, 4.4 M people (73.3%) were dispensed a medicine, 1.2 M (20.5%) were hospitalised, 5.3 M (89.4%) had a GP or specialist appointment, and 54 003 people died. Anti-infectives were the most prevalent medicines dispensed to the cohort in 2019 (43.1%), followed by nervous system (32.2%) and cardiovascular system medicines (30.2%). CONCLUSION: The MedIntel Data Platform creates opportunities for national and international research collaborations and enables us to address contemporary clinically- and policy-relevant research questions about quality use of medicines and health outcomes in Australia and globally.

Analysis of the impact of COVID-19 on Scotland's care-homes from March 2020 to October 2021: national linked data cohort analysis.

BACKGROUND: The impact of the COVID-19 pandemic on long-term care residents remains of wide interest, but most analyses focus on the initial wave of infections. OBJECTIVE: To examine change over time in: (i) The size, duration, classification and pattern of care-home outbreaks of COVID-19 and associated mortality and (ii) characteristics associated with an outbreak. DESIGN: Retrospective observational cohort study using routinely-collected data. SETTING: All adult care-homes in Scotland (1,092 homes, 41,299 places). METHODS: Analysis was undertaken at care-home level, over three periods. Period (P)1 01/03/2020-31/08/2020; P2 01/09/2020-31/05/2021 and P3 01/06/2021-31/10/2021. Outcomes were the presence and characteristics of outbreaks and mortality within the care-home. Cluster analysis was used to compare the pattern of outbreaks. Logistic regression examined care-home characteristics associated with outbreaks. RESULTS: In total 296 (27.1%) care-homes had one outbreak, 220 (20.1%) had two, 91 (8.3%) had three, and 68 (6.2%) had four or more. There were 1,313 outbreaks involving residents: 431 outbreaks in P1, 559 in P2 and 323 in P3. The COVID-19 mortality rate per 1,000 beds fell from 45.8 in P1, to 29.3 in P2, and 3.5 in P3. Larger care-homes were much more likely to have an outbreak, but associations between size and outbreaks were weaker in later periods. CONCLUSIONS: COVID-19 mitigation measures appear to have been beneficial, although the impact on residents remained severe until early 2021. Care-home residents, staff, relatives and providers are critical groups for consideration and involvement in future pandemic planning.

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.

The use of linked administrative data in Australian randomised controlled trials: A scoping review.

BACKGROUND/AIMS: The demand for simplified data collection within trials to increase efficiency and reduce costs has led to broader interest in repurposing routinely collected administrative data for use in clinical trials research. The aim of this scoping review is to describe how and why administrative data have been used in Australian randomised controlled trial conduct and analyses, specifically the advantages and limitations of their use as well as barriers and enablers to accessing administrative data for use alongside randomised controlled trials. METHODS: Databases were searched to November 2022. Randomised controlled trials were included if they accessed one or more Australian administrative data sets, where some or all trial participants were enrolled in Australia, and where the article was published between January 2000 and November 2022. Titles and abstracts were independently screened by two reviewers, and the full texts of selected studies were assessed against the eligibility criteria by two independent reviewers. Data were extracted from included articles by two reviewers using a data extraction tool. RESULTS: Forty-one articles from 36 randomised controlled trials were included. Trial characteristics, including the sample size, disease area, population, and intervention, were varied; however, randomised controlled trials most commonly linked to government reimbursed claims data sets, hospital admissions data sets and birth/death registries, and the most common reason for linkage was to ascertain disease outcomes or survival status, and to track health service use. The majority of randomised controlled trials were able to achieve linkage in over 90% of trial participants; however, consent and participant withdrawals were common limitations to participant linkage. Reported advantages were the reliability and accuracy of the data, the ease of long term follow-up, and the use of established data linkage units. Common reported limitations were locating participants who had moved outside the jurisdictional area, missing data where consent was not provided, and unavailability of certain healthcare data. CONCLUSIONS: As linked administrative data are not intended for research purposes, detailed knowledge of the data sets is required by researchers, and the time delay in receiving the data is viewed as a barrier to its use. The lack of access to primary care data sets is viewed as a barrier to administrative data use; however, work to expand the number of healthcare data sets that can be linked has made it easier for researchers to access and use these data, which may have implications on how randomised controlled trials will be run in future.

The cascade of care for hepatitis C in Victoria, Australia: a data linkage cohort study.

BACKGROUND: Highly effective hepatitis C therapies are available in Australia. However, people living with hepatitis C face various barriers to accessing care and treatment. AIMS: To identify gaps in the cascade of care for hepatitis C and generate estimates of the number living with untreated infection according to population group, using a representative longitudinal study population. METHODS: We linked hepatitis C notification data from Victoria to national pathology, prescribing and death registry data. We assessed receipt of key clinical services in a large cohort who tested positive for hepatitis C from 1 January 2000 to 31 December 2016, with follow-up to 30 June 2018. We estimated the number still living with hepatitis C, adjusting for spontaneous clearance and mortality. RESULTS: The cohort comprised 45 391 people positive for hepatitis C. Of these, 13 346 (29%) received treatment and an estimated 28% (95% confidence interval (CI): 26-30%) were still living with chronic infection at 30 June 2018, with the remainder still living following spontaneous clearance (30%, 95% CI: 29-32%) or having died (12%, 95% CI: 12-12%). Half (50%) of those still living with hepatitis C were born from 1965 to 1980, and 74% first tested positive before 2011. CONCLUSIONS: Despite an enabling policy environment and subsidised therapy, many people in this cohort were not treated. Increased measures may be needed to engage people in care, including those who acquired hepatitis C more than 10 years ago.

Community views on the secondary use of general practice data: Findings from a mixed-methods study.

INTRODUCTION: General practice data, particularly when combined with hospital and other health service data through data linkage, are increasingly being used for quality assurance, evaluation, health service planning and research. In this study, we explored community views on sharing general practice data for secondary purposes, including research, to establish what concerns and conditions need to be addressed in the process of developing a social licence to support such use. METHODS: We used a mixed-methods approach with focus groups (November-December 2021), followed by a cross-sectional survey (March-April 2022). RESULTS: The participants in this study strongly supported sharing general practice data with the clinicians responsible for their care, and where there were direct benefits for individual patients. Over 90% of survey participants (N = 2604) were willing to share their general practice information to directly support their health care, that is, for the primary purpose of collection. There was less support for sharing data for secondary purposes such as research and health service planning (36% and 45% respectively in broad agreement) or for linking general practice data to data in the education, social services and criminal justice systems (30%-36%). A substantial minority of participants were unsure or could not see how benefits would arise from sharing data for secondary purposes. Participants were concerned about the potential for privacy breaches, discrimination and data misuse and they wanted greater transparency and an opportunity to consent to data release. CONCLUSION: The findings of this study suggest that the public may be more concerned about sharing general practice data for secondary purposes than they are about sharing data collected in other settings. Sharing general practice data more broadly will require careful attention to patient and public concerns, including focusing on the factors that will sustain trust and legitimacy in general practice and GPs. PATIENT AND PUBLIC CONTRIBUTION: Members of the public were participants in the study. Data produced from their participation generated study findings. CLINICAL TRIAL REGISTRATION: Not applicable.

Police-reported family violence victimisation or perpetration and mental health-related emergency department presentations: an Australian data-linkage study.

BACKGROUND: Family violence is a leading social determinant of mental ill-health but its link to mental health-related emergency department presentations is poorly understood. Existing research has largely used retrospective designs with a focus on victimisation, typically among women. We examined whether police-reported family violence victimisation and perpetration were prospectively associated with mental health emergency department presentations in women and men. We also identified family violence risk and vulnerability characteristics associated with such presentations. METHODS: Demographics, prior police involvement, and individual and relationship vulnerabilities were provided by Victoria Police for 1520 affected family members (i.e., primary victims) and 1470 respondents (i.e., persons alleged to have perpetrated family violence) from family violence reports in 2016-17. Emergency mental health presentations 22-30 months post-family-violence report were determined through linkage with the Victorian Emergency Minimum Dataset and compared to statewide presentations. RESULTS: Emergency mental health presentations during follow-up were identified in 14.3% of the family violence sample, with 1.9% presenting for self-harm. Mental health presentation rates per 1,000 people were markedly higher among affected family members and respondents of both sexes and all ages than in the general population, except for male affected family members aged 45 + . Adjusting for age and sex, the mental health presentation rate was 6 and 11 times higher among affected family members and respondents, respectively, than in the general population. Individual vulnerabilities were more closely related to risk of emergency mental health presentations than relationship characteristics. CONCLUSIONS: Police-recorded family violence is associated with increased mental health-related emergency department presentations over the short-to-medium term. Strengthened cross-sector collaboration is needed to identify, address, and refer individuals with overlapping family violence and mental health needs and to improve victims' and perpetrators' access to community mental health and related services. This should help prevent individuals from reaching a crisis point in their mental health.

Exploring attitudes and variation by sociodemographic factors in consent provided for financial data linkage in an experimental birth cohort study.

BACKGROUND: Improving our understanding of household incomes and what constitutes financial insecurity can help us to better understand how financial insecurity is experienced and how this can change over time within and between individuals and populations. However, financial circumstances are often perceived as sensitive and stigmatising, particularly within some ethnic minority groups. This research aims to explore attitudes and variation by sociodemographic factors in consent provided for financial data linkage in an experimental birth cohort study, in order to obtain validated income and benefits data and to better understand the impact of community interventions on the financial security of its participants and their families. METHODS: This research utilises an observational study design to explore consent rates, attitudes and variation in sociodemographic factors between participants of an experimental birth cohort in a deprived and ethnically diverse setting who consent and do not consent to financial data linkage. RESULTS: Overall, participants were equally likely to consent and decline consent for financial data linkage. Measures of socioeconomic insecurity were associated with being more likely to provide consent for financial data linkage. Participants who were not employed (OR 1.49 95% CI 0.93, 2.40) and were more financially insecure (OR 1.85 95% CI 1.14, 3.93) were more likely to provide consent for financial data linkage. Where the participant's first language was a language other than English, participants were also less likely to provide consent for data linkage (OR 0.65 95% CI 0.39, 0.98). The choice of consent for financial data linkage was not associated with: ethnicity; relationship factors; employment status of the participant's partner; person present at time of recruitment; and measures of health, such as general health, mental health, wellbeing and health-related quality of life. CONCLUSIONS: This research sets out an approach to obtaining validated income and benefits data, as a proxy measure for financial security, within an experimental birth cohort study in a deprived and ethnically diverse setting. It achieves good consent rates and demonstrates greater input from those who report greater potential need for financial support. Further research should be conducted to further understand the interplay of language spoken in this context.

Reduction in all-cause medical and caregiving costs through innovative health awareness projects in a rural area in Japan: a retrospective cohort study.

BACKGROUND: This study evaluates cost reduction in participants of a health awareness program (the Center of Healthy Aging Program, CHAP) in a Japanese rural area, characterized by an annual check-up and personalized interview on health issues and related risks immediately after the check-up. METHODS: This is a cross-sectional study using medical and caregiving costs and Japan-specific health check-up results in Hirosaki residents stored by the local government, which were individually-based linked to the CHAP information collected by Hirosaki University. This is the first study that used anonymized data with individually-based linkages to both a research institute and a local government in Japan under a strict limitation regarding linking to third-party data. We included residents who had been continuously enrolled for > 6 months as of 1 July 2015. We compared 5-year all-cause costs between three groups (with CHAP, with Japan-specific health check-up, and no check-up) using a multivariate negative binomial regression model considering risk factors including lifestyle habits and an inverse probability weight to adjust for baseline characteristics: age, sex, Charlson comorbidity index, baseline care level, and risk score of coronary heart diseases. RESULTS: A total of 384, 9805, and 32,630 residents aged 40-74 years were included for the CHAP, Japan-specific health check-up, and no check-up groups, respectively. The Japan-specific health check-up group showed older and higher Charlson comorbidity index than the others. After inverse probability weight adjusting, the amount of all-cause medical costs was significantly lower only in the CHAP group. Faster walking speed and exercise habits were independently associated with lower all-cause medical and caregiving costs. CONCLUSIONS: We demonstrated a 5-year all-cause cost reduction in residents who participated in the CHAP and also suggested the effect of exercise habits in Hirosaki, which indicated the significance of individually-based data linkages to external third-party data for all local governments to improve the health condition of residents.

Understanding Pathways into Care-homes using Data (UnPiCD study): a two-part model to estimate inpatient and care-home costs using national linked health and social care data.

BACKGROUND: Pathways into care-homes have been under-researched. Individuals who move-in to a care-home from hospital are clinically distinct from those moving-in from the community. However, it remains unclear whether the source of care-home admission has any implications in term of costs. Our aim was to quantify hospital and care-home costs for individuals newly moving-in to care homes to compare those moving-in from hospital to those moving-in from the community. METHODS: Using routinely-collected national social care and health data we constructed a cohort including people moving into care-homes from hospital and community settings between 01/04/2013-31/03/2015 based on records from the Scottish Care-Home Census (SCHC). Individual-level data were obtained from Scottish Morbidity Records (SMR01/04/50) and death records from National Records of Scotland (NRS). Unit costs were identified from NHS Scotland costs data and care-home costs from the SCHC. We used a two-part model to estimate costs conditional on having incurred positive costs. Additional analyses estimated differences in costs for the one-year period preceding and following care-home admission. RESULTS: We included 14,877 individuals moving-in to a care-home, 8,472 (57%) from hospital, and 6,405 (43%) from the community. Individuals moving-in to care-homes from the community incurred higher costs at £27,117 (95% CI £ 26,641 to £ 27,594) than those moving-in from hospital with £24,426 (95% CI £ 24,037 to £ 24,814). Hospital costs incurred during the year preceding care-home admission were substantially higher (£8,323 (95% CI£8,168 to £8,477) compared to those incurred after moving-in to care-home (£1,670 (95% CI£1,591 to £1,750). CONCLUSION: Individuals moving-in from hospital and community have different needs, and this is reflected in the difference in costs incurred. The reduction in hospital costs in the year after moving-in to a care-home indicates the positive contribution of care-home residency in supporting those with complex needs. These data provide an important contribution to inform capacity planning on care provision for adults with complex needs and the costs of care provision.

Evaluating Linkage Quality of Population-Based Administrative Data for Health Service Research.

BACKGROUND: To overcome the limitations of relying on data from a single institution, many researchers have studied data linkage methodologies. Data linkage includes errors owing to legal issues surrounding personal information and technical issues related to data processing. Linkage errors affect selection bias, and external and internal validity. Therefore, quality verification for each connection method with adherence to personal information protection is an important issue. This study evaluated the linkage quality of linked data and analyzed the potential bias resulting from linkage errors. METHODS: This study analyzed claims data submitted to the Health Insurance Review and Assessment Service (HIRA DATA). The linkage errors of the two deterministic linkage methods were evaluated based on the use of the match key. The first deterministic linkage uses a unique identification number, and the second deterministic linkage uses the name, gender, and date of birth as a set of partial identifiers. The linkage error included in this deterministic linkage method was compared with the absolute standardized difference (ASD) of Cohen's according to the baseline characteristics, and the linkage quality was evaluated through the following indicators: linked rate, false match rate, missed match rate, positive predictive value, sensitivity, specificity, and F1-score. RESULTS: For the deterministic linkage method that used the name, gender, and date of birth as a set of partial identifiers, the true match rate was 83.5 and the missed match rate was 16.5. Although there was bias in some characteristics of the data, most of the ASD values were less than 0.1, with no case greater than 0.5. Therefore, it is difficult to determine whether linked data constructed with deterministic linkages have substantial differences. CONCLUSION: This study confirms the possibility of building health and medical data at the national level as the first data linkage quality verification study using big data from the HIRA. Analyzing the quality of linkages is crucial for comprehending linkage errors and generating reliable analytical outcomes. Linkers should increase the reliability of linked data by providing linkage error-related information to researchers. The results of this study will serve as reference data to increase the reliability of multicenter data linkage studies.