Linked Health Data Research Articles

Navigating the climate-health nexus: linking health data with climate data to advance public health interventions

Navigating the climate-health nexus: linking health data with climate data to advance public health interventions

Housing tenure and acute lower respiratory tract infection admissions in two Scottish birth cohorts

Abstract Introduction Early-life acute lower respiratory tract infections (LRTI) have been associated with increased morbidity and mortality. Despite young children spending much of their time at home, the contribution of home ownership status, on LRTI hospital admissions is unknown. Objectives To estimate the association between housing tenure and the odds of LRTI hospitalization in children <2 years in two birth cohorts. Methods De-identified Scottish birth records were linked to maternal Census data (2001 and 2011) and to hospital admission data to construct two birth cohorts (Cohort 1 (C1), born 2000-2002; Cohort 2 (C2), 2010-2012). Using logistic regression we estimated the association of housing tenure (owned, social rented, private rented, rent-free) with the odds of LRTI hospital admission, before and after adjustment for maternal age, residential area, and maternal qualification level. Results Over the 2-year follow-up, there were 14,833 LRTI admissions in 12,527 children (10,832 children had 1 LRTI admission and 1,695 >1 LRTI admission). 75.6 % of all LRTI admissions were due to bronchiolitis. In C1 and C2, 4.0% and 5.3% children, respectively, had one or more LRTI admission. Compared to children living in owned housing, the odds of LRTI admission were higher in children living in social rented housing (C1: Odds ratio=1.40, 95% confidence interval: 1.31-1.49; C2: 1.23, 1.16-1.31), private rented (C1:1.24, 1.11,1.39; C2: 1.14, 1.06-1.21), and rent-free housing (C1: 1.53, 1.35,1.74; C2: 1.04, 0.80-1.36) after confounder adjustment. Conclusions We found an association between non-owned housing and higher odds of LRTI admission which was more marked in C1 than in C2. Further research is warranted to unpick the mechanisms underlying the association between housing tenure and LRTI admission. Interventions to prevent LRTI admissions could usefully target children living in non-owned housing. Key messages • This study demonstrates the value of administrative and health data linkage in improving our understanding of how socio-environmental factors might impact children’s respiratory health. • Children living in social and private rented housing (compared to owned housing) have a higher risk of LRTI hospital admission and could benefit the most from LRTI-lowering interventions.

Comparing Italian hospital discharge and mortality data: implications for epidemiological research

Abstract Background In Italy, regional governments maintain data warehouses of linked administrative health data (AHD) linked to demographic information including mortality. Legal reporting pathways for death certificate detail bypass the Region, resulting in significant amounts of missing data on cause and location of death in regional AHD warehouses and limiting epidemiological research on mortality and incidence. In this study, we determine for the first time in Italy the degree of agreement between last hospital diagnosis and primary cause of death, and how that agreement changes over time. Previous studies have found agreement ranging from 40% to 60%. Methods The COV-CVD cohort is comprised of 7.3 million adults aged 30+ from the Lombardy region of northwest Italy, representing all Lombardy residents registered with the health system as of 31 December 2019. Concordance was assessed using the first three characters of the reported cause of death (ICD-10 codes) and primary diagnosis at last hospitalization (converted from ICD-9CM). Results In the COV-CVD cohort there were 401,085 deaths between 1 January 2020 and 23 June 2023. Cause and location of death is missing for 50% and 54% of these deaths, respectively. 60% of deceased individuals had a hospitalization in the year before their death. Agreement between primary diagnosis at last hospitalization and cause of death was 27% overall and 40.5% for deaths in hospital. Missing location of death was reduced from 54% to 26%. Conclusions When using AHD from Italy, primary diagnosis at last hospitalization prior to death is not an appropriate proxy for cause of death, even when the death occurred in hospital. Different coding systems (ICD-10, ICD-9CM) further complicate comparisons and definitions in observational studies. Key messages • In Italy, primary diagnosis at last hospitalization before death is not an appropriate proxy for cause of death. • Poor linkage of mortality and health data limits epidemiological research.

Environmental Public Health Tracking in England- support for Health Impact Assessments

Abstract Environmental epidemiology is a key function for the public health service with regards to investigating the public health effects of environmental hazards, monitoring the public health efforts to control the environmental risks, and providing the evidence that informs decisions making and preparedness. At the United Kingdom Health Security Agency (UKHSA), the Environmental Public Health Tracking (EPHT) Programme, initiated in 2010, has developed a number of data streams to help link environment and health data, to support Health Impact Assessment (HIA). The main aims of the EPHT programme in England are to: 1. Identify populations at risk from exposure to significant environmental and chemical hazards 2. Investigate relationships between hazard and disease 3. Inform public health policy making 4. Optimise intervention and prevention strategies 5. Generate hypotheses for further research. Such EPHT functions are based on three key components: a) by building a national EPHT program that integrates surveillance of environmental hazards, exposures and related health outcomes, to allow data linkage and assessment of environmental and health information; b) strengthening the epidemiology science, by conducting research and training of the workforce and c) developing strategies for response to immediate risks, incidents and preparing for future risks. Examples to support HIA include a) developing an air pollution exposure surveillance work programme, that has designed a pilot population vulnerability indicator; b) developing indicators for climate change impacts for public health, c) reporting regularly on the health impacts of public fluoridation water supply schemes (as mandated by Government) and d) exploring risk factors associated with elevated blood lead concentration in children, through laboratory reporting to surveillance systems. The talk will highlight some examples of practice and outline how the EPHT programme in England has supported HIA practices.

11.A. Scientific session: Overcoming Real-World Challenges in Setting up Health Data Linkages for Public Health Policy

Abstract Background Linking available administrative data has gained momentum in the last years to enhance public health research and public health formulation. Linkage of diverse data sources can be leveraged to understand social-determinants of health, the cost-effectiveness of an intervention, and to evaluate impact of policies. For instance, data linkage has been proven to be a powerful approach to periodically analyze real-world progress of the COVID-19 pandemic. Today, we are witnessing an unparalleled increase in electronic health data stemming from citizens who interact with services such as healthcare providers, employers, sick funds, and other governmental structures. This enormous amount of data opens many innovative possibilities in epidemiological research. The main advantages of the secondary use of data are the following: 1) it is enriching for new collected data (e.g. survey study), 2) it provides comprehensive information of the target population, and 3) it is cheaper than new data collection. Data linkage between data sources is, however, often a herculean task, and it comes with considerable challenges such as: 1) juridical complexity related to intra-national and cross-border data governance procedures, 2) fragmented data integration, 3) data delivery delays. Addressing these challenges is essential to unlocking the true potential of data linkages for timely responses to emerging public health questions, thereby contributing to evidence-based policy and care and transforming our health research into a One Health approach. Objectives The workshop’s main aim is to present the researcher’s lessons-learned and approaches in applying data linkage from an European, and a country-level perspective through case-studies while creating a space for the public to share their own view. In this workshop we aim to 1) provide a helicopter overview of current data linkages approaches in Europe, 2) illustrate this with case studies from an international, and a country-level perspective, and 3) emphasize the challenges and disadvantages of those data linkages, while sharing potential solutions. Workshop outline The workshop is divided into a knowledge translation, and an interactive part. In the first part of the workshop, three speakers will give a presentation of each 10 minutes with a Q&A of 5 minutes between each presentation where data linkage will be introduced, and three case studies on how data linkage can be used will be presented. The first presentation will introduce approaches to data linkages in Europe, and will delve into how AI can be used during routine data linkage. The second presentation will show a case-study on how an international data linkages can be done in an European federated manner. The third presentation will further illustrate how nationally data can be linked to investigate health inequalities. In the second part of the workshop, the audience will be invited to interact with the speakers and share their experiences. Key messages • A comprehensive overview of different current data linkages approaches are provided, setting the stage for discussions on methods and best practices. • Administrative data linkages are a powerful tool to answer important public health challenges, but important challenges related to data governance need to be addressed to realize the full potential.

Cardiac events among a cohort of 17,389 patients receiving cancer chemotherapy: short and long term implications

BackgroundThe association between cardiovascular disease and carcinogenesis is bidirectional and well-established. Furthermore, cancer treatment improves overall patient survival, potentially at the cost of incremental and fatal cardiovascular disease (CVD).AimTo evaluate (a) In a real-world cohort, the proportion of patients offered cancer chemotherapy who have antecedent CVD (CVDA); (b) The rates of patient admission with subsequent development of CVD (CVDS) requiring hospital admission post assignment to chemotherapy; (c) The impact of CVDA and CVDS on mortality rates relative to those seen in patients without overt CVD (CVD−) and (d) The time course of mortality in CVD− versus CVDS patients.MethodsRetrospective analysis was performed in deidentified linked health data sets. Correlates of mortality were evaluated by Cox proportional hazards evaluation. Relative and absolute time-variability of CVD as a primary cause of death were determined.ResultsOf the total 17,389 patients, there were 2,159 with CVDA. Over a median follow-up time of 4.6 years, CVDS admissions (n = 8,529) occurred more commonly in the presence of CVDA (70.0% vs. 46.1%, p < 0.001), and more than 50% of CVDS cases occurred in the first 12 months of follow-up. The 5-year mortality rates were 71.5% for CVDA, 64.7% for CVDS, and 40.8% for CVD− (p < 0.001). Development of CVDS was associated with a substantially increased risk of mortality in the next 12 months. The development of CVDs was also associated with an increased risk of cardiovascular, as against non-cardiovascular, mortality (7.1% vs. 1.6%, p < 0.001).ConclusionsApproximately 50% of patients assigned to cancer chemotherapy developed CVDS, heralding a particularly high risk of mortality over the next 12 months. Both CVDA and CVDS are associated with substantial increases in mortality rates relative to those in CVD− patients. This increased risk merits close individual monitoring.

Socioeconomic inequity in the utilization of healthcare among people with eating disorders in Australia.

Little is known about socioeconomic equity in access to healthcare among people with eating disorders in Australia. This study aims to measure the extent of inequity in eating disorder-related healthcare utilization, analyze trends, and explore the sources of inequalities using New South Wales (NSW) administrative linked health data for 2005 to 2020. Socioeconomic inequities were measured using concentration index approach, and decomposition analysis was conducted to explain the factors accounting for inequality. Healthcare utilization included: public inpatient admissions, private inpatient admissions, visits to public mental health outpatient clinics and emergency department visits, with three different measures (probability of visit, total and conditional number of visits) for each outcome. Private hospital admissions due to eating disorders were concentrated among individuals from higher socioeconomic status (SES) from 2005 to 2020. There was no significant inequity in the probability of public hospital admissions for the same period. Public outpatient visits were utilized more by people from lower SES from 2008 to 2020. Emergency department visits were equitable, but more utilized by those from lower SES in 2020. Public hospital and emergency department services were equitably used by people with eating disorders in NSW, but individuals from high SES were more likely to be admitted to private hospitals for eating disorder care. Use of public hospital outpatient services was higher for those from lower SES. These findings can assist policymakers in understanding the equity of the healthcare system and developing programs to improve fairness in eating disorder-related healthcare in NSW.

Perinatal mortality among term births: Informing decisions about singleton early term births in Western Australia.

To minimise the risk of perinatal mortality, clinicians and expectant mothers must understand the risks and benefits associated with continuing the pregnancy. Report the gestation-specific risk of perinatal mortality at term. Population-based cohort study using linked health data to identify all singleton births at gestations 37-41 weeks, in Western Australia (WA) from 2009 to 2019. Lifetable analysis was used to combine the risk of each type of perinatal mortality and calculate the cumulative risk of perinatal mortality, termed the perinatal risk index (PRI). Rates of antepartum and intrapartum stillbirth and neonatal death, as well as the PRI, were examined for each gestational week at term by non-Aboriginal and Aboriginal ethnicity. For non-Aboriginal women, rates were also examined by time-period (pre- vs. post-WA Preterm Birth Prevention Initiative (the Initiative) rollout), primiparity, and obstetric risk. There were 332,084 singleton term births, including 60 perinatal deaths to Aboriginal mothers (3.2 deaths per 1000 births to Aboriginal mothers) and 399 perinatal deaths to non-Aboriginal mothers (1.3 deaths per 1000 births to non-Aboriginal mothers). For non-Aboriginal women, the PRI was at its lowest (PRI 0.80, 95% CI 0.61, 1.00) at 39 weeks gestation. For Aboriginal women, it was at its lowest at 38 weeks (PRI 2.43, 95% CI 0.48, 4.39) with similar risk at 39 weeks (PRI 2.68, 95% CI 1.22, 4.14). The PRI increased steadily after 39 weeks gestation. The risk of perinatal mortality was higher among Aboriginal women. The gestation-specific perinatal mortality rates were similar by the time-period, primiparity and obstetric risk. The gestational ages at term associated with the lowest risk of perinatal mortality reinforce that the recommendation not to deliver before 39 weeks without medical indication is applicable to both Aboriginal and non-Aboriginal women giving birth in WA. There was no increase in the perinatal mortality rate associated with the introduction of the Initiative.

Identifying disease phenotypes from linked health data: Comparison of self-report, hospital inpatient and primary care in UK Biobank.

ObjectivesAdministrative health data is commonly used for epidemiological research, however it is not well understood how disease phenotypes replicate across different data sources. ApproachUK Biobank is a prospective cohort study of 500,000 adults, with ascertainment of health outcomes using administrative health data. Prevalence at recruitment for 33 diseases were calculated in each health data source: self-report, primary-care, and hospital episode statistics (HES). Consistency of disease identification between sources, and median days between first diagnosis across data sources was determined. Linear regression was used to investigate determinant of differences in the average time between first diagnosis in primary-care and HES data. ResultsHypertension was the most commonly identified disease in both self-report and HES (26.5% and 12.1% respectively), and anxiety in primary-care (12.7%). Diseases could be grouped into: 1) those identified largely by self-report alone (e.g. migraine, constipation), with inconsistency in the date first diagnosed; 2) those identified largely by primary care alone (e.g. anxiety, depression), also with inconsistency in the date first diagnosed; and 3) those that appeared mostly in all three sources, with highly consistent date of first report (many were emergency hospital admissions [e.g. stroke]). A number of variables were associated with time between primary-care and HES diagnosis. For example, heavier smokers had a significantly shorter period between first primary-care and first HES record for asthma, diabetes and hypertension. Conclusions and ImplicationsThese results indicate that there are inherent biases in diseases ascertained from linked health data that must be taken into account for epidemiological studies.

Projecting patterns of health inequalities in England up to 2040 using linked health data

ObjectiveThe existence of wide inequalities in self-reported health across England is well-documented. Our research adds to this evidence by describing current patterns and projecting future patterns of inequality in diagnosed illness by deprivation. ApproachWe used a microsimulation model which combines individual-level data on demographics, health and mortality from linked data for primary and secondary care with survey responses on leading modifiable risk factors and epidemiological evidence on the associations between risk factors and chronic illness. We used the Cambridge Multimorbidity Score to measure multimorbidity. This assigns a weight to 20 common long-term conditions based on individuals’ healthcare use and their likelihood of death. We further focus on “major illness” which corresponds to a score greater than 1.5. ResultsWe project that health inequalities are not projected to improve between 2019 and 2040. In 2040, we project the difference in the average time spent without major illness between the most and least deprived 10% of areas in England to be 10.7 years. This is largely unchanged from 10.4 years in 2019. In 2040, we project there will be more working age adults living with major illness in the most deprived areas, more than double the rate in the least deprived areas (15.2% versus 6.8%). These rates remain largely unchanged from 2019 at 14.6% and 6.3% respectively. Conclusion and ImplicationsOn current trends, health inequalities are projected to persist into the future. This has significant implications not just for population health but for labour supply and wider economic growth.

Transparent reporting on multi-site studies about algorithms for linked health data: A systematic review of Health Data Research Network Canada’s Algorithms Inventory

ObjectiveMulti-site studies that use routinely-collected, linked health data often rely on validated algorithms to harmonize definitions of health conditions or other population characteristics across sites. If algorithm validation is not practicable, feasibility studies that assess whether an algorithm can be consistently and accurately implemented across sites, are recommended. We investigated the transparency of reporting on multi-site algorithm feasibility studies found in Health Data Research Network (HDRN) Canada’s Algorithms Inventory. ApproachPublished, multi-site Canadian feasibility studies about chronic or infectious disease algorithms were assessed using an adaptation of the RECORD (REporting of studies Conducted using Observational Routinely collected health Data) and STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) guidelines. Reviewers were trained on a subset of studies. The remainder were independently assessed by two reviewers and quality checks were conducted. Results were descriptively summarized. ResultsThirty published multi-site algorithm feasibility studies were reviewed; the majority were conducted in four or more sites, and 83% assessed chronic disease algorithms. Almost one-fifth (17%) of the studies did not justify the methods used to assess algorithm feasibility. However, the majority (&gt;95%) addressed potential sources of bias and discussed algorithm generalizability. ConclusionsWe observed accurate and complete reporting of most elements of multi-site algorithm feasibility studies conducted in Canada. These studies provided important information about availability of data elements, generalizability, and potential algorithm uses. ImplicationsTransparent reporting of algorithm feasibility studies facilitates algorithm reuse, enhances the credibility and reproducibility of study findings, and promotes collaboration within the data linkage community.

The application of deterministic and probabilistic methods of data linkage methods to link population and health data in western Uganda

IntroductionThere is increasing interest in record linkage between population-level data and health facility records to support epidemiological research in Africa. However, there is a lack of unique and ubiquitous identification systems for linkage. We applied two common data linkage approaches between population-level data from a health and demographic surveillance system and hospital records in Western Uganda. MethodologyWe established a data linkage system using deterministic and probabilistic linkage on population level data collected from 23 villages with hospital records. Deterministic linkage entails connecting a pair of records from the clinic and census data using a common identifier. Probabilistic linkage classifies a pair of records from two data sources as belonging to the same individual based on the statistical probability that a common set of identifiers drawn from the two data sources belong to the same individual. The preliminary results are on the deterministic approaches. ResultsUsing deterministic linkage, we fully linked 1061 records from 12/23 villages. Further updates of linkage with characteristics of the linked patients will be summarized in the next two months. Probabilistic linkage data will be presented with the characteristics of participants after the completion of the study, and the agreement between the two methods will be compared. Note to the results: Presentations during the conference will be done using finalized data. ConclusionPreliminary findings show that the linkage of population and health data is feasible. Findings could be used by researchers to design data linkage studies and answer different types of health and population research questions using innovative data science methods.

A game of snakes and ladders: the world of complex health and social care data linkage

Objective and ApproachResearch on social care services requires large, comprehensive, routine datasets. Launched in November 2019, Developing resources And minimum data set for Care Homes’ Adoption (DACHA) study aims to develop a prototype minimum dataset as proof of concept and to propose implementation. We describe our experience since 2021 of identifying, applying for, and linking care home, local, integrated care system (ICS) and national datasets, including direct-care software-provider data, GP and NHS England (NHSE) datasets. ResultsOur key challenges: Risk aversion and fragmented information governance within and between organisations. Complex information governance structures must be understood before participants are recruited. Shifts in the data landscape: data ownership moved from clinical commissioning groups to ICSs; NHSE merged with NHS Digital. Research funding: research is required of ICSs, but it is not a system priority, so processes and funding aren’t in place, and research burdens an already strained system. Our key lessons: Formalising agreements early on and obtaining, and maintaining, senior, committed buy-in. Studies should value the data sharing process through the inclusion of data controllers and information governance staff in the system in research project budgets. The facilitation of GP and social care data collection nationally must be balanced with its administrative burden. ImplicationsThe DACHA study overlapped with the COVID-19 pandemic and could only engage a limited number (n=3) of ICSs within project resources. Nevertheless, the complexity of the system and the plurality of actors delay or even block legitimate research interests.

Establishing Australia’s national linked COVID Register

Objective and ApproachThe Australian Institute of Health and Welfare (AIHW) is an independent statutory Australian Government agency tasked with collating health data across federal and state/territory governments, and is accredited to provide complex integration, de-identification and secure access to linked data. To support research into the COVID pandemic, the AIHW has created a national-level COVID Register, which integrates COVID case data from infectious disease registers, and data from hospitals and intensive care, immunisation, deaths, health system usage data, aged care and disability support. ResultsData were probabilistically linked using the AIHW’s linkage spine, matching names, addresses, date of birth and sex. The AIHW data linkage protocols are based on the Five Safes framework which reinforce management of the privacy and confidentiality of data. Linkage rates for COVID cases across participating jurisdictions generally exceeded 95%. Ongoing work aims to increase the coverage of COVID cases, both in time and to include case data from one remaining jurisdiction. ConclusionsLinking disparate datasets from multiple sources has created a critical resource for exploring COVID and patient journeys in Australia. Currently, the Register supports projects to estimate expenditure associated with COVID, describe the impact of COVID for subgroups such as people living rural and remote areas, or those with dementia. ImplicationsUltimately, the Register will be integrated into the National Health Data Hub to enable ongoing health research and analysis through enduring national linked health data. The value of the Register extends beyond COVID and into other infectious diseases and chronic conditions.

Detainer Requests Issued by ICE and Fair/Poor Self-Rated Health among Latines in the U.S., 2017–2020

AbstractU.S. Immigration and Customs Enforcement (ICE) issues detainer requests to local law enforcement agencies to hold detainees suspected of being undocumented immigrants until they can be transferred into ICE custody. We examined the association between area-level detainer requests and self-rated health among Latine adults. We linked health data from Latine adults included in the 2017–2020 Behavioral Risk Factor Surveillance System (n = 69,386) to detainer requests per 1,000 non-citizens in core-based statistical areas, (n = 152 across 49 states). We fit logistic regression models of self-rated fair/poor health on detainer requests, adjusted for individual- and area-level confounders. In adjusted analyses, we found that Latine adults living in areas with the highest quartile of requests had 24% higher odds of fair/poor health (OR 1.24, 95% CI = 1.05,1.47) relative to those in the lowest quartile. Local law enforcement agencies should limit cooperation with federal immigrant agencies to protect the health of Latine communities.

The Safety of Methoxyflurane for Emergency Pain Relief in Children and Adolescents: A Retrospective Cohort Study

Objectives The use of methoxyflurane is becoming increasingly popular in the treatment of pain in an emergency setting, in part due to its ease of administration. However, little is known about the risk of serious adverse events in children and adolescents. The aim of this study was to examine the safety of methoxyflurane in a pediatric population. Methods The study was a retrospective cohort study of pediatric prehospital events using probabilistic linked health data. All ambulance transfers in Western Australia between 1990 and 2016 involving children and adolescent patients were identified. Patients were categorized based on administered analgesia: methoxyflurane, an opioid analgesic, both methoxyflurane and an opioid analgesic, or no analgesic. Hospital and mortality data were linked to transferred patients to identify deaths, adverse drug reactions, liver and kidney toxicity, and re-admissions to hospital following ambulance transfer. Generalized linear models, adjusting for sociodemographic and ambulance transfer characteristics, were used to compare outcomes between children exposed to methoxyflurane and the other three groups. Results The study cohort consisted of 37,211 children, including 9,472 patients (25.5%) treated with methoxyflurane alone, 2,764 (7.4%) treated with an opioid analgesic, 1,235 (3.3%) treated with both methoxyflurane and an opioid analgesic, and 23,740 (63.8%) treated with no analgesic. Death in children and adolescents was uncommon, with less than five deaths (<0.1%) observed in the 12 months following treatment with methoxyflurane and no deaths in those treated with both methoxyflurane and an opioid analgesic. Adverse drug reaction was rare (<0.1%) in patients treated with methoxyflurane, as was liver and kidney toxicity with no case observed. At 90-days follow-up, there was no significant difference in hospitalization in patients treated with methoxyflurane and those treated with methoxyflurane and an opioid analgesic (adjusted OR:1.01, 95%CI:0.85-1.21). Compared with methoxyflurane treated patients, patients treated with an opioid analgesic were more likely to be hospitalized (aOR:1.23, 95%CI:1.09-1.39), while patients treated with no analgesic were less likely to be hospitalized (aOR:0.85, 95%CI:0.79-0.92). Conclusions In children and adolescents transported by ambulance, the use of methoxyflurane was not associated with an increased risk of hospitalization, death, serious adverse drug reactions or liver and kidney toxicity.

Long-term cohort study of patients presenting with hypercapnic respiratory failure

ObjectiveWe sought to describe the long-term prognosis for a population-based cohort of people with hypercapnic respiratory failure (HRF) and the associations between underlying diagnoses and the risks of death and...

Healthcare costs following falls and cataract surgery in older adults using Australian linked health data from 2012-2019.

To investigate publicly funded healthcare costs according to faller status and the periods pre- and post-cataract surgeries, and identify factors associated with higher monthly costs in older people with bilateral cataract. This prospective cohort study included community-dwelling older people aged 65 and over (between 2012 and 2019); at baseline participants had bilateral cataract and were waiting for cataract surgery in New South Wales (NSW) public hospitals. Participants were followed for 24 months. The study used self-reported and linked data (Medicare Benefits Schedule, Pharmaceutical Benefits Scheme, NSW Admitted Patient and Emergency Department Data Collections) to identify falls, cataract surgeries and healthcare costs incurred by the Australian and NSW Governments, all costs were inflated to 2018-19 Australian dollars (AUD). Median monthly healthcare costs were calculated for faller status (non-faller, non-medically treated faller, medically treated faller) and surgery periods (pre-surgery, post-first surgery, post-second surgery). Costs in the 30 days following a medically treated fall were estimated. A generalised linear model was used to investigate predictors of healthcare costs. During the median follow-up period of 24 months, 274 participants suffered 448 falls, with 95 falls requiring medical treatment. For medically treated falls, the mean cost in the 30 days after treatment was A$3779 (95% confidence interval $2485, $5074). Higher monthly healthcare costs were associated with a higher number of medications, being of the male sex, having one or more medically treated falls and having bilateral cataract surgery. After excluding the cost of cataract surgery, there were no significant differences in healthcare costs between the pre-cataract surgery, post-first eye cataract surgery and post-second eye cataract surgery periods. To our knowledge, this is the first study investigating publicly funded costs related to falls and cataract surgery in older people with bilateral cataract. This information enhances our understanding of healthcare costs in this group. The patterns in costs associated with falls can guide future government healthcare expenditure on falls treatment and prevention, including timely cataract surgery.

Vaccine Coverage at 36 Months and 7 Years by Parental Birth Country, Washington State.

Ensuring equitable vaccination access for immigrant communities is critical for guiding efforts to redress health disparities, but vaccine coverage data are limited. We evaluated childhood vaccination coverage by parental birth country (PBC) through the linkage of Washington State Immunization Information System data and birth records. We conducted a retrospective cohort evaluation of children born in Washington from January 1, 2006 to November 12, 2019. We assessed up-to-date vaccination coverage status for measles, mumps, and rubella (MMR), diphtheria, tetanus, and pertussis (DTaP), and poliovirus vaccines at ages 36 months and 7 years. Children with ≥1 parent(s) born in selected non-US countries were compared with children with 2 US-born parents, using Poisson regression models to provide prevalence ratios. We identified 902 909 eligible children, of which 24% had ≥1 non-US-born parent(s). Vaccination coverage at 36 months by PBC ranged from 41.0% to 93.2% for ≥1 MMR doses and ≥3 poliovirus doses and 32.6% to 86.4% for ≥4 DTaP doses. Compared with children of US-born parents, the proportion of children up to date for all 3 vaccines was 3% to 16% higher among children of Filipino-, Indian-, and Mexican-born parents and 33% to 56% lower among children of Moldovan-, Russian-, and Ukrainian-born parents. Within-PBC coverage patterns were similar for all vaccines with some exceptions. Similar PBC-level differences were observed at 7 years of age. The linkage of public health data improved the characterization of community-level childhood immunization outcomes. The findings provide actionable information to understand community-level vaccination determinants and support interventions to enhance vaccine coverage.

Design and implementation of the Our Health Counts (OHC) methodology for First Nations, Inuit, and Metis (FNIM) health assessment and response in urban and related homelands.

Methods for enumeration and population-based health assessment for First Nations, Inuit, and Metis (FNIM) living in Canadian cities are underdeveloped, with resultant gaps in essential demographic, health, and health service access information. Our Health Counts (OHC) was designed to engage FNIM peoples in urban centres in "by community, for community" population health assessment and response. The OHC methodology was designed to advance Indigenous self-determination and FNIM data sovereignty in urban contexts through deliberate application of Indigenous principles and linked implementation strategies. Three interwoven principles (good relationships are foundational; research as gift exchange; and research as a vehicle for Indigenous community resurgence) provide the framework for linked implementation strategies which include actively building and maintaining relationships; meaningful Indigenous community guidance, leadership, and participation in all aspects of the project; transparent and equitable sharing of project resources and benefits; and technical innovations, including respondent-driven sampling, customized comprehensive health assessment surveys, and linkage to ICES data holdings to generate measures of health service use. OHC has succeeded across six urban areas in Ontario to advance Indigenous data sovereignty and health assessment capacity; recruit and engage large population-representative cohorts of FNIM living in urban and related homelands; customize comprehensive health surveys and data linkages; generate previously unavailable population-based FNIM demographic, health, and social information; and translate results into enhanced policy, programming, and practice. The OHC methodology has been demonstrated as effective, culturally relevant, and scalable across diverse Ontario cities.