Dataset Information

Public housing and healthcare use: an investigation using linked administrative data.

ABSTRACT: OBJECTIVE:This study investigated whether a move to public housing affects people's use of healthcare services. METHOD:Using administrative data from Manitoba, the number of hospitalizations, general practitioner (GP), specialist and emergency department (ED) visits, and prescription drugs dispensed in the years before and after the housing move-in date (2012/2013) were measured for a public housing and matched cohort. Generalized linear models with generalized estimating equations tested for differences between the cohorts in utilization trends. The data were modeled using Poisson (rate ratio, RR), negative binomial (incident rate ratio, IRR), and binomial (odds ratio, OR) distributions. RESULTS:GP visits (IRR?=?1.04, 95% CI 1.01-1.06) and prescriptions (IRR?=?1.04, 95% CI 1.02-1.05) increased, while ED visits (RR?=?0.90, 95% CI 0.82-1.00) and hospitalizations (OR?=?0.95, 95% CI 0.93-0.96) decreased over time. The public housing cohort had a significantly higher rate of GP visits (IRR?=?1.08, 95% CI 1.04-1.13), ED visits (RR?=?1.18, 95% CI 1.01-1.37), and prescriptions (IRR?=?1.09, 95% CI 1.05-1.13), and was more likely to be hospitalized (OR?=?1.39, 95% CI 1.21-1.61) compared to the matched cohort. The rate of inpatient days significantly decreased for the public housing cohort, but did not change for the matched cohort. CONCLUSION:Healthcare use changed similarly over time (except inpatient days) for the two cohorts. Public housing provides a basic need to a population who has a high burden of disease and who may not be able to obtain and maintain housing in the private market.

SUBMITTER: Hinds AM

PROVIDER: S-EPMC6964390 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Public housing and healthcare use: an investigation using linked administrative data.

Hinds Aynslie M AM Bechtel Brian B Distasio Jino J Roos Leslie L LL Lix Lisa M LM

Canadian journal of public health = Revue canadienne de sante publique 20181213 2

<h4>Objective</h4>This study investigated whether a move to public housing affects people's use of healthcare services.<h4>Method</h4>Using administrative data from Manitoba, the number of hospitalizations, general practitioner (GP), specialist and emergency department (ED) visits, and prescription drugs dispensed in the years before and after the housing move-in date (2012/2013) were measured for a public housing and matched cohort. Generalized linear models with generalized estimating equation ...[more]

PMID: 30547290

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Project description:ObjectiveWe described development, health and justice system outcomes for children in contact with child protection and public housing.DesignDescriptive analysis of outcomes for children known to child protection who also had contact with public housing drawn from the South Australian (SA) Better Evidence Better Outcomes Linked Data (BEBOLD) platform.SettingThe BEBOLD platform holds linked administrative records collected by government agencies for whole-population successive birth cohorts in SA beginning in 1999.ParticipantsThis study included data from birth registrations, perinatal, child protection, public housing, hospital, emergency department, early education and youth justice for all SA children born 1999-2013 and followed until 2016. The base population notified at least once to child protection was n=67 454.Primary outcome measureContact with the public housing system.Secondary outcome measuresHospitalisations and emergency department presentations before age 5, and early education at age 5, and youth justice contact before age 17.ResultsMore than 60% of children with at least one notification to child protection had contact with public housing, and 60.2% of those known to both systems were known to housing first. Children known to both systems experienced more emergency department and hospitalisation contacts, greater developmental vulnerability and were about six times more likely to have youth justice system contact.ConclusionsThere is substantial overlap between involvement with child protection and public housing in SA. Those children are more likely to face a life trajectory characterised by greater contact with the health system, greater early life developmental vulnerability and greater contact with the criminal justice system. Ensuring the highest quality of supportive early life infrastructure for families in public housing may contribute to prevention of contact with child protection and better life trajectories for children.

Project description:BACKGROUND:Residence in public housing, a subsidized and managed government program, may affect health and healthcare utilization. We compared healthcare use in the year before individuals moved into public housing with usage during their first year of tenancy. We also described trends in use. METHODS:We used linked population-based administrative data housed in the Population Research Data Repository at the Manitoba Centre for Health Policy. The cohort consisted of individuals who moved into public housing in 2009 and 2010. We counted the number of hospitalizations, general practitioner (GP) visits, specialist visits, emergency department visits, and prescriptions drugs dispensed in the twelve 30-day intervals (i.e., months) immediately preceding and following the public housing move-in date. Generalized linear models with generalized estimating equations tested for a period (pre/post-move-in) by month interaction. Odds ratios (ORs), incident rate ratios (IRRs), and means are reported along with 95% confidence intervals (95% CIs). RESULTS:The cohort included 1942 individuals; the majority were female (73.4%) who lived in low income areas and received government assistance (68.1%). On average, the cohort had more than four health conditions. Over the 24 30-day intervals, the percentage of the cohort that visited a GP, specialist, and an emergency department ranged between 37.0% and 43.0%, 10.0% and 14.0%, and 6.0% and 10.0%, respectively, while the percentage of the cohort hospitalized ranged from 1.0% to 5.0%. Generally, these percentages were highest in the few months before the move-in date and lowest in the few months after the move-in date. The period by month interaction was statistically significant for hospitalizations, GP visits, and prescription drug use. The average change in the odds, rate, or mean was smaller in the post-move-in period than in the pre-move-in period. CONCLUSIONS:Use of some healthcare services declined after people moved into public housing; however, the decrease was only observed in the first few months and utilization rebounded. Knowledge of healthcare trends before individuals move in are informative for ensuring the appropriate supports are available to new public housing residents. Further study is needed to determine if decreased healthcare utilization following a move is attributable to decreased access.

Project description:Background/aimsThe 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.MethodsDatabases 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.ResultsForty-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.ConclusionsAs 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.

Project description:BackgroundAboriginal people are under-reported on administrative health data in Australia. Various approaches have been used or proposed to improve reporting of Aboriginal people using linked records. This cross-sectional study used self-reported Aboriginality from the NSW Patient Survey Program (PSP) as a reference standard to assess the accuracy of reporting of Aboriginal people on NSW Admitted Patient (APDC) and Emergency Department Data Collections (EDDC), and compare the accuracy of selected approaches to enhance reporting Aboriginality using linked data.MethodsTen PSP surveys were linked to five administrative health data collections, including APDC, EDDC, perinatal, and birth and death registration records. Accuracy of reporting of Aboriginality was assessed using sensitivity, specificity, and positive and negative predictive values (PPVs and NPVs) and F score for the EDDC and APDC as baseline and four enhancement approaches using linked records: "Most recent linked record", "Ever reported as Aboriginal", and two approaches using a weight of evidence, "Enhanced Reporting of Aboriginality (ERA) algorithm" and "Multi-stage median (MSM)".ResultsThere was substantial under-reporting of Aboriginality on APDC and EDDC records (sensitivities 84 and 77% respectively) with PPVs of 95% on both data collections. Overall, specificities and NPVs were above 98%. Of people who were reported as Aboriginal on the PSP, 16% were not reported as Aboriginal on any of their linked records. Record linkage approaches generally increased sensitivity, accompanied by decrease in PPV with little change in overall F score for the APDC and an increase in F score for the EDDC. The "ERA algorithm" and "MSM" approaches provided the best overall accuracy.ConclusionsWeight of evidence approaches are preferred when record linkage is used to improve reporting of Aboriginality on administrative health data collections. However, as a substantial number of Aboriginal people are not reported as Aboriginal on any of their linked records, improvements in reporting are incomplete and should be taken into account when interpreting results of any analyses. Enhancement of reporting of Aboriginality using record linkage should not replace efforts to improve recording of Aboriginal people at the point of data collection and addressing barriers to self-identification for Aboriginal people.

Project description:IntroductionApproximately 14% of Australian women smoke during pregnancy. Although the risk of adverse outcomes is reduced by smoking cessation, less than 35% of Australian women quit smoking spontaneously during pregnancy. Evidence for the efficacy of bupropion, varenicline or nicotine replacement therapy as smoking cessation aids in the non-pregnant population suggest that pharmacotherapy for smoking cessation is worth exploring in women of childbearing age. Currently, little is known about the utilisation, effectiveness and safety of pharmacotherapies for smoking cessation during pregnancy; neither the extent to which they are used prior to pregnancy nor whether their use has changed in response to related policy reforms. The Smoking MUMS (Maternal Use of Medications and Safety) Study will explore these issues using linked person-level data for a population-based cohort of Australian mothers.Methods and analysisThe cohort will be assembled by linking administrative health records for all women who gave birth in New South Wales or Western Australia since 2003 and their children, including records relating to childbirth, use of pharmaceuticals, hospital admissions, emergency department presentations and deaths. These longitudinal linked data will be used to identify utilisation of smoking cessation pharmacotherapies during and between pregnancies and to explore the associated smoking cessation rates and maternal and child health outcomes. Subgroup and temporal analyses will identify potential differences between population groups including indigenous mothers and social security recipients and track changes associated with policy reforms that have made alternative smoking cessation pharmacotherapies available.Ethics and disseminationEthical approval has been obtained for this study. To enhance the translation of the project's findings into policy and practice, policy and clinical stakeholders will be engaged through a reference group and a policy forum will be held. Outputs from the project will include scientific papers and summary reports designed for policy audiences.

Project description:BACKGROUND:High utilizers (HUs) are a small group of patients who impose a disproportionately high burden on the healthcare system due to their elevated resource use. Identification of persistent HUs is pertinent as interventions have not been effective due to regression to the mean in majority of patients. This study will use cost and utilization metrics to segment a hospital-based patient population into HU groups. METHODS:The index visit for each adult patient to an Academic Medical Centre in Singapore during 2006 to 2012 was identified. Cost, length of stay (LOS) and number of specialist outpatient clinic (SOC) visits within 1 year following the index visit were extracted and aggregated. Patients were HUs if they exceeded the 90th percentile of any metric, and Non-HU otherwise. Seven different HU groups and a Non-HU group were constructed. The groups were described in terms of cost and utilization patterns, socio-demographic information, multi-morbidity scores and medical history. Logistic regression compared the groups' persistence as a HU in any group into the subsequent year, adjusting for socio-demographic information and diagnosis history. RESULTS:A total of 388,162 patients above the age of 21 were included in the study. Cost-LOS-SOC HUs had the highest multi-morbidity and persistence into the second year. Common conditions among Cost-LOS and Cost-LOS-SOC HUs were cardiovascular disease, acute cerebrovascular disease and pneumonia, while most LOS and LOS-SOC HUs were diagnosed with at least one mental health condition. Regression analyses revealed that HUs across all groups were more likely to persist compared to Non-HUs, with stronger relationships seen in groups with high SOC utilization. Similar trends remained after further adjustment. CONCLUSION:HUs of healthcare services are a diverse group and can be further segmented into different subgroups based on cost and utilization patterns. Segmentation by these metrics revealed differences in socio-demographic characteristics, disease profile and persistence. Most HUs did not persist in their high utilization, and high SOC users should be prioritized for further longitudinal analyses. Segmentation will enable policy makers to better identify the diverse needs of patients, detect gaps in current care and focus their efforts in delivering care relevant and tailored to each segment.

Dataset Information

Public housing and healthcare use: an investigation using linked administrative data.

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Public housing and healthcare use: an investigation using linked administrative data.

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