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Targeted analytics help Canadian healthcare groups combat homelessness, boost SDOH

Sed ut perspiciatis unde. Homelessness is a complex and challenging phenomenon, not just in the U.S. but across its neighbor to the north: It has been estimated that anywhere from 100,000 to 300,000 individuals experience homelessness in a given year in Canada, with more than 35,000 individuals experiencing homelessness on any given night in the country.THE PROBLEMThe increasing economic pressures faced by people across all levels of society – combined with other recent public health disruptions, such as the pandemic – have placed a spotlight on the growing crisis. The causes and solutions to homelessness are multifaceted and often politically charged.“Prior to the pandemic, I had been working with various colleagues at the Western University Arthur Labatt Family School of Nursing, Lawson Health Research Institute, and ICES – formerly known as the Institute for Clinical Evaluative Sciences – on topics related to the effectiveness of housing interventions and other approaches to assist people experiencing homelessness,” or PEH, said Richard Booth, RN, an associate professor at Western University Arthur Labatt Family School of Nursing in London, Ontario.“One evaluation direction we had begun to explore was the use of secondary healthcare administrative data to better understand homelessness,” he explained. “In some of our previous studies, using healthcare administrative data was a secondary objective to the primary intervention being studied; for example, housing interventions or shelter deferral interventions.”That all changed in late 2019 when the Public Health Agency of Canada (PHAC) released a sizable expression of interest funding contribution, to which the Labatt Family School of Nursing decided to apply and propose a two-armed study to explore homelessness in Canada using both qualitative and quantitative methods.“We were successfully funded, and the Homelessness Counts project came to life in late 2020,” Booth recalled. “My co-primary investigator, Dr. Cheryl Forchuk, led the qualitative arm of the study and has, to date, traveled across Canada to every province and territory multiple times over the last three years, interviewing PEH and other service providers to better understand contemporary homelessness.“With more than 400 interviews, I’m fairly certain Dr. Forchuk has conducted what is the single largest collection of voices and experiences of homelessness in Canada during the height of the pandemic,” he continued.From a quantitative perspective, Booth led aspects of a larger analysis to refine and test a case ascertainment algorithm that could be used to identify cases of homelessness within healthcare administrative data.“Working with ICES Staff Scientist Dr. Salimah Shariff and other colleagues at ICES, we began leveraging a previously developed and validated case-ascertainment algorithm that could be used within secondary healthcare administrative data to locate cases of people who had experienced a recent episode of homelessness,” Booth said.“Development of an algorithm like this had not been attempted within Canada’s data science research domain, and we felt if we were able to generate an algorithm that had reliable sensitivity, we could use this approach to better understand aspects of the homelessness phenomenon,” he continued.Most Ontarian residents receive medically necessary services under the single-payer, provincially funded Ontario Health Insurance Plan (OHIP), which includes primary and specialty physician services, emergency department visits, hospital stays, laboratory and diagnostic testing, and other community healthcare services.These data are prospectively collected and available in centralized databases at ICES, which is an independent, non-profit research institute. Its legal status under Ontario’s health information privacy law allows it to collect and analyze healthcare and demographic data without consent for health system evaluation and improvement.ICES comprises a set of linked databases, connecting more than 100 different sources of health and health-related data on Ontarians (population more than 15 million), encompassing more than 30,000,000,000 records and several hundred thousand variables, spanning a 30-year period.“From this point, with our PHAC study Homelessness Counts launching in fall 2020 during the height of the pandemic, we set out to generate multi-dimensional interpretations of homelessness in Canada,” Booth said. “From a data science perspective, we quickly realized our case ascertainment algorithm could be used to generate immediate and important policy insights.“We were able to calculate the testing, infection and complication rates of COVID-19 among people with a recent history of homelessness,” he continued. “Shortly after, we were also able to use our case ascertainment algorithm to uncover the vaccination coverage of PEH versus others in Ontario. Both of these studies demonstrated the utility of this algorithm and how it could be used to assist in generating policy and practice insights, especially related to contemporary issues.”PROPOSALHomelessness is a complex phenomenon with many moving parts, and no simple solutions exist. The Homelessness Counts project is intended to be one small element in a larger movement required to address modern-day homelessness.“Homelessness is evolving in its complexity and nuance due to pressures experienced during the pandemic and other socio-economic-environmental factors currently affecting society,” Booth explained. “Therefore, while our project and use of data analytics to address questions regarding homelessness are far from a panacea for homelessness, we believe our methodological approaches can be leveraged by others to generate more timely and accurate interpretations of homelessness and the health and well-being of this vulnerable population.“In many ways, unless something is quantified, it can be overlooked in policymaking,” he continued. “Through our approaches, we can quickly and cost-effectively quantify homelessness along with other variables of interest; for example, healthcare utilization, individual health, comorbidities, living location, etc. This ability allows us to enumerate the situations faced by PEH, providing evidence to confirm the existence of these situations.”For instance, in ongoing and future work related to this project, staff have both identified and enumerated emerging trends of concern within PEH populations, including the significant burden of Alzheimer’s disease and related dementias, and the high rates of opioid-toxicity mortality compared to other subpopulations and the entire Ontarian population.“We believe our approaches provide us with much better abilities to generate population-level, quantitative evidence and insights into the realities faced by PEH,” Booth said. “While far from being a solution to homelessness, having more accurate numerical insights into the issues at hand can assist in generating more targeted and proactive solutions.“We have generated a methodological publication explaining our case ascertainment approach, including its benefits, limitations and other considerations,” he added.MEETING THE CHALLENGEWestern University Arthur Labatt Family School of Nursing was fortunate to collaborate with ICES in Ontario to complete various aspects of the larger Homelessness Counts project, Booth noted.“Since most Ontarians receive healthcare services under the single-payer, provincially funded Ontario Health Insurance Plan (OHIP), we can use administrative data, including homelessness definitions within this data, to create cohorts of people who have recently experienced homelessness,” he explained.“While other healthcare organizations, such as the United States Veterans Affairs, and insurance companies may have linked databases like this, we are exceptionally fortunate within Ontario to have an organization like ICES that can explore phenomena at the population level,” he added. “More information about ICES can be found on their brief YouTube video describing their data and organization.”RESULTSThe three organizations working together have been able to enumerate various contemporary phenomena in PEH populations, including increased testing, infection and complications of COVID-19 infection across six waves of the pandemic.Additionally, they have identified reduced coverage of COVID-19 vaccination in PEH, an increasing trend of opioid-toxicity mortality in PEH over the last several years, and rising trends of dementia in PEH populations.They have other preliminary findings from various projects related to Homelessness Counts, but these are still being finalized.“Two weeks after the publication of our paper in CMAJ Open outlining the testing, infection and complication rates of COVID-19 among people with a recent history of homelessness in early 2021, individuals experiencing homelessness were added to the prioritization list for early COVID-19 vaccination in Ontario,” Booth reported.“While a temporal association does not imply causation, we suspect our findings in this work may have been used to inform early vaccination distribution efforts and to help prioritize PEH populations,” he said.ADVICE FOR OTHERS“If anything, having the ability to ask robust and important questions of data; and, having the insights to know what constitutes an appropriate question to ask of large data sets, is by far more important in this type of work than any specific software or technology,” Booth advised. “Researchers and practitioners must confirm the underlying data is of good quality, as otherwise they can run the risk of producing results that follow the ‘garbage in/garbage out’ process – or worse, create or propagate harms.”Follow Bill’s HIT coverage on LinkedIn: Bill SiwickiEmail him: [email protected] IT News is a HIMSS Media publication.Source link Save my name, email, and website in this browser for the next time I comment.By using this form you agree with the storage and handling of your data. * Δdocument.getElementById( "ak_js_1" ).setAttribute( "value", ( new Date() ).getTime() );Tech dedicated news site to equip you with all tech related stuff.I agree that my submitted data is being collected and stored.✉️ Send us an emailTechToday © 2023. 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