Regional variation in healthcare spending and mortality among senior high-cost healthcare users in Ontario, Canada: a retrospective matched cohort study

Socio-demographic determinants of COVID-19 vaccine uptake in Ontario: Exploring differences across the Health Region model

The COVID-19 pandemic continues to be a worldwide public health concern. Although vaccines against this disease were rapidly developed, vaccination uptake has not been equal across all the segments of the population, particularly in the case of underrepresented groups. However, there are also differences in vaccination across geographical areas, which might be important to consider in the development of future public health vaccination policies. In this study, we examined the relationship between vaccination status (having received the first dose of a COVID-19 vaccine), socio-economic strata, and the Health Regions for individuals in Ontario, Canada. Our results show that between October of 2021 and January of 2022, individuals from underrepresented communities were three times less likely to be vaccinated than White/Caucasian individuals across the province of Ontario, and that in some cases, within these groups, individuals in low-income brackets had significantly higher odds of vaccination when compared to their peers in high income brackets. Finally, we identified significantly lower odds of vaccination in the Central, East and West Health Regions of Ontario within certain underrepresented groups. This study shows that there is an ongoing need to better understand and address differences in vaccination uptake across diverse segments of the population of Ontario that the pandemic has largely impacted.

Geographic variation in inpatient medical expenditure among older adults aged 75 years and above in Japan: a three-level multilevel analysis of nationwide data

Introduction

In Japan, a country at the forefront of population ageing, significant geographic variation has been observed in inpatient medical expenditures for older adults aged 75 and above (IMEP75), both at the small- and large-area levels. However, our understanding of how different levels of administrative (geographic) units contribute to the overall geographic disparities remains incomplete. Thus, this study aimed to assess the degree to which geographic variation in IMEP75 can be attributed to municipality-, secondary medical area (SMA)-, and prefecture-level characteristics, and identify key factors associated with IMEP75.

Methods

Using nationwide aggregate health insurance claims data of municipalities for the period of April 2018 to March 2019, we conducted a multilevel linear regression analysis with three levels: municipalities, SMA, and prefectures. The contribution of municipality-, SMA-, and prefecture-level correlates to the overall geographic variation in IMEP75 was evaluated using the proportional change in variance across six constructed models. The effects of individual factors on IMEP75 in the multilevel models were assessed by estimating beta coefficients with their 95% confidence intervals.

Results

We analysed data of 1,888 municipalities, 344 SMAs, and 47 prefectures. The availability of healthcare resources at the SMA-level and broader regions to which prefectures belonged together explained 57.3% of the overall geographic variance in IMEP75, whereas the effects of factors influencing healthcare demands at the municipality-level were relatively minor, contributing an additional explanatory power of 2.5%. Factors related to long-term and end-of-life care needs and provision such as the proportion of older adults certified as needing long-term care, long-term care benefit expenditure per recipient, and the availability of hospital beds for psychiatric and chronic care and end-of-life care support at home were associated with IMEP75.

Conclusion

To ameliorate the geographic variation in IMEP75 in Japan, the reallocation of healthcare resources across SMAs should be considered, and drivers of broader regional disparities need to be further explored. Moreover, healthcare systems for older adults must integrate an infrastructure of efficient long-term care and end-of-life care delivery outside hospitals to alleviate the burden on inpatient care.

How Might We Have Known? Using Administrative Data to Predict 30-Day Hospital Readmission in Clients Receiving Home Care Services from 2018 to 2021

Background

Reducing hospital readmissions can improve individual health outcomes and lower system-level costs. This study aimed to understand the characteristics of home care Personal Support clients who experienced a hospital admission (ie, hospital hold) and to identify factors that predict hospital readmission within 30 days of resuming home care Personal Support services.

Methods

We conducted a retrospective cohort study using client administrative data from a home healthcare provider organization (2018-2021). The sample included clients (⩾18 years) who received publicly funded Personal Support services and experienced a hospital hold. Descriptive statistics and a binary logistic regression model analyzed the relationship between demographics, hospital service utilization, home care service utilization, and contextual factors on the outcome of 30-day hospital readmission.

Results

Approximately 17% (n = 662) of all clients with a hospital hold (n = 3992) were readmitted to hospital within 30 days. Compared with non-readmitted clients, those with greater home care Personal Support service intensity after the index hospital hold were less likely to experience a hospital 30-day readmission. In contrast, those with greater acuity, higher assessed care needs, more hospital holds overall, more extended hospital stays (⩾2 weeks), and lower social support had a higher likelihood of 30-day hospital readmission.

Conclusion

The findings from this study provide a greater understanding of factors associated with home care clients' risk of hospital readmission within 30 days and can be used to inform targeted, evidence-based support to reduce home care clients' hospital readmissions.

Predictive risk modelling of high resource users under different prescription drug coverage policies in Ontario and Manitoba, Canada

INTRODUCTION

Studying high resource users (HRUs) across jurisdictions is a challenge due to variation in data availability and health services coverage. In Canada, coverage for pharmaceuticals varies across provinces under a mix of public and private plans, which has implications for ascertaining HRUs. We examined sociodemographic and behavioural predictors of HRUs in the presence of different prescription drug coverages in the provinces of Manitoba and Ontario.

METHODS

Linked Canadian Community Health Surveys were used to create two cohorts of respondents from Ontario (n = 58,617, cycles 2005-2008) and Manitoba (n = 10,504, cycles 2007-2010). HRUs (top 5%) were identified by calculating health care utilization 5 years following interview date and computing all costs in the linked administrative databases, with three approaches used to include drug costs: (1) costs paid for by the provincial payer under age-based coverage; (2) costs paid for by the provincial payer under income-based coverage; (3) total costs regardless of the payer (publicly insured, privately insured, and out-of-pocket). Logistic regression estimated the association between sociodemographic, health, and behavioral predictors on HRU risk.

RESULTS

The strength of the association between age (≥ 80 vs. <30) and becoming an HRU were attenuated with the inclusion of broader drug data (age based: OR 37.29, CI: 30.08-46.24; income based: OR 27.34, CI: 18.53-40.33; all drug payees: OR 29.08, CI: 19.64-43.08). With broader drug coverage, the association between heavy smokers vs. non-smokers on odds of becoming an HRU strengthened (age based: OR 1.58, CI: 1.32-1.90; income based: OR 2.97, CI: 2.18-4.05; all drug payees: OR 3.12, CI: 2.29-4.25). Across the different drug coverage policies, there was persistence in higher odds of becoming an HRU in low income households vs. high income households and in those with a reported chronic condition vs. no chronic conditions.

CONCLUSIONS

The study illustrates that jurisdictional differences in how HRUs are ascertained based on drug coverage policies can influence the relative importance of some behavioural risk factors on HRU status, but most observed associations with health and sociodemographic risk factors were persistent, demonstrating that predictive risk modelling of HRUs can occur effectively across jurisdictions, even with some differences in public drug coverage policies.

Systematic population-wide ecological analysis of regional variability in disease prevalence

The prevalence of diseases often varies substantially from region to region. Besides basic demographic properties, the factors that drive the variability of each prevalence are to a large extent unknown. Here we show how regional prevalence variations in 115 different diseases relate to demographic, socio-economic, environmental factors and migratory background, as well as access to different types of health services such as primary, specialized and hospital healthcare. We have collected regional data for these risk factors at different levels of resolution; from large regions of care (Versorgungsregion) down to a 250 by 250 m square grid. Using multivariate regression analysis, we quantify the explanatory power of each independent variable in relation to the regional variation of the disease prevalence. We find that for certain diseases, such as acute heart conditions, diseases of the inner ear, mental and behavioral disorders due to substance abuse, up to 80% of the variance can be explained with these risk factors. For other diagnostic blocks, such as blood related diseases, injuries and poisoning however, the explanatory power is close to zero. We find that the time needed to travel from the inhabited center to the relevant hospital ward often contributes significantly to the disease risk, in particular for diabetes mellitus. Our results show that variations in disease burden across different regions can for many diseases be related to variations in demographic and socio-economic factors. Furthermore, our results highlight the relative importance of access to health care facilities in the treatment of chronic diseases like diabetes.

A Framework for Understanding How Variation in Health Care Service Delivery Affects Work Disability Management

Introduction Differences in disability duration after work injury have been observed across jurisdictions, regions and urban and rural settings. A key aspect of effective disability management is the access and utilization of appropriate and high quality health care. This paper presents a framework for analyzing and thus understanding how health service spending and utilization vary across and within work disability management schemes and affect work disability management. Methods Our framework was developed through a literature review and policy analysis. Existing frameworks describing geographic variation in general health care systems identified factors believed to drive that variation. A review of policy and practice documents from Canada's no-fault cause-based work disability management system identified factors relevant to work disability systems. Results We expand on previous frameworks by taking a systems approach that centers on factors relevant to the work disability management system. We further highlight predisposing, enabling, workplace environment and need-based factors that could lead to variation in health care spending and utilization across and within jurisdictions. These factors are described as shaping the interactions between workers, health care providers, employers and work disability management system actors, and influencing work disability management health and employment outcomes. Conclusion Our systems-focused approach offers a guide for researchers and policymakers to analyze how various factors may influence spending and utilization across regions and to identify areas for improvement in health care delivery within work disability management systems. Next steps include testing the framework in an analysis looking at geographic variation in spending and utilization across and within Canadian work disability management systems.

Comparison of claims from high-drug cost beneficiaries in Ontario, Canada, and Australia: a cross-sectional analysis

BACKGROUND

Globally, payers are struggling with rising drug costs, driven primarily by the increasing number of high-cost medications used by their beneficiaries. We aimed to compare the annual drug spending on claims from high-drug cost beneficiaries in the province of Ontario, Canada, and Australia.

METHODS

We conducted a cross-sectional analysis of public drug claims in Ontario and Australia from fiscal years 2006 to 2017. We identified the total government costs for prescribed medications per beneficiary. During the study period, public drug coverage in Ontario was provided to all residents 65 years of age and older, those with financial needs, and those living in long-term care or in need of home care. Australia maintains a publicly funded, universal system covering all citizens. Based on annual spending, we divided beneficiaries into 4 cost groups, representing the top 1%, top 5%, top 10% and the remaining 90%. We reported the following for each cost group: medication cost and proportion of total government spending, number of unique drugs dispensed per person and the top 10 most costly drug classes.

RESULTS

In Ontario and Australia, the top 1% of beneficiaries accounted for a large and increasing proportion of all government drug costs, growing from 12% ($405 946 197) to 24% ($1 345 977 248) in Ontario, and from 14% ($86 565 586) to 34% ($416 097 984) in Australia between 2006 and 2017. The most costly drug classes among high-drug cost beneficiaries in both jurisdictions were biologics and hepatitis C treatments.

INTERPRETATION

In both Ontario and Australia, a small number of beneficiaries accounted for a large proportion of public drug spending, driven largely by the use of expensive medications. The current development of potential national pharmacare strategies in Canada must optimize the use of high-cost drugs to ensure the sustainability of the program.

Medication use and its impact on high-cost health care users among older adults: protocol for the population-based matched cohort HiCOSTT study

BACKGROUND

Health interventions and policies for high-cost health care users (HCUs) who are older adults need to be informed by a better understanding of their multimorbidity and medication use. This study aims to determine the financial contribution of medications to HCU expenditures and explore whether potentially inappropriate prescribing is associated with incident HCU development.

METHODS

This is a protocol for a retrospective population-based matched cohort analysis of incident older adult HCUs (those with the highest 5% of costs and 66 years of age or older) in Ontario during fiscal year 2013. We will obtain person-level data for the index year and year before HCU status from health administrative databases and match each HCU to 3 non-HCUs based on age, sex and geographic location. Average annual medication costs (per patient) and the ratio of medication to total health care costs (at population level) will be examined over the HCU transition period and compared with non-HCUs. We will explore potential quality improvement areas for prescribing by analyzing chronic conditions and the use of medications with a strong evidence base for either clinical benefit or risk of harms outweighing benefits in older adults with these diagnoses. The relation between these medication classes and incident HCU status will be explored using logistic regression.

INTERPRETATION

Using a matched cohort design and focusing on incident rather than prevalent HCUs, this protocol will explore our hypotheses that medications and the quality of their prescribing may be important triggers of HCU status and facilitate the identification of potential preventive clinical interventions or policies. Dissemination of results will occur via publications in peer-reviewed journals, presentations at conferences and academic settings, and knowledge translation activities with relevant health system and patient stakeholder groups.

STUDY REGISTRATION

Clinicaltrials.gov, no. NCT02815930.

Identifying Populations with Complex Needs: Variation in Approaches Used to Select Complex Patient Populations

Interventions to support patients with complex needs are proliferating. However, little attention has been paid to methods for identifying complex patients. This study aims to summarize approaches used to define populations with complex needs in practice, by cataloging specific population criteria and organizing them into a taxonomy. The authors conducted a pragmatic review of literature published January 2000-December 2018 using PubMed. Search results were limited to English-language studies of adults that specified a set of objective criteria to identify a population with complex needs. The authors abstracted data from each article on population parameters, and conducted thematic analysis guided by deductive coding. The review identified 70 studies reflecting 90 unique complex population definitions. Complex populations criteria reflected 3 approaches: stratification, segmentation, and targeting. Six domains of population criteria were found within, including age-based criteria (59 populations); income (12); health care costs (45); health care utilization (39); health conditions (35); and subjective criteria (15). Criteria from multiple domains were frequently used in combination, and exact specifications were highly variable within each domain. Overall, 83% of the 90 population definitions included at least 1 cost- or utilization-based criterion. Nearly every study in the review presented a unique approach to identifying patients with complex needs but a limited number of "schools of thought" were found. Variability in definitions and inconsistent terminology are potential sources of ambiguity between stakeholders. Greater specificity and transparency in complex population definition would be a substantial contribution to the emerging field of complex care.

Characteristics of high-drug-cost beneficiaries of public drug plans in 9 Canadian provinces: a cross-sectional analysis

BACKGROUND

Drugs are the fastest growing cost in the Canadian health care system, owing to the increasing number of high-cost drugs. The objective of this study was to examine the characteristics of high-drug-cost beneficiaries of public drug plans across Canada relative to other beneficiaries.

METHODS

We conducted a cross-sectional study among public drug plan beneficiaries residing in all provinces except Quebec. We used the Canadian Institute for Health Information's National Prescription Drug Utilization Information System to identify all drugs dispensed to beneficiaries of public drug programs in 2016/17. We stratified the cohort into 2 groups: high-drug-cost beneficiaries (top 5% of beneficiaries based on annual costs) and other beneficiaries (remaining 95%). For each group, we reported total drug costs, prevalence of high-cost claims (> $1000), median number of drugs, proportion of beneficiaries aged 65 or more, the 10 most costly reimbursed medications and the 10 medications most commonly reimbursed. We reported estimates overall and by province.

RESULTS

High-drug-cost beneficiaries accounted for nearly half (46.5%) of annual spending, with an average annual spend of $14 610 per beneficiary, compared to $1570 among other beneficiaries. The median number of drugs dispensed was higher among high-drug-cost beneficiaries than among other beneficiaries (13 [interquartile range (IQR) 7-19] v. 8 [IQR 4-13]), and a much larger proportion of high-drug-cost beneficiaries than other beneficiaries received at least 1 high-cost claim (40.9% v. 0.6%). Long-term medications were the most commonly used medications for both groups, whereas biologics and antivirals were the most costly medications for high-drug-cost beneficiaries.

INTERPRETATION

High-drug-cost beneficiaries were characterized by the use of expensive medications and polypharmacy relative to other beneficiaries. Interventions and policies to help reduce spending need to consider both of these factors.

Incremental healthcare utilisation and costs among new senior high-cost users in Ontario, Canada: a retrospective matched cohort study

OBJECTIVES

To describe healthcare use and spending before and on becoming a new (incident) senior high-cost user (HCU) compared with senior non-HCUs; to estimate the incremental costs, overall and by service category, attributable to HCU status; and to quantify its monetary impact on the provincial healthcare budget in Ontario, Canada.

DESIGN

We conducted a retrospective, population-based comparative cohort study using administrative healthcare records. Incremental healthcare utilisation and costs were determined using the method of recycled predictions allowing adjustment for preincident and incident year values, and covariates. Estimated budget impact was computed as the product of the mean annual total incremental cost and the number of senior HCUs.

PARTICIPANTS

Incident senior HCUs were defined as Ontarians aged ≥66 years who were in the top 5% of healthcare cost users during fiscal year 2013 (FY2013) but not during FY2012. The incident HCU cohort was matched with senior non-HCUs in a ratio of 1 HCU:3 non-HCU.

RESULTS

Senior HCUs (n=175 847) reached the annual HCU threshold of CAD$10 192 through different combinations of incurred costs. Although HCUs had higher healthcare utilisation and costs at baseline, HCU status was associated with a substantial spike in both, with prolonged hospitalisations playing a major role. Twelve per cent of HCUs reached the HCU expenditure threshold without hospitalisation. Compared with non-HCUs (n=5 27 541), HCUs incurred an additional CAD$25 527 per patient in total healthcare costs; collectively CAD$4.5 billion or 9% of the 2013 Ontario healthcare budget. Inpatient care had the highest incremental costs: CAD$13 427, 53% of the total incremental spending.

CONCLUSIONS

Costs attributable to incident senior HCU status accounted for almost 1/10 of the provincial healthcare budget. Prolonged hospitalisations made a major contribution to the total incremental costs. A subgroup of patients that became HCU without hospitalisation requires further investigation.