Examining regional variation in health care spending in British Columbia, Canada

Influence of BI-RADS Breast Density Scores on the Implementation of Supplemental Imaging Modalities in Those With Average Risk and Negative Mammogram by Primary Care Providers in British Columbia

Introduction: Breast Imaging-Reporting and Data System (BI-RADS) density scores have been included in screening mammography reports in BC since 2018. Despite these density scores being present in screening mammography reports for numerous years, there remains insufficient evidence to guide supplemental testing for patients with dense breasts. Objective: The primary objective of this study was to evaluate how primary care providers in Canada utilize BI-RADS density scores reported on normal screening mammograms of average risk, asymptomatic patients in their clinical practice. The secondary objective of this study was to determine if there are any patterns related to primary care provider demographics and practice settings in BC that could be linked to differences in screening practices for patients based on BI-RADS density scores. Methods: A cross-sectional survey was conducted with family physicians (FPs) and nurse practitioners (NPs) practicing in BC. Descriptive statistics were calculated using percentages and further stratified by participant demographics. P values were derived from Fisher's exact test and results were regarded as statistically significant at P < .05. Results: Ninety-eight participants (85 FPs, 13 NPs) responded to the survey. The percentage of participants who ordered supplemental testing based on BI-RADS density scores alone was 8% for BI-RADS score D, 37% for BI-RADS scores C or D, and 2% for BI-RADS scores B, C, or D. Forty-eight percent of female participants and 45% of male participants would order supplemental testing based on BI-RADS density scores alone (P = 1). Forty-nine percent of FPs and 39% of NPs would order supplemental testing based on BI-RADS density scores (P = .56). Fifty-three percent of participants who had been in practice for more than 10 years, 50% of those who had been in practice for 6 to 10 years, and 36% of those in practice for 5 years or less would order supplemental testing (P = .34). Fifty-seven percent of those practicing in large urban centres, 43% of those practicing in medium-sized communities, and 32% of those in rural or remote communities would order testing (P = .17). Fifty-seven percent of participants were aware of the increased risk of breast cancer with higher breast density. Conclusion: Variations exist in how primary care providers in BC utilize the BI-RADS density scores reported on normal screening mammography of average risk, asymptomatic patients in their clinical practice. Further research in this area is needed to establish clearer clinical guidelines to educate and inform primary care providers on the need for supplemental testing for patients with dense breasts and to improve resources for breast cancer screening in BC.

Understanding Factors Influencing Geographic Variation in Healthcare Expenditures: A Small Areas Analysis Study

Dramatic geographic variations in healthcare expenditures were documented by developed countries, but little is known about such variations under China's context, and what causes such variations. This study aims to examine variations of healthcare expenditures among small areas and to determine the associations between demand-, supply-factors, and per capita inpatient expenditures. This cross-sectional study utilized hospital discharge data aggregated within delineated hospital service areas (HSAs) using the small-area analysis approach. Linear multivariate regression modeling with robust standard errors was used to estimate the sources of variation of per capita inpatient expenditures across HSAs covering the years 2017 to 2019; the Shapley value decomposition method was used to measure the respective contributions of demand-, supply-side to such variations. Among 149 HSAs, demand factors explained most of the (87.4%) overall geographic variation among HSAs. With each 1% increase in GDP per capita and urbanization rate was associated with 0.099% and 0.9% increase in inpatient expenditure per capita, respectively, while each 1% increase in the share of females and the unemployment rate was associated with a 0.7% and 0.4% reduction in the per capita inpatient expenditures, respectively. In supply-side, for every 1 increase in hospital beds per 1000 population, the per capita inpatient expenditures rose by 2.9%, while with every 1% increase in the share of private hospitals, the per capita inpatient expenditures would decrease by 0.4%. With Herfindahl-Hirschman Index decrease 10%, the per capita inpatient expenditures would increase 1.06%. This study suggests demand-side factors are associated with large geographic variation in per capita inpatient expenditures among HSAs, while supply-side factors played an important role. The evaluation of geographic variations in per capita inpatient expenditures as well as its associated factors have great potential to provide an indirect approach to identify possibly existing underutilized or overutilized healthcare procedures.

Measuring low-value care in hospital discharge records: evidence from China

Background

Plenty of efforts have been made to reduce the use of low-value care (the care that is not expected to provide net benefits for patients) across the world, but measures of low-value care have not been developed in China. This study aims to develop hospital discharge records-based measures of low-value surgical procedures, evaluate their annual use and associated expenditure, and analyze the practice patterns by characterizing its temporal trends and correlations across rates of different low-value procedures within hospitals.

Methods

Informed by evidence-based lists including Choosing Wisely, we developed 11 measures of low-value surgical procedures. We evaluated the count and proportion of low-value episodes, as well as the proportion of expenditure and medical insurance payouts for these episodes, using hospital discharge records in Sichuan Province, China during a period of 2016-2022. We compared the count and expenditure detected by different versions of these measures, which varied in sensitivity and specificity. We characterized the temporal trends in the rate of low-value surgical procedures and estimated the annual percent change using joint-point regression. Additionally, we calculated the Spearman correlation coefficients between the risk-standardized rates of low-value procedures which were estimated by multilevel models adjusting for case mix across hospitals.

Findings

Low-value episodes detected by more specific versions of measures accounted for 3.25% (range, 0.11%-71.66%), and constituted 6.03% (range, 0.32%-84.63%) and 5.90% (range, 0.33%-82.86%) of overall expenditure and medical insurance payouts, respectively. The three figures accounted for 5.90%, 8.41%, and 8.38% in terms of more sensitive versions of measures. Almost half of the low-value procedures (five out of eleven) experienced an increase in rates during the period of 2016-2022, with four of them increasing over 20% per year. There was no significant correlation across risk-standardized rates of different low-value procedures within hospitals (mean r for pairwise, 0.03; CI, -0.02, 0.07).

Interpretation

Despite overall low-value practices detected by the 11 developed measures was modest, certain clinical specialties were plagued by widespread low-value practices which imposed heavy economic burdens for the healthcare system. Given the pervasive and significant upward trends in rates of low-value practices, it has become increasingly urgent to reduce such practices. Interventions in reducing low-value practices in China would be procedure-specific as practice patterns of low-value care varied by procedures and common drivers of low-value practices may not exist.

Funding

The National Science Foundation of China (72074163), Taikang Yicai Public Health and Epidemic Control Fund, Sichuan Science and Technology Program (2022YFS0052 and 2021YFQ0060), and Sichuan University (2018hhf-27 and SKSYL201811).

Clinical outcomes and economic burden of seasonal influenza and other respiratory virus infections in hospitalized adults

The cost of influenza and other respiratory virus infections should be determined to analyze the real burden of these diseases. We aimed to investigate the clinical outcomes and cost of illness due to respiratory virus infections in hospitalized adult patients. Hospitalized patients who had nasal swab sampling for a suspected viral infection between August 1, 2018 to March 31, 2019 were included. Outcome variables were oxygen requirement, mechanical ventilation need, intensive care unit admission, and cost. At least one viral pathogen was detected in 125 (47.7%) of 262 patients who were included in the study. Fifty-five (20.9%) of the patients were infected with influenza. Influenza-positive patients had higher rates for respiratory support, intensive care unit admission, and mortality compared to all other patients. The average cost of hospitalization per person was 2879.76 USD in the influenza-negative group, while the same cost was 3274.03 USD in the influenza-positive group. Although all of the vaccinated influenza-positive patients needed oxygen support, neither of them required invasive mechanical ventilation or intensive care unit admission. The average hospitalization cost per person was 779.70 USD in the vaccinated group compared to 3762.01 USD in the unvaccinated group. Disease-related direct cost of influenza in the community was estimated as 22 776 075.61 USD in the 18-65 years of age group and 15 756 120.02 USD in the 65 years of age and over group per year. Influenza, compared to other respiratory virus infections, can lead to untoward clinical outcomes and mortality as well as higher direct medical costs in adults.

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.

A Cost-Utility Study of Laparoscopic Cholecystectomy for the Treatment of Symptomatic Gallstones

BACKGROUND

Laparoscopic cholecystectomy is a high-volume surgery that is an end-stage treatment for gallstones. There is little understanding of the surgery's effect on the gain in patients' health relative to its cost. The objective of this study is to measure health gain, cost and cost utility of elective laparoscopic cholecystectomy.

METHODS

Participants completed the EQ-5D(3L) pre-operatively and post-operatively. Quality adjusted life years attributable to cholecystectomy were calculated by comparing health state utility values between the pre- and post-operative time points. Laparoscopic cholecystectomy cost was calculated from a health system perspective and included hospital and specialists' fees (in 2016 Canadian dollars). Cost per QALY was calculated for the entire sample and demographic sub-groups.

RESULTS

The cohort consisted of 135 participants who completed surveys between February 2013 and June 2017. The response rate among eligible patients was 50%. Assuming that health gain accrued to the participant for 25 years after cholecystectomy, the mean gain in QALYs was 1.7430, corresponding to an average cost per QALY of $2102. Older patients, on average, had less gain in QALYs than younger patients.

CONCLUSION

Laparoscopic cholecystectomies are inexpensive relative to the gains in health they provide patients. The gains in health were not uniform across age categories. These results should provide health system planners confidence that incremental increases in surgical capacity for elective cholecystectomies is beneficial.

A dynamic capabilities view of improvement capability

Purpose

Organisations within healthcare increasingly operate in rapidly changing environments and present wide variation in performance. It can be argued that this variation is influenced by the capability of an organisation to improve: its improvement capability. However, there is little theoretical research on improvement capability. The purpose of this paper is to set out the current diverse body of research on improvement capability and develop a theoretically informed conceptual framework.

Design/methodology/approach

This paper conceptualises improvement capability as a dynamic capability. This suggests that improvement capability is comprised of organisational routines that are bundled together, and adapt and react to organisational circumstances. Existing research conceptualises these bundles as three elements (microfoundations): sensing, seizing and reconfiguring. This conceptualisation is used to explore how improvement capability can be understood, by inductively categorising eight dimensions of improvement capability to develop a theoretically informed conceptual framework.

Findings

This paper shows that the three microfoundations which make up a dynamic capability are present in the identified improvement capability dimensions. This theoretically based conceptual framework provides a rich explanation of how improvement capability can be configured.

Originality/value

Identifying the component parts of improvement capability helps to explain why some organisations are less successful in improvement than others. This theoretically informed framework can support managers and policy makers to identify improvement capability dimensions in need of development. Further empirical research, particularly in non-market settings, such as publicly funded healthcare is required to enhance understanding of improvement capability and its configuration.

Geographic variation in the costs of medical care for people living with HIV in British Columbia, Canada

Background

Regional variation in medical care costs can indicate heterogeneity in clinical practice, inequities in access, or inefficiencies in service delivery. We aimed to estimate regional variation in medical costs for people living with HIV (PLHIV), adjusting for demographics and case-mix.

Methods

We conducted a retrospective cohort study using linked health administrative databases of PLHIV, from 2010 to 2014, in British Columbia (BC), Canada. Quarterly health care costs (2018 CAD) were derived from inpatient, outpatient, prescription drugs, antiretroviral therapy (ART), and HIV diagnostics. We used a two-part model with a logit link for the probability of incurring costs, and a log link and gamma distribution for observations with positive costs. We also estimated quarterly utilization rates for hospitalization-, physician billing- and prescription drug-days. Primary variables were indicators of individuals’ Health Service Delivery Area (HSDA). We adjusted cost and utilization estimates for demographic characteristics, HIV-disease progression, and comorbidities.

Results

Our cohort included 9577 PLHIV (median age 45.5 years, 80% male). Adjusted total quarterly costs for all 16 HSDAs were within 20% of the provincial mean, 8/16 for hospitalization costs, 16/16 for physician billing costs and 10/16 for prescription drug costs. Northern Interior and Northeast HSDAs had 38 and 44% lower quarterly non-ART prescription drug costs, and 2 and 5% higher quarterly inpatient costs, respectively.

Conclusions

We observed limited variation in medical care costs and utilization among PLHIV in BC. However, lower levels of outpatient care and higher levels of inpatient care indicate possible barriers to accessing care among PLHIV in the most rural regions of the province.

Electronic supplementary material

The online version of this article (10.1186/s12913-019-4391-8) contains supplementary material, which is available to authorized users.

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

Background

Senior high cost health care users (HCU) are a priority for many governments. Little research has addressed regional variation of HCU incidence and outcomes, especially among incident HCU. This study describes the regional variation in healthcare costs and mortality across Ontario’s health planning districts [Local Health Integration Networks (LHIN)] among senior incident HCU and non-HCU and explores the relationship between healthcare spending and mortality.

Methods

We conducted a retrospective population-based matched cohort study of incident senior HCU defined as Ontarians aged ≥66 years in the top 5% most costly healthcare users in fiscal year (FY) 2013. We matched HCU to non-HCU (1:3) based on age, sex and LHIN. Primary outcomes were LHIN-based variation in costs (total and 12 cost components) and mortality during FY2013 as measured by variance estimates derived from multi-level models. Outcomes were risk-adjusted for age, sex, ADGs, and low-income status. In a cost-mortality analysis by LHIN, risk-adjusted random effects for total costs and mortality were graphically presented together in a cost-mortality plane to identify low and high performers.

Results

We studied 175,847 incident HCU and 527,541 matched non-HCU. On average, 94 out of 1000 seniors per LHIN were HCU (CV = 4.6%). The mean total costs for HCU in FY2013 were 12 times higher that of non-HCU ($29,779 vs. $2472 respectively), whereas all-cause mortality was 13.6 times greater (103.9 vs. 7.5 per 1000 seniors).

Regional variation in costs and mortality was lower in senior HCU compared with non-HCU. We identified greater variability in accessing the healthcare system, but, once the patient entered the system, variation in costs was low. The traditional drivers of costs and mortality that we adjusted for played little role in driving the observed variation in HCUs’ outcomes. We identified LHINs that had high mortality rates despite elevated healthcare expenditures and those that achieved lower mortality at lower costs. Some LHINs achieved low mortality at excessively high costs.

Conclusions

Risk-adjusted allocation of healthcare resources to seniors in Ontario is overall similar across health districts, more so for HCU than non-HCU. Identified important variation in the cost-mortality relationship across LHINs needs to be further explored.

Electronic supplementary material

The online version of this article (10.1186/s12877-018-0952-7) contains supplementary material, which is available to authorized users.

Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases

Background

To indicate inefficiencies in health systems, previous studies examined regional variation in healthcare spending by analyzing the entire population. As a result, population heterogeneity is taken into account to a limited extent only. Furthermore, it clouds a detailed interpretation which could be used to inform regional budget allocation decisions to improve quality of care of one chronic disease over another. Therefore, we aimed to gain insight into the drivers of regional variation in healthcare spending by studying prevalent chronic diseases.

Methods

We used 2012 secondary health survey data linked with claims data, healthcare supply data and demographics at the individual level for 18 Dutch regions. We studied patients with diabetes (n = 10,767) and depression (n = 3,735), in addition to the general population (n = 44,694). For all samples, we estimated the cross-sectional relationship between spending, supply and demand variables and region effects using linear mixed models.

Results

Regions with above (below) average spending for the general population mostly showed above (below) average spending for diabetes and depression as well. Less than 1% of the a-priori total variation in spending was attributed to the regions. For all samples, we found that individual-level demand variables explained 62-63% of the total variance. Self-reported health status was the most prominent predictor (28%) of healthcare spending. Supply variables also explained, although a small part, of regional variation in spending in the general population and depression. Demand variables explained nearly 100% of regional variation in spending for depression and 88% for diabetes, leaving 12% of the regional variation left unexplained indicating differences between regions due to inefficiencies.

Conclusions

The extent to which regional variation in healthcare spending can be considered as inefficiency may differ between regions and disease-groups. Therefore, analyzing chronic diseases, in addition to the traditional approach where the general population is studied, provides more insight into the causes of regional variation in healthcare spending, and identifies potential areas for efficiency improvement and budget allocation decisions.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3128-4) contains supplementary material, which is available to authorized users.

Geographic variation in health insurance benefits in Qianjiang District, China: a cross-sectional study

BACKGROUND

Health insurance contributes to reducing the economic burden of disease and improving access to healthcare. In 2016, the Chinese government announced the integration of the New Cooperative Medical Scheme (NCMS) and Urban Resident Basic Medical Insurance (URBMI) to reduce system segmentation. Nevertheless, it was unclear whether there would be any geographic variation in health insurance benefits if the two types of insurance were integrated. The aim of this study was to identify the potential geographic variation in health insurance benefits and the related contributing factors.

METHODS

This cross-sectional study was carried out in Qianjiang District, where the NCMS and URBMI were integrated into Urban and Rural Resident Basic Medical Insurance Scheme (URRBMI) in 2010. All beneficiaries under the URRBMI were hospitalized at least once in 2013, totaling 445,254 persons and 65,877 person-times, were included in this study. Town-level data on health insurance benefits, healthcare utilization, and socioeconomic and geographical characteristics were collected through health insurance system, self-report questionnaires, and the 2014 Statistical Yearbook of Qianjiang District. A simplified Theil index at town level was calculated to measure geographic variation in health insurance benefits. Colored maps were created to visualize the variation in geographic distribution of benefits. The effects of healthcare utilization and socioeconomic and geographical characteristics on geographic variation in health insurance benefits were estimated with a multiple linear regression analysis.

RESULTS

Different Theil index values were calculated for different towns, and the Theil index values for compensation by person-times and amount were 2.5028 and 1.8394 in primary healthcare institutions and 1.1466 and 0.9204 in secondary healthcare institutions. Healthcare-seeking behavior and economic factors were positively associated with health insurance benefits in compensation by person-times significantly, meanwhile, geographical accessibility and economic factors had positive effects (p < 0.05).

CONCLUSIONS

The geographic variation in health insurance benefits widely existed in Qianjiang District and the distribution of health insurance benefits for insured inpatients in primary healthcare institutions was distinctly different from that in secondary healthcare institutions. When combining the NRCM and URMIS in China, the geographical accessibility, healthcare-seeking behavior and economic factors required significant attention.

Senior high-cost healthcare users' resource utilization and outcomes: a protocol of a retrospective matched cohort study in Canada

INTRODUCTION

Senior high-cost users (HCUs) are estimated to represent 60% of all HCUs in Ontario, Canada's most populous province. To improve our understanding of individual and health system characteristics related to senior HCUs, we will examine incident senior HCUs to determine their incremental healthcare utilisation and costs, characteristics of index hospitalisation episodes, mortality and their regional variation across Ontario.

METHODS AND ANALYSIS

A retrospective, population-based cohort study using administrative healthcare records will be used. Incident senior HCUs will be defined as Ontarians aged ≥66 years who were in the top 5% of healthcare cost users during fiscal year 2013 but not during fiscal year 2012. Each HCU will be matched to three non-HCUs by age, sex and health planning region. Incremental healthcare use and costs will be determined using the method of recycled predictions. We will apply multivariable logistic regression to determine patient and health service factors associated with index hospitalisation and inhospital mortality during the incident year. The most common causes of admission will be identified and contrasted with the most expensive hospitalised conditions. We will also calculate the ratio of inpatient costs incurred through admissions of ambulatory care sensitive conditions to the total inpatient expenditures. The magnitude of variation in costs and health service utilisation will be established by calculating the extremal quotient, the coefficient of variation and the Gini mean difference for estimates obtained through multilevel regression analyses.

ETHICS AND DISSEMINATION

This study has been approved by Hamilton Integrated Research Ethics Board (ID#1715-C). The results of the study will be distributed through peer-reviewed journals. They also will be disseminated at research events in academic settings, national and international conferences as well as with presentations to provincial health authorities.