An economic evaluation of chronic obstructive pulmonary disease clinical pathway in Saskatchewan, Canada: Data-driven techniques to identify cost-effectiveness among patient subgroups.

BACKGROUND: Saskatchewan has implemented care pathways for several common health conditions. To date, there has not been any cost-effectiveness evaluation of care pathways in the province. The objective of this study was to evaluate the real-world cost-effectiveness of a chronic obstructive pulmonary disease (COPD) care pathway program in Saskatchewan. METHODS: Using patient-level administrative health data, we identified adults (35+ years) with COPD diagnosis recruited into the care pathway program in Regina between April 1, 2018, and March 31, 2019 (N = 759). The control group comprised adults (35+ years) with COPD who lived in Saskatoon during the same period (N = 759). The control group was matched to the intervention group using propensity scores. Costs were calculated at the patient level. The outcome measure was the number of days patients remained without experiencing COPD exacerbation within 1-year follow-up. Both manual and data-driven policy learning approaches were used to assess heterogeneity in the cost-effectiveness by patient demographic and disease characteristics. Bootstrapping was used to quantify uncertainty in the results. RESULTS: In the overall sample, the estimates indicate that the COPD care pathway was not cost-effective using the willingness to pay (WTP) threshold values in the range of $1,000 and $5,000/exacerbation day averted. The manual subgroup analyses show the COPD care pathway was dominant among patients with comorbidities and among patients aged 65 years or younger at the WTP threshold of $2000/exacerbation day averted. Although similar profiles as those identified in the manual subgroup analyses were confirmed, the data-driven policy learning approach suggests more nuanced demographic and disease profiles that the care pathway would be most appropriate for. CONCLUSIONS: Both manual subgroup analysis and data-driven policy learning approach showed that the COPD care pathway consistently produced cost savings and better health outcomes among patients with comorbidities or among those relatively younger. The care pathway was not cost-effective in the entire sample.

Real-World Cost-Consequence Analysis of an Integrated Chronic Disease Management Program in Saskatchewan, Canada.

An integrated disease management program otherwise called a clinical pathway was recently implemented in Saskatchewan, Canada for patients living with chronic obstructive pulmonary disease (COPD). This study compared the real-world costs and consequences of the COPD clinical pathway program with 2 control treatment programs. The study comprised adult COPD patients in Regina (clinical pathway group, N = 759) matched on propensity scores to 2 independent control groups of similar adults in (1) Regina (historical controls, N = 759) and (2) Saskatoon (contemporaneous controls, N = 759). The study measures included patient-level healthcare costs and acute COPD exacerbation outcomes, both tracked in population-based administrative health data over a one-year follow-up period. Analyses included Cox proportional hazards models and differences in means between groups. The bias-corrected and accelerated bootstrap method was used to calculate 95% confidence intervals (CI). The COPD pathway patients had lower risks of moderate (hazard ratio [HR] =0.57, 95% CI [0.40-0.83]) and severe (HR = 0.43, 95% CI [0.28-0.66]) exacerbations compared to the historical control group, but similar risks compared with the contemporaneous control group. The COPD pathway patients experienced fewer episodes of exacerbations compared with the historical control group (mean difference = -0.30, 95% CI [-0.40, -0.20]) and the contemporaneous control group (mean difference = -0.12, 95% CI [-0.20, -0.03]). Average annual healthcare costs in Canadian dollars were marginally higher among patients in the COPD clinical pathway (mean = $10 549, standard deviation [SD] =$18 149) than those in the contemporaneous control group ($8841, SD = $17 120), but comparable to the historical control group ($10 677, SD = $21 201). The COPD pathway provides better outcomes at about the same costs when compared to the historical controls, but only slightly better outcomes and at a marginally higher cost when compared to the contemporaneous controls.

Impacts of Chronic Obstructive Pulmonary Disease Care Pathway on Healthcare Utilization and Costs: A Matched Multiple Control Cohort Study in Saskatchewan, Canada.

OBJECTIVES: This study aimed to evaluate the real-world impacts of a chronic obstructive pulmonary disease (COPD) care pathway program on healthcare utilization and costs in Saskatchewan, Canada. METHODS: A difference-in-differences evaluation of a real-life deployment of a COPD care pathway, using patient-level administrative health data in Saskatchewan, was conducted. The intervention group (n = 759) included adults (35+ years) with spirometry-confirmed COPD diagnosis recruited into the care pathway program in Regina between April 1, 2018 and March 31, 2019. The 2 control groups comprised adults (35+ years) with COPD who lived in Saskatoon during the same period (n = 759) or Regina between April 1, 2015 and March 31, 2016 (n = 759) who did not participate in the care pathway. RESULTS: Compared with the individuals in the Saskatoon control groups, individuals in the COPD care pathway group had shorter inpatient hospital length of stay (average treatment effect on the treated [ATT] -0.46, 95% CI -0.88 to -0.04) but a higher number of general practitioner visits (ATT 1.46, 95% CI 1.14 to 1.79) and specialist physician visits (ATT 0.84, 95% CI 0.61 to 1.07). Regarding healthcare costs, individuals in the care pathway group had higher COPD-related specialist visit costs (ATT $81.70, 95% CI $59.45 to $103.96) but lower COPD-related outpatient drug dispensation costs (ATT -$4.81, 95% CI -$9.34 to -$0.27). CONCLUSIONS: The care pathway reduced inpatient hospital length of stay, but increased general practitioner and specialist physician visits for COPD-related services within the first year of implementation.

Comparison of the accuracy of classification models to estimate healthcare use and costs associated with COPD exacerbations in Saskatchewan, Canada: A retrospective cohort study.

OBJECTIVE: COPD is a high-cost disease and results in frequent contacts with the healthcare system. The study objective was to compare the accuracy of classification models with different covariates for classifying COPD patients into cost groups. METHODS: Linked health administrative databases from Saskatchewan, Canada, were used to identify a cohort of newly diagnosed COPD patients (April 1, 2007 to March 31, 2011) and their episodes of healthcare encounters for disease exacerbations. Total costs of the first and follow-up episodes were computed and patients were categorized as persistently high cost, occasionally high cost, and persistently low cost based on cumulative cost distribution ranking using the 75th percentile cutoff for high-cost status. Classification accuracy was compared for seven multinomial logistic regression models containing socio-demographic characteristics (i.e., base model), and socio-demographic and prior healthcare use characteristics (i.e., comparator models). RESULTS: Of the 1182 patients identified, 8.5% were classified as persistently high cost, 26.1% as occasionally high cost, and the remainder as persistently low cost. The persistently high-cost and occasionally high-cost patients incurred 10 times ($12 449 vs $1263) and seven times ($9334 vs $1263) more costs in their first exacerbation episode than persistently low-cost patients, respectively. Classification accuracy was 0.67 for the base model, whereas the comparator model containing socio-demographic and number of prior hospital admissions had the highest accuracy (0.72). CONCLUSIONS: Costs associated with COPD exacerbation episodes are substantial. Adding prior hospitalization to socio-demographic characteristics produced the highest improvements in classification accuracy. Accurate classification models are important for identifying potential healthcare cost management strategies.

A prediction model to estimate completeness of electronic physician claims databases.

OBJECTIVES: Electronic physician claims databases are widely used for chronic disease research and surveillance, but quality of the data may vary with a number of physician characteristics, including payment method. The objectives were to develop a prediction model for the number of prevalent diabetes cases in fee-for-service (FFS) electronic physician claims databases and apply it to estimate cases among non-FFS (NFFS) physicians, for whom claims data are often incomplete. DESIGN: A retrospective observational cohort design was adopted. SETTING: Data from the Canadian province of Newfoundland and Labrador were used to construct the prediction model and data from the province of Manitoba were used to externally validate the model. PARTICIPANTS: A cohort of diagnosed diabetes cases was ascertained from physician claims, insured resident registry and hospitalisation records. A cohort of FFS physicians who were responsible for the diagnosis was ascertained from physician claims and registry data. PRIMARY AND SECONDARY OUTCOME MEASURES: A generalised linear model with a γ distribution was used to model the number of diabetes cases per FFS physician as a function of physician characteristics. The expected number of diabetes cases per NFFS physician was estimated. RESULTS: The diabetes case cohort consisted of 31,714 individuals; the mean cases per FFS physician was 75.5 (median = 49.0). Sex and years since specialty licensure were significantly associated (p < 0.05) with the number of cases per physician. Applying the prediction model to NFFS physician registry data resulted in an estimate of 18,546 cases; only 411 were observed in claims data. The model demonstrated face validity in an independent data set. CONCLUSIONS: Comparing observed and predicted disease cases is a useful and generalisable approach to assess the quality of electronic databases for population-based research and surveillance.