Within and across country variations in treatment of patients with heart failure and diabetes

Identification and classification of principal features for analyzing unwarranted clinical variation

RATIONALE, AIMS, AND OBJECTIVE

Unwarranted clinical variation (UCV) is an undesirable aspect of a healthcare system, but analyzing for UCV can be difficult and time-consuming. No analytic feature guidelines currently exist to aid researchers. We performed a systematic review of UCV literature to identify and classify the features researchers have identified as necessary for the analysis of UCV.

METHODS

The literature search followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. We looked for articles with the terms 'medical practice variation' and 'unwarranted clinical variation' from four databases: Medline, Web of Science, EMBASE and CINAHL. The search was performed on 24 March 2023. The articles selected were original research articles in the English language reporting on UCV analysis in adult populations. Most of the studies were retrospective cohort analyses. We excluded studies reporting geographic variation based on the Atlas of Variation or small-area analysis methods. We used ASReview Lab software to assist in identifying articles for abstract review. We also conducted subsequent reference searches of the primary articles to retrieve additional articles.

RESULTS

The search yielded 499 articles, and we reviewed 46. We identified 28 principal analytic features utilized to analyze for unwarranted variation, categorised under patient-related or local healthcare context factors. Within the patient-related factors, we identified three subcategories: patient sociodemographics, clinical characteristics, and preferences, and classified 17 features into seven subcategories. In the local context category, 11 features are classified under two subcategories. Examples are provided on the usage of each feature for analysis.

CONCLUSION

Twenty-eight analytic features have been identified, and a categorisation has been established showing the relationships between features. Identifying and classifying features provides guidelines for known confounders during analysis and reduces the steps required when performing UCV analysis; there is no longer a need for a UCV researcher to engage in time-consuming feature engineering activities.

A methodology for identifying high-need, high-cost patient personas for international comparisons

OBJECTIVE

To establish a methodological approach to compare two high-need, high-cost (HNHC) patient personas internationally.

DATA SOURCES

Linked individual-level administrative data from the inpatient and outpatient sectors compiled by the International Collaborative on Costs, Outcomes, and Needs in Care (ICCONIC) across 11 countries: Australia, Canada, England, France, Germany, the Netherlands, New Zealand, Spain, Sweden, Switzerland, and the United States.

STUDY DESIGN

We outline a methodological approach to identify HNHC patient types for international comparisons that reflect complex, priority populations defined by the National Academy of Medicine. We define two patient profiles using accessible patient-level datasets linked across different domains of care-hospital care, primary care, outpatient specialty care, post-acute rehabilitative care, long-term care, home-health care, and outpatient drugs. The personas include a frail older adult with a hip fracture with subsequent hip replacement and an older person with complex multimorbidity, including heart failure and diabetes. We demonstrate their comparability by examining the characteristics and clinical diagnoses captured across countries.

DATA COLLECTION/EXTRACTION METHODS

Data collected by ICCONIC partners.

PRINCIPAL FINDINGS

Across 11 countries, the identification of HNHC patient personas was feasible to examine variations in healthcare utilization, spending, and patient outcomes. The ability of countries to examine linked, individual-level data varied, with the Netherlands, Canada, and Germany able to comprehensively examine care across all seven domains, whereas other countries such as England, Switzerland, and New Zealand were more limited. All countries were able to identify a hip fracture persona and a heart failure persona. Patient characteristics were reassuringly similar across countries.

CONCLUSION

Although there are cross-country differences in the availability and structure of data sources, countries had the ability to effectively identify comparable HNHC personas for international study. This work serves as the methodological paper for six accompanying papers examining differences in spending, utilization, and outcomes for these personas across countries.