Longitudinal trajectories of healthcare costs among high-need high-cost patients: a population-based retrospective cohort study in British Columbia, Canada
Bibliographic record
Abstract
OBJECTIVES: We sought to identify groups of high-need high-cost (HNHC) patients with distinct cost trajectories and describe the sociodemographic and clinical characteristics associated with group membership. DESIGN: A population-based retrospective cohort study, using administrative health data. SETTING: British Columbia, Canada. PARTICIPANTS: People who were HNHC in 2017, defined as incurring health system costs in the top 5% of the population, and were continuously registered in the Medical Service Plan from January 2015 to December 2019 and alive at the end of the study period. OUTCOME MEASURES: The primary objective was to identify longitudinal patterns of healthcare costs using group-based trajectory modelling. Adopting a health sector perspective, we conducted person-level costing for hospital episodes, day surgeries, physician services, prescription medications, and home and community care services. The secondary objective was to explore sociodemographic and clinical characteristics associated with group membership using adjusted ORs and 95% CIs from a multinomial logit model. RESULTS: Our final sample comprised 5.4 million British Columbians. In 2017, 224 285 people met our definition of an HNHC and were included in our analysis (threshold: $C7968). We selected a model with five groups. These groups included those with persistently very high costs (44%, mean 5-year total: $C124 622); persistent high costs (32%, mean 5 year total: $C38 997); rising costs (7%, mean 5-year total: $C43 140); declining costs (10%, mean 5-year total: $C30 545); and those with a cost spike (7%, mean 5-year total: $C19 601). Being older, being in the lowest income quintile and having a greater number of comorbid health conditions were associated with increased odds of being in the persistently very-high-cost trajectory group relative to each other group. There was heterogeneity in the association between individual comorbidities and trajectory group membership. Several comorbidities were associated with a statistically significant increase in the odds of being in the persistently very-high-cost group compared with all other groups (eg, diabetes, renal failure), while others were associated with decreased odds (eg, metastatic cancer, alcohol abuse). CONCLUSION: This study unveils the complex and diverse cost trajectories of HNHC patients in British Columbia, highlighting the necessity for tailored healthcare strategies that address individual patient needs and circumstances. Notably, a high proportion of HNHC patients exhibit persistently high costs over a 5-year period, and available sociodemographic and clinical data are not predictive of group membership. Future research is needed to develop methods for predicting future HNHC patients and to identify evidence-based interventions that can improve patient outcomes and mitigate unnecessary healthcare utilisation and costs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".