Longitudinal trajectories of healthcare costs among high-need high-cost patients: a population-based retrospective cohort study in British Columbia, Canada
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,005 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».