Are Income-based Differences in TKA Use and Outcomes Reduced in a Single-payer System? A Large-database Comparison of the United States and Canada
Notice bibliographique
Résumé
BACKGROUND: Income-based differences in the use of and outcomes in TKA have been studied; however, it is not known if different healthcare systems affect this relationship. Although Canada's single-payer healthcare system is assumed to attenuate the wealth-based differences in TKA use observed in the United States, empirical cross-border comparisons are lacking. QUESTIONS/PURPOSES: (1) Does TKA use differ between Pennsylvania, USA, and Ontario, Canada? (2) Are income-based disparities in TKA use larger in Pennsylvania or Ontario? (3) Are TKA outcomes (90-day mortality, 90-day readmission, and 1-year revision rates) different between Pennsylvania and Ontario? (4) Are income-based disparities in TKA outcomes larger in Pennsylvania or Ontario? METHODS: We identified all patients hospitalized for primary TKA in this cross-border retrospective analysis, using administrative data for 2012 to 2018, and we found a total of 161,244 primary TKAs in Ontario and 208,016 TKAs in Pennsylvania. We used data from the Pennsylvania Health Care Cost Containment Council, Harrisburg, PA, USA, and the ICES (formally the Institute for Clinical Evaluative Sciences), Toronto, Ontario, Canada. We linked patient-level data to the respective census data to determine community-level income using ZIP Code or postal code of residence and stratified patients into neighborhood income quintiles. We compared TKA use (age and gender, standardized per 10,000 population per year) for patients residing in the highest-income versus the lowest-income quintile neighborhoods. Similarly secondary outcomes 90-day mortality, 90-day readmission, and 1-year revision rates were compared between the two regions and analyzed by income groups. RESULTS: TKA use was higher in Pennsylvania than in Ontario overall and for all income quintiles (lowest income quartile: 31 versus 18 procedures per 10,000 population per year; p < 0.001; highest income quartile: 38 versus 23 procedures per 10,000 population per year; p < 0.001). The relative difference in use between the highest-income and lowest-income quintile was larger in Ontario (28% higher) than in Pennsylvania (23% higher); p < 0.001. Patients receiving TKA in Pennsylvania were more likely to be readmitted within 90 days and were more likely to undergo revision within the first year than patients in Ontario, but there was no difference in mortality at 1 year. When comparing income groups, there were no differences between the countries in 90-day mortality, readmission, or 1-year revision rates (p > 0.05). CONCLUSION: These results suggest that universal health insurance through a single-payer may not reduce the income-based differences in TKA access that are known to exist in the United States. Future studies are needed determine if our results are consistent across other geographic regions and other surgical procedures. LEVEL OF EVIDENCE: Level III, therapeutic study.
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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 | 0,002 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,003 | 0,010 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| 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 ».