方法对比
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| 风险调整病例系列× | 倾向得分匹配× | |
|---|---|---|
| 领域≠ | 流行病学 | 研究统计学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990s–2000s | 1983 |
| 提出者≠ | Copeland, Jones & Walters (POSSUM score, 1991); broader risk-adjustment methodology developed across surgical and critical care audit literature | Paul Rosenbaum and Donald Rubin |
| 类型≠ | Observational study design with statistical risk correction | Method |
| 开创性文献≠ | Copeland, G. P., Jones, D., & Walters, M. (1991). POSSUM: a scoring system for surgical audit. British Journal of Surgery, 78(3), 355–360. DOI ↗ | Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. DOI ↗ |
| 别名 | risk-stratified case series, adjusted case series, risk-corrected case series | PSM, propensity score weighting, covariate balance |
| 相关≠ | 5 | 3 |
| 摘要≠ | A risk-adjusted case series is an observational study design that reports outcomes for a consecutive or defined group of patients undergoing the same procedure or sharing a condition, while statistically correcting for differences in patient-level baseline risk. Rather than presenting raw complication or mortality rates, it compares observed outcomes against expected rates derived from a validated scoring model (e.g., POSSUM, APACHE, ASA grade), enabling fairer evaluation of clinical performance across institutions or over time. | Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias. |
| ScholarGate数据集 ↗ |
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