Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Mfululizo wa Kesi Ulioboreshwa kwa Hatari× | Utafiti wa Kikundi Kazi Uliorekebishwa kwa Hatari× | |
|---|---|---|
| Nyanja | Epidemiolojia | Epidemiolojia |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1990s–2000s | Mid–late 20th century (risk-adjusted cohort designs systematized by 1970s–1990s) |
| Mwanzilishi≠ | Copeland, Jones & Walters (POSSUM score, 1991); broader risk-adjustment methodology developed across surgical and critical care audit literature | Evolution of cohort study methodology; risk adjustment formalized through work of Rothman, Greenland, and others in epidemiology, 20th century |
| Aina≠ | Observational study design with statistical risk correction | Observational epidemiological study design with statistical confounding control |
| Chanzo asilia≠ | Copeland, G. P., Jones, D., & Walters, M. (1991). POSSUM: a scoring system for surgical audit. British Journal of Surgery, 78(3), 355–360. DOI ↗ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| Majina mbadala≠ | risk-stratified case series, adjusted case series, risk-corrected case series | adjusted cohort study, covariate-adjusted cohort, risk-controlled prospective study, propensity-adjusted cohort |
| Zinazohusiana≠ | 5 | 4 |
| Muhtasari≠ | 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. | A risk-adjusted cohort study is an observational epidemiological design in which a defined group of individuals is followed over time to compare outcomes between exposed and unexposed subgroups, with statistical methods applied to control for measured confounders. Adjustment strategies — including multivariable regression, propensity score matching, inverse probability weighting, or standardization — are used to reduce bias and produce effect estimates that more closely approximate what would be observed in a randomized trial. |
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