Table 4 Predictors of prevalence of correctly completed death certificates: Logistic regression analysis, univariate analysis
Death certificate characteristics | Unadjusted OR (95% CI) | p value | GP characteristics and associated parameters. | Unadjusted OR (95% CI) | p value |
|---|---|---|---|---|---|
Elderly (age ≥ 60 yr.) | 1.2 (0.8–1.8) | 0.2 | Age | 0.8 (0.5–1.3) | 0.3 |
Female | 1.1 (0.8–1.6) | 0.5 | Female | 0.6 (0.3–1.3) | 0.1 |
Hospital Sizes | Medical School Sizes | ||||
▪ 400–700 beds | Reference | ▪ > 200 graduates/ year | Reference | ||
▪ 701–1000 beds | 1.1 (0.7–1.7) | 0.6 | ▪ 101–200 graduates/ year | 0.9 (0.4–1.9) | 0.7 |
▪ More than 1000 | 1.4 (0.9–2.0) | 0.1 | ▪ 51–100 graduates/ year | 0.5 (0.2–1.7) | 0.2 |
COD disease groups | ▪ ≤ 50 graduates/ year | 1.6 (0.5–5.1) | 0.3 | ||
▪ Cardiovascular disease | 2.3 (1.6–3.5) | < 0.001 | Future plans for specialist training | ||
▪ Infectious disease | 0.4 (0.2–0.7) | 0.001 | ▪ Specialist training plans | 1.3 (0.5–3.1) | 0.6 |
▪ Cancer group | 3.7 (2.2–6.0) | < 0.001 | GPA Group | ||
▪ Gastrointestinal disease | 0.9 (0.6–1.5) | 0.7 | ▪ GPA ≥ 3.5 | 3.5 (1.5–7.9) | 0.003 |
▪ Pulmonary disease | 1.2 (0.7–2.2) | 0.4 | Time spent during medical curriculum | ||
▪ Endocrine disease | 0.1 (0.04–0.4) | < 0.001 | ▪ Time spent ≥2 h | 1.0 (0.4–2.3) | 0.9 |
▪ External cause | 0.6 (0.3–1.2) | 0.1 | COD coding experience | ||
▪ Nephrology disease | 0.7 (0.2–1.8) | 0.4 | ▪ Have experience in completing DCs by themselves during medical school | 1.8 (0.9–3.8) | 0.1 |
▪ Neurologic disease | 0.5 (0.1–1.7) | 0.2 | ▪ Have experience completing DCs by themselves >5cases/month after graduation | 1.2 (0.6–2.5) | 0.6 |
▪ Musculoskeletal and rheumatologic disease | 0.2 (0.02–1.5) | 0.07 | ▪ Established COD coding training program in work hospital | 0.9 (0.4–1.9) | 0.8 |
▪ Unknown cause of death/ Other | 0.4 (0.2–1.1) | 0.05 | Understands that DCs are used in public health research and policy | 1.5 (0.7–2.9) | 0.2 |