Table 5. Modelling the determinants of correct drug match at the medicine level.
| Predictor | Model 1 | Model 2 | Model 3 |
|---|---|---|---|
| Drug Characteristics | |||
| Drug Class | |||
| Analgesic | - | - | - |
| Antacid | 0.07*** [0.03–0.18] | 0.07*** [0.02–0.17] | 0.07*** [0.03–0.18] |
| Anti-Asthmatic | 0.21 [0.03–1.70] | 0.22 [0.03–1.83] | 0.22 [0.03–1.87] |
| Anti-Diabetic | 0.13** [0.03–0.46] | 0.12** [0.03–0.46] | 0.12** [0.03–0.45] |
| Antihistamine | 0.01*** [0.01–0.02] | 0.01*** [0.01–0.02] | 0.01*** [0.01–0.02] |
| Anti-Hypertensive | 0.19*** [0.10–0.37] | 0.23*** [0.10–0.54] | 0.23*** [0.10–0.54] |
| Anti-Hypertensive##Treatment | 9.95** [1.88–52.69] | ||
| Anti-Hypertensive##Being insured | 25.15*** [4.17–151.61] | ||
| Anti-Malarial | 0.49* [0.27–0.89] | 0.44* [0.24–0.82] | 0.44* [0.24–0.83] |
| Anti-Spasmodic | 0.06*** [0.02–0.19] | 0.08*** [0.02–0.32] | 0.08*** [0.02–0.33] |
| Antibiotic | 0.04*** [0.03–0.06] | 0.04*** [0.03–0.06] | 0.04*** [0.03–0.06] |
| Antibiotic##Being insured | 3.60** [1.45–8.92] | ||
| Expectorant | 0.03*** [0.02–0.07] | 0.03*** [0.01–0.06] | 0.03*** [0.01–0.06] |
| Haematinic | 0.05*** [0.03–0.07] | 0.04*** [0.03–0.07] | 0.04*** [0.03–0.07] |
| Haematinic##Treatment | 2.32* [1.03–5.25] | ||
| Haematinic##Being insured | 5.40*** [2.54–11.50] | ||
| Vitamin & Mineral | 0.02*** [0.01–0.02] | 0.01*** [0.01–0.02] | 0.01*** [0.01–0.02] |
| Vitamin & Mineral##Being insured | 3.76*** [1.88–7.53] | ||
| Place Drug was Obtained | |||
| Public health facility | - | - | |
| Private health facility | 2.01* [1.08–3.77] | 2.04* [1.10–3.80] | |
| Patent Proprietary Medicine Vendors | 1.74* [1.05–2.90] | 1.94* [1.15–3.25] | |
| Other | 1.37 [0.73–2.58] | 1.51 [0.80–2.85] | |
| Demographic characteristics | |||
| Age Group | |||
| 0–18 | - | - | |
| 19–35 | 1.07 [0.71–1.61] | 1.07 [0.71–1.62] | |
| 36–60 | 0.76 [0.51–1.13] | 0.77 [0.52–1.15] | |
| ≥61 | 0.70 [0.47–1.04] | 0.70 [0.47–1.04] | |
| Gender | |||
| Male | - | - | |
| Female | 0.95 [0.77–1.16] | 0.94 [0.77–1.15] | |
| Socioeconomic characteristics | |||
| Marital Status | |||
| Single | - | - | |
| Married | 0.97 [0.70–1.35] | 0.97 [0.70–1.34] | |
| Household Size | |||
| 1–5 | - | - | |
| ≥6 | 0.97 [0.73–1.29] | 0.98 [0.73–1.30] | |
| Education Level | |||
| No education | - | - | |
| Primary | 1.01 [0.80–1.28] | 1.01 [0.79–1.28] | |
| Secondary | 0.85 [0.63–1.13] | 0.86 [0.64–1.15] | |
| Tertiary | 1.63* [1.06–2.49] | 1.61* [1.05–2.47] | |
| Income Level | |||
| Quintile 1 (Poorest) | - | - | |
| Quintile 2 | 1.13 [0.69–1.87] | 1.13 [0.68–1.86] | |
| Quintile 3 | 1.14 [0.72–1.80] | 1.13 [0.72–1.79] | |
| Quintile 4 | 1.38 [0.88–2.18] | 1.37 [0.87–2.15] | |
| Quintile 5 (Richest) | 1.34 [0.85–2.09] | 1.31 [0.84–2.06] | |
| Health-related characteristics | |||
| Chronic Disease | |||
| No | - | - | |
| At least one | 0.95 [0.71–1.27] | 0.93 [0.70–1.25] | |
| Distance from Nearest Health Facility (Km) | 0.98 [0.95–1.02] | 0.98 [0.95–1.02] | |
| Insurance program indicators | |||
| Observation in Treatment Area | |||
| No | - | - | |
| Yes | 1.51** [1.16–1.98] | 1.41* [1.05–1.87] | |
| Insurance Status | |||
| No | - | ||
| Yes | 1.26 [0.93–1.71] | ||
| Chi-square | 835 | 892 | 892 |
| df | 11 | 30 | 31 |
| Deviance | 4,242 | 3,998 | 3,990 |
| N | 6,772 | 6,524 | 6,517 |
* p<0.05
** p<0.01
*** p<0.001 [95% Confidence Interval].
Results of fitting a series of logistic regression models predicting the likelihood of having a medicine use correctly match its actual clinical use, using drug class, and controlling for relevant covariates. Model 1: Drug class only, Model 2: Drug class and socio-demographic factors, Model 3: Drug class, socio-demographic and insurance status.