| Literature DB >> 31898498 |
Aliyu Mamman Na'uzo1,2, Dahiru Tukur3, Mu'awiyyah Babale Sufiyan3, Adebowale Ayo Stephen4, IkeOluwapo Ajayi4, Eniola Bamgboye4, Abdulrazaq Abdullahi Gobir3, Chukwuma David Umeokonkwo5, Zainab Abdullahi6, Olufemi Ajumobi7,8,9.
Abstract
BACKGROUND: Presumptive diagnosis and prescription of anti-malarial medicines to malaria rapid diagnostic test (RDT)-negative patients is a common practice among health care workers (HCWs) in Nigeria. There is paucity of data on HCWs adherence to RDT result in Sokoto metropolis, Nigeria. The study was conducted to determine HCWs adherence to malaria test result and the influencing factors.Entities:
Keywords: Diagnostic test; Guideline adherence; Healthcare workers; Malaria; Nigeria; Routine
Mesh:
Substances:
Year: 2020 PMID: 31898498 PMCID: PMC6941286 DOI: 10.1186/s12936-019-3094-2
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Fig. 1Map of Nigeria highlighting the location of Sokoto State in green within the North western part of Nigeria. Developed using QGIS version 2.4.0 a free GIS software
Sampling of health care workers by probability proportional to size
| S/no | Cadre of HCW | No. in Health facility | Calculated proportion | No. allocated to health facility (n) | Sampling interval (N/n) |
|---|---|---|---|---|---|
| 1. | Junior Community Health Extension Workers | 175 | 175/1100 × 276 = 44 | 44 | 4 |
| 2. | Community Health Officers | 36 | 36/1100 × 276 = 9 | 9 | 4 |
| 3. | Community Health Extension Worker | 279 | 276/1100 × 276 = 70 | 70 | 4 |
| 4. | Nurses | 267 | 267/1100 × 276 = 67 | 67 | 4 |
| 5. | Medical Laboratory Scientist | 183 | 183/1100 × 276 = 46 | 46 | 4 |
| 6. | Medical Doctors | 132 | 132/1100 × 276 = 33 | 33 | 4 |
| 7. | Pharmacy Technicians | 28 | 28/1100 × 276 = 7 | 7 | 4 |
| 8. | Total | 1100 | 276 | 4 |
Socio-demographic characteristics of health care workers in Sokoto metropolis, Nigeria (N = 262)
| Characteristics | Frequency | Percentage |
|---|---|---|
| Age (years) | ||
| < 30 | 98 | 37.4 |
| 30–39 | 107 | 40.8 |
| 40–49 | 47 | 17.9 |
| ≥ 50 | 10 | 3.8 |
| Sex | ||
| Female | 155 | 59.2 |
| Male | 107 | 40.8 |
| Marital status | ||
| Single | 63 | 24.0 |
| Married | 186 | 71.0 |
| Divorced | 6 | 2.3 |
| Widowed | 7 | 2.7 |
| Professional cadre | ||
| CHW | 112 | 42.7 |
| Nurses | 65 | 24.8 |
| Medical Laboratory Scientist/Technicians | 46 | 17.6 |
| Medical Doctor | 32 | 12.2 |
| Pharmacy Technician | 7 | 2.7 |
| Professional qualification | ||
| Certificatea | 39 | 14.9 |
| Diploma | 178 | 67.9 |
| Degree/HND | 45 | 17.2 |
| Years of practice | ||
| < 5 | 118 | 45.0 |
| 5–9 | 77 | 29.4 |
| ≥ 10 | 67 | 25.6 |
| Facility type | ||
| Primary | 190 | 72.5 |
| Secondary | 72 | 27.5 |
CHW Community Health Extension Workers and Community Health Officers, HND Higher National Diploma
aCertificate in Junior Community Health Extension Worker
Factors associated with adherence to test result among health care workers, Sokoto metropolis, Nigeria (N = 262)
| Characteristics | Adherence | OR (95% CI) | |
|---|---|---|---|
| Good | Total | ||
| Age (years) | |||
| < 35 | 128 (81.0) | 158 | 1.08 (0.58–2.01) |
| ≥ 35 | 83 (79.8) | 104 | 1 (ref.) |
| Sex | |||
| Male | 81 (75.7) | 107 | 0.60 (0.33–1.11) |
| Female | 130 (83.9) | 155 | 1 (ref.) |
| Facility type | |||
| Primary | 156 (82.1) | 190 | 1.42 (0.73–2.74) |
| Secondary | 55 (76.4) | 72 | 1 (ref.) |
| Professional qualification | |||
| Certificate | 35 (89.7) | 39 | 4.38 (1.31–14.61)* |
| Diploma | 146 (82.0) | 178 | 2.28 (1.10–4.73) |
| Degree/HND | 30 (66.7) | 45 | 1 (ref.) |
| Cadre | |||
| CHW | 93 (83.0) | 112 | 1 (ref.) |
| Doctors/Nurses | 79 (81.4) | 97 | 0.90 (0.44–1.83) |
| Medical lab/Pharm tech | 39 (73.6) | 53 | 0.57 (0.26–1.25) |
| Years of practice | |||
| < 5 | 95 (80.5) | 118 | 1.0 (0.54–1.84) |
| ≥ 5 | 116 (80.6) | 144 | 1 (ref.) |
| Had training on malaria case management | |||
| Yes | 108 (89.3) | 121 | 3.07 (1.54–6.08)* |
| No | 103 (73.0) | 141 | 1 (ref.) |
| Stock out of mRDT influenced prescription | |||
| Yes | 169 (80.1) | 211 | 0.86 (0.39–1.91) |
| No | 42 (92.4) | 51 | 1 (ref.) |
| Presence of fever in the patient influenced prescription | |||
| Yes | 185 (85.6) | 216 | 4.59 (2.29–9.21)* |
| No | 26 (56.5) | 46 | 1 (ref.) |
| Expectation of the patient to be given antimalarial influenced prescription | |||
| Yes | 115 (91.3) | 126 | 4.36 (2.12–8.95)* |
| No | 96 (70.6) | 136 | 1 (ref.) |
| Clinical judgement of the HCW influenced prescription | |||
| Yes | 184 (81.4) | 226 | 1.46 (0.64–3.33) |
| No | 27 (75.0) | 36 | 1 (ref.) |
| Availability of alternative diagnostic tool | |||
| Yes | 177 (81.9) | 216 | 1.60 (0.76–3.37) |
| No | 34 (73.9) | 46 | 1 (ref.) |
* p ≤ 0.05
Predictors of adherence to Malaria RDT results among health care workers, Sokoto metropolis, Nigeria
| Characteristics | Model 1 | Model 2 | Model 3 | Model 4 |
|---|---|---|---|---|
| COR (95% CI) | aOR (95% CI) | aOR (95% CI) | aOR (95% CI) | |
| Age (years) | ||||
| < 35 | 1.08 (0.58–2.01) | |||
| ≥ 35 | 1 (ref.) | |||
| Sex | ||||
| Male | 0.60 (0.33–1.11) | |||
| Female | 1 (ref.) | |||
| Facility type | ||||
| Primary | 1.42 (0.73–2.74) | |||
| Secondary | 1 (ref.) | |||
| Years of practice | ||||
| < 5 | 0.10 (0.54–1.84) | |||
| ≥ 5 | 1 (ref.) | |||
| Professional qualification | ||||
| Certificate | 4.38 (1.31–14.61)† | 4.38 (1.31–14.61) | 3.59 (0.10–12.10) | |
| Diploma | 2.28 (1.10–4.73) | 2.28 (1.10–4.73)* | 1.89 (0.83–4.14) | |
| Degree/HND | 1 (ref.) | 1 (ref.) | 1 (ref.) | |
| Cadre | ||||
| CHW | 1 (ref.) | |||
| Doctors/Nurses | 0.90 (0.44–1.83) | |||
| Med. Lab/Pharm tech | 0.57 (0.26–1.25) | |||
| Had training on malaria case management | ||||
| Yes | 3.07 (1.54–6.08)† | 2.58 (1.26–5.29)* | 2.63 (1.26–5.44)* | |
| No | 1 (ref.) | 1 (ref.) | 1 (ref.) | |
| mRDT stock level in the facility influenced prescription | ||||
| Yes | 0.86 (0.39–1.91) | |||
| No | 1 (ref.) | |||
| Presence of fever in the patient influenced prescription | ||||
| Yes | 4.59 (2.29–9.21)† | 2.83 (1.33–5.98)* | 2.53 (1.18–5.43)* | |
| No | 1 (ref.) | 1 (ref.) | 1 (ref.) | |
| Patients expectations to be given antimalarial influenced prescription | ||||
| Yes | 4.36 (2.12–8.95)† | 3.18 (1.48–6.80)* | 3.06 (1.42–6.58)* | |
| No | 1 (ref.) | 1 (ref.) | 1 (ref.) | |
| Clinical judgement of the HCW influenced prescription | ||||
| Yes | 1.46 (0.64–3.33) | |||
| No | 1 (ref.) | |||
| Availability of alternative diagnostic tool (microscopy) | ||||
| Yes | 1.60 (0.76–3.37) | |||
| No | 1 (ref.) | |||
Hosmer–Lemeshow p value = 0.185
COR crude odds ratio, OR odds ratio, aOR adjusted odds ratio, Ref reference category = 1
†Significant at 10%; * p < 0.05