| Literature DB >> 26063399 |
Agajie Likie Bogale1, Habtamu Belay Kassa2, Jemal Haidar Ali3.
Abstract
BACKGROUND: The most effective strategies in the fight against malaria are to correctly diagnose and timely treat the illness. A diagnosis based on clinical symptoms alone is subjected to misuse of anti-malarial drugs, increased costs to the health services, patient dissatisfaction and also contributes to an increase in non-malaria morbidity and mortality. Among others, inappropriate perception and inadequate satisfaction of patients are significant challenges reported to affect the quality of laboratory malaria diagnostic services.Entities:
Mesh:
Year: 2015 PMID: 26063399 PMCID: PMC4465737 DOI: 10.1186/s12936-015-0756-6
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Socio-demographic characteristics of respondents’ in Awi zone, Amhara Regional State, North West Ethiopia, 2013 (n = 300)
| Respondents’ characteristics | Frequency | Percent |
|---|---|---|
| Age (in years) | ||
| 18–25 | 138 | 46.0 |
| 26–35 | 90 | 30.0 |
| 36–45 | 36 | 12.0 |
| 46–55 | 15 | 5.0 |
| >55 | 21 | 7.0 |
| Mean (±SD) | 31 (±13) | |
| Sex | ||
| Male | 160 | 53.5 |
| Female | 139 | 46.5 |
| Marital status | ||
| Single | 85 | 28.9 |
| Married | 204 | 69.4 |
| Divorced | 2 | 0.7 |
| Widowed | 3 | 1.0 |
| Patient’s ethnicity | ||
| Awi | 196 | 65.3 |
| Amhara | 103 | 34.3 |
| Other | 1 | 0.3 |
| Patient work area | ||
| Rural | 254 | 84.9 |
| Urban | 45 | 15.1 |
| Employment | ||
| Farmer | 159 | 53.0 |
| Merchant | 26 | 8.7 |
| Government employee | 34 | 11.3 |
| Non-government employee | 2 | 0.7 |
| Other | 79 | 26.3 |
| Educational | ||
| No formal education | 135 | 45.0 |
| Primary education | 84 | 28.0 |
| Secondary education | 47 | 15.7 |
| College/university | 33 | 11.0 |
| Other | 1 | 0.3 |
Patients’ diagnosis and their various responses on malaria, in Awi zone, Amhara Regional State, North West Ethiopia, 2013 (n = 300)
| Respondents’ characteristics | Frequency | Percent |
|---|---|---|
| Diagnosed the illness | ||
| Clinician | 194 | 64.7 |
| Self | 46 | 15.3 |
| Lab tech | 15 | 5.0 |
| Lab tech and Clinician | 36 | 12.0 |
| Perceived to be diagnosed properly by | ||
| Lab tech | 266 | 89.3 |
| Clinician | 4 | 1.3 |
| Pharmacy | 7 | 2.3 |
| Combined | 21 | 7.0 |
| Waiting time | ||
| Within 30 min | 187 | 62.5 |
| 30–60 | 84 | 28.1 |
| >60 min | 29 | 9.4 |
| Frequency of care given when had malaria | ||
| All the time | 162 | 54.2 |
| Most of the time | 103 | 34.4 |
| Some times | 33 | 11.0 |
| Never | 1 | 0.3 |
| Work ethics of providers to patients | ||
| Very concerned | 123 | 41.1 |
| Concerned | 139 | 46.5 |
| Less concerned | 36 | 12.0 |
Response to different perception and satisfaction questions by patients from twelve health centers in Awi zone, Amhara Regional State, North Western Ethiopia, 2013 (n = 300)
| Respondent’s perception and satisfaction | Excellent | Very good | Good | Fair | Poor | Weighted average | Unweighted average (mean ± SD) |
|---|---|---|---|---|---|---|---|
| f (%) | f (%) | f (%) | f (%) | f (%) | |||
| Easy to access the service | 110 (36.7) | 91 (30.3) | 91 (30.3) | 7 (2.3) | 1 (0.3) | 4.01 | 1.99 ± 0.89 |
| Waiting time for lab service | 104 (34.7) | 79 (26.3) | 95 (31.7) | 21 (7.0) | 1 (0.3) | 3.88 | 2.12 ± 0.98 |
| Health professionals respectfulnessa | 108 (36.5) | 101 (34.1) | 74 (25.0) | 9 (3.0) | 4 (1.4) | 4.01 | 1.99 ± 0.93 |
| Encouraged to ask any informationa | 106 (40.8) | 54 (20.8) | 85 (32.7) | 10 (3.8) | 5 (1.9) | 3.95 | 2.05 ± 1.03 |
| Phlebotomy service for malaria examinationa | 100 (33.6) | 131 (44.0) | 66 (22.1) | − | 1 (0.3) | 4.10 | 1.9 ± 0.76 |
| Availability of lab malaria results/not missinga | 105 (35.4) | 158 (53.2) | 24 (8.1) | 8 (2.7) | 2 (0.7) | 4.2 | 1.8 ± 0.75 |
| Perception about quality of lab resulta | 95 (31.9) | 93 (31.2) | 104 (34.9) | 4 (1.3) | 2 (0.7) | 3.92 | 2.08 ± 0.88 |
| Willingness to conduct lab investigation a | 107 (35.7) | 115 (38.3) | 76 (25.3) | 1 (0.3) | 1 (0.3) | 4.09 | 1.91 ± 0.81 |
| Punctuality of service providers during working hours | 114 (38.0) | 138 (46.0) | 40 (13.3) | 7 (2.3) | 1 (0.3) | 4.19 | 1.81 ± 0.78 |
| Staff language to communicate | 224 (74.7) | 57 (19.0) | 15 (5.0) | 3 (1.0) | 1 (0.3) | 4.67 | 1.33 ± 0.65 |
| The response to your request, and problems by lab personnela | 134 (44.8) | 112 (37.5) | 51 (17.1) | 1 (0.3) | 1 (0.3) | 4.25 | 1.74 ± 0.77 |
| Explanation about prescribed malaria drug | 160 (53.3) | 123 (41.0) | 15 (5.0) | 1 (0.3) | 1 (0.3) | 4.47 | 1.53 ± 0.64 |
“f” indicates number of respondents for single variable
SD standard deviation
asample size do not add up to 300 because of illogical response
Univariate and Multivariate analysis for predictors of satisfaction towards patient respondents in selected health centers Awi Zone, Amhara Regional State, North West Ethiopia, 2013 (n = 300)
| Characteristics | Outcome | COR (95%CI) | AOR (95%CI) | |
|---|---|---|---|---|
| Satisfied (≥48) Freq (%) | Dissatisfied (≤47) Freq (%) | |||
| Age | ||||
| 18–25 | 57 (48.7) | 60 (52.3) | 1 | |
| 26–35 | 37 (52.9) | 33 (47.1) | 1.26 (1.02–1.55)* | 1.30 (0.95–1.78) |
| 36–45 | 15 (44.1) | 19 (55.9) | ||
| 46–55 | 9 (69.2) | 4 (30.8) | ||
| >55 | 15 (78.9) | 4 (21.1) | ||
| Sex | ||||
| Female | 48 (42.9) | 64 (57.1) | 1 | 1 |
| Male | 84 (60) | 56 (40) | 2.0 (1.20–3.31)* | 1.35 (0.64–2.86) |
| Ethnicity | ||||
| Awi | 114 (67.5) | 55 (32.5) | 1 | 1 |
| Amhara | 18 (21.7) | 65 (78.3) | 0.13 (0.07–0.24)* | 0.24 (0.11–0.55)* |
| Work area | ||||
| Urban | 4 (12.5) | 28 (87.5) | 1 | 1 |
| Rural | 129 (58.6) | 91 (41.4) | 9.92 (3.36–29.26)* | 4.89 (1.07–22.28)* |
| Educational level | ||||
| Illiterate | 54 (50) | 54 (50) | 1 | 1 |
| Primary education | 35 (46.1) | 41 (53.9) | 0.85 (0.47–1.54) | 0.71 (0.24–2.14) |
| Secondary education | 19 (48.7) | 20 (51.3) | 0.95 (0.45–1.97) | 0.63 (0.18–2.18) |
| College/university | 25 (83.3) | 5 (16.7) | 5.0 (1.78–14.03)* | 2.99 (0.36–24.88) |
| Employment | ||||
| Farmer | 68 (51.5) | 64 (48.5) | 1 | 1 |
| Merchant | 8 (36.4) | 14 (63.6) | 0.53 (0.21–1.36) | 1.62 (0.39–6.72) |
| Government employee | 25 (80.6) | 6 (19.4) | 3.92 (1.51–10.18)* | 4.01 (0.616–26.11) |
| Non-government employee | 1 (50) | 1 (50) | 0.94 (0.05–15.36) | 0.99 (0.01–489.99) |
| Other | 31 (47) | 35 (53) | 0.83 (0.46–1.50) | 0.96 (0.28–3.30) |
| Knowing malaria diagnosis | ||||
| By your selves | 7 (19.4) | 29 (80.6) | 1 | 1 |
| After consulting clinician | 100 (61.3) | 63 (38.7) | 6.576 (2.718–15.910)* | 3.32 (1.11–9.88)* |
| After consulting lab personnel | 6 (40) | 9 (60) | 2.76 (0.74–10.36) | 1.2 (0.23–6.65) |
| Waiting time to receive malaria lab result | ||||
| Within 30 min | 119 (72.6) | 45 (27.4) | 1 | 1 |
| 30 min–1 h | 14 (19.7) | 57 (80.3) | 0.09 (0.05–0.18) | 0.12 (0.05–0.28)* |
| After 1 h | 0 | 10 (100) | 0.001 (0.001) | 0.001 (0.001) |
* p < 0.05