| Literature DB >> 33911839 |
Mebrat Gebreyes1, Abay Sisay2, Dilargachew Tegen1, Abushet Asnake1, Mistire Wolde2.
Abstract
BACKGROUND: WHO recommends that each laboratory should establish turnaround time (TAT) to monitor and evaluate performance throughout processes. The status of established TAT was not yet assessed in Ethiopian Armed Force Comprehensive Specialized Hospital. The aim of this study was to evaluate the laboratory performance and associated factors towards achieving TAT in clinical chemistry and hematology tests at Armed Force Comprehensive Specialized Hospital, Addis Ababa, Ethiopia.Entities:
Keywords: Ethiopia; Laboratory; Quality indicator; Turnaround time; performance
Mesh:
Year: 2020 PMID: 33911839 PMCID: PMC8047274 DOI: 10.4314/ejhs.v30i5.17
Source DB: PubMed Journal: Ethiop J Health Sci ISSN: 1029-1857
Figure 1Proportional sample size allocations AFCSH laboratory staffs at the clinical chemistry and Hematology departments to assess TAT; Addis Ababa, Ethiopia, 2019.
Frequency distribution of TAT for chemistry test result and variables which may influence the achievement of TAT standard in AFCSH, Addis Ababa, 2019 (n=253)
| Variables | Chemistry test sample | Hematology test sample | |
| N(%) | N (%) | ||
| IQC | Passed | 246 (97.2%) | 169(100%) |
| Failed | 7(2.8%) | 0(0.0%) | |
| Total | 253(100%) | 169(100%) | |
| Daily work load | Usual | 65(25.7%) | 73(43.2%) |
| High | 188(74.3%) | 96(56.8%) | |
| Computer system related | Uninterrupted | 39(15.4%) | 68(40.2%) |
| Interrupted | 214(84.6%) | 101(59.8.%) | |
| Test order | For Patient | 115(45.5%) | 84(49.7%) |
| For screening | 138(54.5%) | 85(50.3%) | |
| Power supply interruption | uninterrupted | 181(71.5%) | 144(85.2%) |
| Interrupted | 72(11%`) | 25(14.8%) | |
| Time of collection | 8:00 – 9:59hr | 204(80.4%) | 117(69.2%) |
| 10:00 – 12:00hr | 49(19.6%) | 52(30.%) | |
Correlation between pre-analytical, during analytical, post analytical with daily work load, (n= 253) of TAT standard in AFCSH, Addis Ababa, 2019
| Variables | Clinical chemistry | Hematology | |||||
| Daily | Achieved | Not | P-value | Achieved | Not | P-value | |
| TAT for Pre | Normal | 10(3.9%) | 24(9.5%) | 0.019 | 49(28.9%) | 24(14.2%) | <0.01 |
| High | 30(11.6%) | 189(74.7%) | 13(7.7%) | 83(49.1%) | |||
| TAT for analytical | Normal | 171(67.6%) | 10(3.9%) | <0.01 | 49(28.9%) | 24(14.2%) | 0.03 |
| High | 48(18.9%) | 24(9.5%) | 42(24.9%) | 54(31.9%) | |||
| TAT for post | Normal | 24(9.5%) | 10(3.9%) | <0.01 | 37(21.9%) | 36(21.3%) | <0.01 |
| High | 78(30.8%) | 141(55.7%) | 14(8.3%) | 82(48.5%) | |||
Bivariate and multivariable logistic regression analysis of chemistry and Hematology tests, and factors associated with delay of TAT standard in AFCSH, Addis Ababa. 2019
| variable | TAT for clinical chemistry | TAT for hematology | |||||||||
| Not | COR | p-value | AOR | p-value | Not | COR | p-value | AOR | p-value | ||
| Usual | 24(70.4%) | 1 | 1 | 24(32.9%) | 1 | 1 | |||||
| High | 189(86.3%) | 2.62(1.14–6.03) | 0.002 | 2.89(1.13–7.45) | 0.006 | 83(86.5%) | 13(6.9–22.92) | <0.001 | 8.98(2.01–21.47) | <0.001 | |
| Usual | 10(5.5%) | 1 | 1 | 24(32.9%) | 1 | 1 | 10(5.5%) | ||||
| High | 24(33.7%) | 8.55(3.83–19.11) | <0.001 | 1.03(0.14–10.28) | 0.995 | 54(56.3%) | 2.62(1.39–4.94) | 0.985 | 0.929(0.005–1.026) | 24(33.7%) | |
| Usual | 10(29.4%) | 1 | 1 | 31 (42.5%) | 1 | 1 | 10(29.4%) | ||||
| High | 141(62.4%) | 4.39(1.97–9.54) | <0.001 | 1.76(4.78–12.45) | 0.024 | 85 (88.5%) | 6.02(2.90–12.48) | <0.001 | 5.14(1.26–19.68) | 141(62.4%) | |
| Uninterrupted | 15 (38.5%) | 1 | 1 | 14 (28.0%) | 1 | 1 | 15 (38.5%) | ||||
| Interrupted | 197 | 18.541 (8.22–41.82) | <0.001 | 3.19(1.14–8.92) | 0.027 | 119 | 14.57(5.82–36.49) | <0.001 | 6.21(1.57–24.53) | 197 | |
| For Patient | 62 (63.9%) | 1 | 1 | 53 (63.1%) | 9.36(3.42–25.60) | <0.001 | 7.55(2.01–12.33) | 62 (63.9%) | |||
| For screening | 150 | 14.11 (5.65–35.24) | <0.001 | 6.02(2.190–16.52) | <0.001 | 80 (94.1%) | 1 | 1 | 150 | ||
| Uninterrupted | 143 | 1 | 1 | 122 | 1 | 1 | 143 | ||||
| Interrupted | 69 (95.8%) | 6.11 (1.82–20.49) | 0.049 | 0.998(0.64–28.205) | 0.962 | 11 (100%) | 7.34(1.68–32.07) | 0.008 | 3.03(0.46–23.27) | 69 (95.8%) | |
| 8:00 – 9:59am | 174 | 1 | 1 | 101 | 1 | 1 | |||||
| 10:00–12:00am | 38 (77.6%) | 0.59 (0.27–1.29) | 0.294 | 0.899(0.001–0.994) | 0.999 | 32 | 3.94(1.83–8.50) | <0.001 | 3.01(0.87–10.36) | 0.049 | |
Table showed the level of knowledge, attitude, practices and some characteristics of laboratory department staffs, in AFCSH, Addis Ababa, 2019. (n=35)
| Characteristics | Frequeny(%) | |
| Good | 21(60%) | |
| Poor | 14(40%) | |
| Good | 30(85.7%) | |
| Poor | 5(14.3%) | |
| Good | 22(62.9% ) | |
| Poor | 13 (37.1%) | |
| Masters | 3(8.6%) | |
| Lab | 14(40.0%) | |
| Lab technician | 6(17.1%) | |
| Phlebotomist | 12(34.3%) | |
| ≤ 5 years | 12(34.3%) | |
| 6 – 10 years | 11(31.4% ) | |
| > 10 years | 12(34.3%) | |
| Male | 17(48.6%) | |
| Female | 18(52.4%) | |
Table showed the percentage relationship between the level of KAP and some related characteristics of participants, AFCSH, Addis Ababa, Ethiopia 2019
| Characteristics | Level of knowledge | Level of attitude | Level of practices | ||||
| Good | Poor | Good | Poor | Good | Poor | ||
| Qualification | Masters | 3(100%) | 0(0.0%) | 3(100%) | 0(0.0%) | 2(66.7%) | 1(33.3%) |
| Lab technologist | 10(71.3%) | 4(28.7%) | 11(78.6%) | 3(21.4%) | 9(64.3%) | 5(35.7%) | |
| Lab technician | 4(66.7%) | 2(33.3%) | 6(100%) | 0(0.0%) | 4(66.7%) | 2(33.3%) | |
| Phlebotomist | 6(50.0%) | 6(50.0%) | 10(83.3%) | 2(16.7%) | 7(58.3%) | 5(41.7%) | |
| Work | ≤ 5 years | 5(41.7%) | 7(58.3%) | 10(83.3%) | 2(167%) | 7(58.3%) | 5(41.7%) |
| 6 – 10 years | 8(72.7%) | 3(27.3%) | 11(100%) | 0(0.0%) | 7(63.6%) | 4(36.4%) | |
| > 10 years | 8(66.7%) | 4(33.3%) | 9(75.0%) | 3(25.0%) | 8(66.7%) | 4(33.3%) | |
| Sex | Male | 12(70.6%) | 5(29.4%) | 16(94.1%) | 1(5.9%) | 12(70.6%) | 5(29.4%) |
| Female | 9(50.0%) | 9(50.0%) | 14(77.8%) | 4(22.2%) | 10(55.6%) | 8(44.4%) | |