scholarly journals Laboratory system strengthening and quality improvement in Ethiopia

2014 ◽  
Vol 3 (2) ◽  
Author(s):  
Tilahun M. Hiwotu ◽  
Gonfa Ayana ◽  
Achamyeleh Mulugeta ◽  
Getachew B. Kassa ◽  
Yenew Kebede ◽  
...  
Keyword(s):  
National Laboratory ◽  
Evaluation Process ◽  
Routine Activities ◽  
Laboratory Accreditation ◽  
P Value ◽  
Supportive Supervision ◽  
Laboratory System ◽  
Average Amount ◽  
Laboratory Management ◽  
Percentage Points

Background: In 2010, a National Laboratory Strategic Plan was set forth in Ethiopia to strengthen laboratory quality systems and set the stage for laboratory accreditation. As a result, the Strengthening Laboratory Management Toward Accreditation (SLMTA) programme was initiated in 45 Ethiopian laboratories.Objectives: This article discusses the implementation of the programme, the findings from the evaluation process and key challenges.Methods: The 45 laboratories were divided into two consecutive cohorts and staff from each laboratory participated in SLMTA training and improvement projects. The average amount of supportive supervision conducted in the laboratories was 68 hours for cohort I and two hoursfor cohort II. Baseline and exit audits were conducted in 44 of the laboratories and percent compliance was determined using a checklist with scores divided into zero- to five-star ratinglevels.Results: Improvements, ranging from < 1 to 51 percentage points, were noted in 42 laboratories, whilst decreases were recorded in two. The average scores at the baseline and exit audits were 40% and 58% for cohort I (p < 0.01); and 42% and 53% for cohort II (p < 0.01),respectively. The p-value for difference between cohorts was 0.07. At the exit audit, 61% ofthe first and 48% of the second cohort laboratories achieved an increase in star rating. Poor awareness, lack of harmonisation with other facility activities and the absence of a quality manual were challenges identified.Conclusion: Improvements resulting from SLMTA implementation are encouraging. Continuous advocacy at all levels of the health system is needed to ensure involvement of stakeholders and integration with other improvement initiatives and routine activities.

The Joint External Evaluation process in Cameroon: Assessing the country’s capacity for health security

2019 ◽  
Author(s):  
Viviane FOSSOUO NDOUNGUE ◽  
Mohamed Moctar Mouiche Molium ◽  
Christie Tiwoda ◽  
Oumarou Gnigninanjouena ◽  
Serge Alain Sadeuh-Mba ◽  
...  
Keyword(s):  
National Laboratory ◽  
Evaluation Process ◽  
Average Score ◽  
Laboratory System ◽  
Self Assessment ◽  
Health Security ◽  
Point Of Entry ◽  
Chemical Events ◽  
Joint External Evaluation ◽  
Medical Countermeasures

Abstract Objectives The objective of this study was to present the JEE process in Cameroon as well as Cameroon’s capacities to manage public health threats in accordance with the IHR 2005. Cameroon JEE process and data for the 48 indicators within the 19 technical areas was examined.Results Cameroon's overall score was 1.98 ± 0.93 and 48/34 indicators (70.38%) had scores less than 2 on a 1 to 5 scale. In the “Detect” category the average score was 2.7. Technical areas with the lowest average scores were Reporting and National laboratory system. The weakest indicators in the “Prevent” category were antimicrobial resistance, biosafety and biosecurity, and National legislation, policy and financing. Emergency Response Operations, Preparedness, Medical Countermeasures and Personnel Deployment have the lowest scores in the “Respond” category. Chemical Events and Points of Entry have the lowest score in “Other IHR-related hazards and Point of Entry”. Scores attributed during the country self-assessment were 73% similar to those of the JEE process.

scholarly journals The Joint External Evaluation process in Cameroon: Assessing the country’s capacity for health security

2020 ◽  
Author(s):  
Viviane Ndoungue Viviane Fossouo ◽  
Mohamed Moctar Mouliom Mouiche ◽  
Christie Tiwoda ◽  
Oumarou Gnigninanjouena ◽  
Serge alain Sadeuh-Mba ◽  
...  
Keyword(s):  
Action Plan ◽  
National Laboratory ◽  
International Health ◽  
Evaluation Process ◽  
Laboratory System ◽  
Median Score ◽  
External Evaluation ◽  
Health Security ◽  
Point Of Entry ◽  
Joint External Evaluation

Abstract Objectives: The objective of this study was to present the JEE process in Cameroon’s as well as the country capacities to prevent, detect and respond to public health threats in accordance with the IHR (2005). Data for the 48 indicators within the 19 technical areas of the Joint External Evaluation (JEE) tool was examined. Results: Cameroon's overall median score was 2 (Min =1, Max=4) and 34/48 indicators (71%) had scores less than 2 on a 1 to 5 scale. The weakest technical areas in the “Prevent” category were antimicrobial resistance, biosafety and biosecurity, and National legislation, policy and financing. In the “Detect” category, the median score was 2. Technical areas with the lowest median scores were Reporting and National Laboratory System. Emergency Response Operations, Preparedness, Medical Countermeasures and Personnel Deployment had the lowest scores in the “Respond” category. Chemical Events and Points of Entry had the lowest score in “Other IHR-related hazards and Point of Entry” category. Recommendations from the JEE to address the gaps will be aligned in a costed National Action Plan for Health Security (NAPHS) and implemented using national resources, external donors and multilateral agencies. Key words: International Health Regulation, Joint External Evaluation, Health security, Cameroon.

scholarly journals Origins and Development of the National Laboratory System for Public Health Testing

2010 ◽  
Vol 125 (2_suppl) ◽  
pp. 18-30 ◽  
Author(s):  
J. Rex Astles ◽  
Vanessa A. White ◽  
Laurina O. Williams
Keyword(s):  
Public Health ◽  
National Laboratory ◽  
Laboratory System

scholarly journals Good Laboratory Practice in Analytical Chemistry with Modern Laboratory Management

Proceedings ◽  
2020 ◽  
Vol 55 (1) ◽  
pp. 23
Author(s):  
Jacobus (Koos) Frederick van Staden
Keyword(s):  
Analytical Chemistry ◽  
Business Models ◽  
Management Control ◽  
Laboratory System ◽  
Laboratory Management ◽  
Quality Performance ◽  
New Business ◽  
Good Laboratory ◽  
Performance And Evaluation ◽  
And Function

Analytical chemistry is experiencing dramatic, turbulent change beyond laboratory and laboratory management control. Technological innovations, staffing demographics, new business models, automation, industry consolidation, society, regulatory expectations, and other factors are transforming nearly every aspect of analytical chemistry. This course takes a strategic view of the laboratory system in the context of current quality management philosophies to determine options for achieving best practices. Experiences will be shared to provide insight into the obstacles and expected outcomes for the various approaches. Furthermore, this course includes the mission and function of the analytical enterprise, along with ways to improve the quality, performance, and evaluation of the laboratory for excellent benchmarking in giant industries.

Major Improvements in Survival in Hematologic Malignancies in the Early 2000s.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 632-632
Author(s):  
Dianne Pulte ◽  
Adam Gondos ◽  
Hermann Brenner
Keyword(s):  
Relative Survival ◽  
Population Level ◽  
Hematologic Malignancies ◽  
The United States ◽  
P Value ◽  
Period Analysis ◽  
Non Hodgkin Lymphoma ◽  
Percentage Points ◽  
Recent Advances ◽  
Using Data

Abstract Background: Recent advances in the treatment of hematologic malignancies have led to improvements in response and survival in clinical trials for several conditions. Translation of these improvements to better survival on the population level should be monitored in as timely as possible a manner. Methods: We estimated trends in relative survival in patients with common hematologic malignancies in the United States between the years 2000 and 2004 using data from the Surveillance, Epidemiology, and End Results (SEER) program, employing the recently introduced technique of modeled period analysis to provide the most up-to-date and precise estimates of survival1. We calculated survival according to gender and age group as well as overall survival for each malignancy. Results: Major improvements in 5-year relative survivals were observed for nodal and extra-nodal non-Hodgkin lymphoma (NHL) (+8.3 and +7.1 percentage points, respectively, p<0.0001), acute myeloblastic leukemia (AML) (+4.8 percentage points, p=0.005), and chronic myelocytic leukemia (CML) (+15.9 percentage points, p<0.0001). Improvement in 10-year survivals were observed in nodal and extra-nodal (EN) NHL (+8.7 and +7.8 percentage points, p<0.0001), AML (+4.3 percentage points, p=0.009), CML (+16.2 percentage points, p<0.0001), and myeloma (+3.4 percentage points, p=0.01). Statistically significant improvements in 10-year survival were seen in both genders for NHL and CML, but were limited to women for MM and AML, although a trend towards improved survival was seen in men with these conditions as well. Improvements in prognosis were largely restricted to patients aged less than 65, except for NHL and CML. Patients over 65 with EN NHL actually had a greater improvement than younger patients, with increases of 6.0 and 8.5 percentage points, respectively for patients over and under 65. The single greatest improvement observed was in patients less than 65 with CML, who had a 25.2 percentage point improvement in 10-year relative survival between 2000 and 2004. Conclusions: Application of modeled period analysis to an examination of hematologic malignancies revealed profound improvements in survival in the 5 years between 2000 and 2004. Survival in CML has improved dramatically, and major improvements were also seen for survival in NHL, AML, and MM. A combination of new therapeutic options, improved supportive care, and wider application of recent advances is likely to be responsible for the improvements observed. Our results emphasize the importance of timely information about translation of therapeutic advances into clinical practice, such as can be provided by modeled period analysis. 1. Brenner H, Hakulinen T. Up-to-date and precise estimates of cancer patient survival: model-based period analysis. Am J Epidemiol.2006;164:689–696. 10-year survival in hematologic malignanices in 2000 and 2004 Malignancy Number 10-year survival (SE)-2000 10-yr survival (SE)-2004 Difference P-value HD 9989 78.3 (1.2) 81.8 (1.1) +3.5 0.12 NHL-nodal 40,121 45.4 (0.9) 54.1 (0.9) +8.7 <0.0001 NHL-EN 19,447 60.1 (1.4) 67.9 (1.3) +7.8 0.00015 MM 17,330 14.3 (0.9) 17.7 (1.0) +3.4 0.01 ALL 2222 26.5 (2.8) 33.2 (2.9) +6.7 0.14 CLL 12,881 54.2 (2.0) 56.6 (2.0) +2.4 0.45 AML 10,153 15.0 (1.0) 19.3 (1.2) +4.3 0.0085 CML 5308 22.4 (2.0) 38.6 (2.4) +16.2 <0.0001

The Bootstrap Discovery Behaviour Model

2012 ◽  
pp. 258-279 ◽  
Author(s):  
Simone Borsci ◽  
Stefano Federici ◽  
Maria Laura Mele ◽  
Domenico Polimeno ◽  
Alessandro Londei
Keyword(s):  
Detection Rate ◽  
Evaluation Process ◽  
Statistical Technique ◽  
Investment Model ◽  
P Value ◽  
Experimental Sample ◽  
Estimation Model ◽  
Estimation Problems ◽  
First Time ◽  
Test User

The chapter focuses on the Bootstrap statistical technique for assigning measures of accuracy to sample estimates, here adopted for the first time to obtain an effective and efficient interaction evaluation. After introducing and discussing the classic debate on p value (i.e., the discovery detection rate) about estimation problems, the authors present the most used model for the estimation of the number of participants needed for an evaluation test, namely the Return On Investment model (ROI). Since the ROI model endorses a monodimensional and economical perspective in which an evaluation process, composed of only an expert technique, is sufficient to identify all the interaction problems—without distinguishing real problems (i.e., identified both experts and users) and false problems (i.e., identified only by experts)—they propose the new Bootstrap Discovery Behaviour (BDB) estimation model. Findings highlight the BDB as a functional technique favouring practitioners to optimize the number of participants needed for an interaction evaluation. Finally, three experiments show the application of the BDB model to create experimental sample sizes to test user experience of people with and without disabilities.

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