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El Assil A, Benkirane S, El Kettani Y, Cherif Chefchaouni A, Mamad H, Rahali Y, Masrar A. Turnaround Time of the Hematology Results of Cancer Patients During the COVID-19 Pandemic: An Opportunity to Initiate a Quality Improvement Process. Cureus 2024; 16:e61149. [PMID: 38933641 PMCID: PMC11200148 DOI: 10.7759/cureus.61149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/26/2024] [Indexed: 06/28/2024] Open
Abstract
INTRODUCTION Turnaround time (TAT) is a crucial clinical parameter that reflects the performance of a laboratory especially in the context of oncology and the COVID-19 pandemic. Based on the Lean Six Sigma methodology, we performed a retrospective analysis of the TAT of the complete blood count (CBC) of cancer patients with the aim of reducing this delay in the future. MATERIALS AND METHODS Over one month of the COVID-19 pandemic, a retrospective evaluative audit was carried out on the TAT of the CBC in an oncology department. The root causes of failures of the overall analysis process were detected. The initiation of an improvement approach was implemented through the creation of an improvement flowchart and a new request form. The hospital information system (HIS) data were exported to Microsoft Excel® (Microsoft Corporation, Redmond, Washington, United States). Using the collected data, the mean, standard deviation, median, and interquartile range were calculated using IBM SPSS Statistics for Windows, Version 23, (Released 2015; IBM Corp., Armonk, New York, United States). All time intervals were expressed in minutes. RESULTS Among 263 intra-laboratory TATs analyzed, the median intra-lab TAT was 56 minutes (interquartile range (IQR): 36-80 minutes). A total of 82% of the analyses were performed in less than 90 minutes with a predominance of the interval 30-59 at 42.9%. The main causes of failures were essentially the lack of time stamping of the samples as well as the lack of real-time communication between the biologists and the clinicians. The proposed improvement model is currently being approved by all practitioners whose main items are as follows: At the clinical department level, distinguish the request forms but also the labels of the samples of the oncology hospital by a particular color, indication of clinical signs and sampling time on the request forms and on the HIS. At the laboratory level, create a specific chain for oncology department samples, alarm notification on the HIS, and rapid telecommunication of results for vital situations. CONCLUSION The intra-lab TAT of our study is biologically acceptable. Because our work is limited by the phases outside the control of the laboratory, it should lead to a continuous improvement project.
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Affiliation(s)
- Asmae El Assil
- Central Laboratory Hematology, Ibn Sina University Hospital Center, Rabat, MAR
- Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, MAR
| | - Souad Benkirane
- Central Laboratory Hematology, Ibn Sina University Hospital Center, Rabat, MAR
- Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, MAR
| | - Yasmine El Kettani
- National Institute of Oncology, Ibn Sina University Hospital Center, Rabat, MAR
- Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, MAR
| | - Ali Cherif Chefchaouni
- National Institute of Oncology, Ibn Sina University Hospital Center, Rabat, MAR
- Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, MAR
| | - Hassane Mamad
- Central Laboratory Hematology, Ibn Sina University Hospital Center, Rabat, MAR
- Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, MAR
| | - Younes Rahali
- National Institute of Oncology, Ibn Sina University Hospital Center, Rabat, MAR
- Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, MAR
| | - Azlarab Masrar
- Central Laboratory Hematology, Ibn Sina University Hospital Center, Rabat, MAR
- Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, MAR
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Srinivasaragavan D, Ramalingam K, Ramani P. Root Cause Analysis: Unraveling Common Laboratory Challenges. Cureus 2024; 16:e53393. [PMID: 38435196 PMCID: PMC10908306 DOI: 10.7759/cureus.53393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/01/2024] [Indexed: 03/05/2024] Open
Abstract
Diverse errors occur in a pathology laboratory and manual mistakes are the most common. There are various advancements to replace manual procedures with digitized automation techniques. Guidelines and protocols are available to run a standard pathology laboratory. But, even with such attempts to reinforce and strengthen the protocols, the complete elimination of errors is yet not possible. Root cause analysis (RCA) is the best way forward to develop an error-free laboratory, In this review, the importance of RCA, common errors taking place in laboratories, methods to carry out RCA, and its effectiveness are discussed in detail. The review also highlights the potential of RCA to provide long-term quality improvement and efficient laboratory management.
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Affiliation(s)
- Dharini Srinivasaragavan
- Oral Pathology and Microbiology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
| | - Karthikeyan Ramalingam
- Oral Pathology and Microbiology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
| | - Pratibha Ramani
- Oral Pathology and Microbiology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
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Dawande PP, Wankhade RS, Akhtar FI, Noman O. Turnaround Time: An Efficacy Measure for Medical Laboratories. Cureus 2022; 14:e28824. [PMID: 36225468 PMCID: PMC9535613 DOI: 10.7759/cureus.28824] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 08/28/2022] [Indexed: 11/23/2022] Open
Abstract
Turnaround time (TAT), which doctors frequently use as the benchmark for laboratory performance, is a typical way to communicate timeliness. It also acts as a quality indicator to evaluate the effectiveness and efficiency of the testing process and the satisfaction of clinicians and patients. TAT is the time from receipt of the sample in the laboratory to final delivery or dispatch of the report of said test. The TAT procedure can be broadly divided into three stages pre-analytical, analytical and post-analytical. There is variability in TAT according to different conditions like the volume of sample size, staff expertise, availability of adequate resources, distances of the hospital from the lab, and various sub-departments. To remove obstacles to optimizing TAT, we must take a practical approach. A workload reduction plan, proper stock management, specialized work assignments, and skilled staff retention are crucial strategies to reduce the setting's delayed TAT.
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Mutema L, Chapanduka Z, Musaigwa F, Mashigo N. In-depth investigation of turn-around time of full blood count tests requested from a clinical haematology outpatient department in Cape Town, South Africa. Afr J Lab Med 2021; 10:1318. [PMID: 34007817 PMCID: PMC8111617 DOI: 10.4102/ajlm.v10i1.1318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Accepted: 01/06/2021] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND The performance of laboratories can be objectively assessed using the overall turn-around time (TAT). However, TAT is defined differently by the laboratory and clinicians; therefore, it is important to determine the contribution of all the different components making up the laboratory test cycle. OBJECTIVE We carried out a retrospective analysis of the TAT of full blood count tests requested from the haematology outpatient department at Tygerberg Academic Hospital in Cape Town, South Africa, with an aim to assess laboratory performance and to identify critical steps influencing TAT. METHODS A retrospective audit was carried out, focused on the full blood count tests from the haematology outpatient department within a period of 3 months between 01 February and 30 April 2018. Data was extracted from the National Health Laboratory Service laboratory information system. The time intervals of all the phases of the test cycle were determined and total TAT and within-laboratory (intra-lab) TAT were calculated. RESULTS A total of 1176 tests were analysed. The total TAT median was 275 (interquartile range [IQR] 200.0-1537.7) min with the most prolonged phase being from authorisation to review by clinicians (median 114 min; IQR: 37.0-1338.5 min). The median intra-lab TAT was 55 (IQR 40-81) min and 90% of the samples were processed in the laboratory within 134 min of registration. CONCLUSION Our findings showed that the intra-lab TAT was within the set internal benchmark of 3 h. Operational phases that were independent of the laboratory processes contributed the most to total TAT.
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Affiliation(s)
- Leonard Mutema
- Department of Haematological Pathology, Tygerberg Hospital, National Health Laboratory Service and Stellenbosch University, Cape Town, South Africa
- Department of Internal Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Zivanai Chapanduka
- Department of Haematological Pathology, Tygerberg Hospital, National Health Laboratory Service and Stellenbosch University, Cape Town, South Africa
| | - Fungai Musaigwa
- Department of Haematological Pathology, Tygerberg Hospital, National Health Laboratory Service and Stellenbosch University, Cape Town, South Africa
| | - Nomusa Mashigo
- Department of Haematological Pathology, Tygerberg Hospital, National Health Laboratory Service and Stellenbosch University, Cape Town, South Africa
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IMPROVEMENT OF THE PATIENT CARE PROCESS BASED ON THE PRINCIPLES OF CLINICAL AUDIT. WORLD OF MEDICINE AND BIOLOGY 2020. [DOI: 10.26724/2079-8334-2020-2-72-27-31] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Shiferaw MB, Yismaw G. Magnitude of delayed turnaround time of laboratory results in Amhara Public Health Institute, Bahir Dar, Ethiopia. BMC Health Serv Res 2019; 19:240. [PMID: 31014324 PMCID: PMC6480504 DOI: 10.1186/s12913-019-4077-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 04/08/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Clinical decisions depend on timely laboratory result reporting. The timeliness is commonly expressed in turnaround time and serves as a quality improvement tool to assess the effectiveness and efficiency of the laboratory. According to the International Organization for Standardization (ISO) guidelines, each laboratory shall establish turnaround times for each of its examinations that reflect clinical needs, and shall periodically evaluate whether or not it is meeting the established turnaround times. Therefore, this study aimed to assess the TAT of laboratory results done in the reference laboratories of the Amhara Public Health Institute, Bahir Dar, Ethiopia. METHODS A retrospective cross sectional study was carried out from 01 January to 31 September 2018. Each patient sample was considered as a study unit. Nine months data were extracted from the sample tracking log and from the Laboratory Information System (LIS) database. Descriptive and summary statistics were calculated using SPSS version 20.0 statistical software. RESULTS A total of 34,233 patients samples were tested during the study period. Monthly average TAT ranged from 38.6 to 51.3 days for tuberculosis (TB) culture, 5.3 to 42.4 days for exposed infant diagnosis (EID) for HIV, 8.4 to 26 days for HIV 1 viral load, and 1.9 to 3.5 days for TB genexpert tests. Compared with the standard, 76.5% of the viral load, 68.1% of the EID for HIV and 53.8% of the TB genexpert tests had delayed TAT. Repeated reagent stock out, high workload, activities overlapping, and staff turnover were major reasons for the result delays. CONCLUSIONS There was a delayed turnaround time of laboratory results in APHI. HIV viral load, EID and TB genexpert results were the most affected tests. Workload reduction plan, proper stock management, specific work assignment and trained staff retention are important approaches to minimize the delayed TAT in the setting.
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Affiliation(s)
| | - Gizachew Yismaw
- Amhara Public Health Institute, P.O.Box 447, Bahir Dar, Amhara Ethiopia
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Bhatt RD, Shrestha C, Risal P. Factors Affecting Turnaround Time in the Clinical Laboratory of the Kathmandu University Hospital, Nepal. EJIFCC 2019; 30:14-24. [PMID: 30881271 PMCID: PMC6416806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
BACKGROUND The turnaround time (TAT) as defined by most of the laboratories is the time interval between the specimens received in the laboratory to the time of reports dispatched with verification. Nearly 80% of hospital-attached clinical laboratories receive complaints about delayed TAT. Reporting in time is a crucial indicator of quality services along with accurate, precise and reliable reports, thus each clinical laboratory should identify affecting factors to eliminate them for the enhancement of quality services. METHODOLOGY Dhulikhel Hospital-Kathmandu University Hospital is a tertiary care hospital, where this observational descriptive study was conducted in 2017. Requested tests received on database in the Department of Clinical Biochemistry Laboratory along with test requisition form (TRF) were carefully screened for any possible error. When analysis of individual patient's tests was completed, results of individual parameters were entered in the database manually. TAT was calculated as a time period between specimens received to analysis completed. Once test analysis has completed it was immediately followed by verification. RESULTS A total of 36,108 patients' reports generated from the Department of Clinical Biochemistry Laboratory during study period were analyzed. Nearly 36% of reports exceeded the predefined TAT in case of stat tests, while around 7% of reports were out of predefined TAT in case of routine tests. Among prolonged TAT, around 75% of reports were delayed due to various extra analytical reasons and approximately 48% of total delayed reports were found only due to error by cash unit. CONCLUSION The major reasons of delayed laboratory reports were due to time consumed to fix the pre-analytical errors created by other departments rather than laboratory itself. Cash unit alone has the highest degree of error in total testing process and it is the most significant factor for prolonged TAT. However reasons for prolonged TAT may vary with hospital to hospital depending upon different factors.
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Affiliation(s)
- Rajendra Dev Bhatt
- Department of Clinical Biochemistry Laboratory, Dhulikhel Hospital, Nepal,Corresponding author: Rajendra Dev Bhatt Department of Clinical Biochemistry Dhulikhel Hospital Kathmandu University Hospital Dhulikhel Nepal E-mail:
| | | | - Prabodh Risal
- Department of Biochemistry, School of Medical Sciences, Kathmandu University, Nepal
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Nybo M, Cadamuro J, Cornes MP, Gómez Rioja R, Grankvist K. Sample transportation – an overview. Diagnosis (Berl) 2018; 6:39-43. [DOI: 10.1515/dx-2018-0051] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Accepted: 11/22/2018] [Indexed: 01/25/2023]
Abstract
Abstract
Transportation of blood samples is a major part of the preanalytical pathway and can be crucial in delaying laboratory results to the clinicians. A variety of aspects however makes sample transportation a complex, challenging and often overlooked task that needs thorough planning and dedicated resources. The purpose of this review is to outline the options available for this task and to emphasize the preanalytical aspects that need consideration in this process, e.g. performance specifications for sample transportation as stated in ISO standards 15189 and 20658, quality control of automated transportation systems, monitoring of sample integrity parameters and temperature surveillance in general and for external samplers in particular. All these are tasks that the laboratory must assure on a daily basis in terms of continuous quality control, and simultaneously the laboratory must remain alert to alterations in clinical demands (sample frequency, turn-around-times) and new regulations within this area (e.g. the recent General Data Protection Regulation from the EU).
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Affiliation(s)
- Mads Nybo
- Department of Clinical Biochemistry and Pharmacology , Odense University Hospital , Sdr. Boulevard 29 , Odense 5000 , Denmark
| | - Janne Cadamuro
- Department of Laboratory Medicine , Paracelsus Medical University , Salzburg , Austria
| | - Michael P. Cornes
- Department of Clinical Chemistry , Worcestershire Acute Hospitals NHS Trust , Worcester , UK
| | | | - Kjell Grankvist
- Department of Medical Biosciences, Clinical Chemistry, Umeå University , Umeå , Sweden
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Chloride validity in Emergency Department settings. Am J Emerg Med 2018; 36:1501-1502. [DOI: 10.1016/j.ajem.2017.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Accepted: 12/01/2017] [Indexed: 11/17/2022] Open
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Coetzee LM, Cassim N, Glencross DK. Using laboratory data to categorise CD4 laboratory turn-around-time performance across a national programme. Afr J Lab Med 2018; 7:665. [PMID: 30167387 PMCID: PMC6111574 DOI: 10.4102/ajlm.v7i1.665] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2017] [Accepted: 12/19/2017] [Indexed: 11/17/2022] Open
Abstract
Background and objective The National Health Laboratory Service provides CD4 testing through an integrated tiered service delivery model with a target laboratory turn-around time (TAT) of 48 h. Mean TAT provides insight into national CD4 laboratory performance. However, it is not sensitive enough to identify inefficiencies of outlying laboratories or predict the percentage of samples meeting the TAT target. The aim of this study was to describe the use of the median, 75th percentile and percentage within target of laboratory TAT data to categorise laboratory performance. Methods Retrospective CD4 laboratory data for 2015–2016 fiscal year were extracted from the corporate data warehouse. The laboratory TAT distribution and percentage of samples within the 48 h target were assessed. A scatter plot was used to categorise laboratory performance into four quadrants using both the percentage within target and 75th percentile TAT. The laboratory performance was labelled good, satisfactory or poor. Results TAT data reported a positive skew with a mode of 13 h and a median of 17 h and 75th percentile of 25 h. Overall, 93.2% of CD4 samples had a laboratory TAT of less than 48 h. 48 out of 52 laboratories reported good TAT performance, i.e. percentage within target > 85% and 75th percentile ≤ 48 h, with two categorised as satisfactory (one parameter met), and two as poor performing laboratories (failed both parameters). Conclusion This study demonstrated the feasibility of utilising laboratory data to categorise laboratory performance. Using the quadrant approach for TAT data, laboratories that need interventions can be highlighted for root cause analysis assessment.
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Affiliation(s)
- Lindi-Marie Coetzee
- National Health Laboratory Service, National Priority Programme, Johannesburg, South Africa.,Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South Africa
| | - Naseem Cassim
- National Health Laboratory Service, National Priority Programme, Johannesburg, South Africa.,Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South Africa
| | - Deborah K Glencross
- National Health Laboratory Service, National Priority Programme, Johannesburg, South Africa.,Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South Africa
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