Difference between revisions of "Journal:Timely delivery of laboratory efficiency information, Part II: Assessing the impact of a turnaround time dashboard at a high-volume laboratory"
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==Introduction== | ==Introduction== | ||
[[wikipedia:Turnaround time|Turnaround time]] (TAT) is an important performance indicator of a [[laboratory]]'s efficiency in delivering patient results.<ref name="HawkinsLab07">{{cite journal |title=Laboratory turnaround time |journal=The Clinical Biochemist |author=Hawkins, R.C. |volume=28 |issue=4 |pages=179–94 |year=2007 |pmid=18392122 |pmc=PMC2282400}}</ref> In the South African National Health Laboratory Services, ''ad hoc'' mean TAT reports were previously produced for laboratory managers. These TAT reports assessed performance based on the National Health Laboratory Service global annual performance plan (APP) TAT cutoffs specific to individual tests.<ref name="NHLSAnn1819">{{cite book |url=https://nationalgovernment.co.za/entity_annual/1714/2018-national-health-laboratory-service-(nhls)-annual-report.pdf |format=PDF |title=National Health Laboratory Service Annual Report 2017/18 |author=National Health Laboratory Service |publisher=National Health Laboratory Service |year=2018 |isbn=9780621457018}}</ref> Reports were provided intermittently in a static form that assessed central tendency only (i.e., the tail size was not reported) and did not allow for drilling down to access additional, more detailed [[information]] to direct meaningful corrective action (i.e., laboratory or sample-level TAT breakdown). To improve on these TAT reporting systems, Coetzee ''et al.'' used three additional measures to assess TAT efficiency: (1) median TAT, (2) 75th percentile TAT (tail size), and (3) percentage of within cutoff TAT.<ref name="CoetzeeTheImport18">{{cite journal |title=The importance of reporting individual weekly laboratory turn-around-time (TAT) to identify outliers and underperformance masked during global annual TAT review |journal=Proceedings of the African Society for Laboratory Medicine Conference 2018 |author=Coetzee, L.M.; Cassim, N.; Tepper, M.E.E. et al. |year=2018 |url=https://www.researchgate.net/publication/329610644}}</ref> These measures accurately assessed outliers as tail size and could be used by laboratories to address workflow issues and identify testing delays for intervention. "Tail size" refers to the volume of [[Sample (material)|samples]] in a positively skewed data distribution that has a long tail to the right. These samples often have a much higher TAT value than the central tendency (median) for this data distribution. Tail size can be measured as the percentage of samples that exceed a defined TAT cutoff in hours, or as a percentile. | [[wikipedia:Turnaround time|Turnaround time]] (TAT) is an important performance indicator of a [[laboratory]]'s efficiency in delivering patient results.<ref name="HawkinsLab07">{{cite journal |title=Laboratory turnaround time |journal=The Clinical Biochemist |author=Hawkins, R.C. |volume=28 |issue=4 |pages=179–94 |year=2007 |pmid=18392122 |pmc=PMC2282400}}</ref> In the South African National Health Laboratory Services, ''ad hoc'' mean TAT reports were previously produced for laboratory managers. These TAT reports assessed performance based on the National Health Laboratory Service global annual performance plan (APP) TAT cutoffs specific to individual tests.<ref name="NHLSAnn1819">{{cite book |url=https://nationalgovernment.co.za/entity_annual/1714/2018-national-health-laboratory-service-(nhls)-annual-report.pdf |format=PDF |title=National Health Laboratory Service Annual Report 2017/18 |author=National Health Laboratory Service |publisher=National Health Laboratory Service |year=2018 |isbn=9780621457018}}</ref> Reports were provided intermittently in a static form that assessed central tendency only (i.e., the tail size was not reported) and did not allow for drilling down to access additional, more detailed [[information]] to direct meaningful corrective action (i.e., laboratory or sample-level TAT breakdown). To improve on these TAT reporting systems, Coetzee ''et al.'' used three additional measures to assess TAT efficiency: (1) median TAT, (2) 75th percentile TAT (tail size), and (3) percentage of within cutoff TAT.<ref name="CoetzeeTheImport18">{{cite journal |title=The importance of reporting individual weekly laboratory turn-around-time (TAT) to identify outliers and underperformance masked during global annual TAT review |journal=Proceedings of the African Society for Laboratory Medicine Conference 2018 |author=Coetzee, L.M.; Cassim, N.; Tepper, M.E.E. et al. |year=2018 |url=https://www.researchgate.net/publication/329610644 |quote=Poster ID: PS-2.3b-070}}</ref> These measures accurately assessed outliers as tail size and could be used by laboratories to address workflow issues and identify testing delays for intervention. "Tail size" refers to the volume of [[Sample (material)|samples]] in a positively skewed data distribution that has a long tail to the right. These samples often have a much higher TAT value than the central tendency (median) for this data distribution. Tail size can be measured as the percentage of samples that exceed a defined TAT cutoff in hours, or as a percentile. | ||
Initially, the three measures described above were reported in Microsoft Excel (Redmond, Washington, United States) worksheet format from August 2016 to June 2017.<ref name="Microsoft">{{cite web |url=https://www.microsoft.com/en-za/microsoft-365/products-apps-services |title=Apps and services |publisher=Microsoft |accessdate=12 March 2019}}</ref> Thereafter, from July 2017, an interactive dashboard was developed that reported TAT data for a basket of tests using the Microstrategy Desktop (Tysons, Virginia, United States) analytics tool.<ref name="MicroStratDesk">{{cite web |url=https://www.microstrategy.com/en/get-started/desktop |title=Download MicroStrategy Desktop |publisher=MicroStrategy |accessdate=03 December 2018}}</ref> The previous static reports and the more recent interactive dashboard reports have seen distribution to area (province), business (district), and laboratory managers. Data can now be reviewed in the interactive dashboard reports across the provincial, district or laboratory levels through drill-down functionality, which makes it possible to slice through a data hierarchy to reveal additional details<ref name="MicrosoftDrill">{{cite web |url=https://docs.microsoft.com/en-us/power-bi/consumer/end-user-drill |title=Drill mode in a visual in Power BI |author=Microsoft |accessdate=12 December 2018}}</ref> contained within the aggregated data. In this way, TAT data presented can be visualized at the national, provincial, and laboratory level on the same dashboard page. The approach allows various levels of manager to drill down from a "bird’s-eye" view of TAT performance nationally, down to the provincial or individual laboratory level. | |||
Within the dashboard, TAT can be viewed for a basket of tests, including: | |||
* routine [[hematology]] such as full blood count with platelet and differential testing, international normalized ratio, activated prothrombin testing, and D-dimers; | |||
* [[clinical pathology]] testing such as urea and electrolytes, liver function testing, glucose, and cholesterol; | |||
* microbiology testing such as HIV (HIV viral load, HIV DNA polymerase chain reaction), tuberculosis (Xpert MTB/RIF), and syphilis (rapid plasma reagin and ''Treponema pallidum'' antibodies); and | |||
* other disease testing methods such as cluster of differentiation 4 (CD4) testing. | |||
Proxy marker analytes are used to assess performance of the respective matched assay panel; for example, creatinine is used as the proxy test to review urea and electrolytes performance. Each test has its own predetermined TAT determined at the local level according to the level of care, with absolute national APP cutoffs noted. | |||
Global TAT outcomes for each test are reported according to specifically stipulated, organization-determined TAT APP at the national level and are described elsewhere.<ref name="NHLSAnn1819" /><ref name="CassimFac1_20">{{cite journal |title=Timely delivery of laboratory efficiency information, Part I: Developing an interactive turnaround time dashboard at a high-volume laboratory |journal=African Journal of Laboratory Medicine |author=Cassim, N.; Tepper, M.E.; Coetzee, L.M.; Glencross, D.K. |volume=9 |issue=2 |at=a947 |year=2020 |doi=10.4102/ajlm.v9i2.947 |pmid=32391244 |pmc=PMC7203318}}</ref> National APP cutoffs are set bearing in mind the multi-tiered service that accommodates reporting from primary health care referral to large tertiary centers that may offer emergency services, and do not necessarily reflect the respective individual, laboratory-stipulated TAT, which may be self-determined by laboratories based on their local clinical needs. | |||
Armed with the knowledge of TAT and which tests are identified as poor performers in the interactive dashboard, laboratory managers can identify and address areas of concern through review of the contributing causes.<ref name="KhanRoot14">{{cite journal |title=Root Cause Analysis (RCA) of Prolonged Laboratory Turnaround Time in a Tertiary Care Set Up |journal=Journal of Clinical and Diagnostic Research |author=Khan, K. |volume=8 |issue=4 |pages=FC05–FC08 |doi=10.7860/JCDR/2014/7269.4255 |pmid=24959450 |pmc=PMC4064846}}</ref> This is achieved through root cause analysis, a method of problem solving used to identify the root causes (faults or problems) and determine the most probable underlying causes of error.<ref name="KhanRoot14" /> The ultimate aim of root cause analysis in TAT monitoring is to formulate corrective actions that either mitigate or eliminate the identified causes in order to return TAT efficiency and performance to acceptable levels. | |||
The aim of this study was to report on the impact of an interactive dashboard that provides weekly information about TAT and enables laboratory and senior managers to monitor TAT, as well as identify problematic areas for corrective action. The hypothesis was that an interactive TAT dashboard delivering week-by-week information about laboratory TAT provides the impetus for continuous service review and implementation of appropriate corrective action, where required, to ensure the timeliness of laboratory reporting. Data are presented from a single busy, routinely automated clinical pathology laboratory at a large regional [[hospital]] to reveal how the described TAT dashboard served to continually highlight ongoing TAT delays for urea and electrolyte (creatinine) result reporting and, ultimately, facilitated sustained corrective action. | |||
==Methods== | |||
Revision as of 17:35, 24 January 2021
| Full article title | Timely delivery of laboratory efficiency information, Part II: Assessing the impact of a turnaround time dashboard at a high-volume laboratory |
|---|---|
| Journal | African Journal of Laboratory Medicine |
| Author(s) | Cassim, Naseem; Coetzee, Lindi M.; Tepper, Manfred E.; Perelson, Louella; Glencross, Deborah K. |
| Author affiliation(s) | National Health Laboratory Service, University of the Witwatersrand |
| Primary contact | Email: naseem dot cassim at wits dot ac dot za |
| Year published | 2020 |
| Volume and issue | 9(2) |
| Article # | a948 |
| DOI | 10.4102/ajlm.v9i2.948 |
| ISSN | 2225-2010 |
| Distribution license | Creative Commons Attribution 4.0 International License |
| Website | https://ajlmonline.org/index.php/ajlm/article/view/948/1475 |
| Download | https://ajlmonline.org/index.php/ajlm/article/download/948/1473 (PDF) |
 |
This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
Background: In South Africa’s National Health Laboratory Service, ad hoc mean turnaround time (TAT) reporting is an important indicator of performance. However, historic static TAT reporting did not assess very long or very short times. An interactive TAT dashboard was developed using the following TAT measures: (1) median, (2) 75th percentile, and (3) percentage of within cutoff TAT to allow for improved differentiation of TAT performance.
Objectives: The objective of our study was to demonstrate increased efficiency achieved by using an interactive TAT dashboard.
Methods: A retrospective descriptive study design was used. Creatinine TAT outcomes were reported over 122 weeks from a high-volume laboratory in Gauteng, South Africa. The percentage of within cutoff and 75th percentile TAT were analyzed and reported using Microsoft Excel. A focus group session was used to populate a cause and effect diagram.
Results: The percentage of within cutoff TAT increased from 10% in week four to 90% and higher from week 81. The 75th percentile decreased from 10 hours in week four to under five hours from week 71. Component TAT analysis revealed that the 75th percentile testing was five hours or longer for weeks four, five and 48. The 75th percentile review TAT ranged from one hour to 15 hours. From week 41, the review TAT was under one hour.
Conclusion: Our study demonstrated that the use of an interactive TAT dashboard, coupled with good management, can dramatically improve TAT and efficiency in a high-volume laboratory.
Keywords: turnaround time, laboratory efficiency, pathology, laboratory medicine
Introduction
Turnaround time (TAT) is an important performance indicator of a laboratory's efficiency in delivering patient results.[1] In the South African National Health Laboratory Services, ad hoc mean TAT reports were previously produced for laboratory managers. These TAT reports assessed performance based on the National Health Laboratory Service global annual performance plan (APP) TAT cutoffs specific to individual tests.[2] Reports were provided intermittently in a static form that assessed central tendency only (i.e., the tail size was not reported) and did not allow for drilling down to access additional, more detailed information to direct meaningful corrective action (i.e., laboratory or sample-level TAT breakdown). To improve on these TAT reporting systems, Coetzee et al. used three additional measures to assess TAT efficiency: (1) median TAT, (2) 75th percentile TAT (tail size), and (3) percentage of within cutoff TAT.[3] These measures accurately assessed outliers as tail size and could be used by laboratories to address workflow issues and identify testing delays for intervention. "Tail size" refers to the volume of samples in a positively skewed data distribution that has a long tail to the right. These samples often have a much higher TAT value than the central tendency (median) for this data distribution. Tail size can be measured as the percentage of samples that exceed a defined TAT cutoff in hours, or as a percentile.
Initially, the three measures described above were reported in Microsoft Excel (Redmond, Washington, United States) worksheet format from August 2016 to June 2017.[4] Thereafter, from July 2017, an interactive dashboard was developed that reported TAT data for a basket of tests using the Microstrategy Desktop (Tysons, Virginia, United States) analytics tool.[5] The previous static reports and the more recent interactive dashboard reports have seen distribution to area (province), business (district), and laboratory managers. Data can now be reviewed in the interactive dashboard reports across the provincial, district or laboratory levels through drill-down functionality, which makes it possible to slice through a data hierarchy to reveal additional details[6] contained within the aggregated data. In this way, TAT data presented can be visualized at the national, provincial, and laboratory level on the same dashboard page. The approach allows various levels of manager to drill down from a "bird’s-eye" view of TAT performance nationally, down to the provincial or individual laboratory level.
Within the dashboard, TAT can be viewed for a basket of tests, including:
- routine hematology such as full blood count with platelet and differential testing, international normalized ratio, activated prothrombin testing, and D-dimers;
- clinical pathology testing such as urea and electrolytes, liver function testing, glucose, and cholesterol;
- microbiology testing such as HIV (HIV viral load, HIV DNA polymerase chain reaction), tuberculosis (Xpert MTB/RIF), and syphilis (rapid plasma reagin and Treponema pallidum antibodies); and
- other disease testing methods such as cluster of differentiation 4 (CD4) testing.
Proxy marker analytes are used to assess performance of the respective matched assay panel; for example, creatinine is used as the proxy test to review urea and electrolytes performance. Each test has its own predetermined TAT determined at the local level according to the level of care, with absolute national APP cutoffs noted.
Global TAT outcomes for each test are reported according to specifically stipulated, organization-determined TAT APP at the national level and are described elsewhere.[2][7] National APP cutoffs are set bearing in mind the multi-tiered service that accommodates reporting from primary health care referral to large tertiary centers that may offer emergency services, and do not necessarily reflect the respective individual, laboratory-stipulated TAT, which may be self-determined by laboratories based on their local clinical needs.
Armed with the knowledge of TAT and which tests are identified as poor performers in the interactive dashboard, laboratory managers can identify and address areas of concern through review of the contributing causes.[8] This is achieved through root cause analysis, a method of problem solving used to identify the root causes (faults or problems) and determine the most probable underlying causes of error.[8] The ultimate aim of root cause analysis in TAT monitoring is to formulate corrective actions that either mitigate or eliminate the identified causes in order to return TAT efficiency and performance to acceptable levels.
The aim of this study was to report on the impact of an interactive dashboard that provides weekly information about TAT and enables laboratory and senior managers to monitor TAT, as well as identify problematic areas for corrective action. The hypothesis was that an interactive TAT dashboard delivering week-by-week information about laboratory TAT provides the impetus for continuous service review and implementation of appropriate corrective action, where required, to ensure the timeliness of laboratory reporting. Data are presented from a single busy, routinely automated clinical pathology laboratory at a large regional hospital to reveal how the described TAT dashboard served to continually highlight ongoing TAT delays for urea and electrolyte (creatinine) result reporting and, ultimately, facilitated sustained corrective action.
Methods
References
- ↑ Hawkins, R.C. (2007). "Laboratory turnaround time". The Clinical Biochemist 28 (4): 179–94. PMC PMC2282400. PMID 18392122. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2282400.
- ↑ 2.0 2.1 National Health Laboratory Service (2018) (PDF). National Health Laboratory Service Annual Report 2017/18. National Health Laboratory Service. ISBN 9780621457018. https://nationalgovernment.co.za/entity_annual/1714/2018-national-health-laboratory-service-(nhls)-annual-report.pdf.
- ↑ Coetzee, L.M.; Cassim, N.; Tepper, M.E.E. et al. (2018). "The importance of reporting individual weekly laboratory turn-around-time (TAT) to identify outliers and underperformance masked during global annual TAT review". Proceedings of the African Society for Laboratory Medicine Conference 2018. https://www.researchgate.net/publication/329610644. "Poster ID: PS-2.3b-070"
- ↑ "Apps and services". Microsoft. https://www.microsoft.com/en-za/microsoft-365/products-apps-services. Retrieved 12 March 2019.
- ↑ "Download MicroStrategy Desktop". MicroStrategy. https://www.microstrategy.com/en/get-started/desktop. Retrieved 03 December 2018.
- ↑ Microsoft. "Drill mode in a visual in Power BI". https://docs.microsoft.com/en-us/power-bi/consumer/end-user-drill. Retrieved 12 December 2018.
- ↑ Cassim, N.; Tepper, M.E.; Coetzee, L.M.; Glencross, D.K. (2020). "Timely delivery of laboratory efficiency information, Part I: Developing an interactive turnaround time dashboard at a high-volume laboratory". African Journal of Laboratory Medicine 9 (2): a947. doi:10.4102/ajlm.v9i2.947. PMC PMC7203318. PMID 32391244. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7203318.
- ↑ 8.0 8.1 Khan, K.. "Root Cause Analysis (RCA) of Prolonged Laboratory Turnaround Time in a Tertiary Care Set Up". Journal of Clinical and Diagnostic Research 8 (4): FC05–FC08. doi:10.7860/JCDR/2014/7269.4255. PMC PMC4064846. PMID 24959450. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4064846.
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. Grammar was cleaned up for smoother reading. In some cases important information was missing from the references, and that information was added. The original citation number two (2017-2018 NHLS Annual Report) was dead; an alternately hosted version was found and used for this version.
