BIG DATA ANALYTICS & PATHOLOGY SERVICES IN NHS: ACHIEVING STEP CHANGES IN CAPACITY
(Abstract release date: 05/19/16)
EHA Library. Littlewood R. 06/09/16; 133004; E1455
Dr. Richard Littlewood
Contributions
Contributions
Abstract
Abstract: E1455
Type: Eposter Presentation
Background
A major hospital Trust in London provides healthcare for a large population across Medicine, Surgery, Obstetrics and other specialties. Three laboratories are on sites using automated, high capacity analysers to provide pathology services much of which requires rapid turnaround. The major challenge for laboratories in this situation is centred on the high throughput tests comprising full blood count, assessment of renal/ liver function, and coagulation. To date these services have not been subjected to detailed analysis of demand, efficiency of use of analyser capacity and efficiency of physician requesting.
Aims
First to determine the factors limiting the turnaround times for routine testing throughout periods of varying demand and those factors limiting the optimum use of existing analyser resources. Second, to identify requesting practices that are inefficient or which drive the changes in demand.
Methods
A database consisting 20M data points from 1M pathology test requests, recorded over 1 year was provided including details of requester and site of request with way points defining the passage of the sample from request time through to test reporting. This allowed a map of volume and activity over time and test turnaround times identifying bottlenecks and changes in efficiency. Parameters showing healthcare professional ordering of tests, location of patient and laboratory site were also provided and analysed.
Results
Initial descriptive analysis showed 1 particular laboratory had difficulties achieving its potential capacity utilization rate and target turnaround times. Bottlenecks were clearly identified at sample entry into the laboratory and at validation of results. These resulted in build-up of samples and delays in reporting that were staggered in time: thus although the peak in TAT occurs at 4pm the extra capacity was required prior to this, revealing a negative, delayed impact of test arrival on test turnaround time. This has obvious implications for laboratory management. The fastest 10% of FBC tests were reported in 0.2hr and 80% in 1.5 hrs but the slowest 10% varied from 2-120 hours.Of 200,000 tests processed per year at one lab, 47% were ordered by clinical division Medicine, 34% Surgery & Cancer / Clinical Haematology, 15% Women and Children. Medicine was the leading requester at all 3 sites. Of 2,000 physicians, 87% order fewer than 500 tests per year. Some intensive requesting practices are probably masked by the use of common requesting codes. 61% of patients have only 1 to 2 tests per year, the proportion of patients having 100 tests per year being less than 1%. However at one site >1% of patients had >50 tests per year, identifying an intensively monitored population. Measurement of true machine capacity highlighted a large gap between current performance and maximum potential indicating that better sample profiling and management could produce savings. The maximum capacity for FBC was 420 tests per hour but the average performance was 60/hr and the peak rate of reporting only 95/hr.
Conclusion
Big data analytics and process mapping identified 2 rate-limiting steps to performance inherent in current test system: test received at lab and validation of results. Close analysis of such a large dataset indicates how we can optimise the laboratory processes and improve utilisation of current installed capacity in NHS pathology services.
Session topic: E-poster
Type: Eposter Presentation
Background
A major hospital Trust in London provides healthcare for a large population across Medicine, Surgery, Obstetrics and other specialties. Three laboratories are on sites using automated, high capacity analysers to provide pathology services much of which requires rapid turnaround. The major challenge for laboratories in this situation is centred on the high throughput tests comprising full blood count, assessment of renal/ liver function, and coagulation. To date these services have not been subjected to detailed analysis of demand, efficiency of use of analyser capacity and efficiency of physician requesting.
Aims
First to determine the factors limiting the turnaround times for routine testing throughout periods of varying demand and those factors limiting the optimum use of existing analyser resources. Second, to identify requesting practices that are inefficient or which drive the changes in demand.
Methods
A database consisting 20M data points from 1M pathology test requests, recorded over 1 year was provided including details of requester and site of request with way points defining the passage of the sample from request time through to test reporting. This allowed a map of volume and activity over time and test turnaround times identifying bottlenecks and changes in efficiency. Parameters showing healthcare professional ordering of tests, location of patient and laboratory site were also provided and analysed.
Results
Initial descriptive analysis showed 1 particular laboratory had difficulties achieving its potential capacity utilization rate and target turnaround times. Bottlenecks were clearly identified at sample entry into the laboratory and at validation of results. These resulted in build-up of samples and delays in reporting that were staggered in time: thus although the peak in TAT occurs at 4pm the extra capacity was required prior to this, revealing a negative, delayed impact of test arrival on test turnaround time. This has obvious implications for laboratory management. The fastest 10% of FBC tests were reported in 0.2hr and 80% in 1.5 hrs but the slowest 10% varied from 2-120 hours.Of 200,000 tests processed per year at one lab, 47% were ordered by clinical division Medicine, 34% Surgery & Cancer / Clinical Haematology, 15% Women and Children. Medicine was the leading requester at all 3 sites. Of 2,000 physicians, 87% order fewer than 500 tests per year. Some intensive requesting practices are probably masked by the use of common requesting codes. 61% of patients have only 1 to 2 tests per year, the proportion of patients having 100 tests per year being less than 1%. However at one site >1% of patients had >50 tests per year, identifying an intensively monitored population. Measurement of true machine capacity highlighted a large gap between current performance and maximum potential indicating that better sample profiling and management could produce savings. The maximum capacity for FBC was 420 tests per hour but the average performance was 60/hr and the peak rate of reporting only 95/hr.
Conclusion
Big data analytics and process mapping identified 2 rate-limiting steps to performance inherent in current test system: test received at lab and validation of results. Close analysis of such a large dataset indicates how we can optimise the laboratory processes and improve utilisation of current installed capacity in NHS pathology services.
Session topic: E-poster
Abstract: E1455
Type: Eposter Presentation
Background
A major hospital Trust in London provides healthcare for a large population across Medicine, Surgery, Obstetrics and other specialties. Three laboratories are on sites using automated, high capacity analysers to provide pathology services much of which requires rapid turnaround. The major challenge for laboratories in this situation is centred on the high throughput tests comprising full blood count, assessment of renal/ liver function, and coagulation. To date these services have not been subjected to detailed analysis of demand, efficiency of use of analyser capacity and efficiency of physician requesting.
Aims
First to determine the factors limiting the turnaround times for routine testing throughout periods of varying demand and those factors limiting the optimum use of existing analyser resources. Second, to identify requesting practices that are inefficient or which drive the changes in demand.
Methods
A database consisting 20M data points from 1M pathology test requests, recorded over 1 year was provided including details of requester and site of request with way points defining the passage of the sample from request time through to test reporting. This allowed a map of volume and activity over time and test turnaround times identifying bottlenecks and changes in efficiency. Parameters showing healthcare professional ordering of tests, location of patient and laboratory site were also provided and analysed.
Results
Initial descriptive analysis showed 1 particular laboratory had difficulties achieving its potential capacity utilization rate and target turnaround times. Bottlenecks were clearly identified at sample entry into the laboratory and at validation of results. These resulted in build-up of samples and delays in reporting that were staggered in time: thus although the peak in TAT occurs at 4pm the extra capacity was required prior to this, revealing a negative, delayed impact of test arrival on test turnaround time. This has obvious implications for laboratory management. The fastest 10% of FBC tests were reported in 0.2hr and 80% in 1.5 hrs but the slowest 10% varied from 2-120 hours.Of 200,000 tests processed per year at one lab, 47% were ordered by clinical division Medicine, 34% Surgery & Cancer / Clinical Haematology, 15% Women and Children. Medicine was the leading requester at all 3 sites. Of 2,000 physicians, 87% order fewer than 500 tests per year. Some intensive requesting practices are probably masked by the use of common requesting codes. 61% of patients have only 1 to 2 tests per year, the proportion of patients having 100 tests per year being less than 1%. However at one site >1% of patients had >50 tests per year, identifying an intensively monitored population. Measurement of true machine capacity highlighted a large gap between current performance and maximum potential indicating that better sample profiling and management could produce savings. The maximum capacity for FBC was 420 tests per hour but the average performance was 60/hr and the peak rate of reporting only 95/hr.
Conclusion
Big data analytics and process mapping identified 2 rate-limiting steps to performance inherent in current test system: test received at lab and validation of results. Close analysis of such a large dataset indicates how we can optimise the laboratory processes and improve utilisation of current installed capacity in NHS pathology services.
Session topic: E-poster
Type: Eposter Presentation
Background
A major hospital Trust in London provides healthcare for a large population across Medicine, Surgery, Obstetrics and other specialties. Three laboratories are on sites using automated, high capacity analysers to provide pathology services much of which requires rapid turnaround. The major challenge for laboratories in this situation is centred on the high throughput tests comprising full blood count, assessment of renal/ liver function, and coagulation. To date these services have not been subjected to detailed analysis of demand, efficiency of use of analyser capacity and efficiency of physician requesting.
Aims
First to determine the factors limiting the turnaround times for routine testing throughout periods of varying demand and those factors limiting the optimum use of existing analyser resources. Second, to identify requesting practices that are inefficient or which drive the changes in demand.
Methods
A database consisting 20M data points from 1M pathology test requests, recorded over 1 year was provided including details of requester and site of request with way points defining the passage of the sample from request time through to test reporting. This allowed a map of volume and activity over time and test turnaround times identifying bottlenecks and changes in efficiency. Parameters showing healthcare professional ordering of tests, location of patient and laboratory site were also provided and analysed.
Results
Initial descriptive analysis showed 1 particular laboratory had difficulties achieving its potential capacity utilization rate and target turnaround times. Bottlenecks were clearly identified at sample entry into the laboratory and at validation of results. These resulted in build-up of samples and delays in reporting that were staggered in time: thus although the peak in TAT occurs at 4pm the extra capacity was required prior to this, revealing a negative, delayed impact of test arrival on test turnaround time. This has obvious implications for laboratory management. The fastest 10% of FBC tests were reported in 0.2hr and 80% in 1.5 hrs but the slowest 10% varied from 2-120 hours.Of 200,000 tests processed per year at one lab, 47% were ordered by clinical division Medicine, 34% Surgery & Cancer / Clinical Haematology, 15% Women and Children. Medicine was the leading requester at all 3 sites. Of 2,000 physicians, 87% order fewer than 500 tests per year. Some intensive requesting practices are probably masked by the use of common requesting codes. 61% of patients have only 1 to 2 tests per year, the proportion of patients having 100 tests per year being less than 1%. However at one site >1% of patients had >50 tests per year, identifying an intensively monitored population. Measurement of true machine capacity highlighted a large gap between current performance and maximum potential indicating that better sample profiling and management could produce savings. The maximum capacity for FBC was 420 tests per hour but the average performance was 60/hr and the peak rate of reporting only 95/hr.
Conclusion
Big data analytics and process mapping identified 2 rate-limiting steps to performance inherent in current test system: test received at lab and validation of results. Close analysis of such a large dataset indicates how we can optimise the laboratory processes and improve utilisation of current installed capacity in NHS pathology services.
Session topic: E-poster
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