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 FIGURE 1:


 FIGURE 2:


by the laboratory using benchmarking and the best practices followed by peers. However, most laboratories have the tendency to do the reverse, i.e. start with performance benchmarking. Benchmarking can be used at pre-analytical, analytical as well as


 FIGURE 3:  FIGURE 4:


post-analytical phases.  Pre-analytical benchmarking - The improvisations can be made by minimizing time lapse between sample receipt and sample reaching the work station through automation, minimizing manual errors while entering data of the patient or even minimizing chance of sample loss or mixing. Although automation of pre-analytical phase is an optimal answer, one must not overlook the cardinal rule of benchmarking - ‘Do not throw money at bad processes’.  Analytical benchmarking - This could help in achieving improved cost per test, TAT, efficiency, reduction in wastage and manual errors. Automation can enable faster TAT while bidirectional interfacing of instruments reduces errors significantly by avoiding manual intervention.  Post-analytical benchmarking - The major improvisations in this phase are possible by the intervention of information technology. Computerization of this phase leads to reducing time between release of report and receipt of the same by the client/patient/clinician. Further, computerization helps in transmitting figures and graphs as part of the report which are usually send by most labs as hard copies. Apart from improvising quality, TAT etc, benchmarking can also be used to measure productivity of technical staff and also determine factors associated with favorable staffing ratios. Staff accounts for 50- 70% of direct clinical laboratory costs. Hence management of staffing levels is central to managing overall lab expenses. Inadequate staffing would compromise quality and throughput while excess staffing would unnecessarily increase the cost of testing. According to a CAP Q-PROBES study of staffing at 151 institutions, a wide variation in staffing level among institutions despite standardization of testing methods in the laboratories was observed. Benchmarking, both internal and competitive, at Clinical reference


 FIGURE 5:


Laboratory, Super Religare Laboratories, Gurgaon, India has been used at all phases mentioned above to significantly reduce the TAT and wastage; improve cost effectiveness, productivity, tests to staff ratio. At pre-analytical level, installation of pneumatic chute (see figure 2) has led to a drastic decrease in time lapse between sample receipt and sample reaching the work-bench. It has also minimized errors due to manual transportation of samples (like reaching wrong department, samples lost in transit etc). Benchmarking at analytical level has been brought about by automation and bidirectional interfacing to minimize errors and reduce TAT and optimizing batch size (see figure 3) for cost-effectiveness. The test to staff ratio has been improved, especially by managing manpower in different shifts according to the workload, e.g. lesser manpower at night (see figure 4) and multi-tasking. Marked improvements have also been possible in post-analytical phase with intervention of information technology by reducing the time lapse between review of report by pathologist and report reaching the patient, especially in tests where graphs/figures need to be incorporated in reports. Currently, these graphs and reports are sent as images (e.g. in maternal serum screening, Hb variant analysis etc.) through the integrated software and not through couriers which are time-taking (see figure 5). Systematic and disciplined benchmarking has not only improved customer satisfaction and employee morale but also raised the performance to a level that makes it an unusually productive organization - a point of pride for its staff and the entire laboratory. To conclude, benchmarking shows how a representative sample of


their laboratory competition performs. Benchmarking tools, along with peer-group networking, enable labs to set reasonable goals and action plans and to achieve their goals with a degree of predictability.


018 MEDLAB MAGAZINE ISSUE 1 2012 MAGAZINE


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