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Quality control in the new environment: automated hematology.

Quality control in the new environment: Automated hematology

The hematology laboratory has undergone a technological revolution over the last 20 years-- from tedious manual methods to relatively simple instrumentation to complex multiparameter instruments. Any discussion of cost savings in quality control must begin with the question of whether QC methods have kept pace with the technological changes.

In fact, many hematology quality control procedures are really holdovers from that earlier era when instruments were fundamentally less reliable than they are today. Modern microprocessor-driven instruments are rather precise and stable and almost certainly do not need the degree of precision control common 15 to 20 years ago when procedures were semiautomated or manual.

Therefore, many hematology laboratories could save money on QC while continuing to maintain quality standards. The way to do that, however, is not through a bottom-line approach that trims frequency of controls or cuts back on programs subscribed to in an attempt to reach some predetermined budget figure.

Instead, we need to take a systems approach to the problem. This means analyzing every procedure in terms of the instruments and methods currently in use. The analysis should include not only the obvious costs of QC (reagents, computer time and programs, and labor) but also the hidden costs of too many repetitive runs. We need to discover how much extra cost is generated by quality control protocols that are too restrictive or rigid.

Within the systems analysis framework, there are three specific programs we can institute that are highly cost-effective in hematology: the use of retained patient specimens, weighted moving averages of red cell indices, and clinical quality control. We will discuss these in some detail a little later in the article, along with quality control for some of the newer analyte additions to automated hematology. The systems approach requires us first to address the issues of selection, maintenance, and calibration of analytic systems.

Selecting and maintaining analytic systems. Selection of an analytic system is usually based on a number of factors, including costs of acquisition and operation (labor and consumables); throughput; ease of operation; training requirements; reliability in terms of downtime; accuracy, linearity, sensitivity, and precision data; and manufacturer support and reputation. Additional factors, harder to define, relate broadly to how the proposed instrumentation fits with the existing mix of space, personnel, and equipment.

We cannot ignore these intangibles. Indeed, an analytic system cannot be viewed simply as an instrument. It is an integral unit composed of instrument, reagents, personnel, and performance documentation. For this unit to function effectively, appropriate training and continuing education of system operators are essential, as are readily available and user-friendly operating instructions, maintenance schedules, troubleshooting protocols, and convenient documentation.

To take this reasoning a step further, selecting instrumentation on the basis of ease of process control and the ability to use available quality control material, techniques, and programs can itself be a prudent and cost-effective strategy.

Calibration. The International Committee for Standardization in Hematology has defined a calibrator as "a substance . . . used to calibrate, graduate, or adjust a measurement' that is "traceable to a national or international reference preparation or reference material.' Once an instrument is calibrated, it does not ordinarily have to be recalibrated until there is a major change in an instrument component or a significant drift in control measurements.

Calibration becomes an issue in hematology because of the absence of stable standard substances and the relative instability of most materials that are available. Although there are exceptions, QC materials do not in general meet the ICSH guidelines and thus should not be used for calibration.

Indeed, hematology calibration is mostly a patchwork affair. The cyanmethemoglobin method as described by the ICSH1 is the accepted reference standard for hemoglobin determination. Microhematocrit procedures, on the other hand, depend for precision on operational standardization with "selected' and "reference' methods.2,3 Calibration of hematocytometers can be done in two ways, neither very satisfactory. The choice is between tedious, poorly reproducible manual counting methods that identify cells and only cells and semiautomated counting instruments that may produce erroneous counts due to particles, bubbles, or other optical/electrical interference. Most labs opt for the latter, with appropriate precautions and corrections.

Automated instruments present their own set of calibration problems. Some authorities still recommend repetitive analysis of fresh whole blood specimens, but the disadvantages of this approach are legion: the amount of blood needed; the time it takes to run 10 to 20 determinations on multiple specimens; and the cost of space, personnel, and instrument maintenance resources devoted solely to calibration.

Many laboratoris find whole blood calibration impractical and have turned to commercial stabilized calibrators. The problem is that stabilized cells differ substantially from whole blood in the way they are processed and viewed by aperture impedance and optical light-scattering instruments and in their transferability from one instrument to another.4

Process control with commercial reagents. A number of control materials and alternative strategies should be considered in establishing cost-effective and reliable quality control protocols. Manufactured quality control material offers convenience and stability, but it is expensive, and efforts to extend stability have often compromised the degree to which the material resembles fresh whole blood. Nevertheless, most laboratories buy stabilized commercial QC material. Table I, based on College of American Pathologists Quality Assurance Service data, shows the mean coefficients of variation for one such product, compared with medically useful CVs.

It has been common practice to document control determinations on Levey-Jennings charts and to look for shifts and drifts. Today, many laboratories are implementing alternative statistical options, including cusum analysis and multirule analyses of the Shewhart type.

Interlab comparison and proficiency testing. A valuable quality control tool--and one we recommend --is interlaboratory comparison. These programs, whereby laboratories share a common pool of extended-stability control material and a common database, may be sponsored by a vendor, a local pathology society, the CAP's QAS committee, or a multiregional group of labs. Whatever the source, the purpose of the program is to establish comparisons based on method/instrument/reagent peer groups, as well as to provide intralaboratory summary statistics.

Limitations of interlaboratory comparisons include their cost, the limited stability of control materials, and the difficulty in establishing meaningful databases because of small participant groups further splintered by numerous biases in methods, instruments, and reagents. In addition, problems are created by the characteristics of manufactured control products and their interaction with specific instruments.

The limitations aside, participants can derive great benefit from interlab comparisons. The programs provide control materials at reduced cost as well as access to statistical resources and group data. Moreover, the spread of microcomputers and telecommunication increases the potential for on-line data acquisition and comparison.

Proficiency testing, on the other hand, has limited value in real time. Its advantage lies in identifying trends and defining method bias, educating staff, and satisfying a need for peer group comparison and external validation of results.

Retained patient specimens. No other area of the laboratory is as adaptable as hematology is to the use of retained patient specimens. With the exception of the white cell subpopulations, properly aliquoted, refrigerated blood specimens show no significant change in major hematologic parameters for 24 hours.5 This makes them ideal for run-to-run or shift-to-shift calibration control (at absolutely no cost).

The biggest advantage of retained patient specimens is their transferability from major instruments to backup or satellite instruments, in contrast to commercial control materials, which are subject to significant instrument/ method biases.

Weighted moving averages. The technique that offers a significant opportunity for cost savings in hematology also involves a conceptual leap from what has been standard in the past. Weighted moving averages is a patient-result-based system for process control of red-cell-related parameters.6 It is inexpensive and admirably suited to the control requirements of modern multiparameter automated hematology analyzers.

The technique is based on the empirical observation that averaged red cell indices from patient populations in acute care general hospitals are approximately Gaussian, consistently stable, and similar in all institutions studied. These properties reflect the physiologic consistency of red cell size and hemoglobin content in health, disease, and even many hematologic disorders. The dimensions of the properties are expressed by the Wintrobe indices, ratios independent of certain procedural errors (dilution, inadequate mixing) that may seriously compromise hemoglobin and hematocrit measurements and red cell counts.

Weighted moving averages anchors the validity of the indices by referencing one primary measurement, hemoglobin, to a defined calibration event. It then uses a complex, statistical algorithm to evaluate successive batches of patient sample indices and incorporate them into a continually updated mean.

Means are trimmed (outliers eliminated) and smoothed (data from previous batches incorporated into the new mean), thereby diluting the effect of random error and abnormal results. Deviations of the means from specific limits indicate loss of calibration, a shift in the characteristics of the population under study, or specific types of instrument malfunction.

Several caveats: The method should not be used by laboratories performing fewer than 100 CBCs daily. In addition, because of small sample sizes, random entry of raw data is mandatory, and each group of patients should be representative of the patient population as a whole. No more than one-third of a run should be made up of patients with mean corpuscular volume deviations in the same direction (chemotherapy, pediatric, iron-deficient).

The system takes a little getting used to because it is so statistically intensive and because it completely abandons commercial controls. Many labs may opt for periodic use of manufactured controls or retained patient specimens as a kind of security blanket.

Controversy still colors the subject of weighted moving averages. Some studies, concluding that stabilized whole blood controls are better at separating calibration change from patient variation, recommend that they be used in tandem with weighted moving averages.7 In addition, the system cannot be used for process control lf leukocyte and platelet counts because of the very high physiologic variability of these analytes.

Nevertheless, the hematology resource committee of the CAP has approved, with some reservations, the use of the weighted moving averages for longitudinal process control of seven- and eight-parameter analyzers. Recognition has also been accorded by the CAP's Commission on Laboratory Accreditation. Questions pertaining to the system are included in the current laboratory accreditation checklist.

Clinical quality control: Costs can also be cut in hematology if we eliminate or identify as far as possible the sources of results variation that occur before the specimen is analyzed. This really has more to do with quality assurance than quality control but should not be overlooked in our efforts to improve quality assurance and control costs.

The causes of preanalytic variation range from patient-specific changes, resulting from physiologic, environmental, or pathologic conditions, to a multitude of variables during the process of obtaining and transporting the specimen to the analytic site.

Specimen collection variables include choice of needles, collection systems, containers, anticoagulants, and transport conditions. Systematic variation is associated with specimen source-- earstick versus fingerstick, capillary versus venous--as well as specimen preparation.

QC for new analyte additions. At first glance, new automated hematology instruments that offer additional analytes would seem to increase rather than save costs. After all, if you have to perform quality control on a parameter that did not exist before, it will cost you money. While that is true, new instruments do make cost savings possible in a number of ways--the much smaller amounts of reagents, for example, and the elimination of labor-intensive manual differentials. Let's look briefly at some of the latest analyte additions.

Automated platelet counting. Automation of the platelet count and its incorporation into the routine hemogram are increasingly common on newer multiparameter instruments. These instruments are increasingly precise, although evaluation of specimens with moderate to severe thrombocytopenia is still an area of concern.

Quality control for automated platelet counting has been simplified by stabilized whole blood control material. However, instruments using different technologies may perceive the stabilized or fixed platelets differently from fresh patient samples. Among the trilevel controls that many manufacturers offer, those with platelet counts within the normal and low ranges are most important for quality control monitoring.

Smaller amounts of reagents and less labor account for the major cost savings from automated platelet counting.

Red cell, platelet histograms, and related parameters. Another recent addition to hematology instrumentation is the graphic display of red cells and platelet volume histograms with related indices such as the red cell distribution width, the red cell morphology index, and the mean platelet volume. Used in conjunction with the MCV, these new parameters hold promise in the differential diagnosis of anemia and in identifying specimens that require careful review. In particular, the RDW is of use in the differential diagnosis of iron deficiency and beta thalassemia minor. An elevated RDW has been noted in association with hemoglobinopathies.8

Platelet histograms and the MPV offer information beyond a mere count of platelets in the blood specimen. For example, certain disease states such as chronic myelogenous leukemia are associated with platelets of abnormal size.

Quality control is a problem in this group of parameters. Interpretation of the MPV is complicated by the fact that it varies inversely with the platelet count in normal individuals.9 Furthermore, Threatte et al10 have demonstrated significant changes in MPV resulting from use of different anticoagulants and the temperature at which the analysis is performed. Matrix problems with stabilized control materials also appear to be significant.11

These various studies highlighting MPV difficulties underscore the need for each laboratory to confirm its reference range with regard to instrument, reagent system, and type of anticoagulant used. It is possible that stabilized control material may be limited to providing comparison data only for a similar instrument-reagent combination.

MPV may be best controlled by monitoring groups of patient specimens with similar platelet counts analogous to Bull's algorithm for the red cell indices. The same may be true of the red cell histogram and related parameters. It is unlikely that different levels of manufactured control material will show significant differences in the RDW and red cell histogram distributions since that might be costly to produce.

Automated white cell differential. The manual 100-cell differential is a rather imprecise test,12,13 a fact that poses serious limitations to the clinical usefulness of the test. This conclusion is supported by recent clinical studies that question the inherent value of routine manual differential counts, both in the inpatient and outpatient settings.14, 15

These studies and others, prompted at least in part by medical cost containment, lend support and impetus not only for reducing the number of manual differential counts performed but also for using the alternatives provided in the various automated methodologies.

In general, automated differential instrumentation can be classified as either image analysis or flow analysis systems. Image analysis systems try to replicate the classic manual differential, although cell identification criteria are standardized and test precision is increased. Quality control procedures for these systems are relatively simple: The control material (stained slides) is not consumed by the analysis and can be used over and over to check the system.

Image analysis systems are expensive and limited, however. They are also dedicated instruments and do not provide data on such other parameters as hemoglobin, hematocrit, platelet count, and total white cell count. For these reasons, they are not really suited to small or even mediumsize hospitals.

Flow analysis systems, on the other hand, do provide additional hematologic data, and the required hardware and software can sometimes be added to present laboratory instrumentation via upgrades. These systems therefore offer many institutions a practical alternative to the labor-intensive manual differential. Various studies have estimated that 60 to 80 per cent of manual differentials could be replaced by such automated differentials without compromising patient care.

Quality control for flow analytic systems is still in the formative stage. One possibility is to compare automated results with values obtained from the same patient specimens done manually. This is both expensive and tedious, however, since 400- to 500-cell differentials would be required on several samples to achieve meaningful precision for comparison purposes. The limited stability of white cell populations in the fresh state also raises an obstacle to periodic replicate analysis of patient specimens as control material for differentials.

Stabilized quality control material for flow analytic systems is a relatively recent development and is still not perfected. An ideal control material compatible with all instruments may be extremely difficult if not impossible to produce. If this is the case, then interlaboratory comparison would be limited to similar instrument-reagent combinations.

It is our opinion that the optimal quality assurance system for this area will involve the use of stabilized control materials; limited comparison analysis of patient samples using extended (400-cell) manual differentials coupled with clinical criteria to eliminate unnecessary manual differentials; and laboratory criteria, including instrument flage, review of histograms, and action limits to determine which patient specimen requires careful morphologic review of the blood smear.

By eliminating unnecessary manual differentials and concentrating on those specimens that are abnormal or potentially abnormal, it is possible not only to achieve cost savings but also to increase the medical usefulness of this laboratory test.

1. The International Committee for Standardization in Hematology. Recommendation for reference methods of hemoglobinometry in human blood (ICSH Stand. EP6/2: 1977) and specifications for international hemoglobin cyanide reference preparation (ICSH Stand. EP6/3: 1977). J. Clin. Pathol. 61:139, 1978.

2. Archer, R.K.; Coster, J.F.; Crosland-Taylor, P.J.; et al. Recommended methods for determination of packed cell volume prepared on behalf of the World Health Organization by expert panel on blood cell sizing of the International Committee for Standardization in Hematology. Lab/80.4, Geneva, World Health Organization, 1980.

3. Archer, R.K.; Coster, J.F.; Crosland-Taylor, P.J.; et al. International Committee for Standardization in Hematology selected methode for the determination of packed cell volume, pp. 93-98 in "Advances in Hematological Methods: The Blood Count,' Assendelft, O.W., and England, J.M., eds. Boca Raton, Fla., CRC Press, 1982.

4. Savage, R.A. Evidence for hyperglycemic osmotic matrix effects on the Comprehensive Hematology Survey 1981-1982. Am. J. Clin. Pathol. 80:626-632, 1983.

5. Brittin, G.M.; Brecher, G.; Johnson, C.A.; et al. Stability of blood in commonly used anticoagulants. Am. J. Clin. Pathol. 52:690-694, 1969.

6. Bull, B.S., and Korpman B.A. Intralaboratory quality control using patients data, pp. 121-150 in "Quality Control,' Covill, I., cd. New York, Churchill Livingstone, 1982.

7. Cembrowski, G.S., and Westgard, J.O. Quality control of multichannel hematology analyzers: Evaluation of Bull's algonthm. Am. J. Clin. Pathol. 83:337-345, 1985.

8. Bessman, J.D.; Gilmer, P.R.; and Gardner, F.H. Improved classification of anemias by MCV and RDW. Am. J. Clin. Pathol. 80:322, 1983.

9. Bessman, J.D.; Williams, L.J.; and Gilmer, P.R. Mean platelet volume: The inverse relationship of platelet size and count in normal subjects, and an artifact of other particles. Am. J. Clin. Pathol. 76:289-293, 1981.

10. Threatte, G.A.; Adrados, C.; Ebbe, S.; and Brecher, G. Mean platelet volume: The need for a reference method. Am. J. Clin. Pathol. 81:769-772, 1984.

11. Lippi, U., and Cappelletti, P. Quality control of mean platelet volume: A chimera (letter). Am. J. Clin. Pathol. 79:648-650, 1983.

12. Miller, R.E. "Hematology--Automated White Blood Cell Differential Counting by Flow Analysis,' vol. 1:1, p. 127. Clinics in Laboratory Medicine, 1981.

13. Winkel, P.; Statland, B.E.; Saunders, A.M.; Osborn, H.; and Kupperman, H. Within-day pathologic variation of leukocyte types in healthy subjects as assayed by two automated leukocyte differential analyzers. Am. J. Clin. Pathol. 75:693-700, 1981.

14. Shapiro, M.F.; Hatch, R.L.; and Greenfield, S. Cost containment and labor-intensive tests. JAMA 252(2):231-234, 1984.

15. Rich, E.C.; Crowson, T.W.; and Connelly, D.P. Effectiveness of differential leukocyte count in case finding in the ambulatory care setting. JAMA 249(5):633-636, 1983.

Table: I Mean CVs for extended-stability QC material
COPYRIGHT 1986 Nelson Publishing
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Copyright 1986 Gale, Cengage Learning. All rights reserved.

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Author:Bachner, Paul; Kimler, Stephen C.
Publication:Medical Laboratory Observer
Date:Nov 1, 1986
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