Estimating waiting time for compatible blood: A Negative Binomial approach.

OBJECTIVES: Screening blood units for compatibility constitutes a Bernoulli series. Estimating the number of units needed to be screened represents a classic waiting time problem that may be resolved using the Negative Binomial Distribution. The currently recommended method for estimating the number of units screened, n, to find a required number of compatible units, r, with a given probability, p, is n = r/p. This coincides with the mean of the Negative Binomial Distribution so that the actual number of units screened will often be underestimated by the current method. METHODS: The cumulative distribution function of the Negative Binomial Distribution provides the probability of success (compatibility), F(n;r,p), as a function of the number of trials performed (attempted crossmatches), n, the probability of success on each trial, p, and the number of successes (compatible units) required, r. Choosing a threshold cumulative probability sufficiently high, such as F ~ 0.9, for example, will provide confidence that the projected number of units screened will be underestimated less often (~10% of the time). RESULTS: With F ≥ 0.9, the estimated number of attempted crossmatches ranges from 1.3 to 2.3 times as many as the number calculated by the current method. As a rule of thumb approximately 1.6 times the current estimated number provides a similar estimate (n ~ 1.6∙r/p). CONCLUSIONS: Waiting time underestimation will be reduced significantly by using the Negative Binomial Distribution solution and should be accompanied by improved customer satisfaction.

Pathology and Laboratory Medicine Support for the American Expeditionary Forces by the US Army Medical Corps During World War I.

CONTEXT: Historical research on pathology and laboratory medicine services in World War I has been limited. In the Spanish American War, these efforts were primarily focused on tropical diseases. World War I problems that could be addressed by pathology and laboratory medicine were strikingly different because of the new field of clinical pathology. Geographic differences, changing war tactics, and trench warfare created new issues. OBJECTIVES: To describe the scope of pathology and laboratory medicine services in World War I and the value these services brought to the war effort. METHODS: Available primary and secondary sources related to American Expeditionary Forces' laboratory services were analyzed and contrasted with the British and German approaches. RESULTS: The United States entered the war in April 1917. Colonel Joseph Siler, MD, a career medical officer, was the director, and Colonel Louis B. Wilson, MD, head of pathology at the Mayo Clinic, was appointed assistant director of the US Army Medical Corps Division of Laboratories and Infectious Disease, based in Dijon, France. During the next year, they organized 300 efficient laboratories to support the American Expeditionary Forces. Autopsies were performed to better understand treatment of battlefield injuries, effects of chemical warfare agents, and the influenza pandemic; autopsies also generated teaching specimens for the US Army Medical Museum. Bacteriology services focused on communicable diseases. Laboratory testing for social diseases was very aggressive. Significant advances in blood transfusion techniques, which allowed brief blood storage, occurred during the war but were not primarily overseen by laboratory services. CONCLUSIONS: Both Siler and Wilson received Distinguished Service Medals. Wilson's vision for military pathology services helped transform American civilian laboratory services in the 1920s.

A mathematical model to assess the influence of hematocrit on point of care glucose meter performance.

OBJECTIVES: To develop and apply a mathematical model of the relationship between hematocrit, meter glucose and reference glucose concentrations as a tool for evaluation of whole blood glucose meters. DESIGN AND METHODS: Patient blood gas specimens were used to compare the LifeScan SureStep Flexx and the Nova StatStrip glucose meters with reference results obtained from a Radiometer 725 blood gas analyzer. Linear regression analysis was conducted to determine the extent that patient hematocrit and reference glucose concentrations predicted the performance of the glucose meters. RESULTS: Bland-Altman graphic analysis depicted that both glucose meters showed variance with the reference method. A mathematical model was derived from IFCC consensus equations that relate glucose meter results, hematocrit and plasma glucose values. Using the model, multivariate regression depicted that hematocrit affected the results of the SureStep Flexx meter in a manner dependent on the glucose concentration, whereas the StatStrip meter was not affected by hematocrit. CONCLUSIONS: Linear regression can be used to quantify the extent of hematocrit interference on the performance of glucose meters.

Interference studies with two hospital-grade and two home-grade glucose meters.

BACKGROUND: Interference studies of four glucose meters (Nova Biomedical [Waltham, MA] StatStrip [hospital grade], Roche Diagnostics [Indianapolis, IN] Accu-Chek Aviva [home grade], Abbott Diabetes Care [Alameda, CA] Precision FreeStyle Freedom [home grade], and LifeScan [Milpitas, CA] SureStep Flexx [hospital grade]) were evaluated and compared to the clinical laboratory plasma hexokinase reference method (Roche Hitachi 912 chemistry analyzer). These meters were chosen to reflect the continuum of care from hospital to home grade meters commonly seen in North America. METHODS: Within-run precision was determined using a freshly prepared whole blood sample spiked with concentrated glucose to give three glucose concentrations. Day-to-day precision was evaluated using aqueous control materials supplied by each vendor. Common interferences, including hematocrit, maltose, and ascorbate, were tested alone and in combination with one another on each of the four glucose testing devices at three blood glucose concentrations. RESULTS: Within-run precision for all glucose meters was <5% except for the FreeStyle (up to 7.6%). Between-day precision was <6% for all glucose meters. Ascorbate caused differences (percentage change from a sample without added interfering substances) of >5% with pyrroloquinolinequinone (PQQ)-glucose dehydrogenase-based technologies (Aviva and Freestyle) and the glucose oxidase-based Flexx meter. Maltose strongly affected the PQQ-glucose dehydrogenase-based meter systems. When combinations of interferences (ascorbate, maltose, and hematocrit mixtures) were tested, the extent of the interference was up to 193% (Aviva), 179% (FreeStyle), 25.1% (Flexx), and 5.9% (StatStrip). The interference was most pronounced at low glucose (3.9-4.4 mmol/L). CONCLUSIONS: All evaluated glucose meter systems demonstrated varying degrees of interference by hematocrit, ascorbate, and maltose mixtures. PQQ-glucose dehydrogenase-based technologies showed greater susceptibility than glucose oxidase-based systems. However, the modified glucose oxidase-based amperometric method (Nova StatStrip) was less affected in comparison with the glucose oxidase-based photometric method (LifeScan SureStep Flexx).

Modeling patient service centers with simulation and system dynamics.

We report on the use of simulation modeling for redesigning phlebotomy and specimen collection centers (or patient service centers) at a medical diagnostic laboratory. Research was performed in an effort to improve patient service, in particular to reduce average waiting times as well as their variability. Discrete-event simulation modeling provided valuable input into new facility design decisions and showed the efficacy of pooling sources of variation, particularly patient demand and service times. Initial performance of the redesigned facilities was positive; however, dynamic feedback within the system of service centers eventually resulted in unanticipated performance problems. We show how a system dynamics model might have helped predict these implementation problems and suggest some ways to improve results.