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How three hematology laboratories improved efficiency by automating the preanalytical process, reorganizing lab workspace, using data management systems to identify which samples need further verification, and setting strict criteria limiting the need for nonautomated processes.
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CONTEXT: Notifiable disease surveillance is essential to rapidly identify and respond to outbreaks so that further illness can be prevented. Automating reports from clinical laboratories has been proposed to reduce underreporting and delays. OBJECTIVE: To compare the timeliness and completeness of a prototypal electronic reporting system with that of conventional laboratory reporting. DESIGN: Laboratory-based reports for 5 conditions received at a state health department between July 1 and December 31, 1998, were reviewed. Completeness of coverage for each reporting system was estimated using capture-recapture methods. SETTING: Three statewide private clinical laboratories in Hawaii. MAIN OUTCOME MEASURES: The number and date of reports received, by reporting system, laboratory, and pathogen; completeness of data fields. RESULTS: A total of 357 unique reports of illness were identified; 201 (56%) were received solely through the automated electronic system, 32 (9%) through the conventional system only, and 124 (35%) through both. Thus, electronic reporting resulted in a 2.3-fold (95% confidence interval [CI], 2.0-2.6) increase in reports. Electronic reports arrived an average of 3.8 (95% CI, 2.6-5.0) days earlier than conventional reports. Of 21 data fields common to paper and electronic formats, electronic reports were significantly more likely to be complete for 12 and for 1 field with the conventional system. The estimated completeness of coverage for electronic reporting was 80% (95% CI, 75%-85%) [corrected] compared with 38% (95% CI, 36%-41%) [corrected] for the conventional system. CONCLUSIONS: In this evaluation, electronic reporting more than doubled the total number of laboratory-based reports received. On average, the electronic reports were more timely and more complete, suggesting that electronic reporting may ultimately facilitate more rapid and comprehensive institution of disease control measures.
Laboratory automation systems (LAS) have been installed in over 22 sites across North America providing automation of many preanalytical and analytical tasks in clinical laboratories. Only a few laboratories have automated the analysis of citrated whole blood for the diagnosis of hemostasis disorders. The analysis of coagulation factors in citrated blood requires a large amount of labor in order to provide rapid turnaround; thus automation of this analytical process is attractive. Therefore, we have created an automated coagulation workstation using a systematic approach to automation design and engineering. First, we used discrete event simulation to calculate potential throughput and to identify possible bottlenecks for the proposed coagulation workcell. We then created a three-dimensional animated computer model of the workstation to simplify workstation design. Finally, we constructed a prototype workcell using a mobile robot, an articulated robotic arm, and a coagulation analytical system.
Accompanying hematology laboratory automation, the frequency of morphological observation of blood cells tends to decrease. Although 5-part differentials are performed by automated systems, counting of abnormal cells such as immature cells or leukemia cells still must be performed manually using smears. In the automated hematology laboratories, technicians more frequently find abnormal cells than before. Therefore, poor microscopic observation of blood cells markedly affects the diagnosis. Continuous training of the technologist is mandatory. Also, preparation of smear samples is important, i.e, well prepared slides must be stained properly with an appropriate dye. Technicians must be familiar with staining technology together with the knowledge of the characteristics of several staining methods. On the other hand, the technician's ability to differentiate white blood cells depends on the instructor's knowledge. This makes quality control and the standardization of differentials difficult. Still the problems must be solved under the cooperation of the various societies concerned.
Environmental monitoring for genotoxicity requires that a large number of measurements be made across space and time. This requirement demands a rapid and efficient bioassay system. The SOS Chromotest is a rapid, efficient bacterial system for the detection of DNA damaging agents. Over 100 publications have described its use on a variety of samples. Relatively few studies have used the test to examine complex mixtures. Effective testing of complex samples poses a variety of problems. Although solutions have been proposed, few have validated the resulting protocol. In this work we present a semi-automated microplate version of the SOS Chromotest for the examination of complex mixtures. Experiments were conducted to determine the optimal cell concentration, exposure time, substrate conversion time and S9 enzyme concentration. The performance of the method was evaluated using 6 reference genotoxins and 3 complex mixtures. The complex mixtures examined are extracts of diesel particulate matter, urban dust and coal tar. The results obtained indicate that optimal responses often require fewer cells (approximately equal to 5-10 x 10(6) CFU/ml) and a longer exposure (3 h) than that recommended in the original protocol. Interfering effects of colored and turbid samples are removed using centrifugation and initial optical density readings taken 60 min after cell resuspension and lysis. The performance of the established protocol was evaluated using mitomycin C and benzo[a]pyrene results for 207 microplates and solvent control results for 293 microplates. The results indicate that the established method is accurate, sensitive and precise. Coefficient of variation on mean SOSIP values for mitomycin C and benzo[a]pyrene are < 5%. Solvent control data indicate that the standard threshold for determination of a positive response (induction factor > 1.5) is excessively conservative. All liquid transfers were automated using the Biomek automated laboratory workstation. Automation permits a throughput of up to 72 samples per day and maintains excellent precision and accuracy.
OBJECTIVE: The authors assessed the completeness of disease reporting from a managed care organization's automated laboratory-based reporting system to the California Department of Health Services (CDHS) via local public health departments. METHODS: The authors identified all positive laboratory tests for 1997 from the computerized database of Kaiser Permanente Northern California for seven infections for which there are statutory reporting requirements: Campylobacter jejuni, Chlamydia trachomatis, Cryptosporidium parvum, hepatitis A, Neisseria meningitidis, Neisseria gonorrhoeae, and Salmonella (N = 7,331 reports). Cases were then matched by computer query to records of cases reported to CDHS. To determine why cases were not found in CDHS records, a sample of un-matched cases was searched at two county health departments. RESULTS: Overall, 84.5% (95% CI 83.4, 85.6) of the laboratory reports submitted with accompanying demographic information were successfully matched with cases in the CDHS disease surveillance database. Frequency of matching for specific diseases ranged from 79.4% (95% CI 75.6, 83.3) for N. gonorrhoeae to 88.4% (95% CI 85.3, 91.6) for C. jejuni. Reports were more likely to be matched when the county of residence was the same as the county of the health care facility. At the county level, reasons for failure of cases to be forwarded to CDHS included: errors due to manual data entry, failure to forward information from the county of diagnosis to the county of residence, and incorrect disease coding. CONCLUSION: Automated laboratory-based reporting is highly effective, but some data are lost with off-line transfer of information. To optimize surveillance accuracy and completeness, reporting at all levels should be done via direct electronic data transfer.
BACKGROUND: Quality policies focussed on the patient and applied to a hospital microbiology laboratory have led us to investigate clinicians' needs when requesting test results. The aim of this study was to analyze these requirements and to implement a plan to improve attention to the clinicians, considered as direct customers, particularly in the process of providing results. METHODS: Phase 1: To determine clinicians' needs, we studied the calls made to the Bacteriology Unit. Over a period of two weeks the information requested, the reasons for the call and the hospital Service calling were recorded. A descriptive analysis of this information was performed and the most frequent reasons for calling were identified. Phase 2: A quality improvement plan was designed to improve laboratory reporting of bacteriologic results. One month after its implementation, the results of this quality effort were assessed by analysis of calls to the Unit and use of a questionnaire to determine clinicians' satisfaction. RESULTS: Phase 1: among the total calls made, 43.8% asked for information on specimens being processed, 17.7% for information on specimens processed in other units, 16.1% demanded test results that had not been received within the expected time, and 22.4% were for other reasons. The hospital departments requesting information included 31% Infectious Diseases, 16% Internal Medicine, 13% Intensive Care Unit (ICU), and 40% others. Phase 2: within the quality plan, a microbiologist attended clinical sessions in the above mentioned departments in order to provide information on the specimens being processed, to discuss alternative diagnostic tests, and to comment on treatment prescribed to the patients. EVALUATION: Microbiologists attended two sessions per week during one month in the IM and ID Departments and ICU, and his/her participation was evaluated through analysis of calls and a satisfaction questionnaire. CONCLUSION: Automation of many laboratory tasks has allowed a reorientation of the activity of laboratory professionals toward satisfying the needs of the medical staff and improvements in the reporting process. The direct participation of laboratory professionals in discussions on patient care resulted in an enhancement of the overall quality of the health care provided to the patient.
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Rapid-response testing can help the critical care physician provide more medically relevant decisions when treating critically ill patients. Many technologies have appeared on the market to help deliver rapid analytical tests, including transportation systems, hand-held analyzers, or clinical instruments that have simple user interfaces. Each of these methods can be used to provide the necessary medical information but often at the expense of turnaround time, quality of service, or cost. A robotically automated laboratory system was created that provides rapid turnaround time and low cost, and each result is monitored and reviewed by a laboratory professional. To provide the best quality laboratory services at the lowest cost, we created a remotely controlled robotic clinical laboratory that provides whole-blood analysis of blood gases (pCO2,pO2), pH, electrolytes (sodium, potassium, and chloride), glucose, and hemoglobin near the patient beside yet maintains the distinct advantage of central laboratory control. The automated remote laboratory provides extremely rapid turnaround time, eliminates the costly steps involved with specimen processing, reduces the risk from contaminated specimens, reduces staff training, ensures that every result is reviewed by a professional, and improves patient care.
Chromogenic anti-Xa activity procedures were developed for monitoring LMW heparins on the Automated Coagulation Laboratory 300 Plus (ACL, Instrumentation Laboratory) system. For daily monitoring, a "Routine" procedure was devised which allows accurate measurements between plasma levels of 0.1 and 1.0 u/ml LMW heparin. For lower levels a "Routine-Low" method was developed which assesses activities between 0.05 and 0.4 u/ml. Due to variabilities in dODs of individual baseline plasmas, levels below 0.05 u/ml might be inaccurate when pooled normal plasma is used to establish the reference curve. While levels less than 0.05 u/ml should rarely be encountered when monitoring LMW heparins for routine clinical use, pharmacokinetic studies require accurate measurements below that level. For this reason a "Research-High" and a "Research-Low" procedure was designed. For these procedures a study subject's own baseline plasma was used to establish the reference curve. The "Research-High" measures activities between 0.4 and 2.0 u/ml, the "Research-Low" between zero and 0.4 u/ml. The procedures have excellent within-run and inter-run coefficients of variation (less than 5%) and high levels of accuracies. Even inter-instrumental reproducibilities are less than 10%. Different manufacturers' LMW heparins can be analyzed by these assays. The procedures offer full automation, great cost-effectiveness due to lower reagent volumes, rapid turn-around time and great accuracy and reproducibility.
Rapid changes in healthcare coupled with parallel advances in technology have stimulated the evolution of new approaches for laboratory automation. In particular, the emergence of commercially available laboratory robotic systems offers promise for streamlining the clinical laboratory. Increasing cost-containment pressures make the application of this technology extremely attractive, and several organizations have begun to systematically integrate robotic devices into their laboratory automation schemes. Integration of these technologies, however, presents many challenges for software developers, instrument manufacturers, and laboratory workers. Differing needs across laboratories require flexibility and intelligence in robots, instruments, and control systems. Standardization of mechanical and electronic interfaces will be key to making these systems easy to integrate. Systems engineering, aided by simulation modeling and artificial intelligence schemes, will be important to assist in the design of optimal configurations. Software for the overall control of integrated automation will be needed that can be tailored by the laboratorian to fit the requirements of the individual laboratory. Thus, laboratory workers will need to be actively involved in implementing this new wave of laboratory automation, becoming well-versed in computers, electronics, and systems engineering.
The manual Heptest for measuring low-molecular-weight heparin fractions was applied to a fully automated, coagulation-dedicated analyzer, the Automated Coagulation Laboratory 300 Plus. The clot-based assay mode of the instrument was used, which operates on the principle of light scattering. Undiluted plasmas and the original reagents of the Heptest kit were used. Also, the 2-minute incubation time of the manual procedure was maintained. Automation reduced plasma and reagent volumes by about one half. As a result of the high precision of the automated procedure, single determinations suffice, and 18 plasma samples can be analyzed in about 8 minutes. Coefficients of variation were 1.0% to 3.2% for within-run and 1.9% to 6.0% for inter-run analyses. Analytical recovery was 98% to 104%. Comparisons of 132 samples between the two procedures yielded an R value of 0.974 for activity expression in seconds and 0.945 for U/mL. Several low-molecular-weight heparin fractions were tested.
In the light of recent advances in technology, the basic equipment of an automated ECG laboratory is described. The main features of data acquisition terminals, data receiver/controller units, A/D converters, computers, visual displays and systems for storage and retrieval of tracings, are briefly discussed. Three major alternatives are open for computer-aided ECG interpretation today: 1) complete, dedicated system in the hospital; 2) ECG data collection system with offline analysis by hospital business computer; 3) ECG service center outside of the hospital. Advantages and possible limitations of these methods are discussed. At the Ospedale Civile Regionale of Udine we have choosen the first method. An HP 1530 ECG interpretative system and the 12-lead ECG analysis program developed by Caceres-USPHS are used. Analog tracing and interpretative printout are available in the laboratory and/or at the patient location in about one minute. Our system has been working for less than one year. At present, 150-200 ECG are processed daily. Such an ECG processing system has proven to yield considerable savings in time and manpower. Some operational problems related to shifting from manual to computer work have been gradually overcome and will be discussed.
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