Clinical Laboratory Information Systems Research Articles

Existing data sources for clinical epidemiology: The clinical laboratory information system (LABKA) research database at Aarhus University, Denmark

This paper provides an introduction to the clinical laboratory information system (LABKA) research database in Northern and Central Denmark. The database contains millions of stored laboratory test results for patients living in the two Danish regions, encompassing 1.8 million residents, or one-third of the country’s population. More than 1700 different types of blood test analyses are available. Therefore, the LABKA research database represents an incredible source for studies involving blood test analyses. By record linkage of different Danish registries with the LABKA research database, it is possible to examine a large number of biomarkers as predictors of disease risk and prognosis and as markers of disease severity, and to evaluate medical treatments regarding effectiveness and possible side effects. Large epidemiological studies using routinely stored blood test results for individual patients can be performed because it is possible to link the laboratory data to high-quality individual clinical patient data in Denmark.

Persistent individual tracking within overall improvement in HbA1cin a UK paediatric diabetes clinic over 15 years

There is some evidence of long-term tracking of HbA(1c) levels within diabetes centres, but little evidence of individual tracking. HbA(1c) levels of children in the clinic over a period of 15 years were retrieved from the clinical chemistry laboratory information system. We measured the correlation of HbA(1c) between years (Spearman and Pearson rank correlation), as well as the relationship of HbA(1c) with age and the change over time in the clinic. Data were collected from 362 children and young people [158 female (44%)], aged 0-18 years (median 10.4 years), with 0-13.6 years of follow-up (median 4.7 years). Mean HbA(1c) levels fell from 9.3 ± 1.5% (78 ± 16 mmol/mol) in 2001 to 8.1 ± 1.3% (65 ± 14 mmol/mol) in 2009 in those at least 6 months after diagnosis (P<0.0001). HbA(1c) levels gradually rise with increasing age. HbA(1c) levels from year to year are significantly correlated. This is better for adjacent than subsequent years, but there is a significant correlation up to 9 years from diagnosis. Only 4 of 49 children with a 6-month HbA(1c) level of 9% (75 mmol/mol) or more had a long-term (2-5 years) median HbA(1c) <8% (64 mmol/mol). HbA(1c) levels track in individuals within an improvement in overall clinic levels, suggesting that, if optimal control can be achieved in the first 6 months, it can persist for up to 9 years.

A Novel Class of Laboratory Middleware

A central duty of the laboratory is to inform clinicians about the availability and usefulness of laboratory testing. In this report, we describe a new class of laboratory middleware that connects the traditional clinical laboratory information system with the rest of the enterprise, facilitating information flow about testing services. We demonstrate the value of this approach in efficiently supporting an inpatient order entry application. We also show that order entry monitoring and iterative middleware updates can enhance ordering efficiency and promote improved ordering practices. Furthermore, we demonstrate the value of algorithmic approaches to improve the accuracy and completeness of laboratory test searches. We conclude with a discussion of design recommendations for middleware applications and discuss the potential role of middleware as a sharable, centralized repository of laboratory test information.

Cholesterol reference method and HDL cholesterol designated comparison methods as Performed in the US CDC Cholesterol Reference Method Laboratory Network

Objective To standardize total cholesterol (TC) and HDL cholesterol (HDLC) analytical systems with the US CDC TC reference method and HDLC designated comparison method (DCM). Methods CDC TC reference method and HDLC DCM were set up and the quality was controlled by participating in the CDC Cholesterol Reference Method laboratory Network (CRMLN) bimonthly survey. The performance of 21 TC or HDLC analytical systems from 3 manufacturers were tested with the methods according to the CRMLN certification protocols. Results The coefficient variation (CV) of TC analyses with the reference method in 18 surveys averaged 0.29% and the bias versus CDC target value 0.1%. The DCM HDLC CV in 17 surveys averaged 0.010 mmol/L(0.39 mg/dl) and the averaged biases versus CDC target and group mean were - 0.019 mmol/L (-0.72 mg/dl) and - 0.006 mmol/L (-0.25 mg/dl), respectively. Most of the TC and HDLC analysis events (> 90%) satisfied the CRMLN accuracy and precision criteria for the reference method and DCM. Eighteen of the 21 tested TC or HDLC systems met the performance criteria for analytical systems and were certified for traceability by CDC. Conclusions A reference method for cholesterol and a DCM for HDLC and performed within an international reference laboratory network have been established and used for certification of TC and HDLC analytical systems, Further application of the methods to the standardization of lipid analysis are expected. Key words: Cholesterol; Cholesterol, HDL; Reference standards; Center for disease control and prevention(U. S.); Clinical laboratory information systems

What does dengue disease surveillance contribute to predicting and detecting outbreaks and describing trends?

To review the evidence on the application of tools for dengue outbreak prediction/detection and trend monitoring in passive and active disease surveillance systems in order to develop recommendations for endemic countries and identify research needs. Systematic review of literature in the Cochrane Database of Systematic Reviews, PubMed, EMBASE, Lilacs, WHO library database, manual reference search and grey literature. Two reviewers independently applied pre-defined inclusion and exclusion criteria and assessed the level of evidence. Studies describing the outcome of dengue disease surveillance with respect to trend monitoring and outbreak prediction/detection based on empirical data were included. Twenty-four studies (of 1804 references) met the eligibility criteria. Different indicators and their respective threshold values were identified as potential triggers for outbreak alerts through retrospective analysis of data from passive and/or active surveillance systems. Some indicators are potentially useful for predicting imminent outbreaks in the low transmission season and others for detecting outbreaks at an early stage. However, the information collected is mainly retrospective and often site-specific and appropriate levels of sensitivity and specificity of the outbreak indicators/triggers could not be determined. Retrospective and prospective virus surveillance studies were not conclusive regarding the question of whether a newly introduced serotype is an outbreak predictor, but contributed additional indicators for outbreak prediction/detection. Under-reporting was a major concern. Taking cost and feasibility issues into account, it remains an open question whether dengue surveillance should be passive (based on routine reporting) or active (based on more costly sentinel or other active population based surveillance systems). Adding active surveillance elements to a well-functioning passive surveillance system improves sensitivity; adding laboratory elements to the system improves specificity. In view of the lack of evidence about the most feasible and sustainable surveillance system in a country context, countries could use a stepwise approach to locally adapt their passive routine surveillance system into an improved combined active/passive surveillance approach. Prospective studies are needed to better define the most appropriate dengue surveillance system and trigger for dengue emergency response.

The realization of clinical laboratory online management system and laboratory information system network

目的 研究临床医学实验室(医院的检验科)数据的自动化处理过程,探讨建立实验室联机管理及网络管理系统的方法.方法从实验室需求入手,利用计算机模拟手工处理过程,把系统按功能细化为若干次级逻辑模块,使用VB等工具编程.结果成功实现了两个分析仪的联机管理系统设计以及三个实验室网络管理.结论本设计是功能新颖、符合检验工作模式、实用可靠的管理信息系统。

Computer-assisted surveillance for detecting clonal outbreaks of nosocomial infection.

Whole-house surveillance for healthcare-associated infection is no longer the recommended practice because of the large personnel time investment required. We developed a computer-based tracking system using microbiologic data as an aid in detecting potential outbreaks of healthcare-associated infections on a hospital-wide basis. Monthly total isolates of 25 clinically significant hospital pathogens were tallied from 1991 to 1998 to form a database for future comparison. Two different algorithm tools (based on increases of organism numbers over baseline) were applied to determine alert thresholds for suspected outbreaks using this information. The first algorithm (2SD) defined an alert as two standard deviations above the mean monthly number of isolates. The second (MI) defined an alert as either a 100% increase from the baseline organism number over 2 months or a >/=50% increase (compared to baseline) during a three-consecutive-month period. These two methods were compared to standard infection control professional surveillance (ICP) for the detection of clonal outbreaks over 12 months. Overall, a total of seven clonal outbreaks were detected during the 1-year study. Using standard methods, ICP investigated nine suspected outbreaks, four of which were associated with clonal microbes. The 2SD method signaled a suspected outbreak 15 times, of which three were clonal and ICP had detected one. The MI method signaled a suspected outbreak 30 times; four of these were clonal, and ICP had detected one. The sensitivity and specificity values for ICP, 2SD, and MI for detecting clonal outbreaks were 57, 43, and 57% and 17, 83, and 67%, respectively. Statistical methods applied to clinical microbiology laboratory information system data efficiently supplement infection control efforts for outbreak detection.

Linking laboratory and pharmacy: opportunities for reducing errors and improving care.

A myriad of errors and lost improvement opportunities result from failure of clinical laboratory and pharmacy information systems to effectively communicate. Pharmacotherapy could benefit from enhanced laboratory-pharmacy linkage with respect to (1) drug choice (laboratory-based indications and contraindications), (2) drug dosing (renal or hepatic, blood level-guided adjustments), (3) laboratory monitoring (laboratory signals of toxicity, baseline and ongoing monitoring), (4) laboratory result interpretation (drug interfering with test), and (5) broader quality improvement (surveillance for unrecognized toxicity, monitoring clinician response delays). Linkages can be retrospective or real-time. Many organizations could benefit now by linking existing pharmacy and laboratory data. Greater improvement is possible through implementation of electronic order entry with real-time decision support incorporating linked laboratory and pharmacy data. While many guidelines, admonitions, and rules exist regarding drugs and the laboratory, substantial new knowledge and evidence in this area are needed. Focusing on these unmet needs and accompanying logistical challenges is a priority.

Open laboratory information systems: a case study

The EU-AIM project ?OpenLabs? specified an open systems architecture for a clinical laboratory information system (LIS) environment and coined the term ?open LIS?. Since this conception has not yet been realized into systems and modules commercially available, two university hospitals in Norway had to specify an alternative model for openness when they, in a joint project, screened the market for a new LIS. To be open, a LIS must be (1) based on main-trend hardware and system software running under a standardized operating system, (2) designed for network-based distributed computing, (3) have sufficient documentation available to local staff, (4) be configurable through parameters, tables and scripts, and (5) have general and configurable access mechanisms both to real-time processes and to the database. The present study describes the selection process and examines the compliance of the selected LIS (NetLab) with this model of openness. It is shown that local staff have been able to adapt this LIS to various and changing requirements in the laboratory.

NCCLS: Standardization in Clinical Laboratory Automation and Information Systems

NCCLS: Standardization in Clinical Laboratory Automation and Information Systems

Work on Clinical Laboratory Information Systems Standards Completed

Work on Clinical Laboratory Information Systems Standards Completed

A new clinical laboratory information system architecture from the OpenLabs project offering advanced services for laboratory staff and users

The OpenLabs project aims to improve the efficiency and effectiveness of clinical laboratory services by integrating decision support systems with laboratory information systems and equipment. Standards for electronic data interchange between laboratories and other medical systems using the EUCLIDES/OpenLabs coding scheme and an open architecture for clinical laboratory information systems have been specified. This article gives an account of the proposed architecture and outlines new software applications being developed using the architecture which provide advanced services for ordering and reporting of laboratory tests, advanced instrument workstation and laboratory management services, including an OpenLabs Service Manager application which co-ordinates the available services.

OpenLabs: the application of advanced informatics and telematics for optimization of clinical laboratory services

OpenLabs has four major objectives: to improve the efficiency and effectiveness of clinical laboratory services by the integration of Knowledge Based Systems (KBSs) with Laboratory Information Systems (LISs) and equipment; to provide and implement standard solutions for Electronic Data Interchange (EDI) between laboratories and other medical systems; to specify a fully Open architecture for an integrated Clinical LIS and demonstrate the integration of various KBS modules on the open architecture platform; and to demonstrate the integration of OpenLabs modules with existing LISs.

Migrating a clinical laboratory information system between technologies

The technical revolution that has strongly driven events in the clinical laboratory for the last thirty years is now threatening to make obsolete what has become the central pillar of operation in many laboratories, the minicomputer-based laboratory information system. Some of its functions could easily be absorbed by the personal computers which are proliferating in the laboratory, but any single step leap between systems risks replacing order with chaos. Appropriate use of networking tools, together with essential software development, can provide a systematic migrational path for both the administrative and technical computer support from one environment to another without the trauma of a massive replacement step.

Decision support alerts for clinical laboratory and blood gas data

We have designed and implemented a computerized Intensive Care Unit (ICU) decision support alerting system which analyzes all incoming laboratory and blood gas data for critically abnormal values and trends. A computerized patient data management system (HP 78709A PDMS, Hewlett-Packard Co., Waltham, MA) serving 20 Surgical ICU beds is networked to a Clinical Laboratory Information System and a blood gas computer system. The ALERTS subsystem operates on the PDMS as an automatic program triggered by the receipt of fresh laboratory data. Three types of ALERTS are detected: (1) high and low critical values, (2) calculation-adjusted critical values, and (3) critical trends. Once detected, a specific ALERT message is displayed at the bottom of the patient's bedside PDMS terminal and at the central station. Over an eight month period a total of 1,515 ALERTS were detected from amongst approximately 115,000 laboratory data results transmitted to the Surgical Intensive Care Unit (SICU). Slightly over half of all ALERTS were caused by critical blood gas values. ALERTS were found to be a sensitive indicator of severity of illness: patients with one or more ALERTS suffered an ICU mortality of 9.52%, compared to 0% mortality in patients with no ALERTS. We conclude that automated laboratory data ALERTS represent a valuable decision support tool for the management of high risk ICU patients.

Long-term data storage in a clinical laboratory information system.

The clinical laboratory is pressured on one side by physicians and regulators who want the laboratory to keep more detailed patient records available for longer periods and on the other side by physical space and cost constraints which favor rapidly transferring such records to Medical Records or a warehouse from which retrieval is slow and difficult. Various forms of inactive data storage and archiving in machine-readable form are available to address this dilemma, yet these solutions can create even more difficult problems. Two different approaches were developed within the framework of Relational LABCOM to address both the intermediate and long-term storage of data. In this paper we examine the two methods as solutions to the problems, discuss their limitations, and determine why one is superceding the other in the installation base.

The development of a third generation system for entering microbiology data into a clinical laboratory information system.

Increased demands on technologists' time and the desire to have electronic storage of patient information have led to numerous computer-based efforts to manage microbiology data. Our approach to the design of a new microbiology subsystem has been to maximize the functionality without requiring unusual input devices. DEC VT100-compatible terminals are used for data entry and display. Data are displayed taking advantage of such features of these terminals as reverse video, highlighting, and scroll windowing. Numerous single-key instructions for invoking functions and changing cursor positions have been implemented to minimize keystrokes and to anticipate the entry sequences of the technologists. A program that allows the quick location and display of specimens and results is also included in the package.

Implementing an Information System

Careful attention to the implementation of a clinical laboratory information system is critical to the success of the system. Aspects of implementation, including installation of hardware, training of personnel, and preparation of the data base, are outlined. Commonly encountered problems—and how to avoid them—are highlighted.

CLIS, a clinical laboratory information system designed to optimize microcomputer operation.

Journal Article CLIS, a clinical laboratory information system designed to optimize microcomputer operation. Get access C Bishop C Bishop Search for other works by this author on: Oxford Academic Google Scholar Clinical Chemistry, Volume 27, Issue 5, 1 May 1981, Pages 704–708, https://doi.org/10.1093/clinchem/27.5.704 Published: 01 May 1981

Introduction of computer facilities to a clinical chemistry laboratory.

A clinical chemistry laboratory information system based on MUMPS is described, together with the problems associated with its implementation. Tabular displays and cusum charts as well as cumulative records are available on a real-time basis. Data capture is by both on-line and off-line techniques. After 18 months' live running the management of information within the laboratory has been significantly improved.