The ideal laboratory information system.

CONTEXT Laboratory information systems (LIS) are critical components of the operation of clinical laboratories. However, the functionalities of LIS have lagged significantly behind the capacities of current hardware and software technologies, while the complexity of the information produced by clinical laboratories has been increasing over time and will soon undergo rapid expansion with the use of new, high-throughput and high-dimensionality laboratory tests. In the broadest sense, LIS are essential to manage the flow of information between health care providers, patients, and laboratories and should be designed to optimize not only laboratory operations but also personalized clinical care. OBJECTIVES To list suggestions for designing LIS with the goal of optimizing the operation of clinical laboratories while improving clinical care by intelligent management of laboratory information. DATA SOURCES Literature review, interviews with laboratory users, and personal experience and opinion. CONCLUSIONS Laboratory information systems can improve laboratory operations and improve patient care. Specific suggestions for improving the function of LIS are listed under the following sections: (1) Information Security, (2) Test Ordering, (3) Specimen Collection, Accessioning, and Processing, (4) Analytic Phase, (5) Result Entry and Validation, (6) Result Reporting, (7) Notification Management, (8) Data Mining and Cross-sectional Reports, (9) Method Validation, (10) Quality Management, (11) Administrative and Financial Issues, and (12) Other Operational Issues.

[1]  James O Westgard,et al.  The truth about quality: medical usefulness and analytical reliability of laboratory tests. , 2004, Clinica chimica acta; international journal of clinical chemistry.

[2]  A. Regeniter,et al.  Windows to the ward: graphically oriented report forms. Presentation of complex, interrelated laboratory data for electrophoresis/immunofixation, cerebrospinal fluid, and urinary protein profiles. , 2003, Clinical chemistry.

[3]  John M. Paulett,et al.  Implementation of a closed-loop reporting system for critical values and clinical communication in compliance with goals of the joint commission. , 2010, Clinical chemistry.

[4]  Jean-Baptiste Lamy,et al.  Facilitating Access to Laboratory Guidelines by Modeling their Contents and Designing a Computerized User Interface , 2011, MIE.

[5]  Henk M. J. Goldschmidt A review of autovalidation software in laboratory medicine , 2002 .

[6]  Halife Kodaz,et al.  Medical application of information gain based artificial immune recognition system (AIRS): Diagnosis of thyroid disease , 2009, Expert Syst. Appl..

[7]  M. Serdar,et al.  Rapid access to information resources in clinical biochemistry: medical applications of Personal Digital Assistants (PDA) , 2008, Clinical and Experimental Medicine.

[8]  Andrew Georgiou,et al.  Does Computerised Provider Order Entry Reduce Test Turnaround Times? A Before-and-After Study at Four Hospitals , 2009, MIE.

[9]  W. Oosterhuis,et al.  Evaluation of LabRespond, a new automated validation system for clinical laboratory test results. , 2000, Clinical chemistry.

[10]  Michael Blechner,et al.  Analysis of search in an online clinical laboratory manual. , 2006, American journal of clinical pathology.

[11]  Fevzullah Temurtas,et al.  A comparative study on thyroid disease diagnosis using neural networks , 2009, Expert Syst. Appl..

[12]  Wytze P Oosterhuis,et al.  Gross overestimation of total allowable error based on biological variation. , 2011, Clinical chemistry.

[13]  Andrew R. Post,et al.  Model Formulation: PROTEMPA: A Method for Specifying and Identifying Temporal Sequences in Retrospective Data for Patient Selection , 2007, J. Am. Medical Informatics Assoc..

[14]  C. Fraser Improved monitoring of differences in serial laboratory results. , 2011, Clinical chemistry.

[15]  J O Hoeke,et al.  Evaluation of techniques for the presentation of laboratory data: support of pattern recognition. , 2000, Methods of information in medicine.

[16]  Andrew R. Post,et al.  Temporal data mining. , 2008, Clinics in laboratory medicine.

[17]  J. Baron,et al.  Computerized provider order entry in the clinical laboratory , 2011, Journal of pathology informatics.

[18]  Arthur A. Eggert,et al.  The Combination of Specimen Tracking with an Advanced AutoLog in a Laboratory Information System , 2004, Journal of Medical Systems.

[19]  David W Bates,et al.  Communicating critical test results: safe practice recommendations. , 2005, Joint Commission journal on quality and patient safety.

[20]  Sylvia Schleutermann,et al.  Medical Expert Systems Developed in j.MD, a Java Based Expert System Shell Application in Clinical Laboratories , 2004, MedInfo.

[21]  Maurice O'Kane The reporting, classification and grading of quality failures in the medical laboratory. , 2009, Clinica chimica acta; international journal of clinical chemistry.

[22]  G. Smythe,et al.  REPCAT: desktop expert system for interpreting and validating laboratory data for pheochromocytoma diagnosis with the database application Omnis 7. , 1997, Clinical chemistry.

[23]  K E Blick Decision-making laboratory computer systems as essential tools for achievement of total quality. , 1997, Clinical chemistry.

[24]  C G Fraser,et al.  Quality goals in external quality assessment are best based on biology. , 1993, Scandinavian journal of clinical and laboratory investigation. Supplementum.

[25]  Callum G. Fraser,et al.  Biological Variation: From Principles to Practice , 2001 .

[26]  Mahadev Satyanarayanan,et al.  Handheld computing in pathology , 2012, Journal of pathology informatics.

[27]  Maurice O' Kane,et al.  The reporting, classification and grading of quality failures in the medical laboratory. , 2009 .

[28]  Mark A. Hoffman,et al.  Electronic medical records and personalized medicine , 2011, Human Genetics.

[29]  X Fuentes-Arderiu,et al.  Evaluation of the VALAB expert system. , 1997, European journal of clinical chemistry and clinical biochemistry : journal of the Forum of European Clinical Chemistry Societies.

[30]  Fatih Basçiftçi,et al.  Design of Web-Based Fuzzy Input Expert System for the Analysis of Serology Laboratory Tests , 2011, Journal of Medical Systems.

[31]  D. Burnett ISO 15189:2003 – Quality management, evaluation and continual improvement , 2006, Clinical chemistry and laboratory medicine.

[32]  Greg Strylewicz,et al.  Detecting Blood Laboratory Errors Using a Bayesian Network , 2011, Medical decision making : an international journal of the Society for Medical Decision Making.

[33]  George C. Anastassopoulos,et al.  Genetic algorithm pruning of probabilistic neural networks in medical disease estimation , 2011, Neural Networks.

[34]  J H van Bemmel,et al.  Assessment of Decision Support for Blood Test Ordering in Primary Care , 2001, Annals of Internal Medicine.

[35]  Paul Dexter,et al.  Concept and Development of a Discharge Alert Filter for Abnormal Laboratory Values Coupled With Computerized Provider Order Entry: A Tool for Quality Improvement and Hospital Risk Management , 2012, Journal of patient safety.

[36]  Y. Hsieh,et al.  Significant reduction of laboratory specimen labeling errors by implementation of an electronic ordering system paired with a bar-code specimen labeling process. , 2010, Annals of emergency medicine.

[37]  Patrice Courvalin,et al.  Expert Systems in Clinical Microbiology , 2011, Clinical Microbiology Reviews.

[38]  David T. Bauer,et al.  The design and evaluation of a graphical display for laboratory data , 2010, J. Am. Medical Informatics Assoc..

[39]  Seung Hwan Lee,et al.  A New Specimen Management System Using RFID Technology , 2011, Journal of Medical Systems.

[40]  Mario Plebani,et al.  Towards quality specifications in extra-analytical phases of laboratory services: What information on quality specifications should be communicated to clinicians, and how? , 2006 .

[41]  David W Bates,et al.  Linking laboratory and pharmacy: opportunities for reducing errors and improving care. , 2003, Archives of internal medicine.