PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 2801622

The laboratory information system as a tool for implementing a strategic plan.

B A Friedman
View original source ↗Export metadata ↓

Abstract

A laboratory information system (LIS) is one of the most important strategic tools at the disposal of the pathologist. To better understand the strategic potential of LIS, a matrix is presented, which illustrates generic computer applications on one axis, a hierarchy of information system impacts on another, and specific LIS applications in each cell. The diagram can be used to assess which applications provide the most strategic leverage in a hospital by adding value to the laboratory information product. One of the most important goals for pathologists in the future will be to assist clinicians in caring for patients in the most efficient and effective manner possible. A state-of-the-art LIS with direct support by a cadre of highly trained personnel is necessary to pursue this goal.

Explore related subjects

Clinical Laboratory Information SystemsDecision Making, Computer-AssistedDecision Support Systems, ManagementEfficiencyHospital DepartmentsInformation SystemsManagement Information SystemsPathology Department, HospitalJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

B A Friedman. 1989. The laboratory information system as a tool for implementing a strategic plan.. https://pubmed.ncbi.nlm.nih.gov/2801622/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2007

Enhancement of claims data to improve risk adjustment of hospital mortality.

CONTEXT: Comparisons of risk-adjusted hospital performance often are important components of public reports, pay-for-performance programs, and quality improvement initiatives. Risk-adjustment equations used in these analyses must contain sufficient clinical detail to ensure accurate measurements of hospital quality. OBJECTIVE: To assess the effect on risk-adjusted hospital mortality rates of adding present on admission codes and numerical laboratory data to administrative claims data. DESIGN, SETTING, AND PATIENTS: Comparison of risk-adjustment equations for inpatient mortality from July 2000 through June 2003 derived by sequentially adding increasingly difficult-to-obtain clinical data to an administrative database of 188 Pennsylvania hospitals. Patients were hospitalized for acute myocardial infarction, congestive heart failure, cerebrovascular accident, gastrointestinal tract hemorrhage, or pneumonia or underwent an abdominal aortic aneurysm repair, coronary artery bypass graft surgery, or craniotomy. MAIN OUTCOME MEASURES: C statistics as a measure of the discriminatory power of alternative risk-adjustment models (administrative, present on admission, laboratory, and clinical for each of the 5 conditions and 3 procedures). RESULTS: The mean (SD) c statistic for the administrative model was 0.79 (0.02). Adding present on admission codes and numerical laboratory data collected at the time of admission resulted in substantially improved risk-adjustment equations (mean [SD] c statistic of 0.84 [0.01] and 0.86 [0.01], respectively). Modest additional improvements were obtained by adding more complex and expensive to collect clinical data such as vital signs, blood culture results, key clinical findings, and composite scores abstracted from patients' medical records (mean [SD] c statistic of 0.88 [0.01]). CONCLUSIONS: This study supports the value of adding present on admission codes and numerical laboratory values to administrative databases. Secondary abstraction of difficult-to-obtain key clinical findings adds little to the predictive power of risk-adjustment equations.

Clinical Laboratory Information Systems↗
PubMed2006

Definition of an XML markup language for clinical laboratory procedures and comparison with generic XML markup.

BACKGROUND: Clinical laboratory procedure manuals are typically maintained as word processor files and are inefficient to store and search, require substantial effort for review and updating, and integrate poorly with other laboratory information. Electronic document management systems could improve procedure management and utility. As a first step toward building such systems, we have developed a prototype electronic format for laboratory procedures using Extensible Markup Language (XML). METHODS: Representative laboratory procedures were analyzed to identify document structure and data elements. This information was used to create a markup vocabulary, CLP-ML, expressed as an XML Document Type Definition (DTD). To determine whether this markup provided advantages over generic markup, we compared procedures structured with CLP-ML or with the vocabulary of the Health Level Seven, Inc. (HL7) Clinical Document Architecture (CDA) narrative block. RESULTS: CLP-ML includes 124 XML tags and supports a variety of procedure types across different laboratory sections. When compared with a general-purpose markup vocabulary (CDA narrative block), CLP-ML documents were easier to edit and read, less complex structurally, and simpler to traverse for searching and retrieval. CONCLUSION: In combination with appropriate software, CLP-ML is designed to support electronic authoring, reviewing, distributing, and searching of clinical laboratory procedures from a central repository, decreasing procedure maintenance effort and increasing the utility of procedure information. A standard electronic procedure format could also allow laboratories and vendors to share procedures and procedure layouts, minimizing duplicative word processor editing. Our results suggest that laboratory-specific markup such as CLP-ML will provide greater benefit for such systems than generic markup.

Clinical Laboratory Information Systems↗