Toward hospitals without paper.
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Hospital Information Systems↗
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Identification of key concepts in biomedical literature using a modified Markov heuristic.
MOTIVATION: The recent explosion of interest in mining the biomedical literature for associations between defined entities such as genes, diseases and drugs has made apparent the need for robust methods of identifying occurrences of these entities in biomedical text. Such concept-based indexing is strongly dependent on the availability of a comprehensive ontology or lexicon of biomedical terms. However, such ontologies are very difficult and expensive to construct, and often require extensive manual curation to render them suitable for use by automatic indexing programs. Furthermore, the use of statistically salient noun phrases as surrogates for curated terminology is not without difficulties, due to the lack of high-quality part-of-speech taggers specific to medical nomenclature. RESULTS: We describe a method of improving the quality of automatically extracted noun phrases by employing prior knowledge during the HMM training procedure for the tagger. This enhancement, when combined with appropriate training data, can greatly improve the quality and relevance of the extracted phrases, thereby enabling greater accuracy in downstream literature mining tasks.
Abstracting and Indexing↗
Local electronic storage of radiological studies for radiosurgery.
OBJECTIVE: Although radiosurgical practice mandates meticulous radiological follow-up, even the most efficient radiology department can be overwhelmed by the large number of radiosurgical patients who have undergone diagnostic studies for many years at many different institutions to follow many separate lesions. Although the task of assembling these studies is theoretically possible, because they are spread out in time and space, it is often impractical. We therefore sought to construct a computer-based system that could store images from multiple sources and present them instantly for review. METHODS: We attached a flatbed film scanner to a standard desktop computer in our clinic and scanned selected sheets of film into an image database at each visit of a radiosurgical patient. "Low-tech" solutions were deliberately chosen-that is, to enhance ease and software compatibility, we used the operating system's directory structure for organization of data instead of proprietary software. Standard commercially available software was used to review studies that had been previously scanned. RESULTS: During a 2- to 3-year period, images were scanned from 1129 studies performed on 435 patients. Images could be reviewed instantly and compared with current studies, and scanning a single piece of film required approximately 30 seconds. We estimate that the current capacity of our computer memory will satisfy our needs for approximately 12 years. CONCLUSION: Assembly of an efficient and inexpensive system for image storage and retrieval suitable for radiosurgical practice is feasible and straightforward. Although our system is not a substitute for a radiology department, it obviates the constant frustration of "finding the films" and has become an essential part of our radiosurgical practice.
Brain Diseases↗
Impact of PACS deployment strategy on dictation turnaround time of chest radiographs.
RATIONALE AND OBJECTIVES: The aim of the study is to measure the impact of a picture archive and communication system (PACS) on dictation turnaround time of chest radiographs in a multisite hospital and relate variations across sites to local factors and implementation strategy. MATERIALS AND METHODS: The multisite hospital is composed of three sites. Dictation turnaround time was calculated by using data obtained from the radiology information system for examinations performed during three 90-day periods (immediately before PACS implementation, immediately after PACS implementation, and 1 year after implementation). Productivity, expressed as number of examinations dictated per full-time-equivalent radiologist, also was calculated. For each 3-month period, average interval delay was calculated. Values for average interval delay obtained during the different pre- and post-PACS periods were compared by using analysis of variance. This was done for each hospital. RESULTS: In the immediate post-PACS period at site 1, dictation turnaround time decreased 5% (P < .05), whereas productivity decreased 16.5%. The implementation strategy was revised for the next two sites, and dictation turnaround time decreased 21% (P < .001) in both sites in the immediate post-PACS period. Productivity increased 2% and 3% in these sites. One year after implementation, decreases in turnaround ranged from 28% to 55% (P < .001) in the three sites. CONCLUSION: Our experience suggests that PACSs cannot be isolated from their contexts; therefore, implementation strategy matters in the realization of projected benefits. In addition, regardless of differences in film-based environments before PACS, all three sites benefited from conversion to filmless operation, with the greatest benefits seen in the site that was least efficient before implementation.
Canada↗
A multiple-hospital anaesthetic problem register: establishment of a regionally organized system for facilitated reporting of potentially recurring anaesthetic-related problems.
A regionally organized system aiming to facilitate reporting and retrieval of information about potentially recurring anaesthetic-related problems has been established, covering 20 separate hospitals. Components of the system include a reporting package to facilitate use by anaesthetists in busy clinical practice; centralized clerical support; supervision by anaesthetists; reports and laminated cards supplied to the patient; and a permanently accessible database. A new classification system for difficulties in airway management has been developed as part of the system. After initial establishment, the system has been utilized by a broad cross-section of anaesthetists in the region. The first 350 reports are described. The reporting rate is approximately 0.3% of all anaesthetics given in the region. We believe the success of this system has been primarily due to features aiming to facilitate reporting, "local" ownership and supervision by clinical anaesthetists.
Anesthesia↗
Terminology-driven literature mining and knowledge acquisition in biomedicine.
In this paper we describe Tagged Information Management System (TIMS), an integrated knowledge management system for the domain of molecular biology and biomedicine, in which terminology-driven literature mining, knowledge acquisition (KA), knowledge integration (KI), and XML-based knowledge retrieval are combined using tag information management and ontology inference. The system integrates automatic terminology acquisition, term variation management, hierarchical term clustering, tag-based information extraction (IE), and ontology-based query expansion. TIMS supports introducing and combining different types of tags (linguistic and domain-specific, manual and automatic). Tag-based interval operations and a query language are introduced in order to facilitate KA and retrieval from XML documents. Through KA examples, we illustrate the way in which literature mining techniques can be utilised for knowledge discovery from documents.
Artificial Intelligence↗
Trends in medical information retrieval on Internet.
Information on the World Wide Web is unstructured, distributed, multimedia and multilingual. Many tools have been developed to help users search for useful information: subject hierarchies, general search engines, browsers and search assistants. Although helpful, they present serious limitations, mainly in terms of precision, multilingual indexing and distribution. In this paper, we cover some on-line solutions to medical information discovery and present our own approach, the MARVIN (multi-agent retrieval vagabond on information network) project, which tackles medical information research with specialized cooperative retrieval agents. We also draw some outlines for future extensions.
Computer Systems↗
Using structured text and templates to capture health status outcomes in the electronic health record.
BACKGROUND: Because of the difficulty of implementing clinical outcomes-focused quality improvement (QI) projects, most organizations' efforts and comparative quality report cards have centered on structure and process indicators or on outcomes captured in administrative data systems. Ultimately, however, health care is intended to improve health. Health status is now frequently included in the set of quality of care information requested by purchasers of health care, accrediting and governmental agencies, and consumer groups. Subsequently, users of electronic health record (EHR) systems are demanding that the EHR support the collection and comparative analysis of health status information over time and by clinical population and provider. APPROACH: As opposed to the current practice in most organizations of collecting health status data via an annual mail survey, the approach discussed in this article utilizes standardized coding and classification (SCC) systems and standardized surveys to capture health status information in the EHR during the routine course of care delivery through the use of templates built on structured text. This method is illustrated with examples from the WAVE EHR. The EHR-based structured text and template approach facilitates the incorporation of health status measurement into the documentation of the patient-provider encounter, builds on recognized SCC systems and standardized surveys, and enables information retrieval for a variety of analyses, including those focused on QI. CONCLUSIONS: Health status outcomes are an essential component of an information set focused on health care quality. To routinely capture and analyze health status variables, SCC systems and standardized health status surveys are necessary.
Forms and Records Control↗
Using argumentation to retrieve articles with similar citations: an inquiry into improving related articles search in the MEDLINE digital library.
The aim of this study is to investigate the relationships between citations and the scientific argumentation found abstracts. We design a related article search task and observe how the argumentation can affect the search results. We extracted citation lists from a set of 3200 full-text papers originating from a narrow domain. In parallel, we recovered the corresponding MEDLINE records for analysis of the argumentative moves. Our argumentative model is founded on four classes: PURPOSE, METHODS, RESULTS and CONCLUSION. A Bayesian classifier trained on explicitly structured MEDLINE abstracts generates these argumentative categories. The categories are used to generate four different argumentative indexes. A fifth index contains the complete abstract, together with the title and the list of Medical Subject Headings (MeSH) terms. To appraise the relationship of the moves to the citations, the citation lists were used as the criteria for determining relatedness of articles, establishing a benchmark; it means that two articles are considered as "related" if they share a significant set of co-citations. Our results show that the average precision of queries with the PURPOSE and CONCLUSION features is the highest, while the precision of the RESULTS and METHODS features was relatively low. A linear weighting combination of the moves is proposed, which significantly improves retrieval of related articles.
Abstracting and Indexing↗
Journal searching in non-MEDLINE resources on Internet Web sites.
Internet access to the medical journal literature is absorbing the attention of all relevant parties, i.e., publishers, journal vendors, librarians, commercial providers, government agencies, and end users. Journal content on the Web sites spans the range from advertising and ordering information for the print version, to table of contents and abstracts, to downloadable full text and graphics of articles. The searching parameters for systems other than MEDLINE also differ extensively with a wide variety of features and resulting retrieval. This discussion reviews a selection of providers of medical information (particularly the journal literature) on the Internet, making a comparison of what is available on Web sites and how it can be searched.
Computer Communication Networks↗
Some unintended consequences of information technology in health care: the nature of patient care information system-related errors.
Medical error reduction is an international issue, as is the implementation of patient care information systems (PCISs) as a potential means to achieving it. As researchers conducting separate studies in the United States, The Netherlands, and Australia, using similar qualitative methods to investigate implementing PCISs, the authors have encountered many instances in which PCIS applications seem to foster errors rather than reduce their likelihood. The authors describe the kinds of silent errors they have witnessed and, from their different social science perspectives (information science, sociology, and cognitive science), they interpret the nature of these errors. The errors fall into two main categories: those in the process of entering and retrieving information, and those in the communication and coordination process that the PCIS is supposed to support. The authors believe that with a heightened awareness of these issues, informaticians can educate, design systems, implement, and conduct research in such a way that they might be able to avoid the unintended consequences of these subtle silent errors.
Communication↗
Automated patient care documentation: what's in it for us? An expert system emergency drug card printout.
This article summarizes experiences to date for a collaborative approach, utilizing systems analysis and decision support methods, to design, develop, and implement automated patient centered documentation. Current manual methods for retrieving patient centered data for treatment activities and evaluation of practice are laborious, frustrating and often uneventful. Accessing specific patient information in an arrest or emergent situation, in the hospital and out patient clinical setting, is fraught with difficulties of data and information availability, reliability, legibility, integrity, security, and obsolescence. Treatment decisions made during an arrest or emergent situation, whether for an in-patient or clinical out patient, utilize Advanced Life Support guidelines and also may vary based on the heuristics of the lead practitioner on duty at the time. Walking the informatics talk of "managing and processing data to information to knowledge" lead to standardization for best practice of emergency drug calculations and treatments (1). An expedient and reliable method for retrieving patient specific data to calculate 26 medications, 3 treatments, and upwards of 40 criteria to consider during an arrest or emergent situation was achieved and implemented, as a by product of height and weight charting, across most all patient care areas at Primary Children's Medical Center in Salt Lake City Utah.
Attitude to Computers↗
Extracting a statistical data matrix from electronic patient records.
This paper describes the processing and transformation of medical data from a clinical database to a statistical data matrix. Precise extraction and linking tools must be available for the desired data to be processed for statistical purposes. We show that flexible mechanisms are required for the different types of users, such as physicians and statisticians. In our retrieval tools we use logical queries based on operands and operators. The paper describes the method and appliance of the operators with which the desired matrix is created through a process of selection and linking. Examples with a Kaplan-Meier function and time-dependent covariables demonstrate how our model is useful for different user groups.
Biometry↗
EMBL-search: a CD-ROM based database query system.
This paper describes a system of generally applicable index files provided on the EMBL sequence databases CD-ROM to facilitate the development of front-end software to the sequence databases available on this CD-ROM. The index files are used by a new versatile and user-friendly database retrieval program for the Apple Macintosh, EMBL-Search, which allows the easy construction of complex database queries. EMBL-Search utilizes cross-reference information contained in the databases to support navigation between different information resources. The ability to run EMBL-Search on a local computer network accessing a shared database CD-ROM makes its use particularly cost effective.
Algorithms↗
The Protein Information Resource: an integrated public resource of functional annotation of proteins.
The Protein Information Resource (PIR) serves as an integrated public resource of functional annotation of protein data to support genomic/proteomic research and scientific discovery. The PIR, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the PIR-International Protein Sequence Database (PSD), the major annotated protein sequence database in the public domain, containing about 250 000 proteins. To improve protein annotation and the coverage of experimentally validated data, a bibliography submission system is developed for scientists to submit, categorize and retrieve literature information. Comprehensive protein information is available from iProClass, which includes family classification at the superfamily, domain and motif levels, structural and functional features of proteins, as well as cross-references to over 40 biological databases. To provide timely and comprehensive protein data with source attribution, we have introduced a non-redundant reference protein database, PIR-NREF. The database consists of about 800 000 proteins collected from PIR-PSD, SWISS-PROT, TrEMBL, GenPept, RefSeq and PDB, with composite protein names and literature data. To promote database interoperability, we provide XML data distribution and open database schema, and adopt common ontologies. The PIR web site (http://pir.georgetown.edu/) features data mining and sequence analysis tools for information retrieval and functional identification of proteins based on both sequence and annotation information. The PIR databases and other files are also available by FTP (ftp://nbrfa.georgetown.edu/pir_databases).
Amino Acid Sequence↗
[Studies on the use of computers at the Department of Urology. 3. Practice of dialysis and auxiliary therapeutic system at the dialysis room].
The recent development of blood purification methods is remarkable. Now the physician can choose a different method and apparatus for blood purification according to the condition of each patient. Unlike the days when a uniform therapeutic method was used on all patients, the method and apparatus used on each patient may differ, and therefore if an inappropriate method or apparatus is used, it may result in a serious medical error. Patients on dialysis are in a pathologic state brought about by the causative disease and that brought about by renal failure which can not be cured by blood purification therapy. Therefore, it is necessary to accumulate a large amount of information on the patient's condition, including tests, and to use them effectively to provide optimum management of the patient. The author developed a system to collect and analyse large amounts of such information by using a microcomputer to help improve the practise of dialysis, and enable more appropriate patient management. The input of this system are basic data on the patient, information relating to dialysis treatment, symptoms of the patient, results of tests, treatment applied etc.; its output are medical bills, drug requisition sheet, dialysis record etc. Simultaneously, the various pieces of information stored by this system can be retrieved as required. The planned objective of this system has been achieved in the past 8 months.
Computers↗
A probabilistic and decision-theoretic approach to the management of infectious disease at the ICU.
The medical community is presently in a state of transition from a situation dominated by the paper medical record to a future situation where all patient data will be available on-line by an electronic clinical information system. In data-intensive clinical environments, such as intensive care units (ICUs), clinical patient data are already fully managed by such systems in a number of hospitals. However, providing facilities for storing and retrieving patient data to clinicians is not enough; clinical information systems should also offer facilities to assist clinicians in dealing with hard clinical problems. Extending an information system's capabilities by integrating it with a decision-support system may be a solution. In this paper, we describe the development of a probabilistic and decision-theoretic system that aims to assist clinicians in diagnosing and treating patients with pneumonia in the intensive-care unit. Its underlying probabilistic-network model includes temporal knowledge to diagnose pneumonia on the basis of the likelihood of laryngotracheobronchial-tree colonisation by pathogens, and symptoms and signs actually present in the patient. Optimal antimicrobial therapy is selected by balancing the expected efficacy of treatment, which is related to the likelihood of particular pathogens causing the infection, against the spectrum of antimicrobial treatment. The models were built on the basis of expert knowledge. The patient data that were available were of limited value in the initial construction of the models because of problems of incompleteness. In particular, detailed temporal information was missing. By means of a number of different techniques, among others from the theory of linear programming, these data have been used to check the probabilistic information elicited from infectious-disease experts. The results of an evaluation of a number of slightly different models using retrospective patient data are discussed as well.
Anti-Bacterial Agents↗
A native XML database design for clinical document research.
Health-care institutions are gaining an increasing interest in exploiting the data that are gathered through electronic medical records. Narrative data, generated by transcription or direct entry, represents a far greater challenge for analytic tasks. Moreover, a small number of institutions are beginning to explore deeper structuring of narrative data using natural language processing (NLP). The data produced by NLP systems has a complex, nested structure. Current electronic medical records do not have the ability to store and retrieve data of this complexity in a suitable way.
Database Management Systems↗