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Developing pharmacy applications using a microcomputer relational database in a long-term care psychiatric hospital.

The database applications developed with a microcomputer for a 1000 bed long-term care forensic psychiatric care hospital are described. The implementation of a microcomputer system was instituted as an interim measure prior to the development of a hospital wide minicomputer system. Primary emphasis was placed on increasing the efficiency of professional staff while enhancing clinical therapeutic monitoring. The system operates on an IBM-AT with 30 megabyte hard disk drive and an Epson FX-100 dot matrix printer. A relational database manager, Team-Up, was utilized in the development of applications that included census maintenance, scheduled drug inventory, drug regimen review, drug utilization protocols and a skilled nursing unit dose patient profile. Other ancillary functions included generation of stock labels, a literature abstract database and an on-line policy and procedure manual. Advantages of the system include an increase in staff productivity through the use of information that is readily attainable from the patient database. Possible disadvantages are the programming and hardware limitations imposed by a microcomputer system. Long term care psychiatric facilities may be able to enhance staff efficiency by computerizing existing manual systems. Because of the diverse and specialized requirements of long term care facilities, a microcomputer used in conjunction with a programmable relational database can be easily customized to fulfill this need.

California↗

Design and implementation of a World Wide Web teaching files database on diagnostic radiology.

INTRODUCTION: The aim of this project was to demonstrate the feasibility and effectiveness of a teaching files database on diagnostic radiology accessible via the Internet and the World Wide Web. The Italian experience in developing a national database named "RadioDB" is presented. MATERIALS AND METHODS: "RadioDB" is sponsored by the Italian Society of Radiology (SIRM) and is based on a multicenter academic collaboration. It constitutes a collection of multimedia case record and teaching files. "RadioDB" is based on a Pentium workstation running a Structured Query Language (SQL) database and a World Wide Web server. Each case record contains at least one radiological image and a text file for case comment with key words and codes from the American College of Radiology (ACR). In most cases, a complete teaching file is also available. Peer reviewed teaching files available on this server are contributed via anonymous file transfer protocol (FTP) through the Internet from various Italian academic Departments of Radiology. RESULTS: Worldwide users can easily access and search "RadioDB" database through a World Wide Web query interface and retrieve on-the-fly case record and teaching files. Users can search the database by author name, description, key words, free text or ACR codes. CONCLUSIONS: "RadioDB" enlarges the base of current off-line educational materials offering and it allows radiologists to improve their medical education.

Education, Medical, Continuing↗

Seven years experience with a computerized diabetes clinic database.

With the emergence of information technology applications in medicine, a computerized medical record system that could be used to : (1) maintain patients' clinical records over time, (2) communicate with referring practitioners, and (3) form the basis of a potential research database of information, was sought. In 1987, we developed such a clinical database to register patients attending our busy Diabetes Clinic, now seeing in excess of 300 new referrals and, on average, 3,000 clinic visits per year. Baseline demographic data, clinical history, and examination and investigation results are recorded. We also record diabetes therapy and other medication dosage and changes, monitor follow-up, assess health outcome information (such as stroke or amputation), and generate results, summaries, and reports to referring practitioners and other health professionals. We now have almost seven years of experience using the system. Initially established on a single PC with paper-based data collection and subsequent data entry (running as a DOS application), it is now established on a PC Local Area Network [LAN] with terminals in the clinic consultation rooms enabling direct data entry and allowing patients to view their results in graphic form on screen. From its inception, the Diabetes Clinic Database System has maintained patient demographic and clinical data (which facilitates efficient clinic management) with patient clinic lists and adhesive address labels generated from appropriate menus. Batch mode processing produces daily work sheets which facilitate the running of clinics as well as ad hoc, daily, and weekly reports for all patients (as required). This expedites correspondence with referring doctors. A quality assurance report to the clinic doctor highlights missing clinical information which must be obtained in order to ensure data completeness. The initial system was relatively inefficient in that it required data entry following patient consultation and provided no immediate feedback to patients themselves. In January 1994, to address these deficiencies, the system was established on a PC LAN (running under Novell); it provided on-line data entry within the clinic setting and enabled patients to participate in the recording of their information, observe their own progress by way of on-screen graphs (e.g., blood sugar control, weight, cholesterol), and receive hand-held summaries generated immediately following the clinic visit. Batch programs generate hard copies of this data to be filed in medical records. Two major assessments of the system have been undertaken. In February 1990, we undertook a survey of Local Doctors with 5 or more patient referrals on the system; this resulted in a pleasing 66% response rate. There was an almost universal acceptance and indeed a significant preference for this system over 'traditional' letters. In January 1994, following the introduction of the system onto the PC LAN for direct data entry in the clinic setting, we assessed (by anonymous questionnaire at the end of the consultation) patient attitudes towards these changes. The development of the CRS Diabetes Clinic Database System has improved our approach to diabetes outpatient care and our communication with other health professionals. It has the added benefit of providing a database of information that is suitable to address critical clinical research issues in diabetes management. This system provides an acceptable blend of information technology and clinical medicine, redesigning and enhancing the way we deliver medical care to patients with diabetes. Involving the patient in the collection and interpretation of their clinical data via a computer system (as utilized within our clinical unit), is both acceptable to the patient and her referring doctor. Ongoing system refinement and assessment remains integral to our use of information technology.

Australia↗

MONI: an intelligent database and monitoring system for surveillance of nosocomial infections.

Recording, recognition, and prevention of nosocomial infections are the primary responsibilities of the hospital infection control unit. To perform these tasks, this unit needs information from diverse sources--the patient's symptoms and signs, microbiological and virological test results, and information regarding antibiotics and treatment come from different levels of healthcare delivery. Because of the large amount of data (e.g., about 300 microbiological requests daily) a computer system is required to store this information and to provide a means for subsequent evaluation. MONI (Monitoring of nosocomial infections) is an intelligent database and monitoring system for surveillance and detection of nosocomial infections. Data can be entered into the system manually as well as transferred automatically from external information systems. The central feature of the system is the automatic detection of and calling attention to conditions that may be a detriment to patient recovery, such as possible hospital-acquired infections, risk factors, diseases to be reported, etc. By using this system, we seek to reduce the frequency of infection and the frequency of nosocomial deaths by improving the quality of patient treatment, shortening the length of stay in a hospital, and the use of fewer and/or cheaper antibiotics. MONI provides a means to access relevant medical data (names of infectious agents, antibiotics, department names, monitoring rules, etc.) from a library. This library can be updated or otherwise modified, even during use. An infection control team using this system can customize it to suit the demands of that particular unit. Automatic data transfer from external information systems is made possible by tables that translate between different code systems. The system also offers flexibility; the program can be configured to adapt it for use in other hospitals and institutions. The core element of MONI is the monitoring module, which is implemented as a layer between data input and the database. Upon data acquisition, the system checks the input against several monitoring tools and alerts the user to matches, which may indicate an infection risk. Processing of a rule may be deferred, depending on complexity of the rule and the actual and estimated workload of the system. Examples of the monitoring guidelines are: (1) suspicion of nosocomial infection; (2) infection at a normally sterile site; (3) infection due to bacteria with unusual antibiotic sensitivity patterns; (4) lab report indicates that patient is treated with ineffective antibiotic; (5) possible choice for less expensive antibiotic; (6) infection which is required to be reported to state and/or health authorities; (7) patients receiving prophylactic antibiotics longer than medically indicated; and (8) infections of two or more patients in different wards with the same bacteria (cf. Evans 85). The MONI system was developed at one of the largest hospitals in Europe, the Vienna General Hospital (2,200 beds). This facility serves as the teaching hospital of the University of Vienna Medical School. The size of the hospital and the large amount of data made it necessary to introduce such a system into clinical routine. MONI was programmed in C and C++ with a state-of-the-art graphical user interface (Presentation Manager, Workplace Shell) for OS/2. IBM Database 2 for OS/2 (dB 2/2) was used in constructing the database. The layer between the database and the monitoring application is driven by the multitasking and interprocess communication abilities of OS/2. A pen-based support system that assists in mobile data acquisition is currently under development.

Anti-Bacterial Agents↗

[French pharmacovigilance database system: examples of utilisation].

UNLABELLED: The French drug surveillance (pharmacovigilance) system is based on a network of 31 regional centres which receive adverse drug reaction (ADR) reports from health professionals and are drug information centers. Cases are entered into a common database, with causality scores. This database contains large amounts of data, which may be used for pharmaco-epidemiological studies. As an example, all cases in which an antihypertensive drug, suspect or not, was cited were identified. ACE-inhibitor cough was also explored. RESULTS: Since 1985, > 70,000 case reports have been entered into the database. 63 per cent were reported by specialists, 20 per cent by GPs. 54 per cent came from University Hospitals, 21 per cent from private practice. The most numerous age group was 60 to 69. The overall sex ratio (F/M) was 1.28, the female preponderance being most marked at < 39 and > 70 years of age. 43 per cent took only one drug, 20 per cent two drugs, 13.4 per cent three, and 24 per cent > three drugs. The most frequently reported effects concerned the skin and appendages (15 per cent), general status and central nervous system (9.5 per cent each), platelets, liver, and GI systems (6 per cent each). Outcome was favourable in 74 per cent. Dechallenge was positive in 71 per cent, rechallence in 6 per cent. 3.4 per cent of the patients died; in 2.2 per cent death was related to a reaction. Causality assessment indicated close temporal relationship (C2 or C3) in 69 per cent of cases; in 51 per cent of cases, no other obvious cause was found. 66 per cent of the reactions were labelled when reported. The database could also be used to explore drug utilisation: as an example, we studied the age and sex distribution of reports containing antihypertensive drugs, irrespective of their possible causal role in the reaction. Antihypertensives were mentioned in 14 per cent of the reports. The age distribution was skewed towards greater age, with a maximum of 70 years. F/M was 1.57, with more M use < 20 and 30-59, whereas F were more common between 20-29 and 60 years. beta-blockers were more often associated with patients under 70, whereas above 70 diuretics and centrally acting antihypertensive drugs were more often reported. This could be related to greater use or worse tolerance of these drugs. As an example of the exploration of a specific drug-reaction relationship, we explored the relationship between the use of ACE inhibitors (ACEI) and cough. ACE inhibitors were present in 6 per cent of cases, but in 75 per cent of reports of cough. F/M was 1.29 (NS) for all reports concerning ACEI, 1.28 for cough unrelated to ACEI, 2.1 for cough with ACEI (P < 0.05). Cough was present in 12 per cent of all reports concerning ACEI. There was no clear difference between ACEI for cough or sex ratio; women cough more with ACEI. This does not seem related to greater ACEI use by women or to greater sensitivity of women to cough. The reason for this sex difference remains to be explained. There are large amounts of essentially underutilized data in drug surveillance databases. How they can or should be used remains to be validated.

Adult↗

SQLGEN: a framework for rapid client-server database application development.

SQLGEN is a framework for rapid client-server relational database application development. It relies on an active data dictionary on the client machine that stores metadata on one or more database servers to which the client may be connected. The dictionary generates dynamic Structured Query Language (SQL) to perform common database operations; it also stores information about the access rights of the user at log-in time, which is used to partially self-configure the behavior of the client to disable inappropriate user actions. SQLGEN uses a microcomputer database as the client to store metadata in relational form, to transiently capture server data in tables, and to allow rapid application prototyping followed by porting to client-server mode with modest effort. SQLGEN is currently used in several production biomedical databases.

Computer Communication Networks↗

SNOMED-encoded surgical pathology databases: a tool for epidemiologic investigation.

Pathology departments have invested considerable energy, sometimes extending over several decades, toward coding their anatomic pathology reports. As a result of these labors, there is now a vast amount of electronically coded data from surgical pathology reports, holding a wealth of information relevant to virtually every recognized pathologic entity. The original intent of the Systematized Nomenclature of Medicine (SNOMED) was to prepare population-based disease data from pathology reports, but no such studies have emerged in the medical literature. This is due in part to the nonuniform, idiosyncratic, and incomplete manner in which most SNOMED databases are constructed. Automatic (computer-driven) coding provides uniformity and completeness of SNOMED databases and offers the possibility of customized recoding for an entire collection of reports using any nomenclature and any set of coding algorithms. In prior investigations, we described a computer program that SNOMED-codes surgical pathology reports, and we provided an analysis of a large surgical pathology SNOMED database. In this report, we describe the importance of coded surgical pathology databases for research, teaching, hospital administration, and public health, and we explain the functional differences between coded databases and free-text collections of surgical pathology data. Surgical pathology departments and vendors of laboratory information systems can ensure that surgical report files can be automatically coded or recoded with any chosen nomenclature by adhering to simple guidelines.

Disease↗

Validation of the advanced dynamic anthropomorphic manikin (ADAM) database: horizontal sled test.

As the U.S. Air Force (USAF) continues to introduce advanced technology to make its planes more dynamic, it is becoming increasingly more difficult to adequately test the systems to ensure pilot safety. A cost effective solution to this problem is the use of computer modeling to augment testing. The accuracy of such computer modeling depends on the validity of the analytical formulation, and the correctness of the database characterizing the systems being modeled. One such database is for the large Advanced Dynamic Anthropomorphic Manikin (ADAM); a human surrogate developed by the USAF for high speed ejection testing. The database is used in the Articulated Total Body (ATB) computer model utilized by the Armstrong Laboratories to predict human body dynamics during aircraft crashes and emergency escapes. The large ADAM database, and the parameters from a horizontal sled test were used in an ATB sled simulation. The results of the ATB simulation are compared with actual sled test data. These results include head, chest, and pelvis accelerations; neck and lumbar loads; and elbow, knee, hip and shoulder angular motion. The comparisons are the basis for validating the ADAM database for future predictive simulations.

Acceleration↗

[A computerized database for managing otorhinolaryngologic oncology patients].

In recent years the management and interdisciplinary treatment of oncological patients has become extremely complex due to the progress made in diagnosis and therapy. As a result, the knowledge required to treat patients can no longer be simply memorized or manually filed. Computer technology provides the ideal instrument for organizing, saving and analyzing data from head and neck tumor patients. The authors have prepared a computerized database to meet the following needs: ease of use, even for non computer savvy users; minimal ambiguity for data entry; use for both clinical and scientific purposes; possibility to create a network with similar database at other Centers; possibility to expand to include image management. The archive is based on a personal computer with an INTEL 80486 microprocessor, 40 Mb RAM, DOS 6.0. and Windows 3.1. The software includes four main routines: a) formulation and management of tables where oncological data are gathered; b) entry and management of patient-related clinical data; c) statistical processing for epidemiological and oncological research and; d) management of basic computer services. In clinical practice the database allows the following: a) preparation of a monthly chart of check-ups, b) rapid tracking of patients lost to followup, c) printout of a summary of the clinical history of each patient at the time of check-up and rapid updating at the end of the examination, d) automatic production of forms such as discharge letters and reports to be shared with related services (i.e. medical oncology, radiotherapy). In addition, the database is a powerful, versatile research tool which can promptly provide all sorts of oncological data and can automatically prepare tables, diagrams, correlations, survival curves. The system was developed from 1993 to 1995 and has been operative, with a few minor modifications and updates, since 1995. Today the database contains more than 1200 oncological cases and the system is used daily by medical and paramedical personnel alike. Approximately 15 new cases are entered a month and 80 cases updated after follow-up.

Head and Neck Neoplasms↗

Metabolic database systems for the analysis of genome-wide function.

Genome sequencing projects provide an inventory of molecular components for a wide variety of organisms. Metabolic databases integrate these functional descriptions of individual modules into a higher-level characterization of cellular metabolism. This article reviews efforts related to the development of metabolic databases and discusses how such systems have aided the delineation of genome properties. We illustrate the design features of metabolic databases and discuss the challenges facing metabolic as well as databases of other functional type.

Database Management Systems↗

G6PDdb, an integrated database of glucose-6-phosphate dehydrogenase (G6PD) mutations.

G6PDdb (http://www.rubic.rdg.ac.uk/g6pd/ or http://www.bioinf.org.uk/g6pd/) is a newly created web-accessible locus-specific mutation database for the human Glucose-6-phosphate dehydrogenase (G6PD) gene. The relational database integrates up-to-date mutational and structural data from various databanks (GenBank, Protein Data Bank, etc.) with biochemically characterized variants and their associated phenotypes obtained from published literature and the Favism website. An automated analysis of the mutations likely to have a significant impact on the structure of the protein has been performed using a recently developed procedure. The database may be queried online and the full results of the analysis of the structural impact of mutations are available. The web page provides a form for submitting additional mutation data and is linked to resources such as the Favism website, OMIM, HGMD, HGVBASE, and the PDB. This database provides insights into the molecular aspects and clinical significance of G6PD deficiency for researchers and clinicians and the web page functions as a knowledge base relevant to the understanding of G6PD deficiency and its management.

Databases, Genetic↗

VSD: a database for schizophrenia candidate genes focusing on variations.

Schizophrenia is a common mental disease characterized by delusions, hallucinations, and formal thought disorder. It has been demonstrated with genetic evidence that the disease is a polygenic disorder. Pharmacological, neurochemical, and clinical studies have suggested a number of schizophrenia susceptibility loci. In order to systematically search for genes with small effect in the development of schizophrenia, a database called VSD was established to provide variation data for publicly available candidate genes. Most of the genes encode neurotransmitter receptors, neurotransmitter transporters, and the enzymes involved in their metabolism. Other candidate genes extracted from published literature are also included. The variation information has been collected from publicly available mutation and polymorphism databases such as dbSNP, HGVbase, and OMIM, with single nucleotide polymorphism (SNP) being the most abundant form of collected variations. Reference sequences from NCBI's RefSeq database are used as references when positioning variation at transcript and protein levels. The nonsynonymous SNPs (nsSNPs) that lead to amino acid changes in the functional sites or domains of proteins are distinguished since they are more likely to affect protein function and would be target SNPs for association studies. In addition to variation data, gene descriptions, enzyme information, and other biological information for each gene locus are also included. The latest version of VSD contains 23,648 variations assigned to a total of 186 genes. Five-hundred eighty-eight domains and sites annotated in the SWISS-PROT and InterPro databases are found to contain nsSNPs. VSD may be accessed via the World Wide Web (www.chgb.org.cn/vsd.htm) and will be developed as an up-to-date and comprehensive locus-specific resource for identifying susceptibility genes for schizophrenia.

Databases, Nucleic Acid↗

LOVD: easy creation of a locus-specific sequence variation database using an "LSDB-in-a-box" approach.

The completion of the human genome project has initiated, as well as provided the basis for, the collection and study of all sequence variation between individuals. Direct access to up-to-date information on sequence variation is currently provided most efficiently through web-based, gene-centered, locus-specific databases (LSDBs). We have developed the Leiden Open (source) Variation Database (LOVD) software approaching the "LSDB-in-a-Box" idea for the easy creation and maintenance of a fully web-based gene sequence variation database. LOVD is platform-independent and uses PHP and MySQL open source software only. The basic gene-centered and modular design of the database follows the recommendations of the Human Genome Variation Society (HGVS) and focuses on the collection and display of DNA sequence variations. With minimal effort, the LOVD platform is extendable with clinical data. The open set-up should both facilitate and promote functional extension with scripts written by the community. The LOVD software is freely available from the Leiden Muscular Dystrophy pages (www.DMD.nl/LOVD/). To promote the use of LOVD, we currently offer curators the possibility to set up an LSDB on our Leiden server.

Computational Biology↗

Formal representation of summary tables for health care statistical database management.

There is an ever-increasing demand for statistical information in health-care societies, and voluminous statistics are collected every year. When one needs information on survey results, it is generally not allowed to access the original data, and the summary tables are the most important source of information which can be shared. In order to store summary tables as a well-organized database and to perform flexible retrieval, a formal study has been made on the structure of summary tables. We introduce the notion of summary table scheme and define the operations called table transformation. A statistical database management system has been implemented based on the study. In our study, a statistical database is a collection of summary tables obtained from a survey. If a survey is conducted periodically, a database consists of all the tables obtained in the past. System utilities have been implemented for handling time-oriented information.

Algorithms↗

A framework for querying a database for structural information on 3D images of macromolecules: A web-based query-by-content prototype on the BioImage macromolecular server.

Nowadays we are experiencing a remarkable growth in the number of databases that have become accessible over the Web. However, in a certain number of cases, for example, in the case of BioImage, this information is not of a textual nature, thus posing new challenges in the design of tools to handle these data. In this work, we concentrate on the development of new mechanisms aimed at "querying" these databases of complex data sets by their intrinsic content, rather than by their textual annotations only. We concentrate our efforts on a subset of BioImage containing 3D images (volumes) of biological macromolecules, implementing a first prototype of a "query-by-content" system. In the context of databases of complex data types the term query-by-content makes reference to those data modeling techniques in which user-defined functions aim at "understanding" (to some extent) the informational content of the data sets. In these systems the matching criteria introduced by the user are related to intrinsic features concerning the 3D images themselves, hence, complementing traditional queries by textual key words only. Efficient computational algorithms are required in order to "extract" structural information of the 3D images prior to storing them in the database. Also, easy-to-use interfaces should be implemented in order to obtain feedback from the expert. Our query-by-content prototype is used to construct a concrete query, making use of basic structural features, which are then evaluated over a set of three-dimensional images of biological macromolecules. This experimental implementation can be accessed via the Web at the BioImage server in Madrid, at http://www.bioimage.org/qbc/index.html.

Animals↗

[Adonco. A clinical-scientific database system for the acquisition and analysis of oncologic data in head and neck regions].

BACKGROUND: Our aim was to design and develop a computer database system for head and neck cancer patients for clinical and scientific use. METHODS: A relational database based on Filemaker Pro 6.0 was developed and integrated into our local network. Its precise and easy to handle interface should allow a quick overview of the patient's oncological data. An automatically generated letter was integrated to enhance patient care. For evaluation purposes, statistical analysis functions were incorporated. RESULTS: Over a 7 month period, about 300 patient records were available through the local network. The automated letter function and the well organized display resulted in more efficient patient care. Additionally, the quality of the information presented to referring physicians increased. Statistical analysis provided by the database was reliable and easy to export. CONCLUSIONS: We developed an oncology database for clinical and scientific use and integrated it into our patient documentation system. The combination of clinical and scientific features proved to be very effective in daily patient care routine and research.

Algorithms↗

Panel of human cancer cell lines provides valuable database for drug discovery and bioinformatics.

Studies conducted at the US National Cancer Institute (NCI) and in our laboratory show that databases including the drug sensitivities of panels of many human cancer cell lines provide valuable information on the molecular pharmacology of anticancer drugs. We established a panel of 39 cell lines of various human cancers and developed a database of their chemosensitivities. Drugs were profiled in terms of their "fingerprints", patterns of differential activity against the cell lines. There was a significant correlation between a drug's fingerprint and its mode of action, as observed in the NCI panel of 60 cell lines. Therefore our cell-line panel is a powerful tool to predict the modes of action of new compounds. We have been using this system for drug discovery, coupled with various target-based drug screenings. We used the system to identify a novel DNA minor-groove binder, MS-247, which has inhibitory activity against topoisomerases I and II, and potent in vivo antitumor activity against various human cancer xenografts. We also discovered a potent novel telomerase inhibitor, FJ5002, by mining our database with the COMPARE algorithm, followed by experimental validation. We investigated the gene expression profiles of the cell lines by using DNA microarrays to find profiles determining cellular chemosensitivity and new targets for anticancer drugs. Our integrated database, including the chemosensitivities and gene expression profiles of the cell-line panel, could provide a basis for drug discovery and personalized therapy.

Databases, Factual↗

A visual query-by-example image database for chest CT images: potential role as a decision and educational support tool for radiologists.

Primary reading or further evaluation of diagnostic imaging examination often needs a comparison between the actual findings and the relevant prior images of the same patient or similar radiological data found in other patients. This support is of clinical importance and may have significant effects on physicians' examination reading efficiency, service-quality, and work satisfaction. We developed a visual query-by-example image database for storing and retrieving chest CT images by means of a visual browser Image Management Environment (IME) and tested its retrieval efficiency. The visual browser IME included four fundamental features (segmentation, indexing, quick load and recall, user-friendly interface) in an integrated graphical environment for a user-friendly image database management. The system was tested on a database of 2000 chest CT images, randomly chosen from the digital archives of our institutions. A sample of eight heterogeneous images were used as queries and, for each of them a team of three expert radiologists selected the most similar images from the database (a set of 15 images containing similar abnormalities in the same position of the query). The sensitivity and the positive predictive factor, both averaged over the 8 test queries and 15 answers, were respectively 0.975 and 0.91 The IME system is currently under evaluation at our institutions as an experimental application. We consider it a useful work-in-progress tool for clinical practice facilitating searches for a variety of radiological tasks.

Database Management Systems↗