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At least 991 records · Page 55Linked to original sources
PubMed2003

Caring for a febrile child: the quality of Internet information.

AIM: A small study was conducted to evaluate the quality of information on the Internet about caring for a child with fever in order to alert nurses to the variable nature of information on the Internet for their own professional use and to provide advice to their patients. METHODS: Three search engines were used to locate web sites with information about the management of fever. A total of 22 web sites were assessed after duplicate and irrelevant web sites were excluded from the analysis. Each site was evaluated against the criteria: accuracy; currency; source; original source; and disclosure. The web sites were also examined for warnings against potentially dangerous treatments. RESULTS: The quality of information on the Internet about the management of fever varied greatly, but was generally poor. Accuracy was assessed using five recommendations for managing fever and the proportion of web sites that included these recommendations ranged from 5% to 64%. Less than two-thirds of the sites recorded their creation or review dates. A third of the web sites did not carry warnings about potentially dangerous treatments. CONCLUSION: This study's findings highlight the poor quality of health information on the Internet and indicate factors to consider when using the Internet as an information source. Nurses' awareness of the variable quality of information on the Internet will assist them to identify quality information for their own professional practice and knowledge on which to base advice to patients.

Child↗
PubMed1994

Development of standards and data quality control.

Health care expenses represent 6 to 10% of the Gross National Product in most European countries. This budget exceeds by far those devoted to Defence or Education. The rising cost of health care concerns all governments. In each country of the European Community, measures were and will further be taken in order to increase efficiency in the delivery of health care. Recent advances in information technology offer new opportunities to collect, process and exchange data to document health practices. In Belgium the Ministry of Public Health collects uniform medical summaries for all acute care hospital inpatients, while detailed health care activities are documented for each patient through a very precise billing system. The use of Minimal Clinical Data and Minimal Nursing Data Sets in hospitals became mandatory four years ago. The fundaments for any data collection is reliability, no matter what the preconceived aim was.

Belgium↗
PubMed1994

The development of a client application for the collaborative social and medical services system.

This paper describes the design and implementation of a client application for the Baylor College of Medicine Teen Health Clinics. The application is the front end to the Collaborative Social and Medical Services System (CSMSS) under development by Baylor's Medical Informatics and Computing Research Program [8]. The application provides distributed access to an underlying object oriented database system. A process driven and patient centered design will provide staff members with a complete set of services, including forms for data entry and viewing, query, and access management to facilitate efficient and effective delivery of services. Role-specific interfaces will be supplied for clerks, nurses, nurse practitioners, physicians, and social workers. The client application is being designed using object oriented methodologies and technologies with the C++ programming language, and will operate within a Microsoft Windows operating environment utilizing Object Linking and Embedding for application interoperability.

Adolescent↗
PubMed1995

Curriculum of medical informatics and medical technology in the medical faculty.

1. CURRICULUM DESCRIPTION. Twenty years ago, our faculty organized several lessons in a physiology course to inform students about computers. Recently, new courses in informatics were established. In their first year, students take a compulsory course (15 hours=h) of basic computer science (computers databases, networking, and basic non-medical computer software). A special elective course in medical informatics (30h) can be taken in the 4th year (about 20% of students pass tis course). This course includes the following lessons: computers in medicine (2h), scientific information (4h), classification in medicine (2h- including ICD, SNOMED etc.), computer support of clinical decision (2h-calculation principles with demonstration), artificial intelligence (2h), statistical software (2h), hospital information systems (2h), software for practitioners (2h), biosignal and image analysis (4th), computers in pharmacology (2h), computer simulation (2h), support of metabolic care (2h-consultations, risk calculations), and laboratory information systems (2h). The same course, though slightly differences, is used for paramedical students (occupational therapy, health education, and nursing). Medical technology was established in a three year curriculum courses in the 1st year include common courses in electronic devices (60 h), computers and programming (120 h), biophysics (90 h), biomechanics (30 h), and different medical courses (500 h). For the 2nd and 3rd year, 75% of the courses (700 h per year) are technical e.g., medical devices, information systems, signal and picture analysis, laboratory technique, and data protection. 2. CONCLUSION AND PERSPECTIVES. Students of medicine, and some paramedical studies, are able to use computer in their profession after having taken these courses. Bachelors of medical technology find application in biomedical research, hospitals, and medical technology firms.

Curriculum↗
PubMedDate not supplied

Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting.

A qualitative systematic review of textbooks and clinical guidelines identified assessment criteria for initiation of nipple feeds in premature infants cared for in the neonatal intensive care unit (NICU) setting. Using a structured method for text source selection and data extraction, 43 health care texts were systematically reviewed yielding 153 separate statements related to assessing premature infants' feeding readiness. Following this procedure, a pile sort method was conducted wherein an expert neonatal nurse practitioner (NNP) grouped the statements according to similarity in meaning. Ten piles of terms emerged from this process. Each pile was "named," depicting discrete components used when assessing premature infants' readiness for nipple feeding. Using these public data and the private knowledge of the NNP informant, a concept map was constructed to illustrate a framework for decision support development and to examine the map's usefulness for structuring knowledge that will provide input to an intelligent decision support system.

Computational Biology↗
PubMedDate not supplied

Contract negotiation. The basics.

The contractual process for the purchase of a health-care facility information system is a major endeavor for today's informatics practitioners as more facilities purchase information solution from vendors rather than producing proprietary systems. The goal of the contractual process is not simply to protect either party from future litigation but to produce a clearly understood document that outlines the duties and responsibilities of both the organization and the vendor. This document should anticipate and set forth contingencies for problems that may arise in the future. Guidelines are offered to assist nurses who are members of the acquisition team better understand the contract review process.

Contract Services↗
PubMedDate not supplied

Phase II evaluation of clinical coding schemes: completeness, taxonomy, mapping, definitions, and clarity. CPRI Work Group on Codes and Structures.

OBJECTIVE: To compare three potential sources of controlled clinical terminology (READ codes version 3.1, SNOMED International, and Unified Medical Language System (UMLS) version 1.6) relative to attributes of completeness, clinical taxonomy, administrative mapping, term definitions and clarity (duplicate coding rate). METHODS: The authors assembled 1929 source concept records from a variety of clinical information taken from four medical centers across the United States. The source data included medical as well as ample nursing terminology. The source records were coded in each scheme by an investigator and checked by the coding scheme owner. The codings were then scored by an independent panel of clinicians for acceptability. Codes were checked for definitions provided with the scheme. Codes for a random sample of source records were analyzed by an investigator for "parent" and "child" codes within the scheme. Parent and child pairs were scored by an independent panel of medical informatics specialists for clinical acceptability. Administrative and billing code mapping from the published scheme were reviewed for all coded records and analyzed by independent reviewers for accuracy. The investigator for each scheme exhaustively searched a sample of coded records for duplications. RESULTS: SNOMED was judged to be significantly more complete in coding the source material than the other schemes (SNOMED* 70%; READ 57%; UMLS 50%; *p < .00001). SNOMED also had a richer clinical taxonomy judged by the number of acceptable first-degree relatives per coded concept (SNOMED* 4.56, UMLS 3.17; READ 2.14, *p < .005). Only the UMLS provided any definitions; these were found for 49% of records which had a coding assignment. READ and UMLS had better administrative mappings (composite score: READ* 40.6%; UMLS* 36.1%; SNOMED 20.7%, *p < .00001), and SNOMED had substantially more duplications of coding assignments (duplication rate: READ 0%; UMLS 4.2%; SNOMED* 13.9%, *p < .004) associated with a loss of clarity. CONCLUSION: No major terminology source can lay claim to being the ideal resource for a computer-based patient record. However, based upon this analysis of releases for April 1995, SNOMED International is considerably more complete, has a compositional nature and a richer taxonomy. Is suffers from less clarity, resulting from a lack of syntax and evolutionary changes in its coding scheme. READ has greater clarity and better mapping to administrative schemes (ICD-10 and OPCS-4), is rapidly changing and is less complete. UMLS is a rich lexical resource, with mappings to many source vocabularies. It provides definitions for many of its terms. However, due to the varying granularities and purposes of its source schemes, it has limitations for representation of clinical concepts within a computer-based patient record.

Abstracting and Indexing↗
PubMed1999

Informatics and process improvement. The clinical design unit.

Seeking to integrate departments and services, reduce costs, and enhance quality, administrators at a university medical center implemented a clinical design unit. The authors describe the operations of the unit in testing new processes before rollout to the entire center.

Academic Medical Centers↗
PubMed2007

Informatics systems to promote improved care for chronic illness: a literature review.

OBJECTIVE: To understand information systems components important in supporting team-based care of chronic illness through a literature search. DESIGN: Systematic search of literature from 1996-2005 for evaluations of information systems used in the care of chronic illness. MEASUREMENTS: The relationship of design, quality, information systems components, setting, and other factors with process, quality outcomes, and health care costs was evaluated. RESULTS: In all, 109 articles were reviewed involving 112 information system descriptions. Chronic diseases targeted included diabetes (42.9% of reviewed articles), heart disease (36.6%), and mental illness (23.2%), among others. System users were primarily physicians, nurses, and patients. Sixty-seven percent of reviewed experiments had positive outcomes; 94% of uncontrolled, observational studies claimed positive results. Components closely correlated with positive experimental results were connection to an electronic medical record, computerized prompts, population management (including reports and feedback), specialized decision support, electronic scheduling, and personal health records. Barriers identified included costs, data privacy and security concerns, and failure to consider workflow. CONCLUSION The majority of published studies revealed a positive impact of specific health information technology components on chronic illness care. Implications for future research and system designs are discussed.

Chronic Disease↗
PubMedDate not supplied

Improving health care by understanding patient preferences: the role of computer technology.

If nurses, physicians, and health care planners knew more about patients' health-related preferences, care would most likely be cheaper, more effective, and closer to the individuals' desires. In order for patient preferences to be effectively used in the delivery of health care, it is important that patients be able to formulate and express preferences, that these judgments be made known to the clinician at the time of care, and that these statements meaningfully inform care activities. Decision theory and health informatics offer promising strategies for eliciting subjective values and making them accessible in a clinical encounter in a manner that drives health choices. Computer-based elicitation and reporting tools are proving acceptable to patients and clinicians alike. It is time for the informatics community to turn their attention toward building computer-based applications that support clinicians in the complex cognitive process of integrating patient preferences with scientific knowledge, clinical practice guidelines, and the realities of contemporary health care.

Computer Communication Networks↗
PubMed2006

Inpatient verbal orders and the impact of computerized provider order entry.

OBJECTIVE: To describe the characteristics of verbal orders at a tertiary care children's hospital. STUDY DESIGN: Between August 2003 and January 2004, the computerized provider order entry (CPOE) system was evaluated for the characteristics of verbal orders. The rate of total orders represented by verbal orders and the rate of unsigned verbal orders were examined before, during, and after CPOE implementation. RESULTS: After CPOE implementation, a mean of 19,996 +/- 521 orders were generated weekly; of these, 2094 +/- 65 (10%) were verbal orders. The greatest rates of verbal orders were from psychiatry (74%) units and involved medication orders (38%; 790/2094). The greatest rates of medication verbal orders were psychotherapeutics (24%; 662/2697). Medical physicians had a larger rate of verbal orders than surgical physicians. The rates of verbal orders and unsigned verbal orders were reduced from 23% and 43% before CPOE implementation to 10% and 9% after implementation, respectively. CONCLUSIONS: Medication orders from physicians to nurses are the primary source of verbal orders in this tertiary care children's hospital. CPOE implementation significantly affected both verbal orders and the rate of unsigned verbal orders. This type of data is important for institutions aiming to decrease verbal orders and associated medical errors.

Child↗
PubMedDate not supplied

Accuracy of on-site data entry in a rural primary care research network.

OBJECTIVE: This study examined how accurately research data can be entered into a database by rural research network members with little computer training and no data-entry experience. METHODS: A rural primary care research network in the Upper Peninsula of Michigan collected data from a study, and each practice entered its data on a standard database. The data were then sent electronically to the main research center where they were downloaded and analyzed. Accuracy of data entry was evaluated by comparing data received at the center with data on the original questionnaire. RESULTS: Accuracy of the data, entered by practice coordinators (nurses) with little or no computer experience, was completed with an error rate of one error per 220 keystrokes or .22 errors per 1,000 keystrokes. CONCLUSIONS: Results indicate that remote data entry in research networks can be accomplished accurately and reliably with little training.

Electronic Data Processing↗
PubMed2000

Electronic patient records and the impact of the Internet.

The term electronic patient record (EPR) means the electronic collection of clinical narrative and diagnostic reports specific to an individual patient. A true EPR should allow physicians and nurses to practice in a paperless fashion. The wide adoption of Internet technologies should allow truly distributed sharing of patient data across traditional organizational barriers. Hence, the meaning of an EPR, as a representation of documents, should be transformed into a collaborative environment that supports workflow, enables new care models and allows secure access to distributed health data. This paper reviews the current realization of EPRs in the context of paper-based medical records. The Internet architecture that Boston-based medical informatics researchers refer to as W3-EMRS is described in the context of a successful implementation of CareWeb at the Beth Israel Deaconess Medical center. Finally, we describe how this Internet-based approach can be extended beyond the boundaries of traditional care settings to help evolve new collaborative models of eHealth.

Computer Security↗
PubMedDate not supplied

Trends and pitfalls with nomenclatures and classifications in medicine.

This paper reflects some of the main points in the history and the trends of classifications, nomenclatures and knowledge representation models in medicine. The relations with philosophical background are briefly related. The contributions in this field during the Medical Informatics Europe (MIE) conference in 1997 are presented. International collaborations in the field of lexico-semantic resources and inter-disciplinary partnership in natural language processing technologies are necessary steps to achieve definitive results that will lead to applications in the daily medical practice.

Algorithms↗
PubMed1998

Creating a vision for your medical call center.

MCC technologies and applications that can have a positive impact on managed care delivery are almost limitless. As you determine your vision, be sure to have in mind the following questions: (1) Do you simply want an efficient front end for receiving calls? (2) Do you want to offer triage services? (3) Is your organization ready for a fully functional "electronic physician's office?" Understand your organization's strategy. Where are you going, not only today but five years from now? That information is essential to determine your vision. Once established, your vision will help determine what you need and whether you should build or outsource. Vendors will assist in cost/benefit analysis of their equipment, but do not lose sight of internal factors such as "prior inclination" costs in the case of a nurse triage program. The technology is available to take your vision to its outer reaches. With the projected increase in utilization of call center services, don't let your organization be left behind!

Computer Communication Networks↗
PubMed2006

What does it take to replace an old functioning information system with a new one? A case study.

PURPOSE: To investigate the case of a municipal wound care practice and the process of designing a specific computer documentation record system. In carrying out our kind of action research, creation of the system that integrate digital photos, was supposed to remake the old wound care documentation system and transform it into a more advanced and unified tool. METHODS: Ethnographic studies were conducted before and parallel to the design work. Nurse practitioners were involved in design and actively determining essentials of the computer artefact. Developmental Work Research (DWR) is the framework against which data from the work practice and system development where analyzed and interpreted. RESULTS: First, an old-fashioned information system (IS) within health care work will not successfully be replaced by a new one, unless the new is better "as a whole", that is, better supports work practices of a range of occupational and professional workers. Second, when designing information system for the public sector, system designers will almost always face dilemmas based on a contradiction between central, high level interest and a local level work-practice perspective. DISCUSSION: Our study reveals that the work practice of the municipal nurses is characterized by three distinctive features: High mobility, the need for face-to-face interaction in different locations, and a great variety of artefact usage. This implies that a new information system has to be "better as a whole" dealing with those characteristics.

Diffusion of Innovation↗
PubMed1996

Technology and automation in pharmaceutical care.

Pharmacy computer systems in the future will help pharmacists assess patients' medication needs, evaluate drug therapy, and manage patient information. Technology companies are developing systems for automatic dispensing and for distributing medications from nurses' stations in hospitals and long-term care facilities. Bar codes are being used in medication dispensing, verifying prescriptions, selecting patient brochures, and screening for drug interactions. Pharmacies in the future will rely on information networks to store, manage, and communicate patient information. Drug use review databases offer highly developed drug therapy screening.

Humans↗
PubMedDate not supplied

Developing, implementing, and evaluating decision support systems for shared decision making in patient care: a conceptual model and case illustration.

The importance of including patient preferences in decisions regarding their care has received increased emphasis over recent years. Medical informatics can play an important role in improving patient-centered care by developing decision support systems to support the inclusion of patient preferences in clinical decision making. However, development of such systems is a complex task that requires the integration of knowledge from four major research areas: (1) the clinical domain, for understanding of the decision problem, (2) decision science and research on shared decision making, to provide the theoretical underpinnings and techniques for eliciting patient preferences; (3) medical informatics, to provide the technology and algorithms for the collection, processing, structure, presentation and integration of patient preferences into patient care; and (4) organizational knowledge, to adapt the decision support system to the practices and work flows of clinicians and the organizational and professional context of the clinical practice settings. This paper describes a conceptual model comprising eight key components that are important to be considered in the development, implementation, and evaluation of decision support systems for shared decision making in patient care. The example of CHOICE, a decision support system to assist nurses in eliciting and integrating rehabilitation patients' preferences for functional performance in patient care is used to illustrate the eight components.

Choice Behavior↗