Topics in health information management最新文献

The goal of this article is to provide insight in the evaluation of Electronic Document Management Systems (EDMSs) and the current EDMS vendors and their product offerings. Comparisons are made between the vendors and the products over the past decade. Appendix A and Appendix B outline many of today's key vendor offerings. Issues such as HIPAA and medical errors are discussed as it becomes clearer that the quality of patient care can be positively impacted with the application of information technology such as EDMSs.

No one would deny the need to transform health care. Information technology is capable of transforming health care organizations and delivering measurable value. However, these organizations will have to deploy effective, proactive strategies for managing information and adapting to the opportunities the technology offers. If, for example, an organization wants to become paperless, its information strategy must include appropriate tools to store and access unstructured data components of the medical record as well as structured data. An Electronic Document Management System (EDMS) is a critical element of this strategy. Also, a plan for managing change must be developed to mitigate technology risks. This can be realized through the development of a clear vision of the future and strong leadership, among other key items.

Electronic document management systems (EDMS) have a profound impact on administrative operations of health care provider organizations. Thorough yet conservative system requirements and cost-benefit data can prove the necessity and priority of the EDMS. This case study-based article provides a methodology for all EDMS implementations, including the preparation of the vision and scope, business analysis, cost-benefit analysis, and system specification and project plan. These are illustrated with EDMS examples. To successfully minimize project risk, the article reviews the importance of phasing, standards, and integration, and it provides six detailed examples of this methodology.

The challenges faced by facilities wishing to implement an electronic medical record system are complex and overwhelming. Issues such as customer acceptance, basic computer skills, and a thorough understanding of how the new system will impact work processes must be considered and acted upon. Acceptance and active support are necessary from Senior Administration and key departments to enable this project to achieve measurable success. This article details one hospital's "journey" through design and successful implementation of an electronic medical record system.

The days of using optical disk based mass storage devices for high volume applications like health care document imaging are coming to an end. The price/performance curve for redundant magnetic disks, known as RAID, is now more positive than for optical disks. All types of application systems, across many sectors of the marketplace are using these newer magnetic technologies, including insurance, banking, aerospace, as well as health care. The main components of these new storage technologies are RAID and SAN. SAN refers to storage area network, which is a complex mechanism of switches and connections that allow multiple systems to store huge amounts of data securely and safely.

The decision to implement an Electronic Document Management System (EDMS) should not be made lightly. Such is the advice of a health are provider organization that pioneered the technology a decade ago. University Health Systems of Eastern Carolina's largest facility, Pitt County Memorial Hospital (PCMH), implemented an EDMS in February 1992 and converted to its current EDMS in December 1999. This article describes PCMH's transition from paper to automation, the many trials along the way, and the advantages an EDMS offers.

This article examines how simple descriptive statistical and graphing techniques may be used in compliance efforts. Specifically, we propose the following three-step process: (1) Retrospective review of external data--Where do I stand? (2) Retrospective use of internal data--How can I improve? and (3) Prospective use of external and internal data--How can I avoid future problems? Findings suggest that when examining charges and length of stay (LOS) data, box plots are useful in retrospective analysis in identifying both over and under charges and LOS. Run charts are useful in prospective analysis of data in setting benchmark standards for evaluation.

The Episode Treatment Group (ETG) methodology is a patented case-mix adjustment and episode-building system that uses routinely collected inpatient and ambulatory claims data. The resulting clinically homogenous groups, of which there are approximately 600, adjust for severity by the presence of complicating conditions, comorbidities, and other characteristics of a patient's condition that affect resource utilization.

Coding systems and standardized clinical terminologies are interrelated. Coding schemes can be developed for classification systems, nomenclatures, and clinical terminologies. The coding systems most commonly used in the United States lose clinical detail and cannot meet the demands of the clinical information systems needed to support the computer-based patient record, outcomes studies, or risk-adjusted comparative research. Systems using computerized encoding and structured as terminologies offer more promise of providing the needed clinical detail. Companion systems can be developed to automatically place standardized clinical terms into less granular classification systems, such as ICD-9-CM, to maintain international compatibility and to continue federal programs based on such classifications.

Automated coding is a rapidly growing technology. The implications of this technology for the clinical, business, and research areas of health care today are dramatic. Before a health care organization chooses an automated coding system it is important that the implications of each of the various types as well as the vocabulary to be chosen are understood. This article will discuss three types of automated coding systems that are currently available, but it will not discuss the merits of the various vocabularies available for use in an automated coding system.