14,733 research outputs found
Heterogeneous biomedical database integration using a hybrid strategy: a p53 cancer research database.
Complex problems in life science research give rise to multidisciplinary collaboration, and hence, to the need for heterogeneous database integration. The tumor suppressor p53 is mutated in close to 50% of human cancers, and a small drug-like molecule with the ability to restore native function to cancerous p53 mutants is a long-held medical goal of cancer treatment. The Cancer Research DataBase (CRDB) was designed in support of a project to find such small molecules. As a cancer informatics project, the CRDB involved small molecule data, computational docking results, functional assays, and protein structure data. As an example of the hybrid strategy for data integration, it combined the mediation and data warehousing approaches. This paper uses the CRDB to illustrate the hybrid strategy as a viable approach to heterogeneous data integration in biomedicine, and provides a design method for those considering similar systems. More efficient data sharing implies increased productivity, and, hopefully, improved chances of success in cancer research. (Code and database schemas are freely downloadable, http://www.igb.uci.edu/research/research.html.)
Can the US Minimum Data Set Be Used for Predicting Admissions to Acute Care Facilities?
This paper is intended to give an overview of Knowledge Discovery in Large Datasets (KDD) and data mining applications in healthcare particularly as related to the Minimum Data Set, a resident assessment tool which is used in US long-term care facilities. The US Health Care Finance Administration, which mandates the use of this tool, has accumulated massive warehouses of MDS data. The pressure in healthcare to increase efficiency and effectiveness while improving patient outcomes requires that we find new ways to harness these vast resources. The intent of this preliminary study design paper is to discuss the development of an approach which utilizes the MDS, in conjunction with KDD and classification algorithms, in an attempt to predict admission from a long-term care facility to an acute care facility. The use of acute care services by long term care residents is a negative outcome, potentially avoidable, and expensive. The value of the MDS warehouse can be realized by the use of the stored data in ways that can improve patient outcomes and avoid the use of expensive acute care services. This study, when completed, will test whether the MDS warehouse can be used to describe patient outcomes and possibly be of predictive value
Operational Plan for HMIS Rollout to be Read in Conjunction with the MoH&SW Document of October 2007
The MoH&SW, with a consortium of partners, in October 2007, developed a Proposal to Strengthen the HMIS in Tanzania. This document builds on that proposal to develop a budgeted 6‐month plan to kick‐start implementation of the Revised MTUHA in one region and at national level, to develop a replicable model that can be scaled up to other regions as additional funds become available. The overall HMIS revision process will ensure that, within a period of five years the HMIS will be functional in all 21 regions of the country, in a phased manner Six months intensive systems and database development in Mtwara region Eighteen months implementation in one region in each of the six zones Within 5 years, National rollout to every region The initial six months implementation process, described in depth in this document, will use action research and participatory development methodology that will integrate the six work packages in the HMIS document, in line with the HSSP III proposals for strengthening M&E. A number of dedicated teams will roll out the HMIS, develop a toolkit for implementation in other regions and produce a modern web based data warehouse. The project logframe aims to provide quality routine data for monitoring MDGs and the NHSSPIII by producing five outputs – HMIS revision, HMIS implementation, Capacity development, the DHIS software and action research. Terms of reference are developed for each of the HMIS teams, based on the activities in the logframe – Indicator and dataset revision, HMIS design, Database development and training team. An action‐based budget of US1,25 million for the first year, including the rollout activities, the development of training material, adaptation of software etc. The other six regions will cost 1,05million for first year; all regions will reduce to 300,000 in the third year. National level costs will reduce from 1,2 million for the first year, including the rollout activities, the development of training material, adaptation of software et
Integration of decision support systems to improve decision support performance
Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes
Performance Measures Using Electronic Health Records: Five Case Studies
Presents the experiences of five provider organizations in developing, testing, and implementing four types of electronic quality-of-care indicators based on EHR data. Discusses challenges, and compares results with those from traditional indicators
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Can the US Minimum Data Set Be Used for Predicting Admissions to Acute Care Facilities?
This paper is intended to give an overview of Knowledge Discovery in Large Datasets (KDD) and data mining applications in healthcare particularly as related to the Minimum Data Set, a resident assessment tool which is used in US long-term care facilities. The US Health Care Finance Administration, which mandates the use of this tool, has accumulated massive warehouses of MDS data. The pressure in healthcare to increase efficiency and effectiveness while improving patient outcomes requires that we find new ways to harness these vast resources. The intent of this preliminary study design paper is to discuss the development of an approach which utilizes the MDS, in conjunction with KDD and classification algorithms, in an attempt to predict admission from a long-term care facility to an acute care facility. The use of acute care services by long term care residents is a negative outcome, potentially avoidable, and expensive. The value of the MDS warehouse can be realized by the use of the stored data in ways that can improve patient outcomes and avoid the use of expensive acute care services. This study, when completed, will test whether the MDS warehouse can be used to describe patient outcomes and possibly be of predictive value
The drug logistics process: an innovation experience
Purpose - The purpose of this paper is to present the latest innovations in the drug distribution processes of hospital companies, which are currently dealing with high inventory and storage costs and fragmented organizational responsibilities.
Design/methodology/approach - The literature review and the in-depth analysis of a case study support the understanding of the unit dose drug distribution system and the subsequent definition of the practical implications for hospital companies.
Findings - Starting from the insights offered by the case study, the analysis shows that the unit dose system allows hospitals to improve the patient care quality and reduce costs.
Research limitations/implications - The limitations of the research are those related to the theoretical and exploratory nature of the study, but from a practical point of view, the work provides important indications to the management of healthcare companies, which have to innovate their drug distribution systems.
Originality/value - This paper analyzes a new and highly topical issue and provides several insights for the competitive development of a fundamental sector
Utilizing RxNorm to Support Practical Computing Applications: Capturing Medication History in Live Electronic Health Records
RxNorm was utilized as the basis for direct-capture of medication history
data in a live EHR system deployed in a large, multi-state outpatient
behavioral healthcare provider in the United States serving over 75,000
distinct patients each year across 130 clinical locations. This tool
incorporated auto-complete search functionality for medications and proper
dosage identification assistance. The overarching goal was to understand if and
how standardized terminologies like RxNorm can be used to support practical
computing applications in live EHR systems. We describe the stages of
implementation, approaches used to adapt RxNorm's data structure for the
intended EHR application, and the challenges faced. We evaluate the
implementation using a four-factor framework addressing flexibility, speed,
data integrity, and medication coverage. RxNorm proved to be functional for the
intended application, given appropriate adaptations to address high-speed
input/output (I/O) requirements of a live EHR and the flexibility required for
data entry in multiple potential clinical scenarios. Future research around
search optimization for medication entry, user profiling, and linking RxNorm to
drug classification schemes holds great potential for improving the user
experience and utility of medication data in EHRs.Comment: Appendix (including SQL/DDL Code) available by author request.
Keywords: RxNorm; Electronic Health Record; Medication History;
Interoperability; Unified Medical Language System; Search Optimizatio
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