Computer-based patient care information systems (PCIS) have emerged as an integral component of healthcare organisations. Currently, 4 models of PCIS exist: the centralised model, the hub-and-spoke model, the network model, and the distributed model. The centralised model has the advantage of a central patient database; however, a major disadvantage of this model is the inability to easily interface with other software packages. The hub-and-spoke model links satellite or feeder systems into a mainframe computer; thus, each satellite has the ability to work independently. This system is limited by the ability to interface satellite systems with the mainframe computer. The network model works via a local area network (LAN) using client server technology which allows for high speed data access and transfer. The network model does not provide an integrated view of patient information and can access only 1 host system at a time. The distributed model is similar to the network model in design but provides for data and system integration via relational databases. This allows for the creation of a central data repository and support for decision-support tools. Computer-assisted decision support has the potential to significantly improve clinical decision-making. Six types of computer-assisted decision-support have been defined: alerting, interpreting, assisting, critiquing, diagnosing and managing. Software representing each type of decision-support software has been incorporated into clinical practice; however, with the exception of drug interaction programs, widespread incorporation of decision-support software into PCIS is uncommon. Clinical pharmacokinetic programs are a category of pharmacy-related decision-support software, and current clinical pharmacokinetic software systems can be categorised as interpreting, assisting or critiquing decision-support. Despite the potential for significant clinical contributions, the integration of clinical pharmacokinetic software into PCIS is uncommon. Most packages are available only as stand alone programs or as a module of a pharmacy information system. These packages usually maintain their own centralised database and require special file transfer protocols for integration. Although PCIS are becoming more commonplace, the integration of commercial clinical pharmacokinetic packages into PCIS is limited. New technology using standardised and relational databases should allow for easier integration in the future.
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http://dx.doi.org/10.2165/00003088-199631030-00001 | DOI Listing |
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MicroRNAs (miRNAs) have acquired an increased recognition to unravel the complex molecular mechanisms underlying Diminished Ovarian Reserve (DOR), one of the main responsible for infertility. To investigate the impact of miRNA profiles in granulosa cells and follicular fluid, crucial players in follicle development, this study employed a computational network theory approach to reconstruct potential pathways regulated by miRNAs in granulosa cells and follicular fluid of women suffering from DOR. Available data from published research were collected to create the FGC_MiRNome_MC, a representation of miRNA target genes and their interactions.
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HUN-REN-SZTE Neuroscience Research Group, Hungarian Research Network, University of Szeged (HUN-REN-SZTE), Danube Neuroscience Research Laboratory, H-6725 Szeged, Hungary.
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View Article and Find Full Text PDFJ Integr Neurosci
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View Article and Find Full Text PDFInt J Cancer
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Inequalities in Cancer Outcomes Network (ICON) group, Department of Health Services Research and Policy, Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, London, UK.
We aimed to investigate socio-economic inequalities in second primary cancer (SPC) incidence among breast cancer survivors. Using Data from cancer registries in England, we included all women diagnosed with a first primary breast cancer (PBC) between 2000 and 2018 and aged between 18 and 99 years and followed them up from 6 months after the PBC diagnosis until a SPC event, death, or right censoring, whichever came first. We used flexible parametric survival models adjusting for age and year of PBC diagnosis, ethnicity, PBC tumour stage, comorbidity, and PBC treatments to model the cause-specific hazards of SPC incidence and death according to income deprivation, and then estimated standardised cumulative incidences of SPC by deprivation, taking death as the competing event.
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