Dental College Hospital attached to Yonsei University is a large private dental hospital with 200 dentists and 256 dental unit chairs. It is a nationwide distinguished one with 8 specialties and 1,100 outpatients per ...
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Dental College Hospital attached to Yonsei University is a large private dental hospital with 200 dentists and 256 dental unit chairs. It is a nationwide distinguished one with 8 specialties and 1,100 outpatients per day. Our hospital has information systems such as OCS and full PACS, and we are planning to implement the electronic medical record(EMR) system this *** implement a good qualified EMR system, there are 4 requisitions-technology(hardware & software), well classified clinical terminology(CTs), users' satisfaction and effective interlink with old paper records. This paper is about constructing database of the clinical terminology for the dental hospital EMR. We collected 315 chief complaints(CC), 594 diagnoses and 1,040 procedure terms. They were analyzed and did mapping with SNOMED-CT(SCT) conceptID and descriptionID. Those systematized clinical terminologies put into the database and will be used when the dentists are inputting clinical data in the EMR system. If the systematically classified clinical data were gathered, it would be possible to retrieve clinical data the users want *** technical paper explains the process of gathering and classifying clinical terminologies for the dental hospital EMR. We used ICD-10 and ICD-9-CM for coding disorders and procedures and SNOMED-CT for systematized arrangement of clinical dental terminology.
The casemix-based funding (output-based funding) system was implemented in the Victorian public health care system in 1993 as a system for fair reimbursement of hospital revenue (McNair and Duckett 2002). It is now al...
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The casemix-based funding (output-based funding) system was implemented in the Victorian public health care system in 1993 as a system for fair reimbursement of hospital revenue (McNair and Duckett 2002). It is now also well established as a valuable tool for improving and managing Australia's health care system. The casemix system is being used for output measurement, resource allocation, quality improvement, comparative analysis, and the monitoring of trends over time (Robinson & Ell 2005). This funding model uses Diagnosis Related Groups (DRGs) to measure the mix of inpatient cases that a hospital treats (Swerissen & Duckett 2002). In the casemix-based funding system, there is a critical relationship between clinical coding (disease and procedure classification), the complexity of the case, and the cost of the episode of the care. This funding model depends upon accurate, comprehensive, and timely clinical coding. Hence regular internal and external auditing is required to be carried out to ensure the fairness of the reimbursement and funding. Results from a recent internal coding audit carried out on the coding data for discharged inpatient episodes over three months in one surgical unit in a large tertiary hospital in Melbourne show 22.06% cases in the total of 204 cases audited, in which there was a DRG change;this equated to a significant revenue increase of AU$257, 826.22. The practice of coding auditing is not only of benefit to the health care organization for obtaining fair revenue reimbursement, but also identifies the underlying causes of the DRG change;these include, for example, administration error, lack of clinical documentation, and a requirement for further training of the coders and/or the clinicians. Improvement of any of these factors can positively affect the accuracy of coded data and clinical coders' audited performance. Conclusions The coding auditing process, and the education of auditors, play a very important role in the improvement of c
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