Nichols, K. M., Caperell, K., Cross, K., Duncan, S., Benjamin Foster, Pritchard, H., Southard, G., Shinabery, B., Sutton, B., & Kim, I. K. (2018). Analysis of patient visits and collections after opening a satellite pediatric emergency department. Pediatric Emergency Care, 34, 243-249. doi:10.1097/PEC.0000000000001044
Satellite pediatric emergency departments (PEDs) have emerged as a strategy to increase patient capacity. We sought to determine the impact on patient visits, physician fee collections, and value of emergency department (ED) time at the primary PED after opening a nearby satellite PED. We also illustrate the spatial distribution of patient demographics and overlapping catchment areas for the primary and satellite PEDs using geographical information system. A structured, financial retrospective review was conducted. Aggregate patient demographic data and billing data were collected regarding physician fee charges, collections, and patient visits for both PEDs. All ED visits from January 2009 to December 2013 were analyzed. Geographical information system mapping using ArcGIS mapped ED patient visits. Patient visits at the primary PED were 53,050 in 2009 before the satellite PED opened. The primary PED visits increased after opening the satellite PED to 55,932 in 2013. The satellite PED visits increased to 21,590 in 2013. Collections per visit at the primary PED decreased from $105.13 per visit in 2011 to $86.91 per visit in 2013. Total collections at the satellite PED decreased per visit from $155.41 per visit in 2011 to $128.53 per visit in 2013. After opening a nearby satellite PED, patient visits at the primary PED did not substantially decrease, suggesting that there was a previously unrecognized demand for PED services. The collections per ED visit were greater at the satellite ED, likely due to a higher collection rate.
Jeff Guan, Alan S. Levitan, and Sandeep Goyal (2018). Text mining using latent semantic analysis: An illustration through examination of 30 years of research at JIS. Journal of Information Systems, 32, 67-86. doi:10.2308/isys-51625
Big Data presents a tremendous challenge for the accounting profession today. This challenge is characterized by, among other things, the explosive growth of unstructured data, such as text. In recent years, new text-mining methods have emerged to turn unstructured textual data into actionable information. A critical role of accounting information systems (AIS) research is to help the accounting profession assess and utilize these methodologies in an accounting context. This paper introduces the latent semantic analysis (LSA), a text-mining approach that discovers latent structures in unstructured textual data, to the AIS research community. An LSA-based approach is used to analyze AIS research as published in the Journal of Information Systems (JIS) over the last 30 years. JIS research serves as an appropriate domain of analysis because of a perceived need to contextualize the scope of AIS research. The research themes and trends resulting from this analysis contribute to a better understanding of this identity.
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