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Seasonality of Discrepancies between Admission and Discharge Diagnosis for Medicare Patients

1
Department of Computer Science and Engineering, University of Texas, Arlington, TX 76010, USA
2
School of Health Sciences, Central Michigan University, Mount Pleasant, MI 48859, USA
*
Author to whom correspondence should be addressed.
Technologies 2018, 6(4), 111; https://doi.org/10.3390/technologies6040111
Received: 2 November 2018 / Revised: 20 November 2018 / Accepted: 22 November 2018 / Published: 27 November 2018
(This article belongs to the Special Issue The PErvasive Technologies Related to Assistive Environments (PETRA))
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Abstract

Admission and discharge diagnoses of in-hospital patients are often in discord. Incorrect admission diagnoses are related to an increased cost of care and patient safety. Additionally, due to the seasonality of many conditions, this discord may vary across the year. In this paper, we used medical claims data to develop a methodological framework that examines these differences for Medicare beneficiaries. We provide examples for pneumonia, which is a condition with seasonal implications, and aneurysm, where early detection can be lifesaving. Following a Bayesian approach, our work quantifies and visualizes with time-series plots the degree that any clinical condition is correctly diagnosed upon admission. We examined differences in weekly intervals over a calendar year. Furthermore, the median length of stay and the mean hospital charges were compared between matching and non-matching {admission, discharge Dx} pairs, and 95% confidence intervals of the difference were estimated. We applied statistical process control methods, and then visualized the differences among the hospital charges and the length of stay, per week, with time-series plots. Our methodology and the visualizations underline the importance of a rigorous and non-delayed diagnostic process upon admission, since there are significant implications in terms of hospital outcomes and cost of care. View Full-Text
Keywords: health informatics; clinical decision making; seasonal variations; admission diagnosis; health outcomes; visualization health informatics; clinical decision making; seasonal variations; admission diagnosis; health outcomes; visualization
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Shrestha, A.; Zikos, D.; Fegaras, L. Seasonality of Discrepancies between Admission and Discharge Diagnosis for Medicare Patients. Technologies 2018, 6, 111.

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