TY - CHAP
T1 - Estimating admissions and discharges for planning purposes - Case of an academic health system
AU - Lin, Rung Chuan
AU - Pasupathy, Kalyan S.
AU - Sir, Mustafa Y.
PY - 2011/12/1
Y1 - 2011/12/1
N2 - Hospitals provide care to several thousand patients hospitalized in various nursing units. This process involves admissions of patients entering the nursing units and discharges of patients leaving the nursing units. These admissions and discharges have been identified as hand-off points, and such transitional points have higher potential for errors. Furthermore, admissions and discharges also have several associated activities that need to be accomplished, thus causing an increase in the need for resources like nursing staff, etc., which impacts on efficiency. Hence, a better understanding of the trends and patterns in admissions and discharges is necessary to improve the safety and efficiency of healthcare processes. This healthcare-related forecasting case study uses admission and discharge data from more than 100 thousand patients from 38 nursing units like medicine, surgery, step-down, pediatric, etc., over a three-year period from October 2007 through October 2010 in a large academic health system in the United States. There are two primary goals for this study: (1) to perform pattern analysis on the admission and discharge data, for facility and workforce planning and determining shift structure purposes and (2) to perform forecasting for corrective allocation purposes. Similar methods can be used by other hospitals to improve safety and efficiency.
AB - Hospitals provide care to several thousand patients hospitalized in various nursing units. This process involves admissions of patients entering the nursing units and discharges of patients leaving the nursing units. These admissions and discharges have been identified as hand-off points, and such transitional points have higher potential for errors. Furthermore, admissions and discharges also have several associated activities that need to be accomplished, thus causing an increase in the need for resources like nursing staff, etc., which impacts on efficiency. Hence, a better understanding of the trends and patterns in admissions and discharges is necessary to improve the safety and efficiency of healthcare processes. This healthcare-related forecasting case study uses admission and discharge data from more than 100 thousand patients from 38 nursing units like medicine, surgery, step-down, pediatric, etc., over a three-year period from October 2007 through October 2010 in a large academic health system in the United States. There are two primary goals for this study: (1) to perform pattern analysis on the admission and discharge data, for facility and workforce planning and determining shift structure purposes and (2) to perform forecasting for corrective allocation purposes. Similar methods can be used by other hospitals to improve safety and efficiency.
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U2 - 10.1108/S1477-4070(2011)0000008011
DO - 10.1108/S1477-4070(2011)0000008011
M3 - Chapter
AN - SCOPUS:84871764082
SN - 9780857249593
T3 - Advances in Business and Management Forecasting
SP - 115
EP - 128
BT - Advances in Business and Management Forecasting
A2 - Lawrence, Kenneth
A2 - Klimberg, Ronald
ER -