CHOP Patient Flow and Census

Researchers at the Kinetic Modeling and Simulation Core (KMAS) of the University of Pennsylvania School of Medicine are simulating Patient Flow and analyzing Hospital Census data at The Children's Hospital of Philadelphia (CHOP) using Simul8 and SAS .

Patient Flow Initiative (using simul8)

Pediatric Intensive Care Unit (PICU) beds are a limited resource and patient flow issues often appear in this setting. PICU flow is determined by many internal and external factors with varying loci of control. Patient flow is truly a hospital-wide issue. The goal of this initiative is to describe the patient and flow characteristics of the PICU at one large, urban hospital (CHOP). Things to consider while modeling and simulating this process:

Settings:

The Children's Hospital of Philadelphia :

Data Analysis:

PI: Evan Fieldston, M.D, M.B.A (Robert Wood Johnson Clinical Scholar)
Research Analysts: Mahesh Narayan M.B, M.S.E (KMAS)/ Bhuvana Jayaraman, M.P.H (KMAS)

Hospital Census Project (using SAS):

Background:

Hospital crowding is a growing problem for safety and quality reasons. Avoidance of crowding requires accurate measurement and good management of hospital occupancy. The traditional measure of occupancy uses midnight census, often expressed as monthly or annual averages. Because children's hospitals have a large proportion of short-stay patients, it is not known if midnight census is an accurate measure of hospital occupancy.

Hospital crowding adversely affects:

Sentinel events & medical errors increase when hospital occupancy exceeds 85%-90%

The objective of this project is to determine the difference between daily midnight census/occupancy and daily maximum census/occupancy and the factors that contribute to variability in these measurements.

Data Analysis:

Admission-discharge-transfer (ADT) data for 22,320 inpatients from fiscal year 2008 were abstracted. Each record included dates/times of patient arrival to an inpatient unit and departure from it, as confirmed by unit registrar staff. Using these timestamps, inpatient hospital census was generated for every hour of each calendar day; midnight, peak, and minimum census figures were extracted for each day. Hospital occupancy was calculated as: census / mean beds available in month.

PI: Evan Fieldston, M.D, M.B.A (Robert Wood Johnson Clinical Scholar)
Research Analysts: Bhuvana Jayaraman M.P.H (KMAS) / Mahesh Narayan M.B, M.S.E (KMAS)