BIG DATA ANALYSISFOR HOSPITAL LOGISTICS · 2016 AARHUS KAJ GRØNBÆK & JENS PEDER RASMUSSEN AU...

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AARHUSUNIVERSITYAU KAJ GRØNBÆK & JENS PEDER RASMUSSEN

BIG DATA ANALYSIS FOR HOSPITAL LOGISTICSKaj Grønbæk, Professor, PhD

Department of Computer Science, Aarhus University

[email protected]

Jens Peder Rasmussen, Director

Systematic A/S

[email protected]

2016KAJ GRØNBÆK & JENS PEDER RASMUSSENAARHUS

UNIVERSITYAU

PLANPrevious Galileo & PosLogistics Projects:

u Indoor Positioning and Hospital Service Logistics

u Planning, predicting, and preventing from position tracking data

New DABAI project: Optimized Patient Flows

u Background and visions

u First steps taken

Wrap up



PREVIOUS GALILEO & POSLOGISTICS PROJECTS


UNIVERSITYAU

LOGISTICS REQUIRES INDOOR POSITIONINGGalileo Platform for Pervasive Positioning (2007-2011)

u Indoor and outdoor positioning systems and applications

u AU, Alexandra Institute, Terma, Systematic, Danish Agricultural Service, Danish GPS-Center

u Advanced Technology Foundation support

Combining GPS, WiFi, and Dead Reckoning into hybrid positioning

Positioning algorithms running on devices or on server side


UNIVERSITYAU

POSLOGISTICS: SERVICE LOGISTICS FOR HOSPITALSPosLogistics Goals were to:u Minimize waiting time

u Reduce errors and cancelled operations

Planning and managing orderly tasksu Transportation tasks

u Support tasks all over the hospital

Keeping track of patients, equipment, test samples, personnel, etc.u Tracked by smartphones or tags (WiFi, RFID)

Supported by the Innovation Foundation

Partners:

u CS-AU

u Systematic A/S

u Aarhus University Hospital

u Aalborg University Hospital

5


UNIVERSITYAU

WHAT GENERATES DATA ?

6

10.000 employees, 4.500 patients, 100.000 pieces of equipment… to be found (and disappear) in 7.500 rooms over 450.000 m2 of hospital


UNIVERSITYAU

ANALYZING HUMAN ACTIVITY AT HOSPITALu Initial analysis of 10 days data recording:

› 12.000 smartphones detected

› 1 billion WiFi hotspot contacts

u From smartphone position ”heat map” to common routes


UNIVERSITYAU

WHICH ROUTE TO CHOOSE?

8PhD project by Thor Prentow


UNIVERSITYAU

WHEN DOES A PATIENT ARRIVE AT OP?

PhD project by Thor Prentow


UNIVERSITYAU

TRAVEL TIME AND TRANSPORTATION MODEu Indoor Transportation Mode Detection

needed.

u Changes in WiFi signal strength levelsas a rough estimate of speed

Multiple use casesu Travel-time prediction and

analysis

u Task-phase analysis

PhD project by Thor Prentow


UNIVERSITYAU

WHAT IS THE PROGRESS STATUS OF A TASK?

Infer task phases from mobile sensingavoiding waste of time on registration

Benefits

u Automatic detection of phase shifts

u Better overview of task status

u See who needs help from colleagues?

u Provide advice notifications and status in context on

u wearable devices

Idle

Walking to task

Getting Equipment

Prepare

patient

Transporting patient

Ad-Hoc

situation

PatientDeliver

ed

Return Equipment

Idle

PhD project by Allan Stisen


UNIVERSITYAU

STATUSSystematic has brought PosLogistics in operation at several hospitals

u Aarhus University Hospital and Aalborg University Hospital

u now exported to two hospitals in Finland

Research results deployed

u Positioning algorithms and a subset of logistics algorithms in practical use now

u We achieved high accuracy of positioning and logistics methods

Many potentials in applying the data analysis for items beyond service tasks

u Moving objects in general e.g. at airports and manufacturing plants

u Stationary clinical hospital tasks from wearable and ambient sensors



DABAI BUSINESS CASE:OPTIMIZED PATIENT FLOWS


UNIVERSITYAU

DABAI CASE: OPTIMIZED PATIENT FLOW

Vision and Objective:

u To use Big Data analysis to gain more efficient and better patient flows within Healthcare

u To support enterprise wide optimization of the entire patient pathway.

u To provide enterprise-wide real-time cockpit of information and insight on both current capacity and the status of active pathways at a hospital.

Partners

u Aarhus University Hospital, Region Midt, Aalborg University Hospital, Systematic

u CS-AU plus other DABAI core partners


UNIVERSITYAU

PATIENT FLOW BACKGROUND AND MODELBackground:u Patient flows related to “complicated diagnosis”

and “treatment of chronic diseases” are to be treated across multiple specialties and departments and cause coordination issues for healthcare providers.

u Approx. 75% of the total healthcare budget is spend on treatment of chronic diseases.

u The Healthcare system has a large amount of unexploited information that, through use of Big Data Analysis, can provide knowledge that can improve efficiency as well as provide improved and optimized patient flows through out the enterprise.

Generic model of a healthcare system with patient flow and care providers interacting and consuming services. The arrows between the patient flow and the care providers illustrates that the patient flow is influenced by and depended on the providers and their interactions

Hospital

A

B

C GP

Municipality Specialists...

Patientflow


UNIVERSITYAU

SYSTEMATICS’ EXPECTED OUTCOMEu To obtain improved capabilities within Big Data Analysis,

visualization and machine learning.u To deploy the capabilities within healthcare to provide improved

quality for our customersu To develop a product/toolset that can support our customers in

improving efficiency and quality in the patient flows across the healthcare enterprise

u Abilities to export the product/toolset


UNIVERSITYAU

STATUS

u We are currently setting up the data acquisition procedures to get anonymized patient flow data from two super hospitals

u In collaboration with the hospitals, we are doing empirical studies of analysis needs and central hypothesis to analyze for

u We are preparing the suite of analysis tool to be applied to the data

u We are looking forward to the first results from the exploratory analysis - hoping to find surprising patterns and verify/falsify some central hypothesis



THANKS FOR LISTENNING

BIG DATA ANALYSISFOR HOSPITAL LOGISTICS · 2016 AARHUS KAJ GRØNBÆK & JENS PEDER RASMUSSEN AU...

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