PPM Mobile

Accurate Patient Costing at the Bedside and Your Fingertips

PPM Mobile means you can improve patient costing using actual staff to patient contact time for the allocation of clinical salaries and wages.

With simple to deploy mobile technology literally at our fingertips, patient costing is at a turning point. We can vastly improve the accuracy of healthcare costs in areas that have historically been hard to identify, such as:

Teaching
Medical salaries
Porters and orderlies

Salaries and wages account for the largest costs in acute care. Apart from Nurse Dependency (ND) systems (where available and accurate) the cost of clinical staff tends to be allocated on unweighted bed hours nationally. The national default of bed hours is based on two major assumptions that give rise to inaccurate data. The first assumption is that there are similar patients on a ward, and the second is that the time spent by clinical staff is comparable across patients.

PPM Mobile uses Bluetooth LE 4.0 technology to accurately record the time clinical staff spend at each patient’s bedside. The technology is simple to deploy and easy to use with minimal impact on patients and staff.

A small tracking device is placed behind every bed
The app is loaded onto mobile phones, which are carried by clinical staff (no staff identification is recorded, only role data such as nurse, allied health etc.)
The tracking device records the time staff spend at each patient’s bedside

The PPM Mobile app is fully integrated to PowerPerformance Manager (PPM), and recorded data is passed to PPM in the form of service codes (cost drivers). Logic is setup to enable the creation of standards based on actual data for patients not using the app. ‘Hospital in the Home’ and ‘Nurse Dependency' systems use the data to periodically update the underlying ND workload assumptions, which then feeds into PPM as ND cost drivers.

VIEW PPM MOBILE PDF

PPM Mobile Case Studies

PPM Mobile Private Hospital Trial

Using PPM Mobile, PowerHealth participated in a trial to test the assumption that poor patient experience is often linked to a lack of direct nursing time. View the Case Study to find out more.

View Case Study