Using New Technology to Effectively Capture Residential Aged Care Costs
Patrick Power a
Introduction
Costing in a residential aged care setting is difficult due to the lack of resident-level activity data collected at the point of care, as well as the lack of available cost drivers that could be used to facilitate the costing process. This abstract describes how new technology is used to overcome these difficulties and provide meaningful costing results.
Healthcare costing is the exercise of matching the work performed, i.e., clinical activities, with the expenses incurred in producing that work, i.e., the dollars in the General Ledger. Costing acute patients is made relatively simple due to the various clinical activities that are recorded at the patient level, such as various charges for private patients and clinical activities such as Pathology, Pharmacy, Theatre time and Prosthetic charges for public patients,
Unfortunately, whilst aged care has guidelines for daily tasks, only clinical notes are recorded against each resident, and that information is not useful for costing purposes. As a result, previous residential aged care costing studies have relied on manual time studies, as a surrogate for actual recorded clinical activities.
Previous residential aged care costing studies have relied on manual time studies, as a surrogate for actual recorded clinical activities. Time studies involve the manual tracking of time spent in performing each activity and recording it against individual residents or groups of residents. This information is then used as cost drivers in the costing process. Without these cost drivers, all residents will be costed similarly using length of stay, regardless of the actual care provided.
This presentation will describe the processes used to implement a completely frictionless automated time capture study, along with manual recording of the clinical activity provided.
Methods
To overcome the manual data collection process, card technology was used to automate the recording of time. In addition, a simple user interface, using an iPad, was created to allow staff to easily select the clinical activity provided for each contact time captured by the system. Minimum distances between staff and residents were defined within the card technology, as well as minimum contact times, to minimise the recording of casual contact times, i.e., brief contacts where it was unlikely that a clinical activity was performed.
The costing results are then evaluated to assess the costs/benefits of a fully automated time capture, versus adding an additional manual process to obtain clinical activities. Similarly, their usefulness towards the future development of relative value units (RVUs) will be considered.
Results
The results will be presented in full at the presentation as the project will complete in July 2022.
Conclusions
The project's expected result is that the more manual the data collection process, the more user errors will be introduced into the data collection. The project will therefore aim to conclude whether a fully automated data collection process provides better outcomes to the costing process over one that holds more segmented data, albeit involving a manual collection component.
a PowerHealth Solutions, Australia
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