33% extra capacity for patients at Marie Curie
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Results & ROI
- Administrative team no longer records data within this process – they are now saving (on average) 15 hours per month of their time
- Delivery staff have seen a 33% reduction in the time spent on recording information (likely to improve further once new process is fully embedded)
- Operational managers have also saved 15 hours per month by not having to gather and collate information for reporting purposes (it is now automated)
Marie Curie (MC) is a national charity that provides end-of-life care and support for people with cancer / terminal illnesses and their families. The charity runs a network of 2,000 MC nurses and 9 MC hospices (providing care to over 38,000 people a year). MC wanted to improve the accuracy and availability of performance information – needed to evaluate nursing performance and assess scope for improvement across teams.
The documents and information systems available to the Rapid Response nursing teams had been designed around more planned service models. This led to local managers devising solutions to help the team, but unfortunately these ‘work-arounds’ were not achieving the outputs required.
The processes and systems were not enabling the teams to gather the necessary data, either accurately or in a timely manner. Producing reports was not only taking large amounts of nursing staff and manager time, the process was complicated and results were showing gaps in the information collected. Not having the required information available for review was unacceptable and put the service at risk.
A diagnostic was conducted to fully understand the current state. Process maps were developed by working with 3 key groups – those requesting, those collecting and those recording the information. This meant representatives of all those involved at any stage of the process fed into the diagnostic. Speaking with Commissioners ensured clarity on what information was needed, whilst speaking to those collecting and recording the information identified where errors might occur (including causes).
Using the current state understanding and working with front line staff, a new high-level process was developed that reduced duplication, reduced manual entry of information and automatically checked for obvious data errors. This was simpler and more effective for reporting the required information quickly
Ultimately, reductions in both time spent on data capture by the nursing teams and manual data entry (as a result of less duplication) were achieved. Less time was also spent gathering and analysing data to report to Commissioners. The team gained a clearer understanding of the information being collected, with more accurate information entered on final reports. Information Centres were set up for each of the nursing teams, allowing them to effectively measure what they did and maintain continuous improvement.