Harris Opex Tracker

Linking cost to quality of care

The link between quality and cost has historically been difficult to prove and a standardised system for demonstrating the immediate impact on daily operating costs has been lacking.

Hospitals and finance directors under pressure to make savings the clear choice is to cut services and staff, but this can place them in direct conflict with the founding principles of healthcare and the professionals who deliver it.

The ground-breaking model we developed around our core algorithms and analytical engine is called the Harris Unit.

It creates a sophisticated but accessible ‘profit and loss’ to show on a single page the economic impact (positive and negative) of the quality of care across a hospital.

Applying the Harris Opex Tracker analysis to an organisation helps

Pinpoint the services costing money due to poor quality.
Identify and focus on the biggest cost area for maximum results the professionals who deliver it.
Understand what the quality shortfalls are and how to correct them, so improvements can be made rapidly.
Chart the financial impact of service changes.
Identify where higher quality services are creating savings to share cost-effective models of care able to show it anecdotally.
Benchmark an organisation internationally.

Avoidable costs and therefore (in)efficiency can be identified, for example

Complaints and litigation.
Increased length of stay due to hospital acquired problems.
Avoidable use of HDU/ITU.
Return to theatre/unnecessary surgery and equipment usage.

The Harris Unit analyses the driving factors behind these inefficiencies, including, for example

Clinically risk-adjusted surgical mortality and complications, broken down by specialty.
Specific surgical complication rates against established clinical norms, notably those which significantly impact upon length of stay, use of critical care and return to theatre.
Specific medical and nursing-based performance triggers indicative of avoidable harm, such as failure to rescue (deteriorating EWS).
Acute Kidney Injury (AKI)
Shock/Cardiac Arrest
Hospital-acquired chest infection
C. diff
Pressure ulcers

These factors, together with other variables available from CRAB data, allow for a sufficiently concise analysis represented in a simple dashboard which also enables direct comparison both between trusts and internationally.

It stands to reason that in most hospital organisations, there will be pockets of good and bad practice. Any analysis should therefore take account where performance is better than it should be (resulting in notional efficiency savings) compared to areas of poor performance which may be making the organisation more inefficient.

The result is a balancing of cost pressures and savings with an overall net loss/gain, but a clear understanding of where simple measures could create the greatest savings.

Empirical use of CRAB around the world has demonstrated there are common areas (e.g. AKI, shock and chest infection) which apply to even the best organisations and where savings may be universal.