Unlocking the Power of Data Analytics in Healthcare Finance - Part 2
(If you haven’t already read it, have a look at part 1 of Unlocking the Power of Data Analytics in Healthcare Finance)
Personalising Treatment through Data Analytics
Innovative models are now allowing health care organisations to drive cost reductions and create personalised treatment plans in ways which wouldn’t have been possible, even a few years ago.
By leveraging health data through curated models, data analytic platforms are now able to predict which patients are most likely to benefit from specific treatments. This breakthrough allows healthcare professionals to customise treatment plans based on individual patient characteristics and predicted treatment response.
Although this personalised approach may sound like it requires more resources, it actually means a reduction in expenditure through removing a significant amount of time and expense spent on treatments which don’t benefit patients.
Hospitals in the UK are harnessing this valuable insight to pinpoint areas where costs can be reduced without compromising patient care.
Through this method, healthcare providers can additionally improve treatment outcomes, minimise unnecessary interventions, and enhance the quality of life for patients.
AI for Initial Assessment and Predictive Analytics
We believe this form of analytics will only become more powerful as AI and predictive analytics improves.
Optos PCL recently launched an AI imagining software which can detect symptoms of diabetic retinopathy. Could technology such as this be part of the key to reducing bottlenecks in the patient journey around initial assessment?
Butterfly Data have also been part of this field of development. We recently created a machine learning algorithm which uses computer vision to assess skin cancer risk – one area of ‘narrow AI’ which has improved dramatically over recent years.
Risk Management with Data Analytics
In the healthcare industry, compliance with regulations and effective risk management are paramount. Data analytics plays a crucial role in strengthening these areas by enabling proactive monitoring and detecting any anomalies within systems. Through utilising these, organisations can reduce the risk of fraud and non-compliance.
One of the key advantages of data analytics in compliance and risk management is the ability to identify patterns and outliers in large datasets.
By analysing vast amounts of data from various sources, organisations can uncover irregularities and potential risks that might otherwise go unnoticed. These insights enable proactive measures to be taken, reducing the likelihood of fraudulent activities or compliance breaches.
Data analytics can also help to establish robust internal controls. By monitoring and analysing financial and operational data, organisations can identify areas where controls may be weak or where potential risks exist.
By analysing historical data collected over time, organisations can identify trends and patterns that indicate potential risks. This insight allows for the implementation of risk mitigation strategies and the development of contingency plans.
This empowers decision-makers to implement appropriate control mechanisms, strengthening governance and reducing the likelihood of financial or regulatory risks.
Enhancing Compliance
Analysing Data often also provides organisations with the means to ensure regulatory compliance.
Real-time data insights can quickly identify any deviations from regulatory requirements. This means that remediation actions can be taken quickly and efficiently. This often prevents compliance issues from escalating, potentially resulting in penalties or legal consequences.
By proactively managing risks, organisations can minimise their financial exposure and maintain stability in an ever-changing healthcare landscape.
The Potential Impact Data Analytics on Financial Performance and Driving Business Success
Within a competitive landscape such as Healthcare, organisations that fail to embrace data analytics risk falling behind their competitors.
As we’ve explored so far, data-driven strategies are essential for heads of finance to effectively manage financial resources, forecast performance, and identify critical cost-saving opportunities. However, the impacts of data analytics extend beyond financial management alone.
Investing in data analytics directly influences overall business growth and competitiveness. Through the power of data, finance professionals can:
Identify areas for improvement
Maximise revenue
Reduce costs
Stay agile to adapt to market changes.
All of these can help businesses gain a competitive edge by empowering them to make proactive, evidence-based decisions formed on actionable insights.
Conclusion
Investing in data analytics is crucial for driving informed decision-making and improving financial performance in the NHS. By leveraging data analytics, finance leaders can uncover valuable insights, make informed data-driven decisions, and drive positive outcomes in areas such as patient readmissions, surgical outcomes, treatment personalisation, and cost reduction.
By staying ahead of the curve and harnessing the power of data analytics, you can make a significant impact on the financial health and sustainability of your organisation.
