Making Healthcare Better or Making Better Healthcare?

The demand for better health in chronic diseases is massive in the global healthcare market. Mowever, smarter processes or new electronic health record (EHR) systems provide insufficient impact for lowering the costs of chronic diseases. Instead of producing bandages, to change the macroeconomic equation we need to decrease the number of wounds.

The global cost of cardiovascular disease and diabetes currently amounts to over €1,100bn each year. With 15.5 million annual fatalities, heart disease is the main cause of death worldwide. Diabetes reduces the quality of life and causes premature death among 415 million patients globally. The problem is also booming in the fast growing economies; in China, the cost of chronic diseases is estimated at €24.6 trillion during 2012-2030, with cardiovascular disease being one of the greatest economical threats.

The numbers are unbearable. Incremental improvements in healthcare are needed, but simply making healthcare better is not enough — we need to make better healthcare.

It’s about the impact

Making healthcare better aims to improve ways of working. Smarter processes and organisations, EHR systems and communication tools can potentially save billions of euros. However, these improvements come with a cost. The financial burden of large organisational changes, national healthcare reforms or EHR system implementations are estimated in the billions. In addition, the overall lifecycle costs of the improvements are often difficult to predict.

The returns on investment (ROIs) for these improvements may be positive, but a challenge remains due to the scale of the problem at hand. Whereas the ROIs in smarter processes are typically calculated as fixed for a given time period, the challenge with chronic diseases is not fixed – the problem is quickly increasing worldwide. The impact of the improved ways of working may provide 20% better care and/or lower cost for a patient, but finding a way towards 80% impact is the key. This is why it is insufficient to make healthcare better.

Making better healthcare is about addressing the core of the problem. As it is virtually impossible to put a bandage around every wound, we need to decrease the number of wounds. This is not only required to prevent a fixed number of disease occurrences, but to address the continuously increasing numbers of patients. We need a way to diagnose the risk of chronic diseases early enough to prevent the costly complications.

More biological data

The solution in predicting disease risk lies in the amount of relevant biological data, i.e. biomarkers. This data is vastly obtained from blood – 70% of healthcare diagnoses are based on blood sample analysis. This includes cardiovascular diseases and diabetes for which the risk is diagnosed in routine tests based on five blood biomarkers (lipid panel including cholesterol measures and glucose). Cholesterol levels, for example, are used to estimate the future risk for heart disease. However, the currently used five biomarkers do not show it all – 50% of patients who have been diagnosed with heart attack have normal cholesterol values.

This underlines the simplification of using one or a handful of biomarkers to predict the risk for complex systemic diseases. Although a plethora of scientific evidence shows that the approach works at the population level, the risk estimates based on the limited data are not very good predictors of future disease for the individual patient.

Reinventing blood testing

We at Brainshake are determined to change the macroeconomic equation of chronic diseases. This has led to an innovation that brings vastly more detailed biological data to routine healthcare. Instead of five biomarkers, Brainshake’s blood analysis provides over 220 metabolic biomarkers from a single blood sample, including routine lipids. This is achieved at a similar cost as the standard lipid test. This transforms the possibility to understand the inherent complexity of the chronic diseases and turn the focus from treatment to prevention.

For example, rather than assessing the risk for diabetes based on the glucose level alone (at the moment, if fasting glucose level is above seven, the patient is diagnosed with diabetes), a much more accurate risk estimate can be obtained from the comprehensive biomarker profile. This translates to a better understanding of the disease development and ultimately enables more individual prevention strategies. When the disease can be prevented, the cost of treatment will fundamentally decrease – the acute events of chronic diseases create costs only when they happen.

Towards preventive medicine

Brainshake’s blood analysis technology has been used in more than 100 biomedical publications to study chronic diseases. The science has uncovered over a dozen new blood biomarkers reflective of the risk for pre-diabetes and type 2 diabetes onset as well as multiple new biomarkers indicative of future risk for cardiovascular disease. Many of the new biomarkers have been recognised as even stronger risk predictors than cholesterol.

Being able to measure broad biological data routinely is an unprecedented opportunity to transform healthcare and flip the macroeconomic costs of chronic diseases. With the detailed biological data, we can start implementing a solution that has the power to improve faster than the problem grows.

Like a self-learning system, each measured blood sample added to the database improves the accuracy of the risk prediction. The more accurate the analysis, the better the prediction at the individual patient level. The more individual the prediction, the better the possibility to provide appropriate treatment and prevent chronic diseases.

The steps towards preventing chronic diseases and reaching 80% impact call for an industrial revolution in healthcare. We need to update the standard blood diagnostics technologies to provide routinely affordable broad biomarker data. Technologies to analyse this data already exist, and with appropriate biological input the output of the analytics will be re-invented.

The tools to realise the vision of precision medicine in public health are available today, but we need the will to implement the self-improving, data-driven approach – the way of better healthcare.

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