This week’s Ask the Expert is answered by Mathias Golombek, Chief Technology Officer of Exasol.

Ask the Expert: How can data analytics and big data improve the healthcare sector?

In most discussions, data analytics and big data in the healthcare sector is about becoming more efficient and reducing costs. I personally believe that this is the complete wrong discussion. Shouldn’t the primary goal of advanced technology be about helping us humans? Big data and data analytics can play a huge role in making our world a bit better. Given the wealth of data points in healthcare, it is extremely helpful for improving diagnosis. The complexity of maladies, symptoms, pharmaceuticals, therapies and optimal dosage is extreme, and it is very difficult for doctors to take the right decisions. Data-driven approaches empower our fight against certain infections and diseases.

Reducing to Zero Harm

An example of how data analytics has reduced avoidable harm can be found within Piedmont Healthcare. Piedmont set itself the goal of inflicting zero harm – such as post-operative complications and clinical errors – from the time patients entered its facilities to their leave, seeking to protect them from any further infections and reduce the recidivism rate to as close to 0% as possible.

Within the first year of using data analytics Piedmont saw a 40 per cent reduction in incidents of harm. This was based on measuring 30 metrics, for example the percentage of patients being readmitted after 30 days and tracking the rates of sepsis.

Eradicating Diseases

Mosquito-borne disease kills more than 400,000 people a year. Zambia has set itself a target of 2021 to eradicate Malaria. However, in 2017 alone more than five million cases of malaria were reported.

With the help of data analytics, Zambia’s Ministry of Health is set to break the deadly cycle. It is currently working with PATH (Program for Appropriate Technology in Health) and a consortium of eight technology companies to bring all its relevant data together for analysis under the Visualise No Malaria initiative.

Using existing data sources, the project is training health works to track, treat and report on disease, enabling real-time decisions that will outmanoeuvre the natural spread of infection. The dynamic model is already delivering better data management, analysis, reporting and feedback.

Data analytics has transformed the efficiency and response times of Zambia’s National Malaria Elimination Centre. The project engages with technology providers to track and map the spread of the disease. It also enables coordinators to allocate resources across the country. It ultimately prevents outbreaks from cascading with the use of data-driven decisions on questions such as where to deploy lifesaving resources, ensuring bed nets reach the right places at the right times, while ensuring expensive, life-saving medications don’t expire on the shelf through being located where they aren’t needed.  

Conclusion

These are real-world examples of how tech can help save lives. Vital actionable information can be gleaned from seemingly unimportant datasets. To harness the power of data, healthcare providers must ensure key decision-makers have access to information in a visually understandable manner while assuring that personal data protection is ensured. Data also needs to be as close to real-time as possible – every second is crucial in stopping an infection outbreak for example. Lastly, healthcare providers need to know how to use data. Without asking the right questions, how can we expect the right answers?

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