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Real-time analytics and better healthcare

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John Danaher MD, president of Global Clinical Solutions on the shift from volume to value and, ultimately, individual care.

In recent years, healthcare information has too often been disconnected, inaccessible and outdated, greatly restricting the industry’s efforts to improve quality and efficiency.

According to a recent global survey of 742 healthcare leaders carried out by the Harvard Business Review, only 15% of respondents describe their organisation today as being mature in its ability to access, integrate and analyse healthcare data from diverse sources.

As the current COVID-19 pandemic has demonstrated, when it comes to data, healthcare systems have primarily been reactive rather than proactive. This has made the use of data much less effective than in many other industries.

However, as we head towards an increasingly virtual world, data must sit in the driver’s seat.

As noted in Health IT Outcomes, trends changed hourly during the pandemic, and healthcare workers and public health officials faced significant challenges monitoring high intensive care volumes, tracking staff and optimizing available resources.

Never before has the value of real-time analytics been so clear: healthcare professionals and leaders need to make data-based decisions, and fast.

The shifting focus from volume to value…

As the virus spread throughout the world at varying rates, understanding COVID-19 brought with it an abundance of unique challenges for HCPs on the frontline. For example, there was policy and clinical uncertainty due to an alarming lack of data.

This initial dearth of information was subsequently followed by a dramatic influx of conflicting evidence which confounded healthcare professionals with inaccurate advice and messaging.

When effectively managed, evidence-based information can help direct appropriate care and reduce unnecessary, and potentially harmful, treatment.

Already, we have seen the potential for healthcare professionals to use data and algorithms to track infections to prioritize patient treatments and further mitigate against the spread of disease.

Additionally, by collaborating with other data-rich entities like pharmaceutical and insurance companies, providers and labs could achieve better results at lower costs.

Data has not only been used in a clinical setting but also to support operational outputs by tracking patient numbers, staffing, stock levels of protective health equipment, ICU and ventilator utilisation.

This data is readily available within individual hospitals and can give healthcare professionals, leaders and public health officials the facts required to make hard and fast decisions. Throughout the pandemic, many health systems have struggled with a lack of equipment needed to protect staff.

The facilitation of data-driven systems which analyse supply-use data will ensure those health providers have sufficient resource in stock as local cases surge.

… and ultimately to individual care

Past data can drive clinical insights and guidance, but real-time data which is filtered, ranked and presented through analytics, can provide instant and accurate clinical insights into a patient’s medical history.

This includes valuable knowledge into past conditions, diagnoses, treatments and outcomes.

This will enable clinicians to make better-informed decisions at the point of care, a key factor in reducing unwarranted variation to improve patient outcomes.

This is reflected in a survey by the Harvard Business Review which states that out of 742 healthcare leaders, 78% strongly agree that integrating data from operations across institutions enables better, more consistent care to communities.

Implementing efficient systems will be key in managing the new reality

Technology plays an integral role in the world today and all sectors can benefit from what it has to offer, the healthcare sector is no exception. Predictive analytics are likely to become a core aspect of the future of medicine and healthcare delivery in general.

In the context of the healthcare system, which is increasingly data-reliant, data analytics can help derive insights on the inefficient use of resource. This can track individual practitioner performance in addition to the health of populations.

With this information, the health system can more efficiently allocate resource to maximise revenue, population health and most importantly patient care.

The facilitation of mechanisms that can automate the process of collecting and standardizing huge amounts of healthcare data will be crucial to to guide public health decision-making in the future.

Healthcare analyses such as the 4CE Consortium and the COVID-19 Research Database, that were put in place to address critical clinical and epidemiological questions about COVID-19, should become routine in near real-time to gain reliable insight to optimise care.

It must be recognised however, that the algorithms and models behind predictive analytics are not flawless.

They need to be made more accountable and transparent with clear human intervention points when appropriate.

Going forward, healthcare organisations need to couple digital transformation with an increasingly holistic approach so that the emphasis is not ‘product-focused’ but rather process and patient orientated.

That way we can deliver equitable and positive healthcare experiences, that still preserve the important human-human empathic connection, between healthcare professionals and patients.

 

 

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