1. Why hospitals are unable to turn data into valuable insights

Why hospitals are unable to turn data into valuable insights

The importance of analytics has increasingly found prominence in healthcare but most of the hospitals faces their own unique set of challenges that keep them from turning data into valuable insights

By: | Published: June 17, 2016 10:48 PM
hospital The quality of insights depend on the quality, complexity, and quantity of data is taken into consideration. (Reuters)

The importance of analytics has increasingly found prominence in healthcare.

Some of the leading healthcare providers in India have taken a leap of faith by adopting cutting-edge analytics solutions to reduce misdiagnosis and select the most effective line of treatment.

A trajectory of the conjunction between analytics and healthcare providers may be traced from being aspirational to now, becoming a necessity.

This shift is also evident in terms of functionality – analytics is providing the healthcare providers with not only the impetus to become more efficient and productive, but is also striving to improve patient care and outcome.

The quality of insights depend on the quality, complexity, and quantity of data is taken into consideration.

Even though every provider or hospital faces their own unique set of challenges, they frequently share several issues that keep them from turning data into valuable insights.

Knowing these common obstacles to analytics success can help healthcare organisations take a holistic look at their needs and capabilities, plan to overcome these roadblocks.

A recent survey found corporate culture and internal politics as the largest issue for healthcare organisations implementing or running an analytics program.

While those who work with analytics on a daily basis realize its potential uses, other important individuals within the organisation may not be as aware of these practical applications.

This disconnect can cause analytics to be underutilized.

A lack of ownership was reported to be the second most common problem hindering analytics programs.

Analytics are often seen as a tool to be used by a healthcare organisation’s individual departments without much oversight.

This can cause difficulties in coordinating the use of analytics as a whole, and make collaboration difficult.

Even something as basic as tracking the cost of analytics becomes a challenge. For example, an estimated 33% of healthcare organisations are currently unable to define their total spending on analytics.

Data scientists are in short supply these days, but this problem isn’t limited to the healthcare sector.

A recent study found that demand for analytics talent will outpace its supply by 50% in 2018. That means healthcare organisations are competing not just with each other for knowledgeable analysts but with huge corporations.

To add to the above mentioned, healthcare organisations also face hurdles when attempting to realize the potential of analytics.

There are difficulties in designing workflows, utilizing data and communicating with stakeholders can all prove challenging.

To fully manage through these challenges, healthcare organisations are exploring how to implement analytics at an organisational level – essentially developing Analytics Centres of Excellence to produce insights in areas from population health to supply chain management.

Healthcare industry is currently undergoing digital transformation.

In addition to Analytics, Healthcare providers are exploring and increasingly adopting automation, robotics, health platforms and mobile technology.

While potential of analytics in generating actionable insights is widely recognized, only a few are able to incorporate it in a way that produces meaningful, data-driven decisions.

  1. S
    Sanket
    Jun 20, 2016 at 4:19 pm
    Data scientists are needed in healthcare to make sense of huge unused valuable but rotting data that is at health providers disposal. Just imagine how usefully this data can be mined to do predictive case modelling of disease patterns and their outcomes. IBM's Watson Health is a perfect example of what data science can do in healthcare. Data Science in healthcare is the next BIG thing in healthcare.
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