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Home Business Intelligence Consulting Insights Why business intelligence is crucial to healthcare’s evolution

 

Across the globe, hospitals and other healthcare organisations are turning to business intelligence (BI) solutions to improve patient care. The technology and its associated services enable industry leaders to anticipate disease outbreaks, identify ways to reduce costs and more.

One could argue that knowledge is the chief driver of any innovative business. If a leader knows how to generate consistent revenue, the enterprise in which he or she works will benefit from it. BI can reinforce this knowledge, providing insights that enable industry experts to make the type of decisions that can eventually lead to breakthroughs.

Opportunities and challenges 

Visual analytics developer Qlik commissioned HIMSS Analytics to survey 400 healthcare leaders, many of whom were holding c-suite positions. The research discovered that, of organisations labelled as BI “early adopters”, 56 per cent maintained the technology enabled them to reduce healthcare expenses, enhance patient care, satisfy reporting obligations and find ways to increase an overall population’s access to care.

Less than half (48 per cent) of respondents noted that BI processes and technologies enabled them to take specific actions at a faster pace. This suggests that if a hospital, for instance, were to use a data visualisation program such as QlikView on a regular basis, it could figure out how certain aspects of the business are affected by monthly or weekly changes.

42 per cent of survey participants suggested that end users weren’t adopting BI solutions.

These figures would make one think that BI and healthcare are a match made in heaven, but there are challenges associated with this relationship.

For example, 42 per cent of survey participants suggested that end users weren’t adopting BI solutions. This could allude to a number of situations. Maybe workers have trouble using certain functions. Perhaps personnel don’t know how to structure flexible data analysis projects.

Volume, variety and velocity 

Managing information efficiently is one of the biggest challenges facing healthcare companies. If they can’t create processes that gather and organise data, analysing it becomes much more difficult.

According to a study conducted by researchers from Health Information Science and Systems (HISS), the root of this problem lies in ‘the three Vs’ – volume, variety and velocity, which refer to big data’s characteristics. Let’s break them down:

  1. Volume: The amount of data healthcare companies create and collect.
  2. Variety: The various types of data enterprises need to manage.
  3. Velocity: The speed at which healthcare information is generated.

HISS exemplified the three Vs by listing the kind of information hospitals, health clinics and other such organisations oversee. The typical patient profile may contain medical images, physicians’ notes and insurance information. This doesn’t include hospital financial data, sensor and machine-generated data, social media posts and other disparate information.

Based on these concerns, it’s not surprising that many healthcare organisations seek technical support from professionals who know how to organise and analyse a wide variety of data. Specifically, how can those in the healthcare sector get a handle on it?

An infrastructure for big data 

Infrastructures enable processes – it’s as simple as that. The trains, roads, utility networks and other assets that make up the modern city enable millions of people to go to work, power refrigerators, access clean drinking water and so forth.

The same concept applies to big data: Healthcare companies need infrastructures that enable them to efficiently manage and analyse a huge volume of information in their native formats.

The MapR Converged Data Platform, a Hadoop distribution and one technology ourselves and our partners have been working with quite a bit, is just such a system. According to the distributor’s website, the technology can not only enable administrators to access unstructured data but also support genome processing and DNA sequencing projects.

However, decision makers should be aware that such a system is not a cure-all for big data challenges. To address the problems discussed above, healthcare professionals should work with consultants who specialise in using technologies to structure flexible, iterative data analysis projects.

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