Big data

The Healthcare Analytics Market is expected to reach $18.7 billion by 2020 from $5.8 billion in 2015, sharesUdai Kumar,CEO & President, OHUM Healthcare Solutions with Elets News Network (ENN)

As a patient, I am always worried if I am getting the best treatment at the best cost with the least side effects. A doctor is concerned if he is making an impact on all his patients with the highest outcomes and lowest safety issues while offering maximum convenience. Hospitals and other related medical care delivery organisations worry about productivity, costs and growth. Payers, individuals like me, corporations, insurance firms, governments or non-profit organisations worry about cost-benefit and reach. Research institutes in care delivery, such as hospitals, labs, device manufacturers and pharmaceutical firms, need to understand where to focus their research and development (R&D) spending, so as to improve long-term outcomes. Society at large needs to ensure that no patient is left unserved, no avoidable medical error happens and no cost becomes too burdensome.

As we move from the individual (one doctor, one patient) to the many (multiple providers, caregivers, payers, patients, diseases, conditions, quality, affordability and reach), we enter the world of big data. We have 7 billion patients, 100,000 diseases, 4,000 diagnostic investigations, 8,000 drugs, 4,000 procedures and 1,000s of symptoms. Add to this, 3,000 million base pairs of the human gene sequencing and billions of microorganisms and food/water particulates and minerals and vitamins. Just imagine for a moment, what all this translates into by the way of combinations and permutations. And to make sense of all this, over 100,000 medical journals and over 1 million articles are published each year, reporting on new experiments, findings and approaches to patient care. Now when all these are available to us electronically and at the point of care, we wish to harness this seamlessly and economically to the benefit of all. Enter the world of big data.

Big data is no more the next big thing it is already big. In fact, it is huge. We are talking about an enormous amount of data being stored and processed regularly.

The Healthcare Analytics Market is expected to reach $18.7 Billion by 2020 from $5.8 Billion in 2015.

With fast processing computers and easy data storage today, storing and processing a huge amount of data is no longer a big concern. In fact, most of the times, the mindset seems to be store everything first, worry about how to use it later. It is estimated that Google now controls over 70 per cent of all clinical data available on the Internet. That is not necessarily a good thing. But, it is the price we pay for the interconnected availability of all things electronic.

However, having a large amount of data does not necessarily mean better analytics and, therefore, better decisions. Analytics still has to overcome the biggest hurdle, which is the hurdle of usability and user acceptance. An application presenting completely non-usable data in the form of the swankiest dashboards can hardly be called ausable application. Usability in analytics has a much deeper meaning than ease of navigation, ease of use, fewer clicks, soothing colors and fancy dashboards.

A highly accurate data, presented in a timely manner, which helps me in meeting agoal which I have already taken up, even when given on a piece of paper, written by a5-years old child, has much higher utility value than any of the fancy dashboardswhich show completely useless data in the most attractive manner.

Especially in healthcare, usability is one of the major concerns because it is much beyond the attractive dashboards. For data analytics to achieve higher usability and user acceptance, it as to drive an existing agenda of a hospital or a patient or a payer.

For example, the use of analytics at the University of California Davis, where clinicians are able to use the data collected by EHR to receive early warning about sepsis, which has a 40 percent mortality rate, is far more impressive than any classy dashboard.

There are following three main aspects which play a critical role in the usability of analytics:

Alignment with Goals

Every healthcare organisation works towards improving the quality of care and reduce the cost of operations. The general approach to achieving this is :

  • Have a look at the international benchmarks and measure their own performance against those benchmarks.
  • Based on the analysis, understand where they are lacking behind.
  • Follow a systematic approach to do the root cause analysis on what is wrong and what can be improved.
  • Based on the root cause analysis, devise and act on an action plan

In this whole top-down approach of performance improvement, if the analytics can assist at each and every step and offer concrete, actionable insights, then it can be considered to have higher usability. In short, it needs to be aligned with the performance goals of the hospital. One of the major reasons behind the low adoption of analytics is that it is seldom aligned with the goals and agenda of the healthcare organisation.

Cross-Functional Communication

In any healthcare organisation, intra-departmental keynotes exchange or cross-functional workshops are always necessary to achieve any major goals. In such workshops, the stakeholders need to see the same data from three different points of views. The ability to access the data at thedepartment level, in this cross-functional manner, increases the department-level utilisation. Be it weekly status meetings, monthly review meetings, quarterly quality meetings, or annual reviews with the external agencies or auditors, the methodology that has been applied, the values attached to the captured data, the ability to see the data in multiple dimensions automatically improves the inter-departmental usage. This is the driving factor behind all the goal review meetings and conversations. If the analytics can help the departments achieve these objectives, then that can be considered as the truly usable application.

Individual User-Level Acceptance

Acceptance at an individual level is crucial and critical for making analytics successful in any healthcare organisation. The stakeholders are at different levels and expertise there are doctors and clinicians, technicians, operators, nurses and staff and so on. For any stakeholder, the analytics is useful only when –

  • The captured data is relevant
  • The data is presented in a minimalistic manner and it does not intrude into the job
  • The analytics is deeply integrated into the workflow and it is not a separate sheet or activity to look at. It is completely integrated with the point of care and the underlying system and offers actionable insights

Only when all these criteria are met, the use of analytics at the individual user level can be increased and improved – without necessarily forcing the use at the individual user.

In summary, tremendous data presented on jazzy dashboards is the last thing which can be termed as a usable application. A truly usable application is the one which is tightly aligned with the goals and set agenda of the hospital. It should improve the inter-departmental communication and it is easily acceptable at an individual stakeholder level. Only when these three criteria are satisfied, the analytics application can truly be called as successful.

Udai Kumar, CEO & President, OHUM Healthcare Solutions

Udai Kumar
CEO & President, OHUM Healthcare Solutions

About the Author

Udai Kumar, CEO & President, OHUM Healthcare Solutions, is ahighly successful serial entrepreneur, mentor and investor. Udai has a deep understanding of the global delivery model and specialised in global business development, human capital management, finance, software development, Six Sigma, systems & processes. He is an active member of theHealth Information Network group and is on the panel of Leadership Team at the Government of India level for healthcare technology.He is onTwitter at https://twitter.com/_udaikumar

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