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Healthcare Analytics: Build-Versus-Buy Quandary A Hurdle


| 23 Feb 2018

In Part-1 of this blog post, we read about how the healthcare sector was lagging in data analytics as compared to the other sectors.

The most obvious thing for any Health Care Organization (HCO) to do is to develop in-house infrastructure to manage its healthcare data. That’s simpler said than done, though. Setting up an Enterprise-grade data warehouse not only involves additional hires but there’s also some amount of capital expenditure as well as operational costs involved.

Here’s what’s needed – an investment in the right personnel and the right technology, data warehouse, analytics software, database experts, data architects, and analysts – all of which are required to handle the data & analyze it, & finally deploy the results to improve its line of treatment or research, as the case may be. Then comes the fact that with the ever-changing world of technology, systems and humans need to be almost always constantly updated & upgraded to keep up, which in turn means additional costs. It’s a Catch-22 situation – to reduce costs, hospitals & HCOs need to incur costs.

No doubt there are certain pros in doing your data analytics in-house, especially when a patient’s data is confidential, but the IT costs can be prohibitive, especially for medium & small HCOs.

So why re-invent the wheel?

The above primary reasons are why a healthcare data analytics market has developed around the world. Outsourcing data analytics makes imminent sense for smaller hospitals and financially restrained health providers.

What HCOs can do, like is being done by other sectors, is to keep core tech services under their direct control, while outsourcing the rest.

About two years ago, for example, a major Minnesota health system, Allina Health, outsourced its entire analytics operation in a 10-year, US $108 million deal. It had made headlines then because of the caveat added in the deal -the analytics vendor had a financial incentive to assure that Allina Health actually improves patient outcomes and reduces the cost of care.

Getting caught in the build versus outsource dilemma can lead to a loss in momentum for the HCO, & leave it behind in the care delivery race. The first step for almost all HCO, except perhaps the blue-chip ones, is thus, to outsource their analytics tasks, to get going.

This year, 2018, is all set to see healthcare-focused solutions getting into a more rarified atmosphere – that of Cloud, Artificial Intelligence & Machine Learning, making it that much more imperative for hospitals & medical research labs to arrive at a decision vis-à-vis analytics.

Also remember, before outsourcing, make sure all your business requirements are listed and analyzed before going on the hunt for a vendor. Conduct proper market research & list all the possible companies that can provide the required services.

Before awarding the contract, ensure your HCO has a data security policy in place, including the classification of sensitive and common data. Also start employing the use of database monitoring gateways & firewalls before finally awarding the contract. All this will ensure that sensitive patient data does not fall into the wrong hands, leaving your HCO exposed to lawsuits.

Concluded.

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