My last post addressed a general overview of the entire healthcare analytics continuum - from foundational data integrity to true prescriptive analytics. At the end of that post I promised to dive into each layer with a bit more detail. So today's post will deal with the most important layer in the continuum - foundational data integrity. After all, without high quality, fully integrated and enriched healthcare data, any analytics exercise will be flawed at best.
Recent polls by GE and Accenture show that big data analytics is a priority for almost 90% of organizations within healthcare. Data is an essential tool for market participants that want to increase share while improving the quality of customer deliverables. And, in the not too distant future, healthcare providers and stakeholders that implement an analytics strategy will excel in clinical quality and prevention of operational bottlenecks.
In many fields, it is common to hear the terms "platform" and "application" tossed around interchangeably. The confusion is understandable because, for a non-technical person, platforms and applications can provide similar initial results. The two concepts are quite different, though, and it's important to understand which one your organization needs.
If I were going to design the worst possible health care analytics department in a health plan, TPA, or benefits consultancy, this is what I would do. First, I would go out and buy all the hardware and software licenses I needed, not to mention the database administrators and IT personnel necessary to support it. Why use the cloud? That's just a trend, right? And what about data security? The cloud can’t be nearly as secure as my data warehouse, right?
I’ve spent my entire professional career in healthcare - 24 years and counting. The vast majority of that time was spent in the cost containment segment, in particular PPO network management strategies and out-of-network repricing and negotiation strategies. For years, I passionately believed that the products and services I represented were providing value to my clients by reducing their paid claims expense. Over the last 5-7 years of my tenure in that segment of the business it became more[...]
Due to our presence in the Population Health Analytics space, I often get asked about what we should do about the Affordable Care Act ("ACA") and the declining choices at greatly escalating rates. As ACA open enrollment starts this week, I've been thinking a lot about this question, and I think it's timely to consider some solutions today. I look at a lot of data, so a couple of simple observations first. Health insurance isn't that complicated. Add up total claims on a population and[...]
Reference Based Pricing Lately, all eyes are on Reference Based Pricing (RBP). In fact, it was standing room only at the Reference Based Reimbursement (RBR) discussion panel last month in Austin at SIIA's biggest event of the year. SIIA’s National Educational Conference & Expo is the world’s largest event dedicated exclusively to the self-insurance/alternative risk transfer industry. RBP was also a hot topic at the recent SPBA conference in Minneapolis, and it’s clear that many TPA’s are[...]
No, I am not talking about the Dalai Lama. I am talking about having a Population Health Analytics strategy that incorporates a Single Source of Truth (SSOT). In the past this strategy was often synonomous with a healthcare data warehouse. But with Big Data solutions, it's commonly referred to as a "Data Lake". More and more often, our customers refer to it as their single source of truth, so we decided to adopt the phrase and expand on it.
The more time I spent in the field this past spring, the more I heard from both existing and potential clients about the need to analyze plan allowed amounts against Medicare pricing equivalencies. It's no secret that employers, brokers, consultants, TPA's and health plans are all considering various reference-based or Medicare-based pricing strategies in their plan designs. Whether considering a total PPO replacement, a narrow network strategy complemented with Medicare pricing wrapped[...]
It seems like the more I look at websites in the healthcare IT space, the more confused I get. I don't know how many times I have read a website and come away thinking "Okay. Sounds impressive, but what do you actually do?" In fact, I have gotten away from using the generic term “analytics”, because it can mean almost anything and therefore means nothing. I like the term "rules engine", but even that can be confusing at times. I am sure many people think that if you've seen one, you've seen[...]