Think back to the 80’s and the Revenge of the Nerds. Funny looking glasses. Pocket protectors. Definitely NOT an image associated with “cool kids”. Fast forward 30 years and now many of the people society called geeks are very much the cool kids in today’s changing healthcare landscape. Some of the most daunting challenges in healthcare today are reducing cost and improving quality – and the data geeks are up to the challenge!
This three part blog series will discuss the data revolution that is currently underway within the healthcare industry. The first part of this series will talk about the various data sources that are available and why they are important. The second part will describe the data value chain (in other words, the capabilities that a firm needs to create tangible value from data and data analytics). The third and last part of the series will present a framework for leveraging health data analytics during M&A activity.
The time for change is now. And data can help!
Healthcare is a very much an information and data driven industry. Much like the banking industry in its early days, our healthcare system is going through an information maturity process and is at a critical juncture.
With the advent of the Affordable Care Act, now, more than ever, the US Healthcare system is under pressure to lower costs while improving outcomes. Using healthcare data, organizations can do exactly that.
For example, think being depressed has to do with getting the blues? West Monroe recently used our predictive analytic model to show that social and behavioral factors are not strong predictors of depression. Rather, factual, measurable, clinical factors are much more accurately able to identify and target patients who are likely to suffer from depression, thereby lowering cost by treating only those who really need it as well as improving outcomes. With new discoveries like this emerging every day, the data geeks truly are at the center stage of all that is “cool” in the healthcare landscape.
What Data is Out There?
To understand what healthcare data is out there, it’s best to start by understanding who possesses healthcare data. The major players include:
- Payers: Obviously, payers have a lot of claims data but struggle to get clinical data. Unless payers have merged with a provider system, clinical data can be hard to get.
- Providers: Providers, on the other hand, have EMR and clinical data but often do not have claims data, especially claims history data related to a patient. Think about how many times you need to fill out a paper sheet at your doctor’s office sharing your medical history.
- Pharmaceuticals/Life Science Firms: Pharmaceuticals have several different types of data related to marketing and sales, market responses from patients and care givers, sales history, etc. They also have prescription data (sometimes purchased) from the physicians. Lastly, they possess clinical trial data and anonymous patient level data about the clinical efficacy of a given drug.
- Last, but not least, you the consumer: In our digital age, it’s amazing how much data is actually available to us as consumers. Countless mobile applications and new gadgets like Nike Fuel Band and FitBit help us gather lifestyle related data about ourselves.
What are the Various Types of Data?
In total, there are four types of data when put together form the panacea of healthcare data. They are:
3) Behavioral/socio-economic data and
Claims data is the most mature, since payers have been dealing in claims for a long time. However, not everyone can access claims data, especially when it comes to historical data. Clinical data, though present in some electronic forms, is not always organized in one common, easy to access location. The proliferation of electronic medical records brings much promise, at least for providers, to have access to meaningful data. In contrast to claims and clinical data, having access to meaningful behavioral/socio-economic data is difficult. Some payers or providers have relied on Health Risk Assessments to collect behavioral/socio-economic data. For example, Aetna has invested in mobile applications to capture this segment of the data. There still remains an untapped opportunity to leverage mobile applications to capture lifestyle data, behavioral data and, even in some cases, very high frequency clinical data such as heart rate, blood glucose level, blood pressure, etc. Lastly, financial data poses some interesting opportunities to draw correlations for healthcare. For example, consider the Medicaid market and drug adherence. It is highly possible that drug adherence is low due to financial difficulty rather than neglect from the patient. If payers know that a person faces financial difficulty, they may be able to better coordinate care.
The first player in the market to harness the power of all four types of data together, will enjoy a sustainable first mover advantage.
What’s your next move? Stay tuned for the next part of this blog series which will describe a healthcare data value chain.
Image source: Revenge of the Nerds