Why the US Healthcare System sucks (and how data analytics can help)
America is living in a healthcare paradox. The country has received more Nobel Prizes in Medicine than the rest of the world combined since 1966, yet it was also ranked lowest by the OECD in clinical efficiency.
Think about it, what other country can boast the most advanced hospitals in the world and yet erroneously kill 440,000 of its patients in hospitals through medical errors? That’s comparable to the entire population of Miami being wiped out every year because of medical errors!
These figures are more concerning still when you consider the fact that the US have the highest health expenditures per capita among developed countries. In a year, the government spends on average $8500 on healthcare per American. The second highest spender is almost $3000 behind with $5700 per Canadian spent per year. Yet perhaps the most telling statistic is simply the fact that fax is still the 2nd primary form of peer-to-peer communication in US healthcare.
BTW, it’s originally published right there
Transitioning to a Value-Based System
As you probably already know, the United States has recently begun its transition to a Value-Based Care System (VBC). VBC, as you already know, is opposed to Cost-Based Care (CBC) and is the principle behind the reimbursement system in the US.
It refers to the Value equation: Quality over Cost over Time. So, for patients, it means effective care at low cost. Value Based Payment is slowly displacing CBC. Under this plan, 90% of all traditional CBC Medicare payments should be tied to quality or value and 50% would be tied to alternative payment models by the end of 2018.
Data Analytics key to achieve care coordination.
All these major changes necessitate a greater level of interoperability between payers, providers and fiscal intermediaries, at a national and federal level. The goal of this new interoperability is to create a unified system where data flows from the payer to the provider, allowing for better care and cost reduction.
The core fundamentals of this type of model are the focus on care coordination and collaborative leadership across networks. These use of big data analytics is a major contributor to the success of that accountable care.
And healthcare data is multiple and flowing in from everywhere: social media/web’s data, machine 2 machines’ data, transactional data, biometric data, genomic data, and human-generated data… The HITECH Act of 2009 has sought to promote the adoption and meaningful use of health information technology to put order in that data. Patient data is now required to be electronically available in an effort to establish a healthcare system based on the principles of Value-Based Care (VBC).
A major limit: little (if any) interoperability
However Healthcare in the U.S. is characterized by a high degree of fragmentation. Hospitals have dozens of proprietary tools, siloed systems, and antiquated methods in place that generate severe inefficiencies. Imagine yourself printing datasets out on a sheet of paper and crossing the street to transcribe them on another hospital’s system? That is the kind of thing that happens. Today. In the US.
There is one possible reason for this: as of March 2015, there were 779 health IT vendors. Most of them are selling self-contained systems, intentionally siloed computing systems. That’s why a US hospital can have an average of 10 different Electronic Health Records. This makes data use and sharing far from optimal.
Healthcare Industry lagging behind innovation and money-savings
What is the point in having data if you can’t properly use It? Indeed, many believe this data shortcoming has impeded innovation in healthcare. Skype has been up and running since 2006 but telemedicine is still a far-off prospect. The Internet of Things is a booming market but you still need to go check your sugar rate at the hospital twice a week. We can forecast weather but patient forecasting is still based on historical averages.
Data sharing and use are therefore far from being optimal
Don’t worry, all is not lost. We’ll tell you soon how Dataiku’s DSS plans to save yearly the US healthcare system $450B. Stay tuned for the second part of our article on Dataiku and Healthcare!
Take Care (with DSS).
