By David A. Watson, chief executive officer of Akiri, and former CTO, Kaiser Permanente.
The American Medical Association (AMA) identifies one of the biggest challenges in healthcare today as the secure sharing and use of trusted health data in real time across the complex U.S. healthcare ecosystem. To hijack a Winston Churchill quote — data liquidity is a riddle wrapped in a mystery inside an enigma. The key to solving this puzzle is not more technology; we’ve had good integration technology for 30 years. What we need is a fundamentally different approach that addresses the adoption issues that have so far prevented success.
Do we face challenges caused by the inability to accurately identify different fragments of patient data coming from different systems producing incompatible data that is exacerbated by incomplete or inadequate data standards? Absolutely. And they are being addressed – albeit slowly – by the technology community. The more intractable problem is adoption. That challenge can be boiled down to three overlapping issues which hinder productive health outcomes:
Trust – there is insufficient trust among the healthcare data trading partners (e.g., healthcare organizations fear that shared data could result in some sort of business disadvantage).
Economic Incentive – there is no direct economic incentive for those who possess the data (and bear the cost of creating/communicating it) to share it with those who need it (and who benefit from it).
Control – organizations that share their data want to have a sense of control regarding what is being shared with whom.
Achieving data liquidity in the sprawling systems that make up the U.S. healthcare economy requires a combination of rethinking the applied technology to make it easier and less expensive, while closing the adoption gap by giving the participants in data exchange solid business reasons to do so. Without addressing the economic issues and retaining a strong privacy compliance footprint, no amount of technology will overcome the market entropy noted above.
Guest post by Abhinav Shashank, CEO and co-founder, Innovaccer.
The digitization of healthcare was a much-needed change brought after years of hard work and effort. One might wonder how could one justify the expenditure of $10 billion in a span of five years just on digitization. The problem intensifies when after several studies we find out that EHRs only reciprocate around 30 to 35 cents on a dollar and sometimes the figure dips to 15 cents.
Why have we digitized healthcare when the efforts required to get the desired result is still too much? I think we haven’t used the available technological aids appropriately. It is like driving a car at midnight and not knowing that you have headlights. You can have a clear view of your path, you can get to your destination fairly fast but can’t because you don’t know what is going to help you and in what way, your performance is reduced to a great extent to be able to achieve what you desire
Justified use of EHR could create the needed ecosystem
According to a report, 10 percent to 20 percent of savings are possible if a value-focused healthcare organizations capitalize on EHRs and interact with their patients better through technology. The amount that could be saved annually per bed is in between $10,000 and $20,000.
There are incentives for meaningful use of EHRs, but the truth is that the return through meaningful use incentives is somewhere around 15 or 20 cents on a dollars. There have been implementation, stabilization and optimization problems that have made it hard for healthcare organizations to extract the best out of EHRs. Practices will have to start using data as a source of innovation and come up with solutions that’ll not provide them better incentives but assist them in providing even better patient-centric care.
There are certain key points one can work on to make their healthcare ecosystem more efficient and patient-centric. Only judicious data usage from data disparate sources can help in so many ways, imagine what else is possible with advanced solutions. The integration of EHR with different disparate sources could be really beneficial in understanding the factors that drive value-based care. For instance, with the help of various data one can perform:
Population Health Management: With the help of data collected from different sources, impact at a population could be created and analyzed. Once you have the data of millions of patients, imagine all the things that are possible. Identification of at-risk patients, stratification of patients on the basis of various disease registries, better decision making, and a lot more. According to a study, due to disease management programs the cost of care were reduced by $136 per member per month because of reduction in admission rates by 29 percent.
Variations in Care Delivery: Efficient analytics and data management can help answer many questions. The medication process could be streamlined on the basis of past cases, and identified opportunities could be capitalized. Also, a thorough data-driven analytics could provide substantial insights on the performance of various facilities and how they differ when it comes to care delivery process.