Another year of crazy hype and development around healthcare tech trends is nearly in the books.
A big year for health IT as an industry, the developments of 2018 are now a part of larger ongoing debates about healthcare from a policy perspective. But there have been a number of important developments that failed to make the news.
As 2019 approaches, let’s take a look back at some of 2018’s most notable events and consider what they mean for the future of healthcare around the world.
Data Breaches Continue, Become More Efficient
While the overall number of data breaches across industries is slightly better than 2017, the prevalence of mega-breaches, those involving more than 100 million records, is up, according to Healthcare IT News.
For healthcare, the third quarter of 2018 was troublesome, with 4.4 million health records exposed across 117 breaches, according to Health IT Security. Those numbers followed second quarter numbers of 3.15 million records across 142 breaches and 1.13 million in 110 breaches in the first quarter.
More than half of the breaches were the result of hacking, while around 23% were the result of insider incidents, either error or wrongdoing. Error refers to accidents or incidents in which no harm was intended, while wrongdoing refers to theft or intentional violations of the law.
The industry is responding and evolving quickly in terms of tools and education as it tries to secure health information; however, hackers are keeping pace with the sophistication of phishing attacks and identity theft practices.
The answer, according to Lee Kim, HIMSS North America’s Director of Privacy, is collaboration.
“There are so many divisions in business, but I think we’re learning in cybersecurity, if we aren’t as organized as these nation state actors, cybercriminals (who are very organized as a business), how can we, being diluted in terms of our power and numbers, how can we match up?” Kim said in an interview with Healthcare IT News. “The answer is: ‘We can’t.’”
Interoperability is in Sight
It’s been a long struggle to get here, but 2018 has been a big year for interoperability. But now, as the federal government attempts to put the finishing touches on the Trusted Exchange Framework and Common Agreement, private companies are also stepping in to collaborate on interoperability along with efforts such as The Sequoia Project which have had success in their own right.
Earlier this year, Carequality and CommonWell Health Alliance launched live information exchanges between them. The pair serves around 80% of hospitals and 64% of clinicians nationwide.
This perfect storm of sorts sees interoperability efforts inching toward becoming a reality. That reality is expected to change thinking about the way FHIR and open APIs can help the industry use health data in more meaningful ways.
Things are not perfect just yet, as information is yet to be exchanged on a granular level instead of data dumps. But, for the first time, data liquidity is reaching a level where customizations and use cases such as Continuity of Care Documents are coming to life and can start to make incremental improvements as to how they play into the quality of care received.
Recognition of Social Determinants of Health
If you started to notice the phrase Social Determinants of Health (SDoH) popping up everywhere from conferences to your social media newsfeeds to The New York Times, it’s because there’s a growing consensus that these factors need to be considered in how we examine the quality of care and how doctors are paid.
As the shift toward value-based care takes shape, the use of SDoH is expected to grow among payers and providers looking to ensure that doctors aren’t essentially punished for seeing disadvantaged patients and that those patients receive the proper education regarding their care.
Efforts to incorporate SDoH into EHRs are being aided by the creation of the U.S. Core Data for Interoperability initiative, which aims to identify social factors required to be collected in FHIR format and shared through interoperable EHRs.
This effort could have a big impact on other areas such as patient engagement, medication adherence and care quality. While SDoH is not yet universal, one important stakeholder in the care process has already begun adopting it. According to a study conducted earlier this year by Change Healthcare and the Healthcare Executive Group, 80% of payers are integrating SDoH into member programs.
The Shift to Value-Based Care Continues
Value-based care is being implemented by a lot of payers due to the cost savings it provides, but it is far from completely replacing the traditional fee-for-service model. According to research by Quest Diagnostics, 75% of physicians don’t have all the information they need to implement value-based care and 57% don’t have the tools necessary to implement it.
There are concerns about decisions regarding creating correlations between procedures and outcomes. One example provided by Dr. Mary Barton, vice president for performance measurement at the National Committee for Quality Assurance (NCQA) examines a 30-day post-hip surgery recovery. That treatment provides a very straightforward measurement, she said, compared to treatment of a diabetic patient which can occur over decades and include several providers.
“When someone has a bad long-term effect and goes blind based on decades of poor sugar control, who will you put the outcome on?” she asked. “Will you blame the doctor taking care of that patient at the time he or she turns blind, or will you go back and figure out how to hold all the other doctors in the patients’ past responsible for that?”
The key to overcoming this is data liquidity across providers and payers alike, so that historical trends and context around the continuum of care can be understood and fuel decisions that impact how providers are reimbursed.
AI Continues to Move Beyond Buzzword Status
Artificial intelligence use cases have proliferated in the last couple years. At HIMSS18, the idea of AI serving in the clinical decision support role was a big topic. Former Alphabet Inc. CEO Eric Schmidt spoke of a vision for a system he dubbed “Liz” which would listen to doctor-patient conversations, document the entire interaction and provide advice to the doctor right there. He believes the power to do that is not that far away, adding that “everything I just described is buildable today or in the next few years.”
AI and machine learning are slowly working their way into the healthcare scene, but it’s not without growing pains. One key area of concern is the quality of data coming in. AI and machine learning technologies can only make good data-driven decisions if the data itself is of a good quality and accurate. This, in an industry where people lives can be at stake, leads to slow speed of adoption and some complex debates about the ethical dilemmas of AI.
But with that said, AI’s place at the table is becoming clearer as use cases provide a foot in the door for the technology to prove itself. A report from Tractica notes 22 use cases including areas such as medical image analysis, drug discovery, treatment recommendation, patient data processing and healthcare virtual assistants.
This has led to a growing confidence in the healthcare AI market, which is expected to surpass $34 billion globally by 2025.
