With 2017 in the rear-view mirror, it is time to look forward to 2018 and how healthcare will evolve in this year. The last year has been an eventful one for healthcare, from the uproar in healthcare regulations to potential mega-mergers. Needless to say, it’s a time of transition, and healthcare is in a very fluid state- evolving and expanding. There are certainly going to be new ways to keep healthcare providers and health IT pros stay engaged and excited, and here are our top 10 picks:
The future of the GOP Healthcare bill
The Republican healthcare reform bill gained immense traction this year. In their third attempt at putting a healthcare bill forward, the senators and the White House officials have been working round the clock to gather up votes, but somehow, the reservations persist. The lawmakers have insisted that Americans would not lose their vital insurance protections under their bill, including the guarantee that the plan would protect those with preexisting conditions. However, as it so happens, even these plans have been put to rest. Perhaps sometime in 2018, the GOP may pass a budget setting up reconciliation for tax reform, and then pass tax reform. Then, they would pass a budget setting up reconciliation for Obamacare repeal, and then pass that- it all remains to be seen.
The ongoing shift to value from volume
Despite speculations, healthcare providers, as well as CMS have pushed for more value-based care and payments tied to quality, but it’s been going slow. Although providers have been slightly resistant to take on risk, they do recognize the potential to contain costs and improve quality of care over value-based contracts. And perhaps as data assumes a central role in healthcare, the increasing availability of data and smarter integration of disconnected data systems will make the transition easier and scalable. Notably, with a $3.3 trillion healthcare expenditure this year, there has been slow down the cost growth. 2018 is expected to be much more impactful as it builds on the strong foundation.
Big data and analytics translating data into real health outcomes
Big data and analytics have always brought significant advancements in making healthcare technology-driven. With the help of big data and smart analytics, we are at a point in healthcare we can make a near-certain prediction about possible complications a patient can face, their possible readmission, and the outcomes of a care plan devised for them. Not only it could translate to better health outcomes for the patients, it could also make a difference in improving reimbursements and regulatory compliance.
Blockchain-based systems
Blockchain could arguably be one of the most disruptive technologies in healthcare. It is already being considered as a solution to healthcare’s longstanding challenge of interoperability and data exchange. Bringing blockchain-based systems will definitely require some changes from the ground up, but 2018 will have a glimpse of by innovation centered around blockchain and how it can enhance healthcare data exchange and ensure security.
AI and IoT taking on a central role
2018 can witness a good amount of investment from healthcare leaders in the fields of Artificial Intelligence and Internet of Things. There is going to be a considerable advancement in technology, making the use of technology crucial in healthcare and assist an already unbalanced workforce. AI and IoT will not only prove instrumental in enhancing accuracy in clinical insights, and security, but could also be fruitful in reducing manual redundancy and ensuring fewer errors as we transition to a world of quality in care.
Digital health interventions and virtual care to improve access and treatment
In December 2016, many were suggesting that wearables were dead. Today, wearables are becoming one of the most sought-after innovation when it comes to digital health. And, the market is quickly diversifying as clinical wearables gain importance and as several renowned organizations integrate with each other. Not only wearables- there are several apps and biosensors that can assist providers with remotely tracking patient health, engage patients, interact with them, and streamline care operations. As technology becomes central to healthcare, 2018 will be the year when these apps and wearables boost the patient-physician interaction.
Guest post by Todd Greenwood, PhD, MPH, director of digital strategy, and Benjamin Dean, digital and business strategist, Medullan.
Todd Greenwood, PhD, MPH
Once upon a time, all that pharmaceutical companies had to do to get their drugs on formulary was to package their clinical data and convince payers that their products performed better (or better enough) in clinical trials. Contracts were struck and the revenues flowed. For most new specialty drugs, those days are now history.
With the average retail price of a specialty drug used on a chronic basis exceeding $53,000 (according to an AARP study), nearly 200 times the average price of generics, payers are demanding that pharmaceutical companies make data-driven, value-based cases before access is granted. Even when payers are convinced , they build stipulations into value-based contracts that require manufacturers to prove that outcomes are being met with their covered lives, or else the pharmaceutical company will face additional penalties or further restrictions.
This all means that the data that manufacturers have used to drive regulatory approval are insufficient for garnering payer formulary access. Companies are being required to prove that their drugs work in the real world – not just within the carefully controlled environment of a clinical study. Across therapeutic areas from osteoporosis to oncology, payers have and are currently using real world evidence studies to define their formularies. Payers want to know how expensive specialty drugs will perform as patients adhere to (or in most cases don’t adhere to) their medications, and outside of the rarified air of a traditional clinical trial.
Benjamin Dean
Equally importantly, payers want to know how drugs affect the most important (and most expensive) health outcomes. Clinical data showing that a drug performed some percentage better than either a category leader or a placebo is now insufficient for new specialty drugs. Instead, payers need to know how health outcomes improved and how effective the drugs were at keeping patients out of the hospital and away from the catastrophic costs.
While it may sound easy, providing this kind of data is far from simple. Clinical trial data is controlled, clean and contained. Surveillance data (AKA real-world data) is a different beast, because patients are complicated. We have multiple conditions, take multiple medications, and we are inconsistent, rarely complying with our doctors’ orders. Moreover, the outcomes that payers care about – hospitalization, disability and death – can be difficult to distill. The data needs to be compiled from a variety of sources: medical and prescription drug claims, electronic health records, the lab (genomic and pathology data) and directly from the patient. Compounded with this, different populations of patients have different risks, and comparing one to another is fraught with difficulty. Finally, real world data can take time to accumulate. In order to know if a drug is working “in the wild”, researchers need to follow enough patients, for long enough, to observe negative health events of interest.
Take, for example, the new class of hyperlipidemia drugs, PCSK9-inhibitors. These injection drugs have been shown to cut LDL cholesterol levels in half, compared with about a 20 percent reduction for statin-class drugs like Zetia. But given the high price of these drugs ($14,000 per year in the US) plus their potential to be prescribed to a significant percentage of the population, payers have largely refused an access foothold. Payer organizations in the US and around the world are asking the same question: how well do these drugs work in real patient populations and to what end? Given that these drugs will be sanctioned for high-risk patients (many of whom will continue to use statin class drugs as combination therapy), payers are concerned about adherence, and ultimately if there is lower cardiac risk and fewer related cardiac events in patient populations. Many economists are asking: can’t we achieve the same ends for far less money by getting patients to adhere more faithfully to their statins?
The need is clear: pharma companies who have invested significantly to develop and launch new specialty drugs have to prove their worth with real world data. But in markets like the US, where providers are typically siloed and disconnected, it’s challenging to capture patient-level condition and drug utilization data, and effectively append it with hospitalizations, other outcomes evidence and costs in order to develop a complete picture.
But there’s hope. As the specialty drug market begins to shift to a value-based model, new ways of tracking real-world usage and connecting it to outcomes are emerging. This is where digital health is poised to play a critical role.
