We live in a world where medical errors are the third leading cause of death behind cancer and cardiac disease, leading to more than 200,000 preventable deaths every year. We have an aging population growing at an unprecedented rate: 8.5 percent of people worldwide (617 million) are aged 65 and over, and this percentage is projected to jump to nearly 17 percent (1.6 billion) by 2050, leading to an anticipated physician shortage of more than 50,000 by 2025.
On top of all of this, healthcare costs are projected to increase to over 25 percent of GDP in the United States by 2025. The convergence of these events is pushing the entire industry to begin leveraging technology more than it has in the past.
Many of these challenges can be remedied by leveraging industrial IoT (IIoT) technology that’s been proven to solve similar challenges in other industries. Could an interoperable, connected healthcare platform that applies the principles of an IIoT connectivity architecture to share data throughout the healthcare system be the cure for our ailing healthcare system?
West Health, now the Center for Medical Interoperability, seems to think so. In 2013 they published a report showing how an interoperable, connected healthcare system could provide nearly $30 billion in industry savings while improving patient outcomes in the process. These connected healthcare platforms provide the foundation for innovation that is needed to make a meaningful data-driven change in healthcare. It’s these platforms that open the door to application developers everywhere to create modality-specific applications using artificial intelligence and machine learning.
So what exactly is a connected health platform and how does it provide a foundation for transformational change in healthcare? First, a connected health platform consists of hardware (gateways and servers) and embedded software components that are designed to take all of the data from any medical device (clinical or remote) and convert the data in a single usable format that gives providers access to a complete data set.
This connected platform will provide a variety of user interfaces, analytics and clinical applications to help users throughout the healthcare ecosystem distill value from this newly-gathered data. The applications range from the early detection of sepsis, to predicting cardiac arrest, to providing business analytics like bed and device utilization.
The connected health platform will become the center of an ecosystem for further application development, similar to that of an online app store — but with built-in medical-grade safety and security. The connected health platform must ensure data security and patient privacy by aligning to guidance provided by the FDA on cybersecurity, and meeting the standards defined by HIPAA.
However, these connected health platforms are only as effective as the data they capture, which is determined by the connectivity frameworks they are built upon. Many of the currently deployed platforms are not platforms at all, but a collection of disparate systems that provide silos of individual device data. These legacy systems have been built using internally-developed, proprietary, message-based communication technology.
As the first step towards the development of a connected health platform, modern web services-based communication has been deployed on top of the legacy technology to begin integrating all of the disparate data streams via onsite data centers or the cloud. Although this is a step in the right direction, these platforms are far from complete. Because of legacy communications infrastructure they are built upon, they are only able to aggregate a portion of the data making these systems a poor fit for true near-patient, real-time clinical decision support – the key to efficiently providing improved patient outcomes.
The EMEA market for electronic health record (EHR) IT is estimated to have been worth $3.7B in 2018 (both acute and ambulatory applications) according to Signify Research’s 2019 global EMR market report. However, only one vendor, Cerner, is estimated to have had a double-digit revenue share in 2018. In terms of suppliers the EMEA market is highly fragmented with a mixture of local and international vendors addressing individual countries with few vendors having a truly region-wide footprint.
The table below shows estimated revenue shares in 2018 for the acute & health system EHR market in EMEA (excluding revenues for ambulatory only solutions), alongside the countries/sub-regions where each vendor had a significant share of its EMEA business.
Acute/Network EHR Estimate Revenue Share – EMEA – 2018
2018 Rank
Company
2018 Revenue Share
Key Countries/Sub-Regions
1
Cerner
16%
DACH, UK/Eire, Middle East
2
Agfa Health
8%
DACH, France
3
Asseco
5%
Eastern Europe
4
CompuGroup Medical
5%
DACH, Nordics, Eastern Europe
5
InterSystems
4%
UK/Eire, Middle East, Spain/Portugal
6
Chipsoft
4%
Benelux
7
DXC Technology
3%
Benelux, UK/Eire, Spain/Portugal
8
Tieto
3%
Nordics
9
Dedalus
3%
Italy, France, Spain/Portugal
10
Nexus
3%
DACH, Benelux
11
Engineering Ingegneria
3%
Italy
12
Systematic
2%
Nordics
13
Epic
2%
Benelux, Nordics, UK/Eire, Middle East
14
Telekom Health
2%
DACH
15
Maincare Solutions
2%
France
Others
39%
Source: Signify Research
Note: Does not include ambulatory only revenue/vendors
In a drive for standardization, the proposed U.S. Core Data for Interoperability1, mandated by the 2015 21st Century Cure Act2, calls for the identification and refinement of a basic set of clinical data to be required for all electronic health records. The American Medical Informatics Association, however, recommends that healthcare researchers and providers concentrate on sharing data as quickly as possible, deferring the creation of standards until sometime in the future.3 “This is a false choice and a distraction,” said James D’Arezzo, CEO of Condusiv Technologies.
James D’Arezzo
D’Arezzo, whose company is the world leader in I/O reduction and SQL database performance, adds, “What the healthcare industry really needs to focus on is enabling its heavily overburdened IT infrastructure to do the job it’s being asked to do.”
The industry’s preoccupation with interoperability and standardization, notes D’Arezzo, is perfectly understandable. Turf wars over proprietary interfaces and protocols are having a major impact on healthcare IT budgets.4 Non-compatible electronic health records contribute significantly to the fact that computerized record keeping consumes more than 50 percent of the average physician’s workday, which now stretches to more than 11 hours.6 Healthcare organizations struggling to process this tsunami of data are frustrated by the number and variety of analytics tools they are forced to use.6
Supporting all this activity, however—unnoticed and, says D’Arezzo, dangerously neglected—is the basic computational machinery itself. Data analytics requires a computer system to access multiple and often far-flung databases, pulling information together through millions of individual input-output (I/O) operations. The system’s analytic capability is dependent on the efficiency of those operations, which in turn is dependent on the efficiency of the computer’s operating environment.
According to experts, the most widely used operating system, Microsoft Windows, is in many ways the least efficient. In any storage environment, from multi-cloud to a PC hard drive, Windows penalizes optimum performance because of server inefficiencies in the handoff of data to storage. This is a problem that, untreated, worsens with time. The average Windows-based system pays a 30 percent to 40 percent penalty in overall throughput capability because of I/O degradation.7
By Karen Way, global practice lead for data and intelligence, NTT DATA Services.
Karen Way
A recent study conducted by NTT DATA Services and Oxford Economics highlighted the top three challenges identified by healthcare executives and consumers: standardizing and sharing of data across the healthcare spectrum, preparing for and adapting to regulatory changes and recruiting or retaining the right resources. It’s understandable that these challenges rise to the top of the list, as trying to meet rising consumer demands for access to their healthcare data while maintaining regulatory compliance with limited resources is a bit like juggling raw eggs. If your timing or skills are just a bit off, you end up with egg on your face.
How can a healthcare organization address these challenges? First, it’s important to understand exactly which challenges are present within your own organization, and how they are impacting the patient experience.
Data Sharing
Study results showed that only 24 percent of healthcare organizations share data across the business. Why? There are several reasons:
Interoperability – Even though this concern has been expressed since the inception of the EHR/EMRs, there are still barriers to being able to communicate data between different systems in a consumable, usable format. For example, several years ago, I had a CT scan due to the sudden onset of a continuous migraine headache. After the scan, I was referred to a neurologist that practiced out of another hospital system. I took a copy of the scan (on a DVD) to my specialist appointment, but the doctor was unable to view it on her system. As a result, I had to have another CT scan for the neurologist to see what may have been happening. Data already collected could not be used due to lack of standardization across systems. As noted in Dr. Eric Topol’s book Deep Medicine, “Your ATM card works in Outer Mongolia, but your electronic health record can’t be used in a different hospital across the street.”[1]
Data Volume – The volume of data being generated daily in the healthcare industry has been estimated to be approximately 30 percent of the world-wide total. With the estimates of data generation rates of at approximately 2.5 quintillion (that’s 1, followed by 30 zeros) bytes/day, that’s a lot of healthcare related data. Healthcare organizations aren’t even beginning to tap the depths of this data, simply due to the data volume.
Disparate Data – Like patients, healthcare data comes in many different shapes, sizes and languages. Even if interoperability issues didn’t exist, sharing of data across the healthcare business is hard because of these differences. Data can be an image, a PDF, a written note, a prescription label, etc. Historically, each type of data requires different mechanisms for managing it, often using different tools or systems.
These three factors combined can be overwhelming for healthcare organizations whose main goal is to provide the best healthcare possible.
Resource Management
Another leading challenge identified in the study is that of recruiting and retaining skilled resources. Of the healthcare executives surveyed, only 51 percent stated that they were able to recruit and retain resources with the required skills and knowledge. There are two components to this issue:
Upskilling resources – With the continual advancements in technology, it is important to ensure that resources can take advantage of training opportunities and professional growth. This is often a delicate balance for organizations; time spent in training is often seen as time away from projects with deadlines.
Healthcare experience – While there may be a pool of qualified resources with the required technical skills, it can be hard to find resources with knowledge and/or experience in the healthcare sector. For example, several years ago, a client brought in resources to support their enterprise data warehouse that had extensive experience in data warehousing. There were high expectations of new and improved functionality due to the technical depth of these resources. Unfortunately, the project did not deliver as expected. Why? None of the resources had knowledge of healthcare data or business processes. One resource posed the question to the client: “what is a healthcare claim?”
Just as important as reviewing the patient experience for ways technology can solve the problem, it helps to treat your workforce like your customer and improve the experience of transforming the organization into a digital-first enterprise. A recent article in the Wall Street Journal highlights the difficulty in recruiting resources and approaches to solving this challenge. The article also reinforces that in today’s data economy, it is no longer enough that a resource be technically skilled, they must also have knowledge of the business environment in which they are applying the technology.
By Jessica Kojima, vice president of professional services, AdvancedMD.
Jessica Kojima
Medical providers often battle inefficient and piecemeal software configurations that constitute the technological lifelines of their practices. Even if current solutions aren’t integrated to meet their needs, they sometimes feel it is easier to stick with what they’ve got instead of considering the possibility of upheaval.
Staying current—or better yet, striving for innovation—often comes at a price of temporary disruption for providers and staff. But if a new electronic health record (EHR) and practice management (PM) system are implemented with proper planning and stakeholder buy-in, the practice can realize true efficiency without substantial disruption.
Here are three best practices for implementing a new EHR or PM system for medical practices to minimize disruption.
Consider the big picture
Before the EHR/PM implementation process kicks off, the practice should assess the effectiveness of its clinical and administrative workflows. A practice that wants to cram a new EHR or PM into an existing workflow that isn’t working is thinking short-term. It’s important to consider “big picture” goals and aim to improve bad processes and optimize productivity. An effective approach will realize efficiencies across an entire practice versus one function or role. By considering the importance of productivity optimization across the whole operation, a holistic and integrated approach will enable growth and improvement for both patients and staff.
Preparing for payer migration
While considering the practice’s overall goals, the practice must also perform a payer analysis. A new PM system will require new Electronic Data Interchange (EDI) agreement enrollments to electronically submit and receive claims, remittance, eligibility, and claims status, which differ from payer to payer. This is often a forgotten aspect of moving to a new practice management system, and is arguably the most critical change. The practice should have the following items ready well before implementation:
List of payer IDs as they are credentialed. This information can be found by reviewing how the practice submits and receives electronic transactions currently, or by contacting the payer directly.
The official name as credentialed.
Understand if the providers are credentialed as a group or provider.
Tax ID.
National provider identification (NPI) number.
Many payers also require online registrations, voided checks, letters on specific letterhead—to name a few—to process an agreement. This demands timely attention by a designated individual in the practice for a seamless enrollment process. The practice should also set a “go-live” date to start submitting transactions through the new system. Preparing adequately in the weeks ahead of implementation will enable a timely kickoff of the new system.
Focus on people
Instinctively, an EHR and PM implementation might seem to be all about the software technology. Not so: it’s about the people. It’s vital that a medical practice identifies an implementation champion who will be responsible for both supporting and managing the transition. Depending on how aggressive the go-live goal is, the practice may need a practice management and a clinical champion to ensure all of the configuration and training occurs simultaneously. The champion’s role is to listen to every staff member affected by the transition and communicate openly with the team about why the switch is being made and how the leadership will support them. Ideally, everyone agrees on the approach, objectives, and expected outcomes.
When you think of an industry that’s mastered the creation of a seamless, digitally integrated experience for the customer journey, the airline and travel sector is unlikely the first that comes to mind. The experience has become so seamless as to be practically invisible, and any breakdown in that seamlessness is highly painful and disruptive for the customer.
The airline industry is the perfect example of one that has succeeded in orchestrating the customer journey and improved customer experience. Rather than calling a travel agent to book or manage one’s travel itineraries, passengers now research, book and manage flights on their own – and do so digitally. Not only do these digital tools allow passengers to check-in, upgrade and receive loyalty benefits, but they also keep passengers current with real-time flight status – from check-in times and cancellations or delays, to re-booking and satisfaction surveys.
What used to be a highly fragmented journey for travellers is now seamlessly connected thanks to online services that deliver the sort of automatic, digital experience that today’s consumers have come to expect in every aspect of their lives, from online retail shopping to booking travel accommodations.
Healthcare is not exempt from that expectation. In fact, consumers – Millennials and Generation Z, in particular – who are accustomed to this new world of always-on, instant service are causing the healthcare industry to undergo its own consumerization. Patients want the ability to manage their healthcare digitally the same way airline passengers automatically manage their travel.
Evidence of this industry wide shift has been steady. For example, mail-order prescriptions have been around since the 1990s, slowly increasing in popularity over the years and are more prevalent now than ever before. Just within the past year, we’ve seen new startups like NowRx and Capsule emerge while tech giants (the originators of today’s consumer experience) snatch up others as they foray into healthcare, such as Amazon’s acquisition of PillPack.
In fact, Amazon’s entry into the healthcare market alone is proof of the industry’s broader consumerization. Amazon’s business model has completely disrupted the retail industry and been a primary driver in creating today’s consumer expectations for seamless, digital experiences. Most recently, Amazon announced that its Alexa device is now HIPAA-compliant, allowing health organizations to use the voice-enabled speaker to help patients book appointments, access hospital post-discharge instructions, check the status of a prescription delivery, and much more.
This recent development is further proof of patients’ desire for convenience through using digital tools in their healthcare – something the industry has been slow to adopt.
Prepare for takeoff
Healthcare today consists of a broken, fragmented patient experience. The industry, however, stands at a turning point, where vast amounts of digital patient data are already available. By leveraging this data, healthcare organizations have an opportunity to differentiate their brands and create a seamless care journey – just like airlines keep passengers continually engaged, and ultimately deliver better service at a lower cost.
How can healthcare use available data to take off and further consumerize the patient experience? Real-time health systems, which Gartner considers “a management and operating paradigm…for the next-generation healthcare provider,” will play a pivotal role in transforming the way providers deliver care. Not only can real-time health systems orchestrate the care journey, but they also deliver real-time situational awareness about the patient’s history, as well as current and future care needs. Embracing real-time health systems will be key to unlocking a truly digital consumer experience, ensuring that computer systems execute best-practice behind every care journey.
Each year, Hyland Healthcare conducts focus groups with HIMSS members representing top healthcare provider organizations. The interactive, in-depth discussions always reveal powerful insights we can use to improve our solutions.
This year’s topic was enterprise imaging. We wanted to gain a better understanding of the drivers, strategies, challenges and desires healthcare leaders have in this area.
Consensus from the group seemed to indicate that the evolution of healthcare in general is driving the demand for enterprise imaging. For example, increased consolidation, partner collaboration and merger and acquisition activity are creating imaging environments that are complex and extremely difficult to manage. It becomes problematic, expensive and risky to attempt to manage and maintain multiple silos of imaging data throughout all of these locations.
“The acquisition of outpatient imaging centers combined with the disparate imaging silos we already have internally creates a lot of waste,” said Peter Overeem, CTO of Adventist Healthcare. “Several efficiencies can be gained by bringing all our images — both inpatient and outpatient — together into one consolidated system.”
Furthermore, it was agreed upon that PACS is a dated technology that is centered on radiology and cardiology, and likely not the best equipped to handle the centralized management of images throughout an enterprise.
“With the advancement of AI, we need to start adopting enterprise tools,” said Michael Knopp, MD, professor and director at Ohio State University. “We can’t maintain an environment where everyone has their own departmental solution. PACS vendors are focused on specific niches and are fairly slow to add new innovations that benefit the enterprise. The solutions you implement today need to be capable of adapting and innovating at a much faster pace.”
One-size does not always fit all
The demand for enterprise imaging tools was clear from the group. However, participants also communicated several challenges and roadblocks when it comes to implementing solutions that satisfy the needs of all the stakeholders involved.
“We can’t get the different imaging-centric departments to agree on one technology platform that meets everyone’s needs,” said Overeem. “What one person likes, another hates. We’re concerned about implementing an enterprise solution that causes some departments to settle for a less optimal solution for their specialty.”
Blockchain offers countless opportunities for growth and development of many industries. Sectors like finance, banking, government and public services, education and commerce have already taken the first steps at embracing this revolutionary technology.
One of the industries blockchain can change beyond recognition is healthcare. In this post, we will cover the opportunities blockchain offers for the healthcare sector, and the present use cases of blockchain in healthcare.
Why does healthcare need blockchain?
Healthcare industry has a lot of issues on a local, national and global levels. It has been struggling with data collection, storage, and transfer problems for a long time now. Federal regulations and rules make all the healthcare procedures lengthy and tedious. The current healthcare system does not manage patient data well. Pretty often it happens so that one patient cannot gather all of their medical records in one place and in one format quickly, or cannot gather the needed information at all.
Unfortunately, critical patient information is in most cases scattered across different healthcare institutions in different formats. What makes it even harder for healthcare providers and patients is that data management systems and security regulations often vary across different institutions and states. What’s even worse, many medical records have mistakes in them, and the outdated data management systems cannot trace and fix these mistakes. It all boils down to this: in extreme situations and in time of urgent need, it is practically impossible to access all the needed patient information easily, quickly and securely.
What can blockchain do here? With the help of this innovative technology, healthcare providers will be able to facilitate their data management processes beyond recognition. Blockchain can help healthcare providers collect, exchange, analyze and secure medical records seamlessly. It will give doctors and patients an opportunity to access any needed patient data from anywhere without tolerating the privacy or security of any party.
Can blockchain be a panacea for the healthcare industry? One thing is for sure — this technology can help the healthcare system improve healthcare services greatly without rising the costs of the corresponding processes significantly.
Blockchain and patient data handling
Blockchain can help the healthcare sector solve the issue with patient data storage. Potentially, it can cancel all the cultural, geographical, political and religious limitations that interfere with patient data handling nowadays. When the patient data is stored in the blockchain, it can be processed, managed and transferred seamlessly and securely. It means that in times of greatest need and urgency all the required data will be there to save a life.
MedRec, an Ethereum-based system, is one of the first blockchain-powered solutions that aim at facilitating patient data management. MedRec makes it easy for patients and doctors to view and manage patient data securely.
We live in a world where medical errors are the third leading cause of death behind cancer and cardiac disease, leading to more than 200,000 preventable deaths every year. We have an aging population growing at an unprecedented rate: 8.5 percent of people worldwide (617 million) are aged 65 and over, and this percentage is projected to jump to nearly 17 percent (1.6 billion) by 2050, leading to an anticipated physician shortage of more than 50,000 by 2025.
