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March 2017 - Issue 1
Welcome to Battelle’s Medical Devices newsletter. We offer this newsletter as a service to our clients to keep you informed of the latest news from our researchers and the industry.
Battelle’s Medical Devices team can help you accelerate your medical product development timeline – from ideation to evaluation to commercialization. Our newsletter will help keep you up-to-date on cutting-edge medical devices work, including device security, drug delivery, usability testing and neurotechnology.
By Dr. Darryl W. Roberts and Dr. David Friedenberg
Will all of tomorrow’s healthcare decisions be made by computers? Not quite, but Clinical Decision Support (CDS) tools can make doctors, nurses and other healthcare workers smarter and more effective. Thanks to advances in data analytics, this machine-assisted medical future is closer than you may think.
Beyond the Pop-Up Alert
Technology-enabled healthcare decision making is not new. Alarms on ventilators and IVs, pop-up drug interaction alerts and other basic decision support tools have been in use for decades. However, these simple alerts and alarms do not rise to the level of CDS.
The Office of the National Coordinator for Health Information Technology (ONC; HealthIT.gov) defines CDS as a system that “provides clinicians, staff, patients or other individuals with knowledge and person-specific information, intelligently filtered or presented at appropriate times, to enhance health and health care.” In other words, it is the ability to get the right information to the right people at the right time in order to inform diagnosis, treatment or follow-up. CDS uses data from a variety of sources (e.g. medical sensors, electronic health records (EHRs), physicians’ and nurses’ observations and clinical knowledge bases) to provide real-time guidance to clinicians using established and vetted guidelines. Many examples are already in use today:
CDS has the potential to improve patient outcomes and healthcare efficiencies significantly. CDS tools can help doctors and nurses avoid errors and adverse events and increase quality of care while reducing overall costs. That’s why the Centers for Medicare and Medicaid Services (CMS) gave CDS an important role in the original Medicare and Medicaid EHR incentive program. That worked so well that under the Medicare Access and CHIP Reauthorization Act (MACRA) Final Rule, CMS does not require CDS reporting, because it has “topped out” or achieved its goal. This change suggests that hospitals and healthcare providers will increasingly rely on CDS tools to help them meet patient care and financial goals under CMS’ Alternative Payment Models (APMs)[BND1] and similar models preferred by private insurers.
The Smart, Connected Future of Clinical Decision Support
While healthcare providers already rely on a multitude of tools to support decision making, we have only begun to scratch the surface of what will soon be possible with CDS. Imagine:
These examples are already within reach using the technology we have today, thanks to advances in health IT and data analytics. EHRs improve accessibility to patient data, but limitations to usability and interoperability still present challenges. In its current state, EHRs accessible to clinicians, patients and (with appropriate HIPAA protections) researchers make it possible to employ advances in “big data” analytics tools that can put that data to work. Instead of simply making recommendations for individual patients based on standardized guidelines, we can now use data mining, text mining and machine learning methods to extract subtle patterns in massive data sets and create new recommendations informed by cumulative expert knowledge and statistical analysis.
Sophisticated analytical programs are able to collect and analyze data from disparate sources—for example, body-worn medical sensors, EHRs, PHRs, administrative and billing records, imaging and diagnostic data and more—in order to answer complex medical questions[BND2] . Using these methods, hospitals and care providers will be able to make treatment decisions matched to patient and disease characteristics, quantify the added value of a treatment, or even automate some aspects of patient care. Other programs enable providers to mine large knowledge bases (such as PubMed) to inform evidence-based practice and identify hidden connections. For example, Battelle Sematrix™ uses natural language processing to sort through large corpora of unstructured scientific or technical information, allowing users to answer complex questions. Unlike simple keyword queries, these programs are able to make inferences by combining knowledge contained in different documents within the corpus.
Removing the Barriers to CDS Implementation
While basic technologies for CDS are already in place (and according to CMS “topped out” in their use), that doesn’t mean the industry is maximizing their utility just yet. Before that can happen, the industry needs to resolve significant market, technical and human constraints.
One of the most significant technical constraints is EHR interoperability. Each of the commercially available EHR systems tags and stores data differently. This severely limits our ability to combine records from different hospital systems for large-scale data mining. Interoperability minimizes the differentiators among EHR companies and even healthcare systems. There are currently not enough incentives in place to make data interoperability a priority for them in the current market. In fact, there are disincentives, even in the presence of government-sourced incentive programs. This means that researchers and clinicians who depend on easy exchange of health information for improved care coordination, reduced costs of care, and research to enhance practice are forced to use existing, inefficient workarounds. These workarounds include using traditional resource, such as questionnaires, that obtain needed information at the cost of additional clinician burden.
Another significant factor for the acceptance of CDS is usability. Decision support tools must fit within the clinical and administrative workflows and must be easy to use and understand in a complex, fast-paced environment. This is especially true of decision support built into “RN-ware,”1 or devices used by nurses to make on-the-fly patient care decisions. Already, nurses working in an ER or ICU may have dozens or even hundreds of devices that they use over the course of their day, each with its own unique alert sounds and interface. The resulting confusion makes medical errors more likely as nurses may miss critical alerts buried in the noise or misinterpret recommendations due to data overload. As more of these devices begin to incorporate sophisticated decision support tools, developers need to incorporate human factors to ensure that the systems help clinicians manage the volumes of data they are presented with and enable them draw fast, effective conclusions.
CDS and the Evolution of Medical Care
Clinical decision support is not about supplanting human thought. In an ideal world, CDS frees up doctors, nurses, caregivers and patients themselves to access wider knowledge bases and datasets and to think more deeply about what the collected data and knowledge is telling them. CDS tools are already making healthcare providers more effective and efficient and improving the quality of care for patients.
The data revolution in healthcare is moving fast. According to the MACRA Final Rule, CMS expects 80 to 90 percent of eligible clinicians to participate in APMs and other value-based payment models by 2020, thus shifting away from the current method of payment for quantity. This will result in a similar payment model shift by private insurers, as well as increased competitive pressure for improved quality of care. This will serve to push healthcare systems towards wider adoption of data-driven decision making. Data analytics and CDS tools will be critical components in helping the industry meet CMS targets and improve patient outcomes and financial returns. We can expect to see increasingly sophisticated CDS tools baked into tomorrow’s smart medical devices and programs.
Most of the components necessary to achieve the full promise of CDS already exist in some form. To bring the vision to fruition, medical device manufacturers, EHR and other software developers, health care systems, clinicians and patients will need to work together to solve issues around interoperability, data accessibility and human factors. As we make data more accessible, usable and understandable, CDS and data analytics are poised to take healthcare to a whole new level.
1 Dr. Roberts coined the term “RN-ware” in a 2015 MS Health Blog to explain how nurses pull together knowledge from a multiplex of disparate information sources (e.g., EHR, IV pump, ventilator) to draw the clinical picture of a patient for herself and other clinicians—oftentimes in an instant.
About the Authors
Dr. Darryl W. Roberts is a Registered Nurse and a Healthcare Quality Research Leader at Battelle. He has more than 25 years of experience in patient care, informatics, management, research and education. His recent work includes developing economic metrics for public health interventions, supporting the quality Measures Management System for CMS, developing quality measures for SAMHSA and bending qualitative research methodologies to make their use possible in natural language processing and big data analytics.
Dr. David Friedenberg is an Applied Statistician and Data Scientist whose work focuses on extracting meaningful information and structures from large, high-dimensional datasets. At Battelle, he analyzes complex high-dimensional data in fields such as Neuroscience, Chemical Forensics, Medical Devices and Astronomy as well as large health care and insurance databases.
By Chris McKenzie, Battelle
Exciting new developments in drug delivery are creating unprecedented opportunities for medical device developers. However, in the rush to get to market, it’s easy to make expensive — and potentially dangerous — development missteps. Here are five steps that device developers can take to ensure their final device fully meets technical, user and regulatory requirements.
Build An Effective Theoretical Model
You’ve got a great idea for a novel drug delivery device, and your initial prototype works (more or less). That’s great! But do you understand why it works?
Often, manufacturers move into device development without fully understanding the science and engineering theory behind their device. The device may be a variation on something already on the market, or it may be something new, based on the designer’s intuition and prior knowledge. Before finalizing your design, you should make sure that you fully understand the science and engineering principles behind it and be able to build a mathematical model of how it works.
For example, the theoretical model for drug delivery time in a new auto injector might include variables like:
An effective model is highly predictive, allowing you to determine which variables you need to adjust in your device design to achieve desired performance. Empirical testing is performed to validate the model. If empirical testing using prototypes does not correlate to the model, you know there is a gap in your understanding of the science behind your device and/or issues with the parts used in testing. Additional testing and model development will allow you to fill in these gaps in understanding.
An effective model, demonstrating solid understanding of the science and engineering theory the device is built on, will speed up development by allowing designers to predict device performance sensitivity as design inputs are altered. This sensitivity analysis also can help the technical team determine the design’s “sweet spot” and margin between acceptable and unacceptable performance. It also will help you reduce potential risks by understanding predicted performance under a variety of potential design and use scenarios.
Prove Your Core Technology
As you develop a solid theoretical model, you need to continue testing your prototypes to make sure they perform predictably under reasonably expected environmental conditions and use cases. While successful performance at nominal conditions is a good first step, consider evaluating performance at a wider range of conditions sooner rather than later. The earlier you can more completely challenge your core technology, the less likely you are to encounter avoidable and expensive problems further along the development timeline.
One important aspect that some designers neglect is product performance after aging. Your core technology may perform perfectly out of the box, but do you know how it will perform after six months, one year or five years of use? Accelerated aging studies can give you important insights into potential risks and liabilities for your product once it is released. These evaluations should be performed during early prototyping, as any design weaknesses identified can be more efficiently addressed — and for less money — during this stage of development than after design freeze.
Understand Your Technical Team’s Limits
Do you have materials science expertise on your team? Finite element analysis? Design for assembly? While large device manufacturers may have vast design and engineering departments, most smaller device developers work with a small core team of engineers who wear many engineering “hats.” Whether you have a large or small team, it’s important to objectively and accurately assess their strengths and weaknesses and to identify areas where you may need help from an outside subject matter expert. Beyond basic engineering design, key consideration should be given to such areas as:
Early in the project, gaps in expertise may be considered risks. A realized risk is an issue, and issues don’t usually occur at convenient times during the project. If you don’t have clear expertise in-house, consider bringing in consultative support. The right external resource can be an invaluable asset to quickly mitigate gaps in technical expertise.
Don’t Neglect the Human Element
Human factors testing is required for regulatory approval. However, medical device developers should consider human factors and usability issues at every stage of design. No matter how well your device performs technically, if users are not able to use it correctly, or it does not fit easily into user routines, it is not likely to be accepted in the market.
Human Centric Design (HCD) is an approach to device development that puts the end user at the center of all design decisions. By considering human factors and usability issues from the very beginning of the design process, medical device developers can avoid costly redesigns prior to market release. They also will uncover unexpected insights that can significantly increase market acceptance and, ultimately, sales.
Challenge, Challenge, Challenge
It can’t be said enough: test your device design early and often. Design reviews are not just for the end of the development process. You should be continually challenging your design assumptions, evaluation results and plans at every stage of development, from initial concept to final product.
Early design reviews can save considerable time and money later on. The earlier you find and fix a potential problem, the more cost effective that fix will be. Correcting problems with a device during final verification and validation can be many times more expensive than making corrections at the design phase and will cause considerable delays in your market release schedule.
Often, early-stage design reviews will uncover bad assumptions or limited engineering skills that lead to problematic design choices. For example, a junior engineer at one company designed a device component under load and even went so far as to perform finite element analysis using a readily available software package. Unfortunately, while the staff member could use the software, he did not properly interpret the results. This miss led to the aged component failing. The company did not find the error until the final verification testing, at which point it had to go back to the drawing board, delaying product launch for months. Another company discovered immediately before FDA submission that its drug delivery device didn’t meet a key regulatory requirement. That’s why it’s important to have multiple perspectives during the design review process, including human factors, engineering and regulatory experts.
It’s important to bring independent expert reviewers into the process early in the development cycle. Instead of thinking of independent review as a simple “box checking” exercise for FDA submission, you should consider outside reviewers an important part of your development team. An objective, outside expert opinion at key points in the design process can pinpoint areas that need further attention and suggest changes that will increase the likelihood of technical success.
Taking these critical steps will add some time and money to your design and development process. However, the time spent up front to build and understand theoretical models, test your assumptions and technology, and integrate iterative design reviews into your processes will more than pay for itself when it comes time for successful design verification, regulatory approval and market release. Done right, these five steps will result in better, safer and more competitive medical devices.
About The Author
Chris McKenzie has more than 20 years of experience developing medical devices. He has led medical device development programs at a small device developer/manufacturer, a Fortune 500 pharmaceutical company and, most recently, at Battelle.
Each year, the annual R&D 100 Awards recognize the most significant technologies created during the previous year. Some of the world’s most innovative organizations vie for recognition. Winning one of the coveted awards is a widely recognized stamp of validation—they’re known as the “Oscars of Innovation” for a good reason. This year, scientists and engineers from Battelle brought fascinating technology to the event and were rewarded with a top prize. NeuroLife, a Battelle-invented system that currently allows a paralyzed man to have conscious control of his fingers, hand, and wrist—via his thoughts—took home three prizes.
In addition to being named one of the top 100 technologies for the year, NeuroLife also received special recognition for Social Responsibility and brought home the Editor’s Choice Award. The Battelle team was recognized at R&D Magazine’s annual ceremony on November 4 at National Harbor in Maryland. Battelle, along with the national labs it has a role in managing for the U.S. Department of Energy, won a total of 17 awards, bringing its historical tally to 355 during the last 54 years.
“The work we’ve accomplished to date, and the major milestone we’ve achieved, is a significant step toward producing technologies that will allow people with disabilities to regain some of their lost quality of life,” said Herb Bresler, a Senior Research Leader who leads Battelle’s NeuroLife program. “We are continuing to develop the system as well as its component technologies, which we believe will have applications beyond helping people with spinal cord injury. We could not have achieved this goal without the entire team, including our clinical collaborators at The Ohio State University Wexner Medical Center and our current study participant, whose dedication to this program has been extraordinary.”
NeuroLife is a pioneering neural bypass technology that has enabled a quadriplegic study participant to regain functional movement of his hand. Using an off-the-shelf brain implant that was implanted by study partner Dr. Ali Rezai and his team at the Ohio State University Wexner Medical Center, the NeuroLife system collects and interprets neural activity from the participant, translates that data, and transfers it to a sleeve on the forearm. The sleeve stimulates muscles so the hand can perform the task the participant is imagining—he thinks “make a fist” and then his hand makes a fist in near-real time (less than one-tenth of a second from thought to corresponding action).
The study began in 2014 and many advances have been made in the intervening months. A major paper in Nature magazine was published in 2016. Study sessions are performed twice a week at the Wexner Medical Center with the participant along with OSU doctors and Battelle scientists and engineers.
Two other technologies created with the support of researchers in Battelle’s Health & Consumer Solutions business were also recognized. Battelle partnered with the Ohio Soybean Council on Soy-PK Reactive Oligomer Cross-Linker Resin, which received Green Technology special recognition. Soy-PK Resin is a safe alternative to epoxy resins containing bisphenol-A (BPA), which is common in coatings for metal beer, beverage and food can coatings. Additionally, DESiN LLC received an R&D 100 Award for Obi, a system for people with conditions that keep them from being able to feed themselves, which Battelle helped to develop.
Battelle The DroneDefender™, which achieved finalist status for the Top 100 technology awards, burst onto the scene in October 2016, drawing immediate attention and demand. It is an inexpensive, easy-to-use, lightweight, point-and-shoot system that can stop suspicious or hostile drones in flight. With a demonstrated range of 400 meters, DroneDefender provides instant threat mitigation, disrupting the drone using a proprietary radio control frequency disruption. DroneDefender is only available for sale to federally authorized users because of FCC restrictions. More than 100 have been sold to the Department of Defense and the Department of Homeland Security.
“We’re proud to see Battelle’s talented teams of men and women being recognized for these achievements by the R&D community,” said Battelle’s Steve Kelly, Senior Vice President of Contract Research. “They innovate every day to solve important challenges for our client business and mission needs.”
When it comes to medical device development, T. Grant Leffingwell puts the user at the center of the process. A Certified Usability Analyst (CUA), Grant helps manufacturers improve safety, usability and user satisfaction for their devices. Read More