Article | March 5, 2020
Most physician outreach now takes place digitally or indirectly. This shift in engagement has made it crucial for sales and marketing teams in healthcare and life sciences (HLS) to be aligned with a unified strategy. That’s what we discovered at League. Founded in 2014, League is on a mission to consumerize health and benefits for employers. We started using Salesforce and Pardot in 2017. Back then, marketing and sales were disconnected, and this was impacting our overall performance in a negative way. Our solution was to develop our first account-based marketing strategy. We saw that ABM was a huge trend, and we loved the idea of choosing a set of target accounts, creating playbooks, and personalizing marketing campaigns to help drive meetings. Here’s how we adopted ABM at League, and the results of our ABM efforts.
Article | March 5, 2020
A digital twin is a digital representation of a real-world entity or system. The implementation of a digital twin is a model that mirrors a unique physical object, process, organization, person or other abstraction. For healthcare providers, digital twins provide an abstraction of the healthcare ecosystem’s component characteristics and behaviors. These are used in combination with other real-time health system (RTHS) capabilities to provide real-time monitoring, process simulation for efficiency improvements, population health and long-term, cross-functional statistical analyses.
Digital twins have the potential to transform and accelerate decision making, reduce clinical risk, improve operational efficiencies and lower cost of care, resulting in better competitive advantage for HDOs. However, digital twins will only be as valuable as the quality of the data utilized to create them. The digital twin of a real-world entity is a method to create relevance for descriptive data about its modeled entity. How that digital twin is built and used can lead to better-informed care pathways and organizational decisions, but it can also lead clinicians and executives down a path of frustration if they get the source data wrong. The underlying systems that gather and process data are key to the success for digital twin creation. Get those systems right and digital twins can accelerate care delivery and operational efficiencies.
Twins in Healthcare Delivery
The fact is that HDOs have been using digital twins for years. Although rudimentary in function, digital representations of patients, workflow processes and hospital operations have already been applied by caregivers and administrators across the HDO. For example, a physician uses a digital medical record to develop a treatment plan for a patient. The information in the medical record (a rudimentary digital twin) along with the physician’s experience, training and education combine to provide a diagnostic or treatment plan. Any gaps in information must be compensated through additional data gathering, trial-and-error treatments, intuitive leaps informed through experience or simply guessing. The CIO’s task now is to remove as many of those gaps as possible using available technology to give the physician the greatest opportunity to return their patients to wellness in the most efficient possible manner.
Today, one way to close those gaps is to create the technology-based mechanisms to collect accurate data for the various decision contexts within the HDO. These contexts are numerous and include decisioning perspectives for every functional unit within the enterprise. The more accurate the data collected on a specific topic, the higher the value of the downstream digital twin to each decision maker (see Figure 1).
Figure 1: Digital Twins Are Only as Good as Their Data Source
HDO CIOs and other leaders that base decisions on poor-quality digital twins increase organizational risk and potential patient care risk. Alternatively, high-quality digital twins will accelerate digital business and patient care effectiveness by providing decision makers the best information in the correct context, in the right moment and at the right place — hallmarks of the RTHS.
Benefits and Uses
Digital Twin Types in Healthcare Delivery
Current practices for digital twins take two basic forms: discrete digital twins and composite digital twins. Discrete digital twins are the type that most people think about when approaching the topic. These digital twins are one-dimensional, created from a single set or source of data. An MRI study of a lung, for example, is used to create a digital representation of a patient that can be used by trained analytics processes to detect the subtle image variations that indicate a cancerous tumor. The model of the patient’s lung is a discrete digital twin. There are numerous other examples of discrete digital twins across healthcare delivery, each example tied to data collection technologies for specific clinical diagnostic purposes. Some of these data sources include vitals monitors, imaging technologies for specific conditions, sensors for electroencephalography (EEG) and electrocardiogram (ECG). All these technologies deliver discrete data describing one (or very few) aspects of a patient’s condition.
Situational awareness is at the heart of HDO digital twins. They are the culmination of information gathered from IoT and other sources to create an informed, accurate digital model of the real-world healthcare organization. Situational awareness is the engine behind various “hospital of the future,” “digital hospital” and “smart patient room” initiatives. It is at the core of the RTHS.
Digital twins, when applied through the RTHS, positively impact these organizational areas (with associated technology examples — the technologies all use one or more types of digital twins to fulfill their capability):
Clinical communication and collaboration
Next-generation nurse call
Alarms and notifications
Integrated patient room
Digital Twin Usability
Digital twin risk is tied directly to usability. Digital twin usability is another way of looking at the issue created by poor data quality or low data point counts used to create the twins. Decision making is a process that is reliant on inputs from relevant information sources combined with education, experience, risk assessment, defined requirements, criteria and opportunities to reach a plausible conclusion. There is a boundary or threshold that must be reached for each of these inputs before a person or system can derive a decision. When digital twins are used for one or many of these sources, the ability to cross these decision thresholds to create reasonable and actionable conclusions is tied to the accuracy of the twins (see Figure 2).
Figure 2: Digital Twin Usability Thresholds
For example, the amount of information about a patient room required to decide if the space is too hot or cold is low (due to a single temperature reading from a wall-mounted thermostat). In addition, the accuracy or quality of that data can be low (that is, a few degrees off) and still be effective for deciding to raise or lower the room temperature. To decide if the chiller on the roof of that patient wing needs to be replaced, the decision maker needs much more information. That data may represent all thermostat readings in the wing over a long period of time with some level of verification on temperature accuracy. The data may also include energy load information over the same period consumed by the associated chiller.
If viewed in terms of a digital twin, the complexity level and accuracy level of the source data must pass an accuracy threshold that allows users to form accurate decisions. There are multiple thresholds for each digital twin — based on twin quality — whether that twin is a patient, a revenue cycle workflow or hospital wing. These thresholds create a limit of decision impact; the lower the twin quality the less important the available decision for the real-world entity the twin represents.
Trusting Digital Twins for HDOs
The concept of a limit of detail required to make certain decisions raises certain questions. First, “how does a decision maker know they have enough detail in their digital twin to take action based on what the model is describing about its real-world counterpart?” The answer lies in measurement and monitoring of specific aspects of a digital twin, whether it be a discrete twin, composite twin or organization twin.
Users must understand the inputs required for decisions and where twins will provide one or more of the components of that input. They need to examine the required decision criteria in order to reach the appropriate level of expected outcome from the decision itself. These feed into the measurements that users will have to monitor for each twin. These criteria will be unique to each twin. Composite twins will have unique measurements that may be independent from the underlying discrete twin measurement.
The monitoring of these key twin characteristics must be as current as the target twin’s data flow or update process. Digital twins that are updated once can have a single measurement to gauge its appropriateness for decisioning. A twin that is updated every second based on event stream data must be measured continuously.
This trap is the same for all digital twins regardless of context. The difference is in the potential impact. A facilities decision that leads to cooler-than-desired temperatures in the hallways pales in comparison to a faulty clinical diagnosis that leads to unnecessary testing or negative patient outcomes.
All it takes is a single instance of a digital twin used beyond its means with negative results for trust to disappear — erasing the significant investments in time and effort it took to create the twin. That is why it is imperative that twins be considered a technology product that requires constant process improvement. From the IoT edge where data is collected to the data ingestion and analytics processes that consume and mold the data to the digital twin creation routines, all must be under continuous pressure for improvement.
Include a Concise Digital Twin Vision Within the HDO Digital Transformation Strategy
Digital twins are one of the foundational constructs supporting digital transformation efforts by HDO CIOs. They are digital representations of the real-world entities targeted by organizations that benefit from the advances and efficiencies technologies bring to healthcare delivery. Those technology advances and efficiencies will only be delivered successfully if the underlying data and associated digital twins have the appropriate level of precision to sustain the transformation initiatives.
To ensure this attention to digital twin worthiness, it is imperative that HDO CIOs include a digital twin vision as part of their organization’s digital transformation strategy. Binding the two within the strategy will reinforce the important role digital twins play in achieving the desired outcomes with all participating stakeholders.
Building new capabilities — APIs, artificial intelligence (AI) and other new technologies enable the connections and automation that the platform provides.
Leveraging existing systems — Legacy systems that an HDO already owns can be adapted and connected to form part of its digital platform.
Applying the platform to the industry — Digital platforms must support specific use cases, and those use cases will reflect the needs of patients, employees and other consumers.
Create a Digital Twin Pilot Program
Like other advanced technology ideas, a digital twin program is best started as a simple project that can act as a starting point for maturity over time. Begin this by selecting a simple model of a patient, a department or other entity tied to a specific desired business or clinical outcome. The goal is to understand the challenges your organization will face when implementing digital twins.
The target for the digital twin should be discrete and easily managed. For example, a digital twin of a blood bank storage facility is a contained entity with a limited number of measurement points, such as temperature, humidity and door activity. The digital twin could be used to simulate the impact of door open time on temperature and humidity within the storage facility. The idea is to pick a project that allows your team to concentrate on data collection and twin creation processes rather than get tied up in specific details of the modeled object.
Begin by analyzing the underlying source data required to compose the digital twin, with the understanding that the usability of the twins is directly correlated to its data’s quality. Understand the full data pathway from the IoT devices through to where that data is stored. Think through the data collection type needed for the twin, is discrete data or real-time data required? How much data is needed to form the twin accurately? How accurate is the data generated by the IoT devices?
Create a simulation environment to exercise the digital twin through its paces against known operational variables. The twin’s value is tied to how the underlying data represents the response of the modeled entity against external input. Keep this simple to start with — concentrate on the IT mechanisms that create and execute the twin and the simulation environment.
Monitor and measure the performance of the digital twin. Use the virtuous cycle to create a constant improvement process for the sample twin. Experience gained through this simple project will create many lessons learned and best practices to follow for complex digital twins that will follow.
FUTURE OF HEALTHCARE
Article | March 5, 2020
Let’s face it. It’s been one tough year with too many of us sitting idle and indulging in calorie-laden foods for way too long as the coronavirus pandemic continues to sweep the globe. For all too many, sheltering in place has prompted unwelcome weight gain—a troublesome truth as we head into the holiday season where gluttony oft reigns supreme.
That said, many individuals did have foresight and motivation back in March and the months that followed, wisely leveraging that extreme downtime to “diet for dollars” with HealthyWage—a pioneer of money-driven weight loss contests and challenges for individuals, teams and business groups. In fact, those who started a 6-month HealthyWager challenge during the pandemic (late March through May) broke company records, spurring a dramatic increase in pound shedding success rates—and in-kind cash payouts—against the norm. So motivated became America to drop, or avoid, the so-called ‘quarantine 15’ and score some cold hard cash in the process, HealthyWage reports that this past May it logged a substantial year-over-year increase in challenge participants at large. This is not surprising given Google search trends indicates the portion of people searching for weight loss hit a 5-year high in May of 2020—a level even exceeding the quintessential New Year’s diet resolution season.
Beyond the fact that people who started weight loss wagers during the pandemic achieved much greater success as compared to participant results the prior year, and earning hundreds and even thousands of dollars for their efforts, it is women and individuals under 30 years of age primarily accounting for the sustained increases. For example, among the litany of pandemic era success stories, Lisa S. won over $1,900 for losing 50 pounds in 6 months while Hayden T. won over $1,200 for losing over 62 pounds in 6 months—both during the COVID-19 pandemic.
As the coronavirus rages on well into the fourth quarter, we collectively find ourselves again having to shelter-in-place. Those trying to reconcile how they will survive this next round of being home bound, and the holiday season at large, with mitigated waistline and budgetary wreckage—and who are even planning their New Year resolution approach just beyond—would be wise to consider the gamified dieting approach. “Loss Aversion is a powerful dynamic and the reality of having ‘skin in the game’ can propel the results of a gamified weight loss initiative,” notes HealthyWage co-founder David Roddenberry.
The efficacy of diet gamification is well-proven. For one, according to study findings published by JAMA Internal Medicine, behavioral economics-based gamification led to “significantly” increased physical activity among overweight and obese Americans. In this particular study, pairing a step tracking device with social incentives led to sustained, long-term behavior change—prompting participants to take more steps then with a step tracking device, alone. While the report explains that “gamification interventions significantly increased physical activity during the 24-week intervention,” with competition being the “most effective.”
That’s something HealthyWage has seen play out since launching its weight-loss gamification platform in 2009. HealthyWage is, in fact, founded on earlier substantive research and "double-incentivization" methodology that proves competition and rewards—especially the cash variety—can as much as triple the effectiveness of weight loss programs.
“A key element for the success of a gamification program is giving participants something to lose if they fail to meet their goal—whether tangible or intangible,” notes Roddenberry. “In this particular study, it was just points at stake but even this effected behavior change. There are actually throngs of studies demonstrated that the threat of losing something of value is much more effective than the opportunity to win something of equal value. That’s precisely why we advocate that program participants ‘pay to play’ and make an investment out of their own pocket in order to win rewards—in our case large cash prizes—for losing weight and getting more active in the program.”
A few other notable HealthyWager success stories (both female and male) are case-in-point. These include Jean N. who lost 71 lbs. and won $3,357.99 for her efforts, and Jeremy M. who also lost 71 lbs. and won $1,886.32 for his own slimdown success. From its website, HealthyWage.com shares yet more inspirational success stories of both women and men who gained financially for their pound-shedding achievements using the company’s unique gamification approach. This includes Kristin W. who lost a staggering 114 pounds and won $4,000 for her efforts, Anastasia W. who lost 41 pounds and won a whopping $10,000 in kind, and Blake S. who lost an impressive 151 pounds and won $4,670 for his own slimdown success. Figures that are tasty, indeed.
These and other such HealthyWage payouts are proof positive. For their weight-loss achievements that collectively exceeds an astounding 1,050,000 pounds for this year, alone—269 of which losing in excess of 100 pounds (and nearly 7.5 million pounds lost since the company’s launch), HealthyWage has reportedly paid more than xx30,000 dieters over $13 million cash in 2020, specifically, and over $55 million cash since its inception in 2009.
HealthyWage programs apply these principles:
HealthyWager Challenge: participants commit to a weight loss goal and an upfront financial payment and get their money back plus a financial return if they accomplish their weight loss goal. The average participant loses 40.7 pounds and gets paid $1,245.
HealthyWage Step Challenge: participants commit money and agree to increase their steps by 25% over 60-days. If they achieve their goal they get their money back plus the money from those who don't hit their goal.
Upholding the new findings while also further validating HealthyWage’s well-honed approach, an additional study published in the journal Social Science and Medicine continue to prove that money is an effective motivator to “increase both the magnitude and duration of weight loss.” The same hold true in business for staff wellness initiatives. Results from one study published in the Annals of Internal Medicine indicated that “Loss Incentive’ Motivates Employees to Take More Steps ,” finding that financial incentives framed as a loss were most effective for achieving physical activity goals.
As a prolific corporate and group wellness purveyor, since 2009 HealthyWage has worked with an array of hi-caliber participants on workplace and staff wellness initiatives, including Halliburton, ConocoPhillips and more than 25% of the largest school districts in the country. HealthyWage has, in fact, formally created competitive, money-motivated programs for more than 1000 Fortune 500 and other public and private companies, hospitals, health systems, insurers, school systems, municipal governments and other organizations throughout the U.S., and their program has been more informally run at more than 7,000 companies and organizations seeking to bolster staff health and well-being, and boost bottom lines in kind.
“Throngs of studies reiterate the importance of the 'stick' in the design of a wellness incentive program, whether for individuals at home or for employee groups,” Roddenberry says. “Many studies have demonstrated that the threat of losing something of value is much more effective than the opportunity to win something of equal value. That’s precisely why we advocate that program participants ‘pay to play’ and make an investment out of their own pocket in order to win rewards—in our case large cash prizes—for losing weight and getting more active in the program.”
Studies do consistently show that monetary incentives serve to enhance the effectiveness of, and duly complement, weight-loss programs of any and all sorts, especially when paid out quickly like HealthyWage’s various programs. For its part, HealthyWage reports that the average participant more than doubles their investment if they are successful at achieving their goal. The financial upside potential is impressive.
So, if this is the season when you would like to not only resolve to lose those extra lbs. but also actually achieve that worthy goal, consider a cash-fueled approach. It just might give you that extra dose of motivation that’ll truly help you stay the course, shed weight and make some extra money in the process. There’s no better time than right now to bank on yourself.
Article | March 5, 2020
Tempted to throw in the towel on your New Year’s resolutions? It’s a natural reaction during this unprecedented year. I’m here to tell you it’s okay—and you probably don’t need them anyway.
You’re in good company if you’ve given up on the big shifts. According to widely-cited research study, only 19% of people keep their New Year’s resolutions. In addition, this may not have been the best time to make changes, given all that’s going on with the pandemic.
Also, worthwhile to consider the following insights on the unease with making big changes these days. According to research published in Molecular Psychiatry, when you go through prolonged challenging times (and the pandemic certainly qualifies), chronic stress can change the architecture of your brain and make you feel worn out, anxious, fearful, or depressed. These aren’t the best conditions for making major changes.
You may also face “change saturation,” or in other words, you’ve had to make so many transitions, you just can’t make any more. To prevent yourself from becoming overwhelmed, focus on attainable aspirations. Here are a few recommendations.
DREAM ON A SMALLER SCALE
Success for the next 12 months may be closely tied to a less-is-more approach. Instead of seeking a whole new career, maybe you can set your sights on getting assigned to a new project at your current company. In other words, consider how you can tweak your behaviors rather than overhauling them.
Cultivate gratitude. Appreciate the little things. When you’re more tuned into what you have, you’re less focused on what you still want. This “enough mentality” can be helpful to your mental health. You don’t have to make big changes to achieve satisfaction or happiness. Contentment starts with gratitude.
Avoid perfectionism. Often, the fuel for big changes is a feeling you or your situation are not perfect. Remind yourself that perfection is a myth and focus on what’s working. This will help you find fulfillment with your present reality (even if it’s not all you aspire to).
Make a list, then edit down. Another great way to keep your ambitions reasonable is to make a list of all you want to accomplish and then eliminate everything but the top three items. A surefire route to frustration is to expect too much and put unrealistic pressures on yourself. Instead, focus on just a few vital things you want to accomplish, rather than a long list that does not empower you. After you’ve accomplished the first three goals on your list, you can always come back to the others, but give yourself a fighting chance to achieve the most integral top three, first.
Keep yourself accountable through specific techniques—and pay attention to events that may cause you to slide backwards. Research in the Personality and Social Psychology Bulletin explains that 40% of your behaviors occur in similar situations, which is to say familiar circumstances encourage the repetition of choices. Therefore, if you’re able to adjust one potentially repeated behavior, it can make a difference.
Create routines and conveniences. When you want to nurture a behavior, make it a default so you’re not thinking consciously about it. Research published in the European Journal of Social Psychology found when you repeat behaviors in a consistent context, it helps with habit formation and these take hold much more effectively. You can use this to your advantage. Instead of making a conscious choice each morning whether you want the donut or the smoothie, have the sliced fruit ready to go and the blender on the counter so when you arrive bleary-eyed to the kitchen in the morning, you’re just doing what’s already laid out. Start each day with the routine of responding to quick-hit emails. Rather than deciding what to work on first, just create a routine where you’re repeating behavior that works without as much conscious thought.
Plan ahead. When you can plan for things, you can usually control them more effectively. If you’re going to be in a situation that might create challenges for your new behaviors, make a plan. Perhaps you’re going to the grocery store and you can make a plan to avoid the cookie aisle. Or if you’re back in the office, avoid the calorie-tempting socially distanced happy hour with colleagues by leaving right on time and get a head start on the big project you’re working on. Anticipating what might present challenges will help you overcome them.
Support can be the difference between making small changes and not succeeding at all. Find a source that works for you.
Find friends. Create a virtual group of people also trying to make changes. Perhaps there’s an online group where you can exchange healthy recipes or provide mutual encouragement for regular trips to the gym. Also tap into your existing network and ask your friend to check in with you to see if you’ve had your workout for the day. Seek out colleagues who can nurture the writing skills you want to develop. Find people who encourage you, provide feedback, and remind you about your ability to succeed.
Use technology thoughtfully. There are a wide variety of virtual solutions to help you shift your behavior. Download the app that allows you to track your water intake or the app that will send you notifications if you haven’t moved enough in the last hour. Look for apps that can help you learn the new language you’ve been wanting to add to your skill set or that can connect you with colleagues who have like-minded ambitions. Behavior shifts are most likely to occur with planning, reminders, and feedback. So, find apps that provide these three kinds of support.
Give yourself permission to do less for now and know you can always do more later. In the meantime, stay strong and be satisfied with a little progress for now.