Healthcare Perspectives and insights on healthcare technology and healthcare industry trends and topics 2017-12-15T17:34:41Z WordPress Copyright © Healthcare IT Solutions 2011 Michael Porter <![CDATA[AHIP Digital Conference: AI in Healthcare 2018 Trends]]> 2017-12-15T17:33:26Z 2017-12-05T21:37:49Z Here at the American Health Insurers Digital Experience Conference (AHIP),  Jeff Cribs of Gartner and Ang Sun of Cambia Solutions gave an interesting presentation on AI trends to Watch in 2018.

Example: the imageNet large scale challenge. Over the last 7 years it’s improved. in 2010, there was a 30% error rate. Today, Microsoft and Google have an error rate of around 5%. Humans do it slightly worse

Example: Google Photos does facial recognition.  He showed a photo where a loved one was in a picture he didn’t even realize. His memory of his last years with this person is helped by the ability to get all those photos together.

If you want to consider what trends to follow in 2018, get used to the whole story.  Think personal story. Both examples above are the same trend. One is inside out. The personal story is outside in. Both form the whole story.

Quote: Someday everything digital will improve its own performance without recoding

What is digital? Over 50% of payer industry users have done something digitally. Gartner likes to think of this in terms of ease of use vs trust.  Members trust insurance companies to use AI for health insurance things like check benefits and copays. They don’t trust as much for online tools, diagnosis, etc.

Advice: Jump in with both feet………into AI Strategy.  Understand that AI is still maturing and you can’t jump into a whole bunch of machine network solutions.

  1. How will the enterprise define AI. What is AI?
  2. The the enterprise views the impact of AI on the payer industry overall.
  3. Where the payer organization sees its most valuable use cases for AI
  4. What criteria will be used to determine how to acquire AI capabilities

Ang Sun is the Chief AI Officer at Cambia. He was the senior data scientist at Expedia before that. He’s a “strategic” data scientist. His personal background is natural language processing.

Cambia uses AI for three things:

  1. HealthSparq: empowers consumers with curated choice on services options. Also allows for comparison of cost
  2. MedSavvy: Enables better medication choices. Simplifies the jargon. Informs the conversation with physicians.
  3. Personalized Care Management Tool. It’s a data driven view of the member and allows you to enable an optimized personalized care approach. It makes predictions on where they will be.

The power behind the solutions above is AI. At Cambia AI is less about AI and more about augmented intelligence. They are building AI with humans. AI algorithms know their limits and when to ask a human for help.  The AI learns from feedback.

Cambia applies augmented intelligence to front and back end use cases.  One model prioritizes the list of claims to be reviewed. This resulted in a 15X reduction in claims reviewed with 3X more savings.  In this model, the AI detects issues before they actually pay the claim. The bill to the member is correct the first time.

On the front end, Cambia uses a smart bot. They use a bot to answer a number of questions. The member feedback is great with comments like: “It’s simple and easy to use”, “I like the bot’s personality.”  The bot reacts within seconds and starts answering questions quickly.

Trends to Watch

  1. Machine learning
    1. The most mature area
    2. Amazon, MSFT, and Google are investing heavily in this infrastructure
    3. Can help in care management, risk adjustment, and underwriting.
  2. Computer vision
    1. Think early diagnosis of charts, scans, etc.
    2. Relatively mature area but you need a lot of training data
  3. Natural language processing
    1. Not very mature
    2. Think Amazon voice service
    3. Entry level is lower now because of open source package like Open NLP
    4. Can do this with your developers without hiring data scientists
  4. Conversational User Interface
    1. chat bot
    2. Least mature area even though it’s one of the hottest areas
    3. Most chat platforms are not chatbot platforms. They are rule based vs learning based
    4. Need to help the bots build knowledge and needs to have the ability to learn over time

Best Practice: Back end of your AI platform MUST be service oriented.


Susan Kight <![CDATA[Mobile First is Imperative for Healthcare Provider Intranets]]> 2017-12-05T14:18:38Z 2017-11-30T13:18:59Z Employees are using mobile devices more than ever before and are likely accessing important information from intranets via tablets and smart phones. This creates a number of challenges when intranets have been designed for optimal use with desktops resulting in a poor user experience and low adoption for employees accessing intranets via mobile devices.

Mobile first is therefore no longer a choice but an imperative if you wish for your intranet to remain the go-to source for key information. By adopting a mobile first approach you can ensure you:

  • Support the increasing mobile clinical workforce so that your employees can access the intranet remotely and from any device
  • Meet the informational needs of various internal audiences with engaging content that aligns with the device they are on
  • Deliver a positive user experience with enhanced functionality
  • Support all employees regardless of which device they use with a responsive website design that is mobile-optimized

Redesigning your intranet with a mobile first approach will ensure increased user adoption and increased clinician mobility. Securely improving mobility will lead to improved clinician workflows and result in better patient outcomes.

What steps are you taking to transform into a truly mobile healthcare provider?

Kate Tuttle <![CDATA[3 Technology Essentials for Health Plans in 2018]]> 2017-12-05T14:18:55Z 2017-11-28T13:32:34Z The state of uncertainty in the health insurance marketplace makes preparing for 2018 a challenge. Rather than sitting back and waiting to see what happens, health plans that recognize the ongoing need to transform their business models and embrace the shift to B2C will be in the driver’s seat. This B2C shift makes consumer insight and engagement even more critical as health plans focus on delivering outstanding consumer experiences and building loyalty with existing members.

To be successful, organizations must embrace technology to not only retain an increasingly demanding consumer but also to manage costs and improve quality and satisfaction. Three technology essentials to help make this happen:

  1. Predict and influence consumer behavior with advanced analytics. With vast amounts of data available including medical records, claim history and social data, health plans should be following in the footsteps of retailers by leveraging data to engage consumers. Bringing disparate data sources together, including both structured and unstructured formats, will help health plans manage the populations they serve and ultimately allow them to look at how social determinants impact health outcomes. Data-driven and actionable insights from advanced analytics will not only help increase engagement and consumer satisfaction but also improve efficiency in call centers and claims management.
  2. Build a consumer-centric digital strategy. To attract, engage, and retain consumers, health plans must create a digital strategy that seamlessly delivers their brand message across all touch points, both on- and offline. A truly great consumer experience is achieved when a harmonious  experience is created, no matter the channel, device, or moment. Building a great digital strategy requires health plans to listen to the data they have, create an accurate and 360-degree view of their consumer, and understand the different consumer journeys. Data-driven insights are vital to a strong digital strategy and by gathering consumer insights from research and data, organizations can understand their needs and establish goals in terms of consumer experience and engagement.
  3. Embrace innovation and emerging technologies to thrive in the age of the consumer. More often than not health plans spend a good majority of their resources on their systems of record including claims systems. However, it is imperative that health plans leverage technologies such as the cloud to achieve scale and agility. The cloud is critical for health plans looking to transform, from organizations that manage technology, into wellness companies that more rapidly provide new services to consumers. Cloud-based technologies provide a scalable foundation for ingesting and analyzing large amounts of disparate data to gain a holistic view of consumers. In addition to the cloud, health plans also need to embrace mobile to deliver a more connected and personalized consumer experience, and provide better care at a lower cost. Health plans that continue to build IoT connectivity and utilize healthcare everywhere tools such as mHealth and telehealth will be on the right path to meeting the rising demands of healthcare consumers.

The shift from B2B to B2C in the health insurance industry shows no sign of slowing down. In an industry that is full of uncertainties, one thing that we know is consumer experience trumps all.



Jim Kouba <![CDATA[Help is Here: Webinar to Cover Key Cloud Considerations]]> 2017-12-15T17:34:29Z 2017-11-14T17:15:34Z With so much information in the marketplace today, it is often difficult to distill key parameters for strategic decisions. I enjoy helping people find useful guideposts for making informed choices in technology.

The Cloud is a key topic for everyone engaged in today’s strategic IT planning and software solution decisions. As such, I look forward to joining a Perficient Healthcare colleague and HIMSS Analytics guest speaker to present an upcoming webinar that will provide context for decision makers trying to assess the role Cloud technologies could play in their organizations.

The webinar, Moving to the Cloud: Modernizing Data Architecture in Healthcare, is scheduled for 1 to 2pm CT on November 29. During that time, we will deliver a better understanding of critical benefits and risks associated with committing to a Cloud technology.

Topics will include:

  • The benefits and risks of moving data and analytics environments to the cloud
  • Main healthcare use cases for cloud migration
  • Deep dive into two leading healthcare organizations’ cloud journeys including drivers, challenges, benefits, and lessons learned

You can register here or via the form below. I look forward to connecting with you.

Kate Tuttle <![CDATA[How The Internet of Things (IoT) Benefits Patients and Providers]]> 2017-12-15T17:34:03Z 2017-10-31T12:18:38Z According to a Business Insider report, companies are going to spend almost $5 trillion on the IoT in the next five years. In fact, according to IDC, in the years to come, the fastest spending growth in IoT will come from the healthcare industry. IoT has a variety of applications in healthcare from smart sensors and remote monitoring to medical device integration. IoT can enable providers to proactively diagnose illnesses and create personalized treatment for patients. It can enable hospitals to track resources, dispense medicine, and locate staff and patients. Download our latest guide, The Why, What and How of IoT to take a look at some additional healthcare IoT use cases and to see more than 50 examples of how other industries are leveraging the IoT.

Susan Kight <![CDATA[How Bots are Improving Consumer, Member, and Patient Interactions]]> 2017-12-15T17:34:41Z 2017-10-24T12:30:51Z The practical development and deployment of bots has accelerated in the last year within healthcare. bots are playing a role in the improvement of consumer-member-patient interactions with providers as well as health plans by enhancing customer service support, supporting wellness programs for patients with chronic conditions, and an array of other applications. Additionally, bots make it extremely easy and cost effective to interact with providers, health plans, and care teams.

In customer service, customer-patient interactions improve with the use of:

  • Scheduling assistant bots that help patients set appointments with the right doctor, provide appointment reminders, and post appointment actions reminders.
  • Website navigator bots that are being leveraged to help patients-consumers easily find the right department within a comprehensive website.
  • Conversational bots are supporting providers to check–up, remind, and encourage patents to take their medication – increasing adherence and improving outcomes.

With the use of artificial intelligence, chatbots in particular are supporting providers, care teams, and health plans in the ongoing coaching of patient populations.

  • Coaching wellness programs where bots are able to track and provide guidance on nutrition, exercise, as well as encouraging consumers to make healthier choices.
  • Managing chronic care such as diabetes by reminding patients to take insulin at regular intervals, sending automated alerts to care teams if there is a lack of medication adherence, recommending appropriate diet, and appointment reminders.

The use of bots will continue to grow and get smarter in the applications they can be used within to solve more problems. For the foreseeable future bots will continue playing a key role in improving patient experience and medical staff productivity, while driving down the cost of care.

What bots are you currently using and how have they improved the patient-consumer experience?

Chris Donahue <![CDATA[Revenue Cycle Management Requires “Trust But Verify” Mentality]]> 2017-11-09T16:49:49Z 2017-10-19T12:21:37Z Healthcare Providers depend on their electronic health records (EHR) and revenue cycle management (RCM) solution systems to capture and present metrics so that clinical and operational performance can be reviewed. In particular, RCM solutions/modules position themselves as a key component for spotlighting effective/ineffective processing areas within the “Front-End”, “Middle”, and “Back-End”. Having insights into operating efficiency and effectiveness details within each area of processing of RCM is critical because without them, the potential for identifying – and addressing – avoidable “revenue leakage” is dramatically reduced.

Enabled by the availability of RCM tools, Providers have been prescriptive with monitoring their internal RCM activities. But monitoring processes should not stop at internal RCM activities. It should include diligently reviewing the interactions with its key external party, the Payor. Per defined Provider-Payor and Payor-Member agreements, the Provider will provide clinical services to patients, e.g., Payor’s members, and the Payor agrees to pay for specific services rendered. With all of the various permutation of Patient-Member scenarios that could exist, Providers need to execute “a trust but verify” approach with all parties, its Payor partners and its patients/guarantors, to ensure that the appropriate and agreed upon clinical care is provided and paid for.

Provider and Payor have defined their operating relationship through signed contract and/or program acceptance. Over the years, a variety of contract types have been introduced and executed successfully between Providers and Payors. Some examples of contract types include case-based, per-diem, fee-for-service (FFS), pay-for-performance (P4P), or some other arrangement. Recognizing that most Provider-Payor contracts are not simple, straight-forward percent-of-charge (PoC) contracts (another contract type example), Providers can feel overwhelmed with determining whether or not they received proper reimbursement from their Payor partner. However, this is where the introduction of a Contract Management System (CMS) into their RCM review processes can alleviate some of the concern. CMS’ specialize in providing the capabilities for Providers to author the agreed-upon Provider-Payor contract terms into executable algorithms. As a result, Providers can simulate the specific Payor reimbursement methodology(ies) against generated claims to calculate “expected” revenue (charges), cash (payments), and contractual allowances (adjustments) – which can be ultimately compared against the actual values from the Payor, e.g., providing “Trust But Verify” support.

When a CMS is properly maintained, and its output is properly leveraged within the Provider-Payor relationship, the “Trust” side of the relationship grows because the “Verify” part of the process operates via a consistent and continuous feedback-loop. This feedback-loop is initiated as Providers execute comparative analysis activities between “expected” CMS-generated reimbursement results to the actual remittance advice information received from the Payor. The result is immediately identification of payment variances.

Variances between expected and actual reimbursement should be scrutinized to determine root-cause for the variance observed. In some cases, it will be determined that the Payor paid the claim according to the contract — and the error can be attributed to the term(s) authored or the fee schedule(s) maintained within the CMS. In cases like these, Providers will correct the term(s)/fee schedule(s) in the CMS, and then internally recalculating the submitted claims to generate a “new” expected reimbursement. The result should be a new, recalculated payment variance of zero. In other cases, the Provider will determine that it believes the Payor actually paid the claim incorrectly, initiating Under Payment/Denial (or Over Payment) review activities with its Payor “partner”. This review may lead to a correction in payment received from the Payor, e.g., additional cash (cash recovery), or it may lead to term clarification which may require contract term updates in the CMS, e.g., denied appeal/unrecoverable cash.

As Peter Drucker said, “If you can’t measure it, you can’t improve it.” Providers spend a lot of time and resources in identifying and addressing “revenue leakage” within RCM. Payors should be reviewing their Provider-Payor processing relationships with a similar, “trust but verify” mentality. Through analytics that can be generated out of their RCM and CMS solutions. Providers should not only be able to quickly compare Payor performance and contractual compliance, but should also be able to “drill-down-to” the encounter/claim attributes for root-cause identification – specially with the added pressures that today’s environment is creating against operating margins. Providers need to ensure they are “armed with information” so they can actively correct any revenue “leakage” situations – regardless where upon the RCM Life Cycle they may exist.

Art Kesteloot <![CDATA[Hospital at Home: An Effective Model for Acute Care Patients]]> 2017-12-05T14:19:18Z 2017-10-12T13:03:40Z Remote patient monitoring has been implemented over the last few years in select use cases with varied success based on the level of patient and provider team engagement. A new model that is gaining widespread adoption is Hospital at Home, developed by Bruce Leff, professor of medicine at Johns Hopkins. Hospital at Home provides remote monitoring and support for acute care patients after discharge. Providers implementing the model include Presbyterian Healthcare Services in New Mexico, Kaiser Permanente in California, Atrius Health in Massachusetts and 11 Veterans Affairs hospitals.

The Hospital at Home program involves an initial home visit to set up the hospital equipment. The initial visit is then followed by three days of intensive medical services with in-home nurse visits of 1-3 times per day and a physician visit once a day. This is then followed by 30 days of transitional care. The results so far include higher patient satisfaction, reduced cost, and fewer complications.

Such care at home both reduces stress and is reassuring to the patient, family, and caregivers.

How are you exceeding patient expectations and improving the quality of care?

Chris Donahue <![CDATA[The Information Impact on Providers, Plans, and Consumers]]> 2017-10-26T20:28:10Z 2017-10-10T12:02:37Z Over the better part of the last decade, most healthcare organizations have significantly invested into technologies like EHRs with Care Management and Population Health support. These investments have equipped their healthcare practitioners with accurate information about their patients necessary to provide timely and appropriate quality clinical care to their patients. Certainly, CMS helped influenced some healthcare institutions into this type of technology adoption by continuing to influence pay-for-performance (P4P) over fee-for-service (FFS) practices via payment incentives and penalties through programs like Meaningful Use, Value-Based programs (HVBP, HRR, PVBM, HAC, ESRD, SNFVBP, and HHVBP), and APMs / MIPS (made available via MACRA). Whether being a forward-thinking organization or one that was incentivized into doing so, the end result is that many healthcare organizations are positioned better now, then even just a few years ago, with the infrastructure they need to obtain insights into a multitude of performance areas that directly impact their bottom-line and subsequently how they could be perceived in the market.

With this said, healthcare organizations need to remain acutely aware of this very dynamic and ever-changing market that is right in front of us. For one thing, consumerism is here, and it is here to stay. Today’s patients and members expect to be more actively involved in their care decisions as well as more willing to comparison shop for services and service providers not only because they are incurring more of the cost of healthcare services, but also because information about care providers and care services options is more readily available. However, navigating and consuming the information that is available can be extremely time consuming and overwhelming. This is where healthcare organizations have the opportunity, through initiatives like Population Health Management and the institutionalizing of Patient 360 / Member 360 programs, to differentiate themselves by developing and executing a more proactive and personalized relationship with their consumer.

Similarly, the informational relationship between healthcare provider and health plan needs to continue to progress towards full transparency. As Congress continues to review options to address issues with the ACA including allowing for participation in health associations across state lines plans and expanded HSA contributions, providers and health plans will need to work ever-more-closely together to deliver appropriate and timely care is to its patients / members. Through collaborative activities like utilization reviews and truly understanding contract performance, both parties have the information available to effectively communicate and correct any processing anomalies to directly impact the increase of “clean” claims and accelerated payment. By operating with aligned priorities, this “processing partnership” creates more confidence and comfort to engage in shared-savings / risk-sharing / risk-adjusted agreements including bundled payments and ACOs versus health plan-owned-risk-arrangements, e.g., fee-for-service agreements, or provider-owned-risk-arrangements, e.g., capitation agreements. And, in some cases, where the local market and organizational attributes present opportunity, value-based health care has created an environment for providers to consider offering provider-sponsored health plans as a competitive solution to locally available health plan products.

The reality for today’s healthcare organizations is that in order to address the informational demands of today’s consumer and business operations, they need to continue to develop and execute effective business intelligence and Connected Health strategies. Traditional systems like EHRs and ERPs still and will always process essential data for users, but IoT has presented new opportunities / challenges that cannot be overlooked. Therefore, any data strategy will need to be able to address the availability of structured data as well as unstructured data and present information via easy to understand dashboards and other visualizations, e.g., enterprise data warehousing, Data Lake, NLP, and potentially Machine Learning solutions. Bottom line, Healthcare organizations need to remain proactive in their approaches to listen, understand, and address the informatics needs as they present.

Sonia Goraya <![CDATA[How AI Verifies Insurance Eligibility to Benefit Members & Plans]]> 2017-12-05T14:19:36Z 2017-10-03T19:02:00Z Artificial Intelligence (AI) continues to mature as companies such as IBM, Amazon, and Google race to bring AI into the daily life of consumers. Underlying the technology of AI is natural language processing, which integrates fields as diverse as linguistics, neuroscience, anthropology, computer science, and psychology. As AI begins to permeate healthcare, its vast potential for improving the way healthcare is delivered, reimbursed, and perceived is rapidly evolving. One key use case of AI today is improving the speed at which health plans and providers are able to verify benefits and eligibility.

As health plans evolve their businesses to stay on top of a rapidly evolving technology landscape, they are presented with many opportunities to improve revenue and profits, while also improving provider and member perception. A seamless and intuitive self-service option that allows for easy insurance verification between providers, members, and health plans reduces call times, improves satisfaction, and increases accuracy and efficiency in in claims processing.

The current challenges for health plans in regards to benefit verification begins with miskeyed or mismatched patient information, resulting in unsuccessful IDs of patients. This leads to operational inefficiencies between providers and health plans, as well as members who have to wait longer for verification. AI, using advanced natural language processing algorithms, can guide providers, members, and health plans to complete their desired tasks without having to physically type anything in. Less time spent keying patient information in will result in reduced claim denials and reduced verification time. For those providers that call health plans for verification, the result is reduced call times and the ability to free up health plan call center staff for more complex inquiries.

Health plans, providers, and consumers continue to look for ways to receive and deliver quality healthcare at an efficient cost. As tech companies continue to change how healthcare is delivered, health plans have an opportunity to take a step ahead by using AI to delight members and providers by improving the ease and time required to determine insurance eligibility.

What are you doing to delight members and providers?