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Health IT Continues To Drive Healthcare Leaders’ Agenda

Posted on October 23, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

A new study laying out opportunities, challenges and issues in healthcare likely to emerge in 2018 demonstrates that health IT is very much top of mind for healthcare leaders.

The 2018 HCEG Top 10 list, which is published by the Healthcare Executive Group, was created based on feedback from executives at its 2017 Annual Forum in Nashville, TN. Participants included health plans, health systems and provider organizations.

The top item on the list was “Clinical and Data Analytics,” which the list describes as leveraging big data with clinical evidence to segment populations, manage health and drive decisions. The second-place slot was occupied by “Population Health Services Organizations,” which, it says, operationalize population health strategy and chronic care management, drive clinical innovation and integrate social determinants of health.

The list also included “Harnessing Mobile Health Technology,” which included improving disease management and member engagement in data collection/distribution; “The Engaged Digital Consumer,” which by its definition includes HSAs, member/patient portals and health and wellness education materials; and cybersecurity.

Other hot issues named by the group include value-based payments, cost transparency, total consumer health, healthcare reform and addressing pharmacy costs.

So, readers, do you agree with HCEG’s priorities? Has the list left off any important topics?

In my case, I’d probably add a few items to list. For example, I may be getting ahead of the industry, but I’d argue that healthcare AI-related technologies might belong there. While there’s a whole separate article to be written here, in short, I believe that both AI-driven data analytics and consumer-facing technologies like medical chatbots have tremendous potential.

Also, I was surprised to see that care coordination improvements didn’t top respondents’ list of concerns. Admittedly, some of the list items might involve taking coordination to the next level, but the executives apparently didn’t identify it as a top priority.

Finally, as unsexy as the topic is for most, I would have thought that some form of health IT infrastructure spending or broader IT investment concerns might rise to the top of this list. Even if these executives didn’t discuss it, my sense from looking at multiple information sources is that providers are, and will continue to be, hard-pressed to allocate enough funds for IT.

Of course, if the executives involved can address even a few of their existing top 10 items next year, they’ll be doing pretty well. For example, we all know that providers‘ ability to manage value-based contracting is minimal in many cases, so making progress would be worthwhile. Participants like hospitals and clinics still need time to get their act together on value-based care, and many are unlikely to be on top of things by 2018.

There are also problems, like population health management, which involve processes rather than a destination. Providers will be struggling to address it well beyond 2018. That being said, it’d be great if healthcare execs could improve their results next year.

Nit-picking aside, HCEG’s Top 10 list is largely dead-on. The question is whether will be able to step up and address all of these things. Fingers crossed!

Alexa Can Truly Give Patients a Voice in Their Health Care (Part 3 of 3)

Posted on October 20, 2017 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

Earlier parts of this article set the stage for understanding what the Alexa Diabetes Challenge is trying to achieve and how some finalists interpreted the mandate. We examine three more finalists in this final section.

DiaBetty from the University of Illinois-Chicago

DiaBetty focuses on a single, important aspect of diabetes: the effect of depression on the course of the disease. This project, developed by the Department of Psychiatry at the University of Illinois-Chicago, does many of the things that other finalists in this article do–accepting data from EHRs, dialoguing with the individual, presenting educational materials on nutrition and medication, etc.–but with the emphasis on inquiring about mood and handling the impact that depression-like symptoms can have on behavior that affects Type 2 diabetes.

Olu Ajilore, Associate Professor and co-director of the CoNECt lab, told me that his department benefited greatly from close collaboration with bioengineering and computer science colleagues who, before DiaBetty, worked on another project that linked computing with clinical needs. Although they used some built-in capabilities of the Alexa, they may move to Lex or another AI platform and build a stand-alone device. Their next step is to develop reliable clinical trials, checking the effect of DiaBetty on health outcomes such as medication compliance, visits, and blood sugar levels, as well as cost reductions.

T2D2 from Columbia University

Just as DiaBetty explores the impact of mood on diabetes, T2D2 (which stands for “Taming Type 2 Diabetes, Together”) focuses on nutrition. Far more than sugar intake is involved in the health of people with diabetes. Elliot Mitchell, a PhD student who led the T2D2 team under Assistant Professor Lena Mamykina in the Department of Biomedical Informatics, told me that the balance of macronutrients (carbohydrates, fat, and protein) is important.

T2D2 is currently a prototype, developed as a combination of Alexa Skill and a chatbot based on Lex. The Alexa Skills Kit handle voice interactions. Both the Skill and the chatbot communicate with a back end that handles accounts and logic. Although related Columbia University technology in diabetes self-management is used, both the NLP and the voice interface were developed specifically for the Alexa Diabetes Challenge. The T2D2 team included people from the disciplines of computer interaction, data science, nursing, and behavioral nutrition.

The user invokes Alexa to tell it blood sugar values and the contents of meals. T2D2, in response, offers recipe recommendations and other advice. Like many of the finalists in this article, it looks back at meals over time, sees how combinations of nutrients matched changes in blood sugar, and personalizes its food recommendations.

For each patient, before it gets to know that patient’s diet, T2D2 can make food recommendations based on what is popular in their ZIP code. It can change these as it watches the patient’s choices and records comments to recommendations (for instance, “I don’t like that food”).

Data is also anonymized and aggregated for both recommendations and future research.

The care team and family caregivers are also involved, although less intensely than some other finalists do. The patient can offer caregivers a one-page report listing a plot of blood sugar by time and day for the previous two weeks, along with goals and progress made, and questions. The patient can also connect her account and share key medical information with family and friends, a feature called the Supportive Network.

The team’s next phase is run studies to evaluable some of assumptions they made when developing T2D2, and improve it for eventual release into the field.

Sugarpod from Wellpepper

I’ll finish this article with the winner of the challenge, already covered by an earlier article. Since the publication of the article, according to the founder and CEO of Wellpepper, Anne Weiler, the company has integrated some of Sugarpod functions into a bathroom scale. When a person stands on the scale, it takes an image of their feet and uploads it to sites that both the individual and their doctor can view. A machine learning image classifier can check the photo for problems such as diabetic foot ulcers. The scale interface can also ask the patient for quick information such as whether they took their medication and what their blood sugar is. Extended conversations are avoided, under the assumption that people don’t want to have them in the bathroom. The company designed its experiences to be integrated throughout the person’s day: stepping on the scale and answering a few questions in the morning, interacting with the care plan on a mobile device at work, and checking notifications and messages with an Echo device in the evening.

Any machine that takes pictures can arouse worry when installed in a bathroom. While taking the challenge and talking to people with diabetes, Wellpepper learned to add a light that goes on when the camera is taking a picture.

This kind of responsiveness to patient representatives in the field will determine the success of each of the finalists in this challenge. They all strive for behavioral change through connected health, and this strategy is completely reliant on engagement, trust, and collaboration by the person with a chronic illness.

The potential of engagement through voice is just beginning to be tapped. There is evidence, for instance, that serious illnesses can be diagnosed by analyzing voice patterns. As we come up on the annual Connected Health Conference this month, I will be interested to see how many participating developers share the common themes that turned up during the Alexa Diabetes Challenge.

Alexa Can Truly Give Patients a Voice in Their Health Care (Part 2 of 3)

Posted on October 19, 2017 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

The first part of this article introduced the problems of computer interfaces in health care and mentioned some current uses for natural language processing (NLP) for apps aimed at clinicians. I also summarized the common goals, problems, and solutions I found among the five finalists in the Alexa Diabetes Challenge. This part of the article shows the particular twist given by each finalist.

My GluCoach from HCL America in Partnership With Ayogo

There are two levels from which to view My GluCoach. On one level, it’s an interactive tool exemplifying one of the goals I listed earlier–intense engagement with patients over daily behavior–as well as the theme of comprehensivenesss. The interactions that My GluCoach offers were divided into three types by Abhishek Shankar, a Vice President at HCL Technologies America:

  • Teacher: the service can answer questions about diabetes and pull up stored educational materials

  • Coach: the service can track behavior by interacting with devices and prompt the patient to eat differently or go out for exercise. In addition to asking questions, a patient can set up Alexa to deliver alarms at particular times, a feature My GluCoach uses to deliver advice.

  • Assistant: provide conveniences to the patient, such as ordering a cab to take her to an appointment.

On a higher level, My GluCoach fits into broader services offered to health care institutions by HCL Technologies as part of a population health program. In creating the service HCL partnered with Ayogo, which develops a mobile platform for patient engagement and tracking. HCL has also designed the service as a general health care platform that can be expanded over the next six to twelve months to cover medical conditions besides diabetes.

Another theme I discussed earlier, interactions with outside data and the use of machine learning, are key to my GluCoach. For its demo at the challenge, My GluCoach took data about exercise from a Fitbit. It can potentially work with any device that shares information, and HCL plans to integrate the service with common EHRs. As My GluCoach gets to know the individual who uses it over months and years, it can tailor its responses more and more intelligently to the learning style and personality of the patient.

Patterns of eating, medical compliance, and other data are not the only input to machine learning. Shankar pointed out that different patients require different types of interventions. Some simply want to be given concrete advice and told what to do. Others want to be presented with information and then make their own decisions. My GluCoach will hopefully adapt to whatever style works best for the particular individual. This affective response–together with a general tone of humor and friendliness–will win the trust of the individual.

PIA from Ejenta

PIA, which stands for “personal intelligent agent,” manages care plans, delivering information to the affected patients as well as their care teams and concerned relatives. It collects medical data and draws conclusions that allow it to generate alerts if something seems wrong. Patients can also ask PIA how they are doing, and the agent will respond with personalized feedback and advice based on what the agent has learned about them and their care plan.

I talked to Rachna Dhamija, who worked on a team that developed PIA as the founder and CEO of Ejenta. (The name Ejenta is a version of the word “agent” that entered the Bengali language as slang.) She said that the AI technology had been licensed from NASA, which had developed it to monitor astronauts’ health and other aspects of flights. Ejenta helped turn it into a care coordination tool with interfaces for the web and mobile devices at a major HMO to treat patients with chronic heart failure and high-risk pregnancies. Ejenta expanded their platform to include an Alexa interface for the diabetes challenge.

As a care management tool, PIA records targets such as glucose levels, goals, medication plans, nutrition plans, and action parameters such as how often to take measurements using the devices. Each caregiver, along the patient, has his or her own agent, and caregivers can monitor multiple patients. The patient has very granular control over sharing, telling PIA which kind of data can be sent to each caretaker. Access rights must be set on the web or a mobile device, because allowing Alexa to be used for that purpose might let someone trick the system into thinking he was the patient.

Besides Alexa, PIA takes data from devices (scales, blood glucose monitors, blood pressure monitors, etc.) and from EHRs in a HIPAA-compliant method. Because the service cannot wake up Alexa, it currently delivers notifications, alerts, and reminders by sending a secure message to the provider’s agent. The provider can then contact the patient by email or mobile phone. The team plans to integrate PIA with an Alexa notifications feature in the future, so that PIA can proactively communicate with the patient via Alexa.

PIA goes beyond the standard rules for alerts, allowing alerts and reminders to be customized based on what it learns about the patient. PIA uses machine learning to discover what is normal activity (such as weight fluctuations) for each patient and to make predictions based on the data, which can be shared with the care team.

The final section of this article covers DiaBetty, T2D2, and Sugarpod, the remaining finalists.

HIT for HIEs

Posted on October 17, 2017 I Written By

The following is a guest blog by Mike O’Neill, CEO at MedicaSoft. This is the third blog in a three-part sponsored blog post series focused on new HIT for integration. Each month, a different MedicaSoft expert will share insights on new and innovative technology and its applications in healthcare.

Health Information Exchanges (HIEs) have been in the news lately, and for good reason. With major hurricanes devastating Texas, Florida, the British Virgin Islands, and Puerto Rico, accessibility of patient health information rapidly became a major concern. Electronic Health Record adoption has led to most patient data being in electronic form, but it hasn’t necessarily made that data available when and where care is delivered. HIEs can help make that data available; during the recent storms two HIEs were able to spring to action to help clinicians provide care for patients. The ability of the Houston and San Antonio-area HIEs (Greater Houston Healthconnect (GHHC) and Healthcare Access San Antonio (HASA) to exchange information allowed patient records to be accessed remotely – which was absolutely critical during this natural disaster.

If you were on the fence about “the cloud,” this is the perfect case study in its effectiveness. More than ever, HIEs are called upon to assist by making health records available during critical care encounters. HIEs need modern technology to best serve their communities in these instances, going beyond basic connectivity and interoperability to deliver tangible value using the wealth of data they collect –

  1. Organize the data into meaningful health records. HIEs often have access to years of raw data. They may need help organizing it into a clinical data repository, matching patients, and providing a health record that is clinically useful. This is one way we assist HIEs in using the data they’ve collected.
  2. Provide valuable alerts & notifications. These are useful, especially in a crisis, to locate patients, but they can also give patients notice on events they need to follow-up on. This is another layer we build onto HIEs’ data foundation.

Health records that are useful go a long way – beyond individual hospitals, and regions and state lines. To be useful, health records must go where the patients go, wherever that may be.

An emerging approach to meet this need is the Strategic Health Information Exchange Collaborative (SHIEC’s) Patient-Centered Data Home (PCDH) concept among HIEs. PCDH helps providers access real-time health information across regional and state lines, wherever the patient is seeking care. Regardless of where the clinical data originates, it becomes part of the patient’s longitudinal patient record – the PCDH – giving patients control of their data.

About Mike O’Neill
Mike is the CEO at MedicaSoft. He came to MedicaSoft from the U.S. Department of Veterans Affairs (VA) where he was a Senior Advisor and member of the founding team of the VA Center for Innovation. Mike serves as the Chairman of the Board of Directors of the Open Source Electronic Health Record Alliance (OSEHRA). Prior to VA, Mike was involved in the commercialization of new products and technology in startups and large companies. He is a die-hard Virginia Tech Hokie.  

About MedicaSoft
MedicaSoft designs, develops, delivers, and maintains EHR, PHR, and UHR software solutions and HISP services for healthcare providers and patients around the world. For more information, visit www.medicasoft.us or connect with us on Twitter @MedicaSoftLLC, Facebook, or LinkedIn.

Alexa Can Truly Give Patients a Voice in Their Health Care (Part 1 of 3)

Posted on October 16, 2017 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

The leading pharmaceutical and medical company Merck, together with Amazon Web Services, has recently been exploring the potential health impacts of voice interfaces and natural language processing (NLP) through an Alexa Diabetes Challenge. I recently talked to the five finalists in this challenge. This article explores the potential of new interfaces to transform the handling of chronic disease, and what the challenge reveals about currently available technology.

Alexa, of course, is the ground-breaking system that brings everyday voice interaction with computers into the home. Most of its uses are trivial (you can ask about today’s weather or change channels on your TV), but one must not underestimate the immense power of combining artificial intelligence with speech, one of the most basic and essential human activities. The potential of this interface for disabled or disoriented people is particularly intriguing.

The diabetes challenge is a nice focal point for exploring the more serious contribution made by voice interfaces and NLP. Because of the alarming global spread of this illness, the challenge also presents immediate opportunities that I hope the participants succeed in productizing and releasing into the field. Using the challenge’s published criteria, the judges today announced Sugarpod from Wellpepper as the winner.

This article will list some common themes among the five finalists, look at the background about current EHR interfaces and NLP, and say a bit about the unique achievement of each finalist.

Common themes

Overlapping visions of goals, problems, and solutions appeared among the finalists I interviewed for the diabetes challenge:

  • A voice interface allows more frequent and easier interactions with at-risk individuals who have chronic conditions, potentially achieving the behavioral health goal of helping a person make the right health decisions on a daily or even hourly basis.

  • Contestants seek to integrate many levels of patient intervention into their tools: responding to questions, collecting vital signs and behavioral data, issuing alerts, providing recommendations, delivering educational background material, and so on.

  • Services in this challenge go far beyond interactions between Alexa and the individual. The systems commonly anonymize and aggregate data in order to perform analytics that they hope will improve the service and provide valuable public health information to health care providers. They also facilitate communication of crucial health data between the individual and her care team.

  • Given the use of data and AI, customization is a big part of the tools. They are expected to determine the unique characteristics of each patient’s disease and behavior, and adapt their advice to the individual.

  • In addition to Alexa’s built-in language recognition capabilities, Amazon provides the Lex service for sophisticated text processing. Some contestants used Lex, while others drew on other research they had done building their own natural language processing engines.

  • Alexa never initiates a dialog, merely responding when the user wakes it up. The device can present a visual or audio notification when new material is present, but it still depends on the user to request the content. Thus, contestants are using other channels to deliver reminders and alerts such as messaging on the individual’s cell phone or alerting a provider.

  • Alexa is not HIPAA-compliant, but may achieve compliance in the future. This would help health services turn their voice interfaces into viable products and enter the mainstream.

Some background on interfaces and NLP

The poor state of current computing interfaces in the medical field is no secret–in fact, it is one of the loudest and most insistent complaints by doctors, such as on sites like KevinMD. You can visit Healthcare IT News or JAMA regularly and read the damning indictments.

Several factors can be blamed for this situation, including unsophisticated electronic health records (EHRs) and arbitrary reporting requirements by Centers for Medicare & Medicaid Services (CMS). Natural language processing may provide one of the technical solutions to these problems. The NLP services by Nuance are already famous. An encouraging study finds substantial time savings through using NLP to enter doctor’s insights. And on the other end–where doctors are searching the notes they previously entered for information–a service called Butter.ai uses NLP for intelligent searches. Unsurprisingly, the American Health Information Management Association (AHIMA) looks forward to the contributions of NLP.

Some app developers are now exploring voice interfaces and NLP on the patient side. I covered two such companies, including the one that ultimately won the Alexa Diabetes Challenge, in another article. In general, developers using these interfaces hope to eliminate the fuss and abstraction in health apps that frustrate many consumers, thereby reaching new populations and interacting with them more frequently, with deeper relationships.

The next two parts of this article turn to each of the five finalists, to show the use they are making of Alexa.

Health Data Standardization Project Proposes “One Record Per Person” Model

Posted on October 13, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

When we sit around the ol’ HIT campfire and swap interoperability stories, many of us have little to do but gripe.

Is FHIR going to solve all of our interoperability problems? Definitely not right away, and who knows if it ever will? Can we get the big EMR vendors to share and share alike? They’ll try, but there’s always a catch. And so on. There’s always a major catch involved.

I don’t know if the following offers a better story than any of the others, but at least it’s new one, or at least new to me. Folks, I’m talking about the Standard Health Record, an approach to health data sharing doesn’t fall precisely any of the other buckets I’m aware of.

SHR is based at The MITRE Corporation, which also hosts virtual patient generator Synthea. Rather than paraphrase, let’s let the MITRE people behind SHR tell you what they’re trying to accomplish:

The Standard Health Record (SHR) provides a high quality, computable source of patient information by establishing a single target for health data standardization… Enabled through open source technology, the SHR is designed by, and for, its users to support communication across homes and healthcare systems.

Generalities aside, what is an SHR? According to the project website, the SHR specification will contain all information critical to patient identification, emergency care and primary care along with background on social determinants of health. In the future, the group expects the SHR to support genomics, microbiomics and precision medicine.

Before we dismiss this as another me-too project, it’s worth giving the collaborative’s rationale a look:

The fundamental problem is that today’s health IT systems contain semantically incompatible information. Because of the great variety of the data models of EMR/EHR systems, transferring information from one health IT system to another frequently results in the distortion or loss of information, blocking of critical details, or introduction of erroneous data. This is unacceptable in healthcare.

The approach of the Standard Health Record (SHR) is to standardize the health record and health data itself, rather than focusing on exchange standards.

As a less-technical person, I’m not qualified to say whether this can be done in a way that will be widely accepted, but the idea certainly seems intuitive.

In any event, no one is suggesting that the SHR will change the world overnight. The project seems to be at the beginning stages, with collaborators currently prototyping health record specifications leveraging existing medical record models. (The current SHR spec can be found here.)

Still, I’d love for this to work, because it is at least a fairly straightforward idea. Creating a single source of health data truth seems like it might work.

Where Patient Communications Fall Short?

Posted on October 12, 2017 I Written By

The following is a guest blog post by Sarah Bennight, Marketing Strategist for Stericycle Communication Solutions, as part of the Communication Solutions Series of blog posts. Follow and engage with them on Twitter: @StericycleComms

We are constantly switching devices to engage in our daily lives. In fact, in the last ten minutes I have searched a website on my desktop computer, answered a phone call, and checked several text messages and emails on my cellphone. Our ability to seamlessly jump from one device to the next affects our consumer behavior when interacting with places of business.

Today, we can order coffee and groceries online, web chat with our internet service company, and research store offerings before ever physically walking into a building. Traditionally, healthcare consumers had mainly phone support until the 2014 Meaningful Use 2 rule dictated messaging with a physician and patient portal availability. Recently, online scheduling and urgent care check in has been an attractive offering for consumers of health wanting to take control of their calendars and wait times.

Healthcare is certainly expanding functionality and communication channels to meet consumer demand. But where are we falling short? The answer may be relatively simple: data integration. Much like the clinical side of the healthcare business, integration is a gap we must solve. The key to turning technological convenience into optimal experience is evolving multichannel patient interactions into omnichannel support.

Omnichannel means providing a seamless experience regardless of channel or device. In the healthcare contact center, this means ensuring live agents, scheduling apps, chat bots, messaging apps, and all other interaction points share data across channels. It removes the individual information silos surrounding the patient journey, and connects them into one view from patient awareness to care selection, and again when additional care is needed.

In 2016, Cisco Connect cited four key reasons a business should invest in omnichannel consumer experiences, but I believe this resonates in the healthcare world as well:

  1. A differentiated patient and caregiver experience which is personal and interactive. Each care journey is unique, and their initial experiences should resonate and instill confidence in your brand. We now communicate with several generations who have different levels of comfort with technology and online resources. Offering multiple channels of interaction is crucial to success in the competitive healthcare space. But don’t stop there! Integrated channels connecting the data points along the journey into and beyond the walls of the care facility will create lasting loyalty.
  2. Increased profit and revenue. The journey to finding a doctor or care facility begins long before a patient walks in your door. Most of these journeys begin online, by interviewing friends, and checking online reviews. Once an initial decision is made to visit your organization, you can extend your marketing budget by targeting patients who might actually be interested in your services. When you know what your patients’ needs are, there is a greater focus and a higher chance of conversion.
  3. Maintain and contain operating costs. Integrating with EMRs is not always the easiest task. However, your scheduling and reminder platforms must be able talk to each other not only for the optimal experience, but also for efficient internal process management. For example, if a patient receives a text reminder about an appointment and realizes the timing won’t work, they can request to reschedule via text. Real time communication with the EMR enables agents currently on the phone with other patients to see the original appointment open up and grab the slot. Imagine the streamlining with the patient as well in an integrated platform. Go beyond the ‘request to reschedule’ return text and send a message says “We see that you want to reschedule your appointment. Here are some alternative times available”. Take it one step further with a one-step click to schedule process. With this capability, the patient could immediately book without a follow-up phone call reminder or staff having to hunt them down to book.
  4. Faster time to serve the patient. When systems and people communicate pertinent data, faster issue resolution is possible. Healthcare can be scary, and when you address patient and caregiver needs in a timely manner, trust in your organization will grow. In omnichannel experiences, a patient can search for care in the middle of the night online, and when they don’t find an appointment opening a call could be made. Imagine the value of already knowing that a patient was searching for a sick visit for tomorrow morning with Dr. X. With this data in mind, you are able to immediately offer alternatives and keep that patient in your system before they turn to a more convenient option.

You can see how omnichannel experiences are going to pave the way for the future of the contact center. Right now, the interactions with patients before and after treatment provide an enormous opportunity to build trust and further engagement with your organization. By integrating the data and allowing cross-channel experiences that build on each other, the contact center will extend into the main hub of engagement in the future. The time to build that integrated infrastructure is now, because in the near future new channels of engagement will be added and expected. Are you ready to deliver an omnichannel experience?

The Communication Solutions Series of blog posts is sponsored by Stericycle Communication Solutions, a leading provider of high quality call center & telephone answering servicespatient access services and automated communication technology. Stericycle Communication Solutions combines a human touch with innovative technology to deliver best-in-class communication services.  Connect with Stericycle Communication Solutions on social media: @StericycleComms

Role of Provider Engagement for Improving Data Accuracy – #HITsm Chat Topic

Posted on October 10, 2017 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

We’re excited to share the topic and questions for this week’s #HITsm chat happening Friday, 10/13 at Noon ET (9 AM PT). This week’s chat will be hosted by @CAQH on the topic of “Role of Provider Engagement for Improving Data Accuracy.”

Healthcare provider data forms the foundation of many important processes in the nation’s healthcare system, whether referring a patient to a specialist, paying insurance claims, credentialing providers or maintaining accurate provider directories. Yet access to accurate, timely provider data has remained elusive.

A lack of authoritative and reliable sources has resulted in a costly, piecemeal approach to acquiring and maintaining provider information. The commercial healthcare industry spends at least $2.1 billion annually on inefficient processes to maintain the data, according to a recent CAQH white paper.

While healthcare providers are important contributors of their professional and practice information, the task of submitting frequent updates to different organizations, through different channels, has created a significant administrative challenge.

Join @CAQH in a discussion about the role of provider engagement in improving data accuracy. Topics will cover strategies for collaboration and enhanced communication to ease the burdens on providers and users of provider data.

Reference Materials:

Topics for This Week’s #HITsm Chat:

T1: Stakeholders define provider data differently. How do you use provider data & in what role, i.e. payer, provider, consumer? #hitsm

T2: How does the shifting definition of “provider” (e.g. emerging provider types) impact data management? #hitsm

T3: How can the industry empower providers to participate more actively in data accuracy? #hitsm

T4: What can industry stakeholders do to reduce the administrative burden on providers? #hitsm

T5: What strategies would help providers and payers hold each other accountable for high-quality provider data? #hitsm

BONUS: What is the biggest opportunity you see for improving the quality of provider data right now? #hitsm

Upcoming #HITsm Chat Schedule
10/20 – Community Sharing Chat
Hosted by the #HITsm Community

10/27 – Aggregating the Patient Perspective and Incorporating It Into Software to Change Healthcare
Hosted by Lisa Davis Budzinski (@lisadbudzinski)

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FDA Announces Precertification Program For Digital Health Tools

Posted on October 5, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

The FDA has recruited some the world’s top technology and medical companies to help it pilot test a program under which digital health software could be marketed without going through the through the agency’s entire certification process.

The participants, which include Apple, Fitbit, Johnson & Johnson, Samsung and Roche, will give the agency access to the measures they’re using to develop, test and maintain their software, and also how they collect post-market data.

Once armed with this information, the FDA will leverage it to determine the key metrics and performance indicators it uses to see if digital health software meets its quality standards.

Companies that meet these new standards could become pre-certified, a status which grants them a far easier path to certification than in the past. This represents a broad shift in the FDA’s regulatory philosophy, “looking first at the software developer digital health technology developer, not the product,” according to a report previously released by the agency.

If the pilot works as planned, the FDA is considering making some significant changes to the certification process. If their processes pass muster, pre-certified companies may be allowed to submit less information to the FDA than they currently must before marketing a new digital health tool.  The agency is also considering the more radical step of allowing pre-certified companies to avoid submitting a product for premarket review in some cases. (It’s worth noting that these rules would apply to lower-risk settings.)

The prospect of pre-certifying companies does raise some concerns. In truth, the argument could be made that digital health software should be regulated more tightly, not less. In particular, the mobile healthcare world is still something of a lawless frontier, with very few apps facing privacy, security or accuracy oversight.

The fact is, it’s little wonder that physicians aren’t comfortable using mobile health app data given how loosely it can be constructed at times, not to mention the reality that it might not even measure basic vital signs reliably.

It’s not that the healthcare industry isn’t aware of these issues. about a year ago, a group of healthcare organizations including HIMSS, the American Medical Association and the American Heart Association came together to develop a framework of principles dressing app quality. Still, that’s far short of establishing a certification body.

On the other hand, the FDA does have a point when it notes that a pre-certification program could make it easier for useful digital health tools to reach the marketplace. Assuming the program is constructed well, it seems to me that this is a good idea.

True, it’s pretty unusual to see the FDA loosen up its certification process – a fairly progressive move for a stodgy agency – while the industry fails to self-regulate, but it’s a welcome change of style. I guess digital health really is changing things up.