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Artificial Intelligence in Healthcare: Medical Ethics and the Machine Revolution

Posted on July 25, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

Artificial Intelligence could be the death of us all.  I heard that roughly a hundred times last week through shares on twitter. While this theme may be premature, the concern of teaching ethics and valuing human life is a relevant question for machine learning, especially in the realm of healthcare. Can we teach a machine ethical bounds? As Elon Musk calls for laws and boundaries I was wondering what semantics and mathematics would be needed to frame that question.  I had a Facebook friend that told me he knew a lot about artificial intelligence and he wanted to warn me about the coming robot revolution.

He did not, in fact, know a lot about artificial intelligence coding. He did not know code nor did he have any knowledge of mathematical theory, but was familiar with the worst-case scenarios of the robots we create finding humanity superfluous and eliminating us. I was so underwhelmed I messaged my friend who makes robots for Boston Dynamics and asked him about his latest project.

I was disappointed with that Facebook interaction. This disappointment was offset for me last week when the API changed and a happy Facebook message asked me if I wanted to revisit an ad that I had previously liked. I purposefully like ads if I like the company. Good old Facebook predictive ads. Sometimes I also comment on a picture or tag someone in an add to see if I can change which advertisements I see in my feed.

One of the happiest times with this feature was finding great new running socks. I commented on a friends’ picture that I liked her running socks and within an hour saw my first ad for those very same socks. While I’m not claiming to have seen the predictive and advertising algorithms behind Facebook advertising, machine learning is behind that ad.  Photo recognition through image processing can identify the socks my friend Ilana was wearing while running a half marathon. Simple keyword scans can read my positive comments about the socks which gives them information about what I like. This can pair with photos from advertisers and- within one hour of “liking” those socks they seamlessly show up in my feed as a buying option. Are there ethical considerations about knowing exactly what my buying power is and my buying patterns and my personal history? Yes. Similarly, there will be ethical considerations when insurance companies can predict exactly which patients will and won’t be able to pay for their healthcare. While I appreciate great running socks, I have mixed feelings about assessing my ability to pay for the best medical care.

Can a machine be taught to value the best medical care and ethics? We seem to hear a lot of debate about whether they can be taught not to kill us. Teaching a machine ethics will be complicated as they show how poor nutrition directly changes how long patients live. Some claim these are dangerous things to create, others say the difference will be human intuition. Can human intuition be replicated and what application will that have for medicine?  I always considered intuition connections our brain recognizes that we are not directly aware of, so a machine should be able to learn intuition through deep learning networks.

Creating “laws” or “rules” for ethics in artificial intelligence as Elon Musk calls for is difficult in that ethical bounds are difficult to teach machines. In a recent interview Musk claimed that Artificial Intelligence is the biggest risk that we face as a civilization. Ethical rules and bounds are difficult for humanity. Once when we were looking at data patterns and trust patterns and disease prediction someone turned to me and said- but insurance companies will use this information to not give people coverage. If they could read your genes people will die. In terms of teaching a machine ethics or adding outward bounds, one of the weaknesses is that trained learning systems can get really good on a narrow domain but they don’t do transfer learning in different domains- like reason by analogy- machines are terrible at that. I spoke with Adam Pease about how you can increase the ability of machines to use ontology to increase benefits of machine learning in healthcare outcomes. Ontology creates a way to process meaning that is more robust in a semantic view. He shared his open source projects about Ontology and shared that we should be speaking with Philosophers and Computer science experts about ontology and meaning.

Can a machine learn empathy? Will a naturally learning and evolving system teach itself different bounds and hold life sacred, and how will it interpret the challenge of every doctor to “Do no Harm?” The Medical community should come together for agreement about the ethical bounds and collaborate with computer scientists to see the capacity to teach those bounds and the possible outliers in motivation.

Most of the natural language processing is for applications that are pretty shallow in terms of what the machine understands. Machines are good at matching patterns- if your pattern is a bag of words it can connect with another bag of words within a quantity of documents. Many companies have done extensive work in training systems that will be working with patients to learn what words mean and common patterns within patient care. Health Navigator, for example, has done extensive work to form the clinical bounds for a telemedicine system. When a patient asks about their symptoms they get clinically relevant information paired with their symptoms even if that patient uses non-medical language in describing their chief complaint.  Clinical bounds create a very important framework for an artificial intelligence system to process large amounts of inbound data and help triage patients to appropriate care.

With the help of Symplur signals I looked at Ethics and Artificial Intelligence in Healthcare and who was having conversations online in those areas. Wen Dombrowski MD, MPH lead much of the discussion. Appropriately, part of what Catalaize Health does is artificial intelligence due diligence for healthcare organizations. Joe Babian who leads #HCLDR discussion was also a significant contributor.

Symplur Signals looked at the stakeholders for Artificial Intelligence and Ethics in Healthcare

A “smart” system needs to be able to make the same amount of inferences that a human can. Teaching inferences and standards within semantics are the first steps to teaching a machine “intuition” or “ethics.” Predictive pattern recognition appears more developed than ethical and meaning boundaries for sensitive patient information. We can teach a system to recognize an increased risk of suicidal behavior from rushing words or dramatically altered behavior or higher pitched speaking, but is it ethical to spy on at risk patients from their phone. I attended a mental health provider meeting about how that knowledge would affect patients with paranoia. What are the ethical lines between protection and control? Can the meaning of those lines be taught to a machine?

I’m looking forward to seeing what healthcare providers decide those bounds should be, and how they train the machines those ontologies.

WorkFlow Wednesday: Patient Satisfaction and West’s Patient Experience Survey

Posted on July 5, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

Providers can improve patient experiences and revenue. So much of what improves satisfaction is outside the clinical setting.  West’s Insights and Impact Study titled “Prioritizing the Patient Experience” examines the gaps in patient value perception in the current healthcare marketplace.

West recently conducted a survey of patients providers to get more insights into what patients and providers value.  With value based payment models and consumer focused health providers are increasingly motivated to provide high quality service. Today’s patient is more aware of choice in provider options and will shop around for a provider that matches their needs.

Patients and Value Based Care Provide More Awareness of Choice in the Healthcare Marketplace

Patient experience using current technology and workflows is the space West has been working in for 25 years, including patient reminders for large hospital systems. As a company that specializes in patient experience, they used an outside firm to get insight about how well provider and patient perceptions were aligned. It was impressive to see an engagement company practicing what they preach and being proactive about feedback and improvement.

The most interesting takeaway from all of the statistics and research and report is that we know what the drivers of a good experience are. If you ask patients and providers what their motivation are answers are not usually aligned. This gap in what providers and patients value in terms of healthcare experience can cost providers revenue and patients. Patients value a high level of communication and transparency about cost of care more than providers believe.

Looking at the study, 78% of patients with a Chronic condition are likely to say that their provider cares about them as a person. Personally I’ve experienced this with my son that has a Chronic condition. We researched providers to ensure that we had similar values about communication and follow-up. Social Media groups like mom groups on Facebook have a lot of feedback about provider value. I know his provider gives great care and cares about him.

Patients with a Chronic Condition are Likely to Receive Personalized Care.

My Takeaways From the West Report

  • Current Systems do not always create a seamless workflow. Smooth workflow and patient communications improve patient experience.
  • Patients really want to know about what to expect in appointments. Sending a notification about costs including copays and obligations improves patient satisfaction.
  • Wait times are a huge cause of concern for patients. Electronic messaging or text information about waits can improve patient satisfaction even in cases where delays cannot be avoided.
  • Making payment as easy for patient as possible improves patient healthcare experience. A reminder about a bill with information about how to pay will improve practice revenue and patient experience.
  • Simple workflow improvement and automation improves clinical outcomes and patient retention in an increasingly consumer aware healthcare world.
  • Providers can focus on using the technology to better measure that for further strategy for improvement.

Well developed workflow can ensure that physicians have fewer patient surprises. Rather than waiting for an HCAP you can proactively collect data and brief surveys on specific topics before you are doing emergency triage. Contact recently discharged patients via an automated phone message or email. Have the questions tie back to HCAP survey questions so they can see what they will get.

What can systems do? Select Key measures for patient satisfaction.

What can physicians do? Tell patients that what to expect.

West is following their own advice and getting feedback about the value of communications and technology The survey is a connector for patients and for technology companies in the HealthIT space. Great ideas about Workflow improvement and best practice for business from West.

The report can be accessed online here and these key takeaways and is a great read for providers.

Artificial Intelligence in Healthcare Series: Women in Technology

Posted on June 29, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

Meeting with Lauren Hayes, the model behind Amelia, an AI cognitive agent.

What I Learned from Lauren Hayes: the Face of Artificial Intelligence.

This month I was invited to a workforce summit with companies interested in Artificial Intelligence (AI) cognitive agents in New York City. I had the opportunity to hear from great thinkers about AI, including research about workforce transformation from the McKinzie institute. I also met Lauren Hayes, the face behind Amelia, a cognitive agent for IPsoft specializing in customer experience.

Michael Chui – Partner at the McKinsey Global Institute.

One of the most impactful things for me personally was Lauren’s perspective about women in technology. Lauren has worked as a partner for a Jacaranda Ventures focusing on early stage startups, and served as an executive and communications expert, as well as being a model for Wilhelmina models. As a veteran of the technology space Lauren commented on male dominated events  “One of my past jobs as a Director of Communications & PR included hosting events that typically ended up being 90% male. The audience was comprised of our investors, partners, and C-level business development folks. It’s always sad when there’s no line for the women’s restroom.”  Her  grace in dealing with the dynamics taught me two valuable lessons: Be fiercely positive and seek out your people.

Today Lauren works in technology as a Founder at Ritual and the face of a cognitive agent that interfaces with customers for several industries, (patients for a healthcare system.) What does current customer experience look like? In my experience- not great. There is a definite need to improve the experience for patients online and many companies and healthcare systems have solutions that help improve outcomes and cost.  My personal strategy? Get on the phone and press as many buttons as I can, while hoping a real human comes on the line since I don’t remember my insurance ID number. Or my account number with the power company.

Lauren is part of the future of healthcare as AI automates repetitive tasks. A little background on the potentials and current benefits can start with the patient as a consumer. Many healthcare companies use an automated system when a patient calls with medical questions or personal patient information. They may want a copy of their records and need identity confirmation or need to know if they should make an appointment with a doctor or go to a local emergency room. These questions can be answered through digital tools and phones.

Systems can range in sophistication from a series of recordings to a chat bot to an artificial intelligence cognitive agent and a human with highly specialized training and clinical knowledge. Not to brag, but at one of my jobs the company asked me to be the voice for their system so I can relate to being the face of AI. A cognitive agent can use artificial intelligence technology and interact with a clinical framework to help patients get great care. This can be paired with the clinical bounds of a program like Health Navigator and use natural language processing to help patients get appropriate support quickly and in the context of their personal history and insurance or healthcare information. Adoption and development of these technologies will see huge positive impact on patient outcomes and security.

I interacted with Lauren on twitter before the conference to discuss working as a woman in tech. The thing that struck me meeting her was her grace. Some people have powerful positive energy and I wonder how we can teach that type of interaction to a machine learning system. We can teach a system to have an asymmetrical appearance like humans. Artificial intelligence engines are learning to identify customers by voice and appearance. The human experience in medicine is also about presence and connecting us digitally. I asked Lauren what she thought about working with Amelia, and about being a woman in Technology. Mainly I wanted to understand the way she has established expectations and boundaries.

Janae: What is it like working in technology as a woman?

Lauren: This is not specific to one of the roles I’ve held particularly, whether at IPSoft or any of my other jobs, however, I think in some of the male dominated industries, there’s a feeling as though you have to prove yourself and get over the “female hump” before a conversation with someone who expects to be talking to another man. I’ve had past jobs that bred a bit of a “bro” culture, where there are no women in high-level positions and I think that really trickles down and impacts the rest of the culture. It goes without saying that I’ve also overheard and been part of situations where sexist comments were made, or where visitors of the company assumed the first girl they saw was an assistant/office manager, etc.

Janae: What do you wish men understood about being a woman in tech?

Lauren: “That the same way racism is still rampant in the US, the same goes for sexism. Even when there’s not overt instances or actions that are clearly offensive, there are small, every day micro instances of things that are said under the breath or actions that are hard to prove clear wrongdoing that still add up and take a toll over a period of time.”

Janae: What do you love about working with Amelia?

Lauren:  “I think Amelia can potentially have such a positive impact on the workforce and ultimately world. After all, to date, she’s the most sophisticated AI in history. Throughout history we’ve changed our jobs to leverage technology. AI is going to do that too. I heard a lot of the execs presenting at the conference talking about how they are changing the structure of their teams in order to have Amelia take on a lot of the high volume repetitive queries and let their staff evolve to take on more exception cases that help them have more interesting conversations with customers. I think most of us would prefer to spend our time on tasks we find challenging and rewarding and less on repetitive chores. That idea of freeing up our day to spend more time doing things we love really appeals to me.”

Overcoming general fatigue from interactions that question credibility based on gender can be hard to grasp. Repetitive music and actions that themselves are harmless have been weaponized into torture. Constant references about appearance can be difficult. Talking to Lauren about women in technology was positive. For women, the sum is greater than it’s parts. The result for providers can be burnout or a lack of empathy for patient requests.

Artificial intelligence will restructure workforce roles and take some of the stress of repetitive tasks and recording. Building positive interactions while filtering through repetitive actions that lead to burnout can provide better support. Physician time can be used for helping and connecting on a personal level. I was grateful for the time I had discussing women in technology and the future. Establishing boundaries in workforce interactions can be like structuring the bounds of a healthcare customer service system. Creating purposeful positive interactions improves the system. Be fiercely positive to other women in technology.

Clinical Insights from Social Media Data: Amplifying Patient Voice with Symplur

Posted on May 31, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

What data from social media can help healthcare organizations?

One of the biggest challenges of online and social data is the sheer volume of unstructured data. Can your physician read all your tweets and postings? Hopefully not. Physicians have data and work overload, a daily report of steps taken from activity trackers or online social media use hurts their ability to treat patients. HealthIT solutions can help process this data and find patterns and changes.

I had a conversation with Audun Utengen about actionable insights into healthcare from his company, Symplur. At Datapalooza he participated in a panel and mentioned the rich amount of patient data that can be found on twitter (shocked gasp followed by a furrowed brow). Symplur signals tracks online engagement.  You can find healthcare insights from conversations really quickly. They provide tools that help healthcare providers get patient insights where they are naturally interacting. There is value in meeting patients where they are, and patients are discussing their healthcare online.

Originally, the assumption was that patients would not say things online. Sensitive topics do not naturally show up in social media use- fewer people are discussing gonorrhea online than receive treatment for gonorrhea. Providers assumed that things which are protected patient information would not show up on twitter. They were wrong. As most social media users know- it’s shocking what people will post online. Not every aspect of health is on twitter but patients want to engage online.  They go to twitter because they want their voices to be heard. They want things to change. They can’t be ignored on twitter. They want their voices to be heard by people in decision-making positions.

Patient’s online discussion have positive impacts on organizations. The key is to be proactive about patient engagement online. Stanford did a study looking about patients’ engagement at conferences. Typically, you will find 1 patient in the top 1 percent of influencers. While this number is low, conferences which have a higher percentage of patients active as top influencers have a greater reach. Want to increase your Healthcare voice and conference audience? Engage patient advocates online. Engaging patients is commercially valuable in amplification. Future patients get more insight as well.  Audun Utengen and I looked at the data from Datapalooza and found that 11 of the top 100 influencers were patients.  That is way ahead of the median number for all healthcare conferences- in 2016 the average number of top influencers that were patients at a conference was one.

“They did a great job giving patients a voice at the conference. I am impressed.”

-Audun Utengen, Co-Founder of Symplur

Healthcare Stakeholder breakdown of the top 100 influencers ranked by the Healthcare Social Graph Score.

Datapalooza had a higher than average reach and a unique blend of participants. Audun Utengen described some of the unique features of the conference:

“The social conversation from the conference was very dynamic. From the 9,366 tweets, 80% included at least one mention. Lot’s of connections were made and we witnessed the typical “flattening of healthcare” that social media is known for by breaking down the barriers between the stakeholder groups. Below is a network analysis graph showing the flattening and the conversational patterns between Twitter account and their healthcare stakeholder groupings.”

Conversations blend between different stakeholders in the healthcare conversation at Datapalooza

The ability for many stakeholders to access information and interact with each other in one place is one of the advantages of twitter. Using hashtags can help stakeholders learn about content about a specific topic quickly. One of the things Symplur is allows is the visualization of keywords surrounding conversations on twitter. When looking at the conversations from Datapalooza the topic of “patients” was very high. Unsurprisingly, “data” is the topic of focus. Patient, Health and Patients rounded out the top conversation topics.

Keyword Frequency Analysis Graph

Symplur Signals have been used for over 200 healthcare studies. They partner with academic research centers seeking more information from online conversations. Companies can also look at competitors in their area and see how they compare. Does a nearby provider have more positive mentions on social media?

Data from online interactions can also give insights into patient health. Social usage has unique implications for mental health. Frequently, online behavior change can predict mental health change. Pediatricians and Providers are in a position to see online behavior in their area and help families understand the implications. If bullying is a problem in your area providers can know their patients will have higher stress levels and provide resources and support. Certain behaviors and even emojis indicate a higher risk of depression. A suicide that will predictably happen based on social data will not show up in clinical records. Listening to what patients want us to hear will help provide greater support.

The sheer volume of social data can mask its usefulness. Online activity and data can be difficult to process for many clinicians. In a world of ever-increasing data and patients reporting everything from steps taken a day to now online behavior many providers have data overload. Data insight tools such as Symplur filter data into a format that allows physicians and systems to use it to improve patient outcomes.

Women Executives in Telehealth American Telemedicine Association ATA2017

Posted on May 18, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

Susan Dentzer, Charlotte Yeh, Janet McIntyre, and Janae Sharp at the American Telemed Women Executives in Telehealth Panel

One of the highlights of the American Telemedicine conference in Orlando Florida was excellent coverage of women in telemedicine and leadership.  They had a panel of women in leadership which focused on promoting women in telemedicine and had the best moderation of a panel I’ve seen at a conference.  Highlights of great advice for women in HealthIT were from that panel, and from speaking with women that were tasked with going to the conference as buyers in the telemedicine space.

Charlotte Yeh acted as moderator of the panel. She framed what the panel would cover and what they were not concerned with. She mentioned that we would not cover work life balance since that also applies to men and has been covered on many platforms.  Framing a conversation within the conference and healthcare setting made a huge impact.  Promoting women in telemedicine and HealthIT needs to have a specific framework.

Susan Dentzer, President and CEO of the Network for Excellence in Healthcare innovation suggested making an award for advancing women in leadership in Telehealth.  I’m a huge fan of medals for participation. Every day I get up and when I work out I suspect that I deserve a medal.  The medals for best contribution for advancing women next year should be an amazing ceremony at ATA.

Susan quoted Madeline Albright that “there’s a special place in hell for women who don’t support other women.” Think deliberately about creating something you want to be a part of. This year I’ve personally seen Max Stroud of Doyenne Connections simply create something she wanted to be a part of.

Julie Hall-Barrow invited leaders to find a young woman and become their mentor. Some of the women in leadership in healthcare are happy to promote other women but the promotion seems more strategic than like actual concern. Leaders should purposefully craft their ideal mentor relationship. ATA discussed creating a group dedicated to what women and companies in the telemedicine space would like to do with collaboration.

Paula Guy, when asked what she would tell a younger self, said “first of all I would tell myself not to get married so many times.” Her advice was hilarious and focused on not letting people tell you no. There is a power in knowing what you are capable of and surrounding yourself with other women who are also in that space. Paula’s advice was also to be part of a group that promotes mentors and other women working together.

Kristi Henderson spoke about not being afraid to push boundaries. Never settle until you get where you want to go. The advice and positive belief that women are capable of breaking through boundaries and leveraging their social connecting makes women poised for success despite being underrepresented.

Janet McIntyre, The Vice President of Professional services of the Colorado Hospital association, decided to approach Patrick Kennedy about coming to Colorado to help with the opioid epidemic there. He shared his family story and personal conviction about making a difference and Janet decided to invite him to help with her state.  Women need to be fearless in their ask and expect that people will want to help them succeed.

Rachel Dixon, director of Telehealth for AccessCare services, pointed out that women should have a safe space to discuss gender issues in their work. We can create a place to discuss which companies are working well with women in the telemedicine space and which ask about an older man partner or lack professionalism. I shared a story with her about a potential employer asking if he should consider my job only a work proposition.  Gender issues for a younger woman in leadership can be complex in navigating personal relationship. A soft intelligence network about how a company treats women is valuable for investors and employees.

I was impressed with the positive planning of women in healthcare leadership in telehealth. The thought leadership at this conference was one of the best organized in terms of giving organizations and individuals actionable plans for increasing female technology talent in leadership positions.

The Sexiest Data in Health IT: Datapalooza 2017

Posted on May 15, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

The data at this conference was the Best Data. The Biggest Data. No one has better data than this conference.

The sexiest data in all of healthIT was highlighted in Washington DC at Datapalooza April 27-28, 2017.  One of the main themes was how to deal with social determinants of health and the value of that data.  Sachin H. Jain, MD of Caremore Health reminded us that “If a patient doesn’t have food at home waiting for them they won’t get better” social data needs to be in the equation. Some of the chatter on the subject of healthcare reform has been criticism that providing mandatory coverage hasn’t always been paired with knowledge of the area. If a patient qualifies for Medicaid and has a lower paying job how can they afford to miss work and get care for their health issues?
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Rural areas also have access issues. Patient “Charles” works full time during the week and qualifies for Medicaid. He can’t afford to miss a lot of work but needs a half a day to get treatments which affect his ability to work. There is no public transportation in his town to the hospital in a city an hour and a half away. Charles can’t afford the gas or unpaid time off work for his treatment.

Urban patient “Haley” returns to her local ER department more than once a week with Asthma attacks.  Her treatments are failing because she lives in an apartment with mold in the walls. As Craig Kartchner from the Intermountain Healthcare team responded to the #datapalooza  hashtag online- These can be the most difficult things to change.

The 2016 report to Congress addresses the difficulty of the intersection between social factors and providing quality healthcare in terms of Social Determinants of Health:

“If beneficiaries with social risk factors have worse health outcomes because the providers they see provide low quality care, value based purchasing could be a powerful tool to drive improvements in care and reduce health disparities. However, if beneficiaries with social risk factors have worse health outcomes because of elements beyond the quality of care provided, such as the social risk factors themselves, value based payment models could do just the opposite. If providers have limited ability to influence health outcomes for beneficiaries with social risk factors, they may become reluctant to care for beneficiaries with social risk factors, out of fear of incurring penalties due to factors they have limited ability to influence.”

Innovaccer just launched a free tool to help care teams track and monitor Medicare advantage plans. I went to their website and looked at my county and found data about the strengths in Salt Lake where I’m located. They included:

  • Low prevalence of smoking
  • Low Unemployed Percentage
  • Low prevalence of physically inactive adults

Challenges for my area?

  • Low graduation rate
  • High average of daily Air pollution
  • High income inequality
  • High Violent crime rate per 100,000 population

Salt Lake actually has some really bad inversion problems during the winter months and some days the particulate matter in the air creates problems for respiratory problems. During the 2016-2017 winter there were 18 days of red air quality and 28 days of yellow air quality. A smart solution for addressing social determinants of health that negatively impact patients in this area could be addressing decreasing air pollution through increased public transportation. Healthcare systems will see an increase in cost of care during those times and long term population health challenges can emerge. You can look at your county after you enter your email address on their site. This kind of social data visualization can give high level insights into the social factors your population faces.

One of the themes of HealthDataPalooza was how to use system change to navigate the intersection between taking care of patients and not finding way to exclude groups. During his panel discussion of predictive analytics, Craig Monson the medical director for analytics and reporting discussed how “data analytics is the shiny new toy of healthcare.”    In addition to winning the unofficial datapalooza award for the most quotes and one liners – Craig presented the Clinical Risk Prediction Initiative (CRISPI).  This is a multi variable logistic regression model with data from the Atrius health data warehouse. His questions for systems to remember in their data analysis selection are “Who is the population you are serving? What is the outcome you need? What is the intervention you should implement?”

Warning- Craig reminds us that in a world of increasing sexy artificial intelligence coding a lot of the value analysis can be done with regression. Based on that statement alone I think he can be trusted. I still need to see his data.

CRISPI analyzed the relative utility of certain types of data, and didn’t have a large jump in utility when adding Social Determinant Data. This data was one of the most popular data sets during Datapalooza discussions but the reality of making actionable insights into system improvement? Craig’s analysis said it was lacking. Does this mean social determinant data isn’t significant or that it needs to be handled with a combination of traditional modeling and other methods?  Craig’s assertion seemed to fly in the face of the hot new trend of Social Determinants of Health data from the surface.

Do we have too much data or the wrong use of the data? Most of the companies investing into this space used data sources outside the traditional definition to help create solutions with social determinate of health and Patient outcomes. They differed in how they analyzed social determinant data. Traditional data sources for the social determinants of health are well defined within the public health research.  The conditions in which you work and live impact your health.

Datapalooza had some of the greatest minds in data analytics and speakers addressed gaps in data usefulness. Knowing that a certain large county wide population has a problem with air quality might not be enough to improve patient outcomes. There is need for analysis of traditional data sources in this realm and how they can get meaningful impact for patients and communities. Healthcare innovators need to look at different data sources.  Nick Dawson, Executive director of Johns-Hopkins Sibley Innovation Hub responded to the conversation about food at home with the data about Washington DC.  “DC like many cities has open public data on food scarcity. But it’s not part of a clinical record. The two datasets never touch.” Data about food scarcity can help hospital systems collaborate with SNAP and Government as well as local food programs. Dawson leads an innovation lab at Johns Hopkins Sibley where managers, directors, VPs and C Suite leaders are responsible for working with 4 innovation projects each year.

Audun Utengen, the Co Founder of Symplur said “There’s so much gold in the social media data if you choose to see it.” Social data available online helps providers meet patients where they are and collect valuable data.  Social media data is another source to collect data about patient preferences and interactions for reaching healthcare populations providers are trying to serve. With so much data available sorting through relevant and helpful data provides a new challenge for healthcare systems and providers.

New Data sources can be paired with a consultative model for improving the intersection of accountable care and lack of access due to social factors. We have more sophisticated analytic tools than ever for providing high value care in the intersection between provider responsibility and social collaboration. This proactive collaboration needs to occur on local and national levels.  “It’s the social determinants of health and the behavioral aspects that we need to fund and will change healthcare” we were reminded. Finding local community programs that have success and helping develop a strategy for approaching Social Determinants of Health is on the mind of healthIT professionals.

A number of companies examine data from sources such as social media and internet usage or behavioral data to design improvements for social determinants of health outcomes.   They seek to bridge the gaps mentioned by Dawson. Data sets exist that could help build programs for social determinants of health.  Mandi Bishop started Lifely Insights centered around building custom community plans with behavioral insights into social determinant data. Health in all Policies is a government initiative supporting increased structure and guidelines in these areas. They support local and State initiatives with a focus on prevention.

I’m looking forward to seeing how the data landscape evolves this year. Government Challenges such as the Healthy Behavior Data Challenge launched at Datapalooza will help fund great improvements. All the data people will get together and determine meaningful data sets for building programs addressing the social determinants of health. They will have visualization tools with Tableau. They will find ways to get food to patients at home so those patients will get better. Programs will find a way to get care to rural patients with financial difficulty and build safe housing.

From a healthcare delivery perspective the idea of collaborating about data models can help improve community health and decrease provider and payer cost. The social determinants of health can cost healthcare organizations more money than data modeling and proactive community collaboration.

Great regressions, saving money and improving outcomes?

That is Datapalooza.

First Time HIMSS: Parker Redding, Banyan Social

Posted on March 10, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

One of the main themes of HIMSS was using digital tools to manage your patient engagement and social engagement online. Banyan Social was there for their first conference introducing their digital solution for storing patient permissions to post reviews or photos online. I spoke with Parker Redding from Banyan Social. They were a first time Exhibitor at HIMSS and I wanted to hear what their impressions were from the conference.  Banyan Social is a platform with marketing tools for providers including digital storage of HIPAA forms and integration with Google reviews. From their website:  “Extend your reach and grow your practice with real-time reviews, HIPAA-compliant social media posts and automated practice listings.”

What was your first health IT conference like?

“Honestly, I thought it was pretty cool. It was almost overwhelming how many people were there. It was the biggest event I’ve ever been to. It was cool to see how many people are in the Health IT space. We were constantly busy at our booth and with how many people came to our booth we didn’t really have the opportunity to explore in depth. We are unique in the Health IT space and aren’t always the perfect fit for these database guys and those kinds of people but they were always willing to refer us to the right people and who to talk to.

One thing that I liked about this event is that even if they don’t think it’s a good fit everyone is willing to be open and have a conversation. Everyone there is trying to learn more and share knowledge it’s not just “I’m trying to get my CE credits and leave.”  It’s about learning something new – about gaining knowledge.

A lot of the people who were first time exhibitors that we talked to told us how it was crazy how big it was and how many people were there. The conference was really diverse in terms of experts from different countries.  It was cool to see the big EMR or the IBM booth and to see how much effort they put into their space.

What were your goals?

Our main goal was to create partnerships with other companies in the healthcare industry and to learn more about the healthcare IT industry and how our business fits in with this. We wanted to share our HIPAA approved social media app and how doctors/clinics can use social media and reviews to engage patients.

What was your favorite part of HIMSS?

Honestly, speaking with a pediatrician that owns multiple practices the last day and learning about why he’s been in the medical industry.  Learning about how much he cared about his patients and how he knew he could make more money in another industry. It’s amazing to see how passionate people are about healthcare and being positive. He gives up money because he’s passionate about helping with children.

What did you learn about Health IT?

Bunch of nerds.  Just kidding.  I love the nerds and the developers those are my people.

What do you wish you could do differently?

I would bring more people to have at our booth. We had a consistent flow of people stopping to talk with us that we didn’t get to spend the time we wanted to connect with other companies and learn more about the IT healthcare world. You can’t complain about having a busy booth.  I would take an Uber to the conference. Trying to find a parking spot and walking a mile to get to your booth was difficult.

International Women’s Day – Women in HIT Wish List

Posted on March 8, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed


Inequality in healthcare IT can get discouraging. Simplistic articles and advice for organizations on support from other women isn’t helping decrease the wage gap. (According to the 2016 report from HIMSS.) This year while attending HIMSS I asked women what advice they had for other women in Health IT.  I wanted to write life changing advice about what women in healthcare can learn from knowing women in tech and from each other.  I wanted to convince my good friend that left Health IT to move to other parts of Tech to come back. Many activists encouraging documenting your experiences negative and positive within the healthcare IT system. Some of the things I could share I judged too damaging for my personal goals to write about. As I spoke with Sarah Lacy and Cindy Gallop they directly said- if no one shares their story nothing will change.

Women’s issues in technology and the workplace make me livid. Here’s a list of some of them.

  1. Being casually hit on by married men in a professional setting. Or lack of professionalism. I’ve heard shocking stories from doctors and CEOs. Recent legal action has highlighted some systemic sexism in technology companies.
  2. Women who discredit each other in public and in private.
  3. At one meeting a woman mentioned “It must be hard to be in a room with so much estrogen.”
  4. Being afraid of mentioning anything for fear of losing credibility or hurting people I value.
  5. Feeling unsupported by men when I have greater fallout from relationships than they ever will. Do not forget that some of the fear is actually founded. Women who speak up do not always have support at work.
  6. Balancing positive and negative experiences can be exhausting. I am a mother like Sarah Lacy- I loved her comment that becoming a mother changed everything.  While I want to be a good example and provide for my three children I haven’t had the moment when I call out sexism and inequality in my personal experience.

Double standards scare me. In chatting with Sarah Lacy about being unafraid of sharing I was impressed by her candor about real personal losses.  Her comment that standing up for women has made her enemies reminded me that gender parity isn’t free.  It takes fearlessness. Through losing someone to suicide a year and a half ago I saw some fallout of people and realized that not everyone is for us. People disappeared that I never expected to leave my life and not everyone knew how to interact with me anymore. The advice I give to people from that experience is- When you don’t fit into the same mold you will lose people. Not everyone will want to work with you. Take people where they are. Always be where you are. Let go of some people so your professional life has room for true allies. For my friend that meant leaving Healthcare tech for another software industry. For me it meant a higher paying job after John’s death and only working with people I chose to connect with. It was a huge financial adjustment for personal reasons. I was also one of 4 women with a team of approximately 70 men at the time. In a very real way the women at that company had different expectations than the men. For one woman I spoke to at HIMSS it has meant losing her job at 55 and experiencing wage discrimination despite extensive experience. Have the courage to be where you are.

Systemically the culture of women in technology has to change. The loss of potential innovation and revenue and talent is a major cost to companies and the industry. There are educators teaching the economics of gender equality and trying to balance the equation. Thank you.

I have an amazing group of women in my life. I’ve had the honor to be part of Doyenne Connections this year. They are a group of women dedicated to grassroots support and mentoring. I was able to attend the Women in Tech Luncheon hosted by Disruptive Women in Healthcare.   I’m still pretty sure that Ceci Connolly and I are going to lunch next year.  I sat next to Dr. Wen Dombrowski at the luncheon and she reminded me to make my own opportunities.

Statistics about women in healthcare IT are discouraging. The wage gap is alive and well in healthcare especially at the executive level. Some of the theories about why this might be true seem apologist to me. HIMSS Vice President Loren Pettit was quoted in regards to the for profit gender pay divide shortly before HIMSS. “To be perfectly honest, we can’t explain that,” he said. “It’s just how the data came out.”

WE CAN’T EXPLAIN IT!?

Expletive?  There is probably an informatics specialist out there that has a digital solution to this problem. Can we gamify equality for corporations? This year has seen some new initiatives encouraging women to be involved in technology, including Melinda Gates announcing she was planning to invest in programs.  The 2017 report about Gender Barriers from ISACA.org reported that “a lack of female mentors (48 percent), a  lack of female role models (42 percent) and limited networking opportunities (27 percent) are the top three” barriers to women advancing in technology.   I went to some great women’s networking events at HIMSS. Can we make women specific events free? Many women’s events at HIMSS have an additional registration and cost. Companies that asked about helping women – I’ll give you an idea about what you can do. Sponsor a women’s event.

As Cindy Gallop reminded me- “If nobody speaks up, nothing changes.”

Here’s my wish list for Women’s Day this year.

  1. I want the gender gap in Health IT to get narrower this year.
  2. I would love to see support of female counterparts for gender differences without fanfare or expectations. Show up for women. Show up because it is what people do.
  3. I would love a health IT solution for gender parity in tech. If it already exists, please contact me so I can write about it.
  4. I wish we could all be as brave as female leaders that aren’t afraid of making enemies.  I wish I could be as brave as they are.
  5. I would love to see Melinda Gates as a mentor. My mentor.  Actually as my sponsor.

This Women’s Day I don’t have an inspirational article about moving proudly forward. I am tired. Some of the people I thought would be on my side as a woman are not. That’s not where they are. There are some safe places but it is exhausting. I’m not fearlessly calling out wrongdoing to raise awareness. I’m not sure what the complete solution is. We are all stumbling forward through darkness. We will make a way. We will make our opportunities.

Post Script- Can we never clap for men asking how they can help again?  I sort of expect men to show up. It’s a financial problem for Healthcare that women don’t stay here. The first time I saw the clapping was my first HIMSS when a man asked how men can help and everyone clapped and I didn’t know what was happening. This was clearly not like other feminist groups I know. I looked around and thought- maybe start by not making a women’s event about you. Also have you heard of a thing called Google – you can insert questions and will get some relevant data. You could type “what can I do to encourage women in tech” into the search bar. Spoiler alert – money is the answer. You can pay women the same amount you pay men. Your company will also be more profitable.

 

First Time HIMSS: Hospital CEO John Kurvink

Posted on March 7, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

I met John Kurvink from Georgian Bay General Hospital at the Salesforce party at HIMSS this year. We discussed the relative value of a VIP pass vs a regular guest pass. As a hospital CEO, John was wearing a shiny VIP necklace complete with sparkling flashing lights. We found the flashing light wands together and discussed how HIMSS was going for them.

John has the ability to motivate staff and managers to develop their potential and participated in the Intermountain Healthcare video series on healthcare in November 2016.  It was immediately clear that he was there with his team, to maximize the HIMSS experience. I wanted to hear more about the decision making process and differentiating between sales pitches on the exhibitor floor and value for Hopital CFO and CEOs. I asked if I could walk the exhibit floor a bit with their team.  After the show John shared his insights about his first visit to HIMSS.

What was your first health IT conference like?

It was a good experience.  Overwhelming at first.  It took a day to get my conference legs under me.

What were your goals?

See some of the latest health IT projects.  Connect with some of the vendors we do business with.

What was your favorite part of HIMSS?

Networking with other attendees and vendors.  I met some very interesting smart people

What did you learn about Health IT?

There are so many vendors who all appear to be offering the same solutions.  Differentiating between them is a challenge.

What did you learn?

I learned that as a hospital we have lots of options as far as technology solutions.  Need to be very careful before making a commitment.

What was your least favorite part of HIMSS?

Not having a plan which meant I wasted a lot of time walking back and forth arriving late for sessions.

What do people need to know about Health IT from HIMSS?

You need to be sure to have a plan before you arrive.  Know what you want to learn about and focus on executing instead of being caught up with the “new shiny object”.

Many vendors have similar offerings or business solutions and making buying decisions for a hospital or healthcare group can be overwhelming. Brenda and Elizabeth from the Georgian Bay were intelligent and hilarious. Georgian Bay had proposals from patient security partners and other vendors and walking the exhibit floor with John helped me see how vendors interact with Hospital CEOs. They are more aggressive and less technical in their product description. There are more invited dinners with sales pitches. His consideration for his team and ability to see past the “new shiny object” were impressive.

Here’s to many more years of learning with John and his team.

Selecting the Right AI Partner in Healthcare Requires a Human Network

Posted on March 1, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

Artificial Intelligence, or AI for short, does not always equate to high intelligence and this can have a high cost for healthcare systems. Navigating the intersection of AI and healthcare requires more than clinical operations expertise; it requires advanced knowledge in business motivation, partnerships, legal considerations, and ethics.

Learning to Dance at HIMSS17

This year I had the pleasure of attending a meetup for people interested in and working with AI for healthcare at the Healthcare Information and Management Systems Society (HIMSS) annual meeting in Orlando, Florida. At the beginning of the meetup Wen Dombrowski, MD, asked everyone to stand up and participate in a partner led movement activity. Not your average trust fall, this was designed to teach about AI and machine leaning while pushing most of us out of our comfort zones and to spark participants to realize AI-related lessons. One partner led and the other partner followed their actions.

Dedicated computer scientists, business professionals, and proud data geeks tested their dancing skills. My partner quit when it was my turn to lead the movement. About half of the participants avoided eye contact and reluctantly shuffled their feet while they half nursed their coffee. But however awkward, half the participants felt the activity was a creative way to get us thinking about what it takes for machines to ‘learn’. Notably Daniel Rothman of MyMee had some great dance moves.

I found both the varying feedback and equally varying willingness to participate interesting. One of the participants said the activity was a “waste of time.” They must have come from the half of the room that didn’t follow mirroring instructions. I wonder if I could gather data about what code languages were the specialty of those most resistant. Were the Python coders bad at dancing? I hope not. My professional training is actually as a licensed foreign language teacher so I immediately corroborated the instructional design effectiveness of starting with a movement activity.

There is evidence that participating in physical activity preceding learning makes learners more receptive and allows them to retain the experience longer. “Physical activity breaks throughout the day can improve both student behavior and learning (Trost 2007)” (Reilly, Buskist, and Gross, 2012). I assumed that knowledge of movement and learning capacity was common knowledge. Many of the instructional design comments Dr. Dombrowski received while helpful, revealed participants’ lack of knowledge about teaching and cognitive learning theory.

I could have used some help at the onset in choosing a dance partner that would have matched and anticipated my every move. The same goes for healthcare organizations and their AI solutions.  While they may be a highly respected institution employing some of the most brilliant medical minds, they need to also become or find a skilled matchmaker to bring the right AI partner (our mix of partners) to the dance floor.

AI’s Slow Rise from Publicity to Potential

Artificial Intelligence has experienced a difficult and flashy transition into the medical field. For example, AI computing has been used to establish consensus with imaging for radiologists. While these tools have helped reduce false positives for breast cancer patients, errors remain and not every company entering AI has equal computing abilities. The battle cry that suggested physicians be replaced with robots seems to have slowed robots. While AI is gaining steam, the potential is still catching up with the publicity.

Even if an AI company has stellar computing ability, buyers should question if they also have the same design for outcome. Are they dedicated to protecting your patients and providing better outcomes, or simply making as much profit as possible? Human FTE budgets have been replaced by computing AI costs, and in some instances at the expense of patient and data security.  When I was asking CIOs and smaller companies about their experiences, many were reluctant to criticize a company they had a non-disclosure agreement with.

Learning From the IBM Watson and MD Anderson Breakup

During HIMSS week, the announcement that the MD Anderson and IBM Watson dance party was put on hold was called a setback for AI in medicine by Forbes columnist Matthew Herper. In addition, a scathing report detailing the procurement process written by the University of Texas System Administration Audit System reads more like a contest for the highest consulting fees. This suggests to me that perhaps one of the biggest threats to patient data security when it comes to AI is a corporation’s need to profit from the data.

Moving on, reports of the MD Anderson breakup also mention mismanagement including failing to integrate data from the hospital’s Epic migration. Epic is interoperable with Watson but in this case integration of new data was included in Price Waterhouse Cooper’s scope of work. If poor implementation stopped the project, should a technology partner be punished? Here is an excerpt from the IBM statement on the failed partnership:

 “The recent report regarding this relationship, published by the University of Texas System Administration (“Special Review of Procurement Procedures Related to the M.D. Anderson Cancer Center Oncology Expert Advisor Project”), assessed procurement practices. The report did not assess the value or functionality of the OEA system. As stated in the report’s executive summary, “results stated herein are based on documented procurement activities and recollections by staff, and should not be interpreted as an opinion on the scientific basis or functional capabilities of the system in its current state.”

With non-disclosure agreements and ongoing lawsuits in place, it’s unclear whether this recent example will and should impact future decisions about AI healthcare partners. With multiple companies and interests represented no one wants to be the fall guy when a project fails or has ethical breaches of trust. The consulting firm of Price Waterhouse Coopers owned many of the portions of the project that failed as well as many of the questionable procurement portions.

I spoke with Christine Douglas part of IBM Watson’s communications team and her comments about the early adoption of AI were interesting. She said “you have to train the system. There’s a very big difference between the Watson that’s available commercially today and what was available with MD Anderson in 2012.”  Of course that goes for any machine learning solution large or small as the longer the models have to ‘learn’ the better or more accurate the outcome should be.

Large project success and potential project failure have shown that not all AI is created equally, and not every business aspect of a partnership is dedicated to publicly shared goals. I’ve seen similar proposals from big data computing companies inviting research centers to pay for use of AI computing that also allowed the computing partner to lease the patient data used to other parties for things like clinical trials. How’s that for patient privacy! For the same cost, that research center could put an entire team of developers through graduate school at Stanford or MIT. By the way, I’m completely available for that team! I would love to study coding more than I do now.

Finding a Trusted Partner

So what can healthcare organizations and AI partners learn from this experience? They should ask themselves what their data is being used for. Look at the complaint in the MD Anderson report stating that procurement was questionable. While competitive bidding or outside consulting can help, in this case it appears that it crippled the project. The layers of business fees and how they were paid kept the project from moving forward.

Profiting from patient data is the part of AI no one seems willing to discuss. Maybe an AI system is being used to determine how high fees need to be to obtain board approval for hospital networks.

Healthcare organizations need to ask the tough questions before selecting any AI solution. Building a human network of trusted experts with no financial stake and speaking to competitors about AI proposals as well as personal learning is important for CMIOs, CIOs and healthcare security professionals. Competitive analysis of industry partners and coding classes has become a necessary part of healthcare professionals. Trust is imperative and will have a direct impact on patient outcomes and healthcare organization costs. Meetups like the networking event at HIMSS allow professionals to expand their community and add more data points, gathered through real human interaction, to their evaluation of and AI solutions for healthcare. Nardo Manaloto discussed the meetup and how the group could move forward on Linkedin you can join the conversation.

Not everyone in artificial intelligence and healthcare is able to evaluate the relative intelligence and effectiveness of machine learning. If your organization is struggling, find someone who can help, but be cognizant of the value of the consulting fees they’ll charge along the way.

Back to the dancing. Artificial does not equal high intelligence. Not everyone involved in our movement activity realized it was actually increasing our cognitive ability. Even those who quit, like my partner did, may have learned to dance just a little bit better.

 

Resources

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