big data

Archive for big data

Are Women Better Surgeons? Patient-Generated Data Knows The Answer

As empowerers of patients and collectors of patient-generated data, we’re pretty bullish on the ability for this data to show insights. We fully admit to being biased, and view things through a lens of the patient experience and outcomes, which is why we had some ideas about a recent study that showed female surgeons had better outcomes than male surgeons.

The study, conducted on data from Ontario, Canada, was a retrospective population analysis of patients of male and female surgeons looking at rates of complications, readmissions, and death. The results of the study showed that patients of female surgeons had a small but statistically significant decrease in 30-day mortality and similar surgical outcomes.

Does this mean that women are technically better surgeons? Probably not. However, there is one sentence that stands out to a possible reason that patients of female surgeons had better outcomes.

A retrospective analysis showed no difference in outcomes by surgeon sex in patients who had emergency surgery, where patients do not usually choose their surgeon.

This would lead us to believe that there is something about the relationship between the patient and the provider that is resulting in better outcomes. We have seen this at Wellpepper, while we haven’t broken our aggregate data down by gender lines, we have seen that within the same clinic, intervention, and patient population, we see significant differences in patient engagement and outcomes between patients being seen by different providers.

Some healthcare professionals are better than others at motivating patients, and the relationship between provider and patient is key for adherence to care plans which improve outcomes. By tracking patient outcomes and adherence by provider, using patient-generated data, we are able to see insights that go beyond what a retroactive study from EMR data can show.

While our treatment plans, and continued analysis of patient outcomes against those treatment plans go much further than simply amplifying the patient-provider relationship, for example with adaptive reminders, manageable and actionable building blocks, and instant feedback, never underestimate the power of the human connection in healthcare.

Posted in: Adherence, Behavior Change, big data, Clinical Research, patient-generated data

Leave a Comment (0) →

In Defense of Patient-Generated Data

There’s a lot of activity going on with large technology companies and others trying to get access to EMR data to mine it for insights. They’re using machine learning and artificial intelligence to crawl notes and diagnosis to try to find patterns that may predict disease. At the same time, equal amounts of energy are being spent figuring out how to get data from the myriad of medical and consumer devices into the EMR, considered the system of record.

There are a few flaws in this plan:

  • A significant amount of data in the EMR is copied and pasted. While it may be true that physicians and especially specialists see the same problems repeatedly, it’s also true that lack of specificity and even mistakes are introduced by this practice.
  • As well, the same ICD-10 codes are reused. Doctors admit to reusing codes that they know will be reimbursed. While they are not mis-diagnosing patients, this is another area where there is a lack of specificity. Search for “frequently used ICD-10 codes”, you’ll find a myriad of cheat sheets listing the most common codes for primary care and specialties.
  • Historically clinical research, on which recommendations and standard ranges are created, has been lacking in ethnic and sometimes gender diversity, which means that a patient whose tests are within standard range may have a different experience because that patient is different than the archetype on which the standard is based.
  • Data without context is meaningless, which is physicians initially balked about having device data in the EMR. Understanding how much a healthy person is active is interesting but you don’t need FitBit data for that, there are other indicators like BMI and resting heart rate. Understanding how much someone recovering from knee surgery is interesting, but only if you understand other things about that person’s situation and care.

There’s a pretty simple and often overlooked solution to this problem: get data and information directly from the patient. This data, of a patient’s own experience, will often answer the questions of why a patient is or isn’t getting better. It’s one thing to look at data points and see whether a patient is in or out of accepted ranges. It’s another to consider how the patient feels and what he or she is doing that may improve or exacerbate a condition. In ignoring the patient experience, decisions are being made with only some of the data. In Kleiner-Perkin’s State of the Internet Report, Mary Meeker estimates that the EMR collects a mere 26 data points per year on each patient. That’s not enough to make decisions about a single patient, let alone expect that AI will auto-magically find insights.

We’ve seen the value of patient engagement in our own research and data collected, for example in identifying side effects that are predictors of post-surgical readmission. If you’re interested, in these insights, we publish them through our newsletter.  In interviewing patients and providers, we’ve heard so many examples where physicians were puzzled between the patient’s experience in-clinic or in-patient versus at home. One pulmonary specialist we met told us he had a COPD patient who was not responding to medication. The obvious solution was to change the medication. The not-so-obvious solution was to ask the patient to demonstrate how he was using his inhaler. He was spraying it in the air and walking through the mist, which was how a discharge nurse had shown him how to use the inhaler.

By providing patients with useable and personalized instructions and then tracking the patient experience in following instructions and managing their health, you can close the loop. Combining this information with device data and physician observations and diagnosis, will provide the insight that we can use to scale and personalize care.

Posted in: Adherence, big data, Clinical Research, Healthcare Disruption, Healthcare Research, Healthcare Technology, Healthcare transformation, Interoperability, M-health, patient engagement, patient-generated data

Leave a Comment (0) →

HIMSS 2017 Recap: What’s Hot and What’s Hype

Wellpepper had a great HIMSS 2017 Conference with a very busy booth in the Innovation Zone, a panel on the current state of innovation, and a talk on Delivering Empathy Through Telehealth. Here are a few of our thoughts on the conference compiled from our team.Empathetic Care Through Telehealth

Cognitive and AI: Hype

Starting with Ginni Romety’s keynote, Cognitive and AI were definitely the buzzwords of the conference. Everyone is excited about the promise but it seems like the current status is not ready for takeoff. First, there’s a lot of work to get data out of the EMR, and second, no one seems quite sure what the killer use case is going to be. Immediately before HIMSS, MD Anderson announced that after a $62M investment they weren’t seeing value in IBM Watson and were pulling out of the program. That did not stop them from co-presenting with Mayo Clinic and Watson at the conference. The main use case seemed to be shortening the time to identify cancer patients for clinical trials from 30 minutes to 8 minutes. Another example, which just highlights the sorry state of clincial technology, was to use Watson on top of Epic to help staff figure out how to use features. During the session, Mayo CIO Christopher Ross referred to Watson as a toddler. While all of this was disappointing, it’s heartening that for once healthcare is on trend with the rest of the tech world, and possibly pointing to an accelerated evolution of health IT.

IMG_0611Patient Engagement: Hot

In 2016, patient engagement was also hot, but this year, we’d also say it was real. Buyers visited our booth with checklists of capabilities they wanted to see. Pilots were completed last year, and now they are making platform decisions for patient engagement. We’ve noticed this ourselves in the past 6 months, we’ve seen the patient engagement purchase decision elevated to the C-suite, and the decision being made based on capabilities that will address the needs of all patients and all service lines.

Interoperability: Hot

Compared to the previous year, we saw a lot more talk about interoperability, whether that was EMRs building out APIs and developer programs, the CommonWell Alliance, or talk about how block-chain could be used to both secure and transfer healthcare data. Understanding that data needs to flow with the patient, and also that a heck of a lot of data is being created outside the EMR (in patient engagement solutions for example), is driving a greater commitment to interoperability in the industry.

Healthcare Investment: Hot

The Sharks said so, so it must be hot. The HIMSS Venture+ Investment forum this year had a much more diverse set of pitches than previously, including a social venture. and was won by DiaCardio, a woman-led company from Israel automating evaluation of heart ultrasound.

The Affordable Care Act: Prognosis Unclear

Make no mistake, the potential repeal of the ACA is looming heavy even in health IT. Health systems Boehner, HIMSSare concerned about impact on Medicare and Medicaid revenue. While bundles and value-based care have been quite positively received, the current uncertainty is putting a hold on capital expenditures. (Did we mention that Saas can be accounted for as operating expense?) Possibly the most entertaining speculation on the ACA came from former house speaker John Boehner and former governor Ed Rendell. Rendell suggested that we repeal Obamacare and replace it with the Affordable Care Act. Boehner mused that repealing without a plan would place all the blame and problems with the current system firmly on the sitting government, and recommended that it not be repealed.

The Takeway?

We’re still optimistic. IT is increasingly having a seat at the table within healthcare. Although not all EMR implementations have been seen as a success for clinicians, we are seeing a shift to an expectation of better software for both patients and providers, for data to move smoothly, and the promise of insights and better care when that data can be analyzed and acted on. We’re already looking forward to HIMSS 2018 Las Vegas.

Posted in: big data, Clinical Research, Interoperability, patient engagement

Leave a Comment (0) →

HIMSS17 Sessions of Interest

We are thrilled to attend a number of sessions at HIMSS17 with topics pertaining to Wellpepper’s Vision and Goals!

Patient Engagement

Sessions that impact our ability to deliver an engaging patient experience that helps people manage their care to improve outcomes and lower cost:

Insight from Data

Sessions that impact our ability to derive insight from data to improve outcomes and lower cost:

Clinical Experience

Sessions that impact our ability to deliver more efficient experience for existing workflows and are non-disruptive for new workflows:

 

Posted in: big data, Healthcare Technology, Interoperability, M-health, patient engagement

Leave a Comment (0) →

Our Picks for HIMSS17

himss17-exhibitor-ad-design-300x250-copyHIMSS17 is right around the corner and we at Wellpepper have a lot to be excited about! By empowering and engaging patients, deriving insight from the data we collect, and delivering new value to clinical users without major disruption to existing clinical workflows, we can continue to improve outcomes and lower costs of care. At HIMSS17, we look forward to connecting with friends, partners, colleagues and industry leaders to continue the journey towards an amazing patient experience.

Sessions that we look forward to:

Our CEO and co-founder, Anne Weiler, will be speaking at 2 sessions:

  • Anne will be a featured speaker at the Venture+ Forum, where former competition winners will be sharing how their business has grown, lessons learned and plans for the future. Since being named a winner of the 2015 Venture+ Forum Pitch competition, Wellpepper has continued to bridge the gap between the patient and care team and we are excited to share our progress and vision.
  • Anne will also be presenting a session titled, Designing Empathetic Care Through Telehealth for Seniors, which will explore the role of design-thinking in design empathetic applications to deliver remote care for seniors based on studies completed by Boston University and researchers from Harvard Medical School.

Patient engagement expert Jan Oldenburg, who was featured in our August 2016 webinar, will be speaking at 2 sessions:

  • Jan will be presenting a session titled, The “P” is for Participation, Partnering and Empowerment. This session will highlight what it takes to create a truly participatory healthcare system that incorporates patients and caregivers, using digital health technology to reinforce and support participatory frameworks.
  • Jan will also be presenting a session titled, Importance of Narrative: Open Notes, Patient Stories, Human Connections. This session will focus on how Open Notes enhance the patient’s narrative of their journey through their condition and how this both strengthens the patient-physician relationship and empowers patients to take charge of their illness and wellness.

Christopher Ross, Chief Information Officer at Mayo Clinic will be leading a session on Emerging Impacts of Artificial Intelligence on Healthcare IT. This session will discuss how the advancement of Artificial Intelligence (AI) and Machine Learning (ML) are having a profound impact on how insights are generated from healthcare data.

Posted in: big data, M-health, patient engagement

Leave a Comment (0) →

Population Health and Patient Engagement: A Reckoning Is Coming

Population health and patient engagement should be best friends. To draw conclusions for population health, you need a lot of data, and patient engagement that is, patients interacting digitally with treatment plans and healthcare providers, generates a ton of data. Population health tries to analyze the general to get to the specific and identify patients at risk. Patient engagement starts with the specific patient, and with enough data recorded by those patients, can find general trends.

With patient engagement, the information is real-time. With population health it is backwards-looking. Population health has the richness of the medical teams notes and diagnosis but it is missing the patient perspective. Patient-generated data will have diagnosis if it’s part of a treatment plan prescribed by a physician, but it won’t have the full notes. A blurring of the boundaries between population health and patient engagement presents a way forward to greater insights about both individuals and groups, and can make population health actionable at the individual patient level by providing personalized instructions (with or without care managers).

However, to get to this desired end-state, we need to clear some obstacles, first of which is the idea that patient engagement generates too much data for physicians.

Yes, an individual physician does not want to see or review each data point that a true patient engagement solution generates. However, this information can be extremely interesting to the patient, especially when looking for trends to help self-manage a chronic condition so it is worth enabling patients to collect it. For example, looking at whether certain foods trigger arthritis, or whether certain activities trigger headaches. However, to draw conclusions like this, you must record a lot of data points and in real-time, and this makes physicians nervous. They have enough to do, and not enough time to do it in, so this data cannot add to that workload.

As well, patient-generated data is messy, which can be intimidating, especially in an industry that is looking for deviations from norms. The challenge with patient-generated data is that it can uncover that the long-tail is actually longer than previously thought, that there are sub-groups within previously thought to be homogeneous groups of patients with a similar condition. In the long run, this will result in medical breakthroughs and personalized medicine. In the short run this can be difficult to deal with in the current systems.

the long-tail is actually longer than previously thought

Does that mean that we shouldn’t collect patient-generated data? Not at all. Helping patients track their experiences is a great first step to self-management. Knowing whether they are following a treatment plan, and what their experiences are with that treatment plan can help healthcare systems determine the impact of their instructions outside the clinic.

Although physicians don’t want all this data, healthcare organizations both providers and payers, should want it. Other industries would kill for this type of data. Data scientists and population health managers at health systems should be clamoring for this valuable patient-generated data.

Patient-generated data is usually collected in real-time so it may be more representative of the actual current population. The benefit of real-time collection is that further exploration of the actual patient experience is possible and can be used to prevent issues from escalating. With backwards looking data whatever was going to happen has happened, so you can only use it to impact new groups of patients not current groups.Patient-Generated Data

Finally, patient-generated data is less likely to be siloed, like clinical data often is, because the patient experience is broad and often messy and crosses clinical department thresholds (or more simply, patients are usually treated for more than one issue at a time.) Being relatively new to market, patient-engagement systems are built on modern and interoperable technology which also makes accessing data for analysis easier.

So where will we end up? To our team at Wellpepper, it seems inevitable that influencing and understanding patient experience outside the clinic. If you are making decisions for an individual patient with only a few clinical touch points, this is a very thin slice, often with a specific clinician’s specialty lenses on the actual situation. While healthcare systems are currently dipping their toes in the water on collecting and analyzing this data, if they don’t embrace the whole patient, patients will vote with their feet and pocket books towards organizations that are data and technology driven.

Posted in: Adherence, big data, Healthcare Technology, Healthcare transformation, Interoperability, M-health, patient engagement, population health

Leave a Comment (0) →
Google+