Super interesting! Couple of thoughts:
1) What type of alerts do you think Ginger.io could design to send to the patient that would actually encourage behavior modification? If it were me, being told by an app “You’ve been spending a lot of time on your phone lately!” might contribute to any feelings of social exclusion, isolation, and/or depression instead of engendering behavior change in a positive and healthy way.
2) Similarly, what types of alerts would be sent to the providers that would enable them to leverage the information in a meaningful way? If a provider gets an alert that a patient has not been sleeping for 4 days straight, what liberties do they have to do anything about it? What would/could they do?
3) What are the payment incentives that will be tied into this system to encourage participation by providers? In the above example, what incentive does a provider have to take time out of his/her busy day to follow up with a patient who hasn’t been sleeping when there are no direct payment mechanisms tied to the action and no way to bill for his/her time? My feeling is that until more provider systems move to an ACO (accountable care organization) model where they are responsible for holistic patient outcomes and are held accountable for preventing adverse outcomes, there will be little incentive for providers to do anything with this information.
Great post! I actually worked for the MTA for a couple of years, and saw its plethora of issues firsthand. The organization loses millions of dollars every year and is in a continual deficit. Most of its efforts thus far have been focused on cleaning up internal operations, consolidating back-office functions, and dealing with its excess employee base that can’t be fired because of union issues. Any leveraging of data to save money was largely focused on optimizing train schedules (more trains during peak hours and more express trains to stops with high employment during peak hours) and analyzing workarounds or alternate options for re-routing trains during train construction and maintenance periods. These uses of big data are basic, and they can/should certainly improve their efforts to leverage data for internal and external purposes to save money and improve the customer experience. How about push notifications to your phone when there is a shut down or delay in your regular morning train route? And internally, how can they use data to prevent costly mistakes? In 2008, the MTA removed station attendants at 100+ subway stops in an attempt to save money by not paying salaries. They subsequently lost $30M in fares by people who “jumped the turnstiles” to get in without paying because there were no station attendants on duty. Such a fail. They could have easily used big data to predict, track, and measure the impact of their decisions on consumer behavior and created instruments for increased surveillance and security within subway stations.
Thanks for the post, Drew! Super interesting approach to using big data for healthcare, which is an industry that has certainly lagged behind the times in leveraging data and analytics in an effective manner. My questions on Carolinas Healthcare are the following: how they are actually going to use credit card information to help them predict consumer health issues, and what flexibility do they have to really do anything about high-risk consumer behavior?
Are they tracking primarily medical related spending? i.e. – over the counter medications at a CVS, urgent care clinic visits, out of pocket payments at a routine doctor’s visit, etc? These might help predict certain behaviors or issues but it is likely too late to actually do anything. This dataset would also be largely incomplete, as many of these purchases are not made by consumers but are later billed to insurance companies.
Are they tracking personal spending? i.e. fast-food purchases, sports equipment purchases, travel-related purchases, etc? While this information might certainly help predict patient health or accidents, the link will only be correlative and not causative. It is easy to say that a patient’s heart disease may have been exacerbated by eating McDonald’s every week, but it is not a causal link to say that every patient who eats at McDonald’s will acquire heart disease. Similarly, what can Carolinas Health do about patients with high-risk behavior other than encourage them to come in for preventive care visits or enroll them in population health management programs?
Would love to hear your thoughts and clarifications about what data they plan to collect and how they plan to use it!
ilny – I totally agree! I think the benefits far outweigh these potential challenges, and you’re completely right that there is never any treatment without the consultation and guidance of the patient’s physician. I also agree that the doctors’ resistance will go down over time and that it’s okay if not all the voices are “heard” right now. Thanks!
Thanks for your comment! A LOT of health professionals definitely are participating – I think the draw is the ability to return to why they wanted to practice medicine in the first place – to help people. It’s interesting, challenging, mysterious – like a case study but with actual human impact. I think it helps keep them sharp and on their toes and they seem to want to be part of this community that is on the cutting edge of differential diagnoses. Interestingly, a lot of medical residents are enrolled in CrowdMed, which is useful because they just went through training where they studied hundreds of rare diseases that most practicing physicians have long forgotten about because they never or almost never see them. It’s a very useful group of people!
Along those lines, CrowdMed invests in an Ambassador Program to recruit top medical school talent. CrowdMed Medical Detective Ambassadors represent CrowdMed on their respective campuses, help recruit fellow medical students, provide feedback to the company, and get exposure to Silicon Valley entrepreneurship and training. As the word spreads, it seems natural that more medical professionals will participate.
Great post! Super interesting to hear about a crowdsourcing effort gone wrong, as all the cases we have read on it make it seem as if it can do no wrong. It would be helpful for companies to think through implementation guidelines or policies for crowdsourcing as part of their digital marketing or innovation teams prior to launching these types of initiatives!
It’s interesting to note the backlash for this event was so different from the views of the programmers working for TopCoder, for instance. I believe TopCoder retained most of the IP and work done by their programmers to maintain a virtual playbook of all coding solutions, which they then used to attract clients, promising shorter delivery times by building on an already existing repository of coding work. I wonder what the difference is between TopCoder and the loyal fan base of Moleskine. Perhaps it is the greater focus on art and creativity and originality? Would love to hear your thoughts!
I’m also curious to get your opinion on whether or not this entire fiasco could have been avoided if Moleskine had just claimed that all IP would be returned to the designers, or if there were other elements that made this competition undesirable and rage-inducing to the fans.
Interesting post, thanks for sharing! Do you have any insights on how successful the product is now compared to other Kraft products? It would be interesting to see if there is a similarity between the launch success of this product and the super successful product launch of Nivea’s crowd-sourced deodorant.
I also question that Kraft purposely botched the name to gain awareness and consumer engagement. It seems as if crowdsourcing was a way to fix a bad situation. If they had really wanted to drive consumer awareness prior to the product launch, it would have seemed more plausible that they engaged the crowd beforehand or maybe offered a contest to determine the best Kraft name (similar to Threadless last year), or something along those lines. It could have easily turned out another way and been a super costly mistake from a PR perspective. Either way, they got lucky bringing it back around!
Great post! I think your point about HourlyNerd not being able to scale and disrupt as rapidly as Uber is right on. One of the contributing factors is the fact that while Uber is a simple, transactional service that anyone can provide (get consumer from point A to point B), labor is a much more complicated need and it’s very hard to trust that someone you find through clicking online will be able to satsify these complex and high-level requirements.
I also find it particularly interesting how many of the projects now available on HourlyNerd are for large companies (i.e. GE, Microsoft, as you mentioned) instead of small or medium sized enterprises that HourlyNerd initially wanted to target. This “upscaling” of the demand market may very well serve to oust these SMEs who still don’t have the financing to access expensive consultants. I worry that their initial goal of providing access to quality labor for SMEs is being hampered.
Great discussion! Two thoughts:
1) Groupon also captured some value through network effects by offering additional discounts if a user purchased the same item through your referral link, which incentivizes users to share their purchases with friends or purchase in bulk together. Additionally, Groupon created some network effect value when a user “grouped” 3 or 4 friends together and bought the same item, as they then were given the value of one of the purchases for free. Arguably, the merchants may not be capturing as much of this value, but I think Groupon does have some network effects through their deal structure.
2) Agree with Drew that it doesn’s bode well for your business if you’re offering a Groupon – consumers now take that to mean your business is struggling and may not be around for very long, so they may not consider coming back for repeat business. This reduces any possible value from network effects the merchant can capture. Also, merchant exploitation seems to be pretty widespread, so Groupon isn’t making a terribly popular name for itself. They’ll have to figure that out to continue to operate successfully in the future.
Great post, really interesting! I wonder if there are creative ways Care.com can employ to keep replenishing its user base. For instance, to get a large supply of caregivers, perhaps it can advertise at local businesses or schools where graduate students are studying and may need supplemental income, or it can target advertising to graduates of early childhood development programs. In order to continue to generate a large number of paying users, perhaps it can target advertising at preschools, day-care facilities, or even tap into the small business network of home day-care centers or play centers.
I also wonder if their model of charging users will continue to work or if they will be upset by a new, free service, or perhaps a service that only charges a referral fee if you try out the nanny/babysitter and successfully decide to move forward (instead of the subscription model). This might be a more palatable way to charge the consumer. Additionally, in order to continue to achieve success, Care.com might want to look into more ways to transfer some of the operational burden of reviewing, rating, and background checking the caregivers from themselves onto the caregivers (i.e. making caregivers provide necessary documentation, etc instead of doing it all themselves). I’m also curious to know what happens if a nanny/babysitter provides false information and the care seeker is unsatisfied – does Care.com play any role at that point?
Really interesting post!
I agree that Teladoc and telemedicine companies in general need to do something to differentiate themselves and not fall prey to multi-homing and interchangeability amongst users. One possibility is investing in developing stronger relationships with ancillary service providers such as Visiting Nurse Associations (VNAs) and Skilled Nursing Facilities (SNFs). If Teladoc is able to leverage a regional approach and work with the types of facilities that patients are often discharged to (such as SNFs, or when patients are discharged home with visiting nurse care), they can differentiate themselves and create more incentives for hospitals to focus on them as their primary telemedicine provider. For instance, leveraging a partnership with the dominant VNAs in a certain area can ensure that the VNAs help patients get set up with telemonitoring and teach them how to use remote monitoring, interact with doctors, and so on, which would greatly lessen the burden and cost on the hospital for setting up these services. Many patients (especially older ones that are less tech savvy) need more constant monitoring and could really benefit from telemedicine, but are wary of using technology on their own. Partnering with VNAs can make setting up and monitoring telemedicine services part of their routine visits to patients homes, which would certainly increase hospitals’ incentives to just focus on Teladoc.
Super interesting post. I think you’re right that PatientsLikeMe need to be careful with their use of patient data and definitely keep an eye on the past, but even if one of those (very plausible!) scenarios you mentioned occurs, I don’t think patients would feel they have lost value by participating on the site. In my opinion, patients go on the website to share a burden they can’t share with others close to them and genuinely connect with people going through the same thing. That is the value to them. A side benefit is the possible for improvements in medicines, diagnostics, and devices from their shared data, but a lot of these patients know that these improvements likely may not come in their lifetime, and I think they are okay with that.
PatientsLikeMe is also pretty upfront about how they use and share patients’ health data and encourage patients to support their endeavor to do so. The potential for personalized medicine is huge – companies can see what types of patients respond well to which types of treatment and can customize treatment plans, consciously select types of patients with higher probabilities of success for their clinical trials, and conduct a number of other good, semi-good, and questionable actions. That being said, PatientsLikeMe promises to de-identify, anonymize, and aggregate all patient data before selling it to companies. Recent allegations suggest that PatientsLikeMe are using tools to collect patient names and other information, which is obviously completely unethical and terrible. However, patients are still uploading data to the site and flocking to it, which suggests they derive a benefit from the website that goes beyond the potential for better treatment – genuine human connection and support.
I agree FitBit is a real winner in managing to revolutionize the personal fitness and healthcare tracking industry. I also think you have a great idea on how FitBit’s vast amount of user data could be harnessed to understand themes in user health and fitness for use by doctors. It would be a great way to hold people accountable if their primary care physician (PCP) could see their actual daily exercise outputs! Perhaps an optional link to your EHR record where you could “select” which activities or vital signs you would want to have uploaded into your EHR, and your PCP could refer back to this data if you come in for a regular checkup or you come in complaining of sleeping issues. I think that would be a great extension of FitBit’s data, and it would be totally optional and user driven.
On the personalized medicine front, I’m not sure a FitBit is sophisticated enough to track biological responses or adverse events related to pharmaceutical products, or that you would be able to prove causation between something like an increased heart rate and an adverse reaction to a new drug. However, perhaps users could opt in to sharing a profile with pharmaceutical companies regarding their basic health stats in order to help pharma companies design targeted drugs and identify target patients for clinical trials.
One final idea for an extension of FitBit’s services is to expand further into the nutrition space based on customized user information inputted into the device. FitBit can track all the food you eat as you enter it, so it could develop predictive models to identify recipes or dishes you might like based on your previous meals, and suggest healthy recipes, healthier versions, or new dishes to try. FitBit could develop partnerships with grocery stores or Instacart-type organizations to offer discounts on certain ingredients that you eat frequently.
Great post! I agree with your arguments and you did a great job of outlining the specifics of why Teladoc’s model hasn’t driven adoption for customers or employers. The one thing I think Teladoc does really well, however, is to use big data to create sophisticated predictive models to identify who super-users/high-utilizers of the healthcare system are, and offer triaged care accordingly. For instance, a very high utilizer patient who has a history of presenting to the ED for unjustified visits might be directed to a video consultation first, whereas patients with a history of chronically serious or life threatening diseases will be fast tracked into the hospital. The ability to gather this type of data is the type of benefits Teladoc has from being the largest telemedicine provider, and this is ultimately where providers and payers will care about these services. Much of the costs to our healthcare system are from overuse of urgent care or ED facilities, and the ability to reduce unnecessary visits or readmissions using customized predictive analytics is going to be crucial for the success of any telemedicine company.
Great post KMY! I fully agree with your assessment of the success factors of the telemedicine industry and why Doctor on Demand looks to be on top. I would add a few elements to your analysis that will help telemedicine companies both create and capture more of this value:
In order to be truly successful, telemedicine needs to develop stronger partnerships with hospitals, insurance companies, and ancillary service providers such as Visiting Nurse Associations (VNAs), Patient Centered Medical Homes, (PCMH), and Skilled Nursing Facilities (SNFs). Telemedicine has great potential value for reducing 30-day readmissions rates (something that hospitals are assessed on publicly and nationally) and can, for example, reduce readmissions for congestive heart failure (CHF) patients from 20% to 4% in some instances. By working with hospitals and demonstrating their cost effectiveness in a quantitative way, telemedicine companies can integrate themselves more deeply into the fabric of these hospitals and their discharge processes. By partnering more actively with state-run insurance exchanges and increasing payer coverage of telemedicine services by demonstrating their value, they can further expand their reach, particularly as more Americans obtain public health insurance. For example, MassHealth only recently started to cover some telemedicine services, and there is a long way to go. Reimbursement is the main reason many hospitals have not set up telemedicine programs. Finally, many patients are discharged with home health care (visiting nurses who provide care at a patient’s home) or to a skilled nursing facility, and telemedicine companies can increase their value capture by partnering with these organizations to offer set-up of telemonitoring devices (scales, blood pressure machine, oximeter, glucometer, etc) as well as encourage patients to input their vital signs daily and help them track their progress.
Many low-income patients are automatically excluded from being able to participate in telehealth programs given a lack of smartphones, internet access, language barriers, and secure housing in which to store telehealth equipment. Innovating to find alternate methods to include these patients in telemedicine programs can significantly expand the number of patients reached by telemedicine, as well as substantially improve population health outcomes for those marginalized citizens who need it most. Telemedicine companies should also think about taking their services globally – one of the most effective tools in the recent Ebola outbreak in West Africa could have been telemedicine, which would have helped physicians assess patients for Ebola symptoms without risking exposure of other patients and citizens to the virus as they traveled long distances to health centers or remained in waiting rooms in healthcare facilities.
Telemedicine capitalizes on the increasing digitization of our generation and globe. However, healthcare remains the industry that renders people the most vulnerable, afraid, and uncertain. Telemedicine companies must be careful not to digitize all the way and lose the human element of healthcare. Telehealth monitoring for cardiovascular and mental health patients has shown to be clinically most effective when a mix of technical remote monitoring and human contact is used (i.e. daily or weekly phone calls to remind patients to input information and discuss health status, visiting nurses discussing patient progress, creating ways for patients to talk to healthcare providers live when they need to, etc). These companies will need to find the right balance of digitization to generate true cost savings, improved health outcomes, and increased patient satisfaction.