Optimizing product/market fit through user research

Optimizing product/market fit through user research

Most digital health companies understand the importance of achieving product/market fit (i.e., the degree to which their products meet an actual demand from customers).

At least in theory.

In practice, a lot of digital health companies still struggle to develop visions for products that reflect actual user needs. Similarly, many digital health companies are struggling to translate technological innovations into products that people can and want to use.

One way to resolve these challenges is through user research – an effective, but underutilized practice that helps product developers understand their prospective users’ needs and gather actionable insights that optimize product designs. Using various methods, such as ethnographic observations, individual and group interviews, surveys, and usability tests, user researchers help ensure that products are designed in a user-centered manner that is likely to increase a product’s success.

How is user research different from market research?

At a glance, user research might seem similar or even equivalent to market research. Both utilize similar methods, such as surveys and interviews, to gather insights about prospective customers. But, the two disciplines apply these methods differently and have different goals for the types of insights they seek to collect.

At a high level, market research involves the investigation of consumer behaviors, opinions, and trends with the goal of identifying insights that will help direct business strategy. By contrast, user research involves the study of users’ hands-on interactions with products, as well as their needs and expectations for future products, with the goal of identifying insights that will help direct product design and development activities.

Market and user research and not substitutes for one another. Rather, they are complementary activities that can build on each other’s strengths.

The right method at the right time

User research can reveal valuable insights at all stages of product development, from early discovery and conceptualization phases through final development and validation. In each phase, different research methods might be more or less suitable.

In the early discovery phases, observation-based research can be especially valuable. I’m still surprised to discover companies that are developing digital health or medtech without ever having visited the clinical environment in which they expect their product to be used. Observation-based research in prospective use-environments can reveal the current challenges that your prospective users are facing and can often be a great source of inspiration for thinking of innovative solutions that actually help users.

Interviewing users, either one-on-one or in a focus group, is another activity that can be particularly helpful during early product development. In particular, interviews are an effective means for developing a deep understanding of users’ opinions about their experiences with relevant products and their expectations for future products.

In comparison to observations and interviews, surveys can provide an efficient means to collect answers from a large number of respondents. Although surveys are less effective at providing rich qualitative information, they can provide reliable answers to specific questions that are likely to arise in later stages of product development.

Other user research methods are especially effective at evaluating evolving product designs. Activities such as expert reviews and usability tests, in which representative users perform actual tasks with prototype or final versions of a product, reveal specific opportunities for improving a product’s design so as to optimize its usability, usefulness, and appeal.

Getting a helping hand

It’s always better to conduct some user research than none at all. That said, there can be downsides to conducting user research without assistance or guidance from experienced user research professionals such as human factors engineers, usability specialists, or user experience (UX) researchers. Without support from trained researchers, product developers might utilize research methods that are not well suited to their research goals or utilize flawed research protocols that result in the collection of misleading information.

Getting started

The good news for digital health companies eager to dive into user research is that it’s never been easier. Industry enthusiasm for the potential of digital health means that many clinicians are eager to contribute to user research, while the rise of remote communication and research tools enables efficient and simple execution of many research activities.

With its large pool of clinical, product, and user research experts, as well as with its new research tools, MDisrupt has seen first hand how digital health companies improve their product/market fit through user research.

Jonathan Kendler

Jonathan Kendler

For over 20 years, Jonathan has been helping medical device and healthcare technology companies make their products safe and easy to use by applying human factors engineering and user-centered design to their product development efforts. He has consulted for a wide range of companies, including both startups and large companies, helping to ensure that their products meet users’ needs, comply with best design practices, and conform to international regulations and standards for usability engineering.

At MDisrupt we believe that the most impactful health products should make it market quickly. We do this by uniting digital health companies with experts from the healthcare industry to help them accelerate their time to market responsibly.

Our expert consultants span the healthcare continuum and can assist with all stages of health product development: This includes regulatory, clinical studies and evidence generation, payor strategies, commercialization, and channel strategies. If you are building a health product, talk to us.

Breast Cancer Awareness Month: How digital health is improving breast cancer screening and care

Breast Cancer Awareness Month: How digital health is improving breast cancer screening and care

October is Breast Cancer Awareness month. According to the CDC, in the United States, about 264,000 cases of breast cancer are diagnosed in women and about 2,400 in men, making it the second highest cause of cancer among women in the United States. In 2020, 2.3 million people were diagnosed with breast cancer around the world. However, when diagnosed early, the cancer has a 90% 5 year survival rate. Over the last decade, women’s health has seen a burst in innovation and funding, with a market size of around $51 billion USD. FemTech (digital health for female health needs) is tackling breast health, among other clinical areas, and I am seeing promising new breast cancer screening, diagnosis, and patient experience companies hit the market.

Tech Advances Screening and Diagnosis

The CDC recommends that women with an average risk profile start breast cancer screenings at the age of 40. But how does a person know if they have an average risk profile? Enter: CancerIQ. Their software provides customized screening recommendations based upon each individual’s genetics, family history, lifestyle, and comorbidities. I’m excited about this product because it improves how healthcare resources are allocated and works towards patients getting the right screening at the right time for them.

Fear of radiation and discomfort during mammograms are often cited as reasons why women delay breast cancer screenings. New ultrasound technology such as the iBreast Exam by UE Life Sciences (FDA 510K cleared) addresses both of those concerns. The handheld breast examination device syncs with a mobile phone and creates a digital image file from the exam that can be attached to a patient’s medical record. In addition to improving patient comfort, ultrasound tools like the iBreast Exam are beneficial for advancing health equity. Areas lacking hospitals with radiology services nearby can perform cancer screenings in a clinic and can send the scans to a radiologist for review. iSONO’s ATUSA wearable breast ultrasound scanner (FDA 510K cleared) also offers an alternative to mammography and creates 2D and 3D images of the breast tissue. The company is currently researching the use of AI to identify abnormal lesions via their software. While I think we will continue to need trained radiologists to review scans, AI could provide a second pair of (virtual) eyes to improve diagnosis.

Digital Patient Experience Tools Address Symptoms and Provide Support

While breast cancer can have a high survival rate, treatment and recovery are still harrowing experiences. Mobile apps and connected devices are making the journey easier for patients. The Belong Beating Cancer Together App has a 4.9/5 star rating on the Apple App Store with over 2,000 reviews. Patients love being able to find research studies, chat with oncologists and peers, and manage their care journey all in one place– from medications to appointment tracking. The overarching theme from the review comments is that Belong Beating Cancer Together provides them hope and community.

Breast cancer survivors continue to have side effects from treatment while in remission and a few wearables have come out to address them. Brilliantly was created to tackle the symptom of constant coldness that patients reported after having reconstructive breast surgery. The wearable slips into any bra for safe, flexible, natural-feeling warmth and the temperature is controlled by a phone app for discrete and easy adjustment throughout the day. Medications can also force women into menopause, and the Embr Wave 2 bracelet works as a “personal thermostat” to curb hot flashes. There is promising evidence that the Embr Wave 2 reduces hot flashes interfering with sleep.

We are just scratching the surface of how we can improve breast cancer screening, diagnosis, and treatment with digital health, and I am confident that with continued funding and research we will see more exciting innovations in the near future.

Katie D. McMillan

Katie D. McMillan, MPH is the CEO of Well Made Health, LLC

Katie D. McMillan, MPH is the CEO of Well Made Health, LLC and is actively researching FemTech and digital health evidence. She is currently collaborating with MDisrupt to identify clinically validated digital health products for women’s health.

At MDisrupt we believe that the most impactful health products should make it market quickly. We do this by uniting digital health companies with experts from the healthcare industry to help them accelerate their time to market responsibly.

Our expert consultants span the healthcare continuum and can assist with all stages of health product development: This includes regulatory, clinical studies and evidence generation, payor strategies, commercialization, and channel strategies. If you are building a health product, talk to us.

7 P’s to evaluate healthcare companies: A framework for physicians

7 P’s to evaluate healthcare companies: A framework for physicians

Physicians are increasingly interested in medical innovation for several reasons:

  • We have an innate intellectual curiosity. 
  • We desire to offer the best care for our patients.
  • Many of us have experienced burnout from COVID and administrative frustrations. 
  • Many of us are looking for opportunities for additional income.
  • Some of us are interested in career transition.

Whether your entrepreneurial background includes an InnovatorMD Conference, a Society of Physician Entrepreneurs event, a StartUp Health Festival, or an AngelMD Pitch Club, I wrote this article to describe a healthcare framework physicians can use to evaluate healthcare companies and to encourage investment and involvement in the innovation process.

Use the 7 P’s below to identify a company’s strengths and areas of improvement, describe opportunities for improvement, and influence future company goals. This framework informs investment decisions. It can also be paired with your unique professional background to offer relevant insights as a company advisor or chief medical officer (CMO).

Product

The first step is to evaluate the proposed solution and how well it addresses a medical practice pain point. The company may be in the idea phase, may have a minimum viable product (MVP), or have a functioning prototype.

Ask:

  • Is their solution better and cheaper than the available alternatives?
  • How big of a pain point are they addressing?
  • How big is their potential market?
  • Was the solution built by experts in their space?

Process for product clearance

While not every health innovation requires FDA clearance, understanding how a product you’re evaluating is regulated is important for assuring patient safety and mitigating potential risk. Understanding the approval process also helps you budget for future regulatory needs.

Ask:

  • Does the product have 510(k) clearance for a medical device, early-stage FDA clinical trials for a pharmaceutical, or Software as Medical Device (SaMD) approval for an artificial intelligence algorithm?
  • In addition to US clearance, have the company applied for a CE mark to sell their product in Europe?
  • Has the company looked at product approval for other international markets?

 

fda-review

(Intellectual) Property

Patents can be obtained for medical devices, pharmaceutical compounds, and digital health assets. These provide protection from knockoff products and also provide companies with a valuable asset that is the core of many healthcare acquisitions.

Ask:

  • Does the company have utility and design patents?
  • Do they own a company trademark?
  • In addition to US intellectual property protection, do they have intellectual property protection in other countries?

Pilots

Healthcare startups achieve traction by obtaining early customers. The first product users from physician offices and hospitals provide feedback that can be used to improve the solution before scaling the company. When evaluating a company, ask about current pilot programs and how they are going.

Ask:

  • Are there currently pilots in place with individual physicians or healthcare institutions?
  • How has the product been received?
  • Has this process led to product changes and iterations?
  • Have the newer versions been evaluated in pilots also?

Payment

This ‘P’ recognizes the cost of the product and how a company is reimbursed. This includes the company cost to product the product. You’ll also want to know how much the company charge patients, offices or hospitals to use their product and whether that is covered by billing codes.

Ask:

  • What is the company’s cost per unit?
  • How will physicians generate revenue by using the product?
  • If it is a digital health tool, are physicians able to use one of the new American Medical Association billing codes listed below for reimbursement?
  • As this is a newer process, does the company offer assistance in training their billing team?

 

remote-patient-monitoring

Publications

Particularly for diagnostics, medical devices, and drugs, track the efficacy of treatment. Sometimes this is internal information, but companies will publish studies related to their product’s performance. Even if they don’t have peer-reviewed journal publication, they will have materials you can review and assess.

Ask

  • Is their idea evidence-based and does it work?
  • Have they compared it to the current gold standard and published their results in peer reviewed publications?
  • Have they entered their product into evidence-based events such as NODE.heatlh’s ‘Evidence Matters’ pitch event, or the like?
  • Have they published research on patient safety or product efficacy?

Physician and patient feedback

This ‘P’ is affiliated with Pilots. How is the product perceived by patients and physicians? It’s important to evaluate what kind of feedback was sought from patients and physicians as the product was developed.

Ask

  • Was a patient involved in product design and how do they like using the product?
  • How has this been evaluated?
  • Were the physicians involved in pilot studies happy with the product?
  • Did the product/service solve problems and make life easier for the patient/physician?
  • More importantly, does the company have a physician co-founder or advisor?

As a physician, you are a healthcare expert. You are acutely aware of your practice pain points, whether a product could be incorporated into your workflow, and their current market competition. You are able to offer valuable insight into the viability of an idea, potential use cases, and how to bring it to market. Based on your specialty and professional background, MDisrupt can connect you with healthcare companies who value your input. They provide opportunities to work either as a paid advisor or in a CMO (chief medical officer) role.

    John R. Dayton, MD

    John R. Dayton, MD, FACEP, FAAEM

    John Dayton, MD is an Emergency Physician and the first Medical Innovation Fellow with Stanford’s Department of Emergency Medicine. He is a physician consultant for Zus Health, a Venture Partner for SpringTide, and he writes about healthcare innovation for several publications, including Emergency Physicians Monthly. He also founded MedForums, a ‘yelp’ for physician feedback, that focuses on social proof and research related to education resources and healthcare innovations. You can reach out to him via LinkedIn.

    At MDisrupt we believe that the most impactful health products should make it market quickly. We do this by uniting digital health companies with experts from the healthcare industry to help them accelerate their time to market responsibly.

    Our expert consultants span the healthcare continuum and can assist with all stages of health product development: This includes regulatory, clinical studies and evidence generation, payor strategies, commercialization, and channel strategies. If you are building a health product, talk to us.

    AI In Healthcare: 5 Considerations for Decision-Makers

    AI In Healthcare: 5 Considerations for Decision-Makers

    Artificial intelligence, or AI, is gaining importance in healthcare settings. However, it’s a technology surrounded by misunderstandings and confusion. AI is not a panacea or a quick fix; it’s a tool – and just one of many that providers and organizations can use to facilitate better patient care and operations.

    When I’m talking with executives about the potential of AI for their organizations, the analogy I often use is that of a child. Like children, AI technologies are continually gathering data about the world around them and making intuitive leaps based on what they learn. That data may be structured like the things children learn in school, or unstructured like when children grow to grasp the concept of object permanence.

    While it’s not perfect, this analogy often helps healthcare executives to understand what they need to think about when choosing and deploying AI solutions in their organization.

    Change Management

    When a family welcomes a new child, it requires a lot of planning. Homes need to be childproofed, routines changed, spaces adapted, expectations communicated. Similarly, adding an AI technology to a healthcare organization requires careful planning and communication.

    Healthcare organizations are one of the most complex enterprises on earth when it comes to workflows and processes. A snag in a process here or a misstep there can have fatal consequences. An AI solution has a large potential to improve things in healthcare organizations, but also to upend carefully balanced processes and procedures – and not just early on, but as it grows and adapts.

    Like AI tech, children become more complex as they learn and grow. School runs, football practice timing, weekend language classes, play dates, all these can easily throw a spanner in the rhythm of parent’s lives.

    As AI tech ingests more data and “learns” from the information its given, it holds the potential to challenge the everyday decisions being made by team members. From identifying an image as cancerous, to predicting bed capacity in the ICU, to processing doctor’s notes and extracting medical ontological information from them, AI can easily start “stepping” on people’s toes.

    Healthcare leaders must prepare for change management as their teams start implementing AI solutions. Make sure all stakeholders impacted by the decisions made by the AI solution are involved right from the start and that a clear-cut communication plan is in place as the deployment goes on.

    Ethical considerations of AI in healthcare

    Like children, AI technologies are a product of the data inputs they collect. And, like children, AI solutions extrapolate what will happen based on what has happened. Children learn what works by applying something that gained a desired result in one situation to a different situation and discovering that it doesn’t apply. In healthcare, this type of trial and error is not acceptable.

    AI models developed for a given geography, for example, are unlikely to fit another one. In the same way, models developed based on data from patients from a particular background will likely start giving wrong predictions when applied to a different set of patients. This is where the concept of Responsible AI must be incorporated by the leadership in the culture of their organizations.

    The methodologies being worked out by the Responsible AI institute, by Google, and by Microsoft are just a few examples of how organizations and vendors are trying their best to ensure that fairness, interpretability, and privacy becomes a core part of any AI solution.

    Specifically for the healthcare industry, a great resource for executives to help understand Responsible AI is provided by Actium Health.

    ROI takes time

    Children are an 18-year time investment. While seeing the fruits of your labor as your kids settle down in their lives isn’t truly analogous to achieving return on investment (ROI), the understanding that long-term outcomes outweigh short-term rewards is.

    You won’t have to wait 18 years to realize return on your AI investment, but the timeline for any AI tool is never shorter than 2 years (longer for more complex projects). What this means is that you have to have a long-term strategy in place rather than look for quick-fire return value from your AI investments.

    Read more about ROI on Artificial Intelligence initiatives from Accenture and Deloitte.

    Monitor constantly

    Back in the day, you would buy software on a CD, put the CD in a disk drive, click setup and wait for the program to install. These days, the same thing is done via online downloads. What is important to understand, is that once you install the software you can start using it right away and it more or less behaves in the same manner throughout the time you use it.

    Not for AI technology, though. It is rarely a separate piece of software with its own icon on the desktop. Rather, it is a complex set of algorithms that sit quietly in a “corner” and learn through the data it reads. This means that the if the nature of data changes, the output of the AI will also change. In other words, any AI solution constantly requires monitoring.

    Just as you would monitor what media a child is consuming or the types of food they’re eating to support their mental, emotional, and physical development, it’s critical to understand what data your AI is ingesting. Limited data sets will lead to inappropriate conclusions, as will bad data.

    In one recent case, an algorithm intended to minimize racial disparities began allocating care disproportionately away from individuals who self-identified as black. The algorithm was using data based on total accrued healthcare costs, which were similar across racial lines, despite the black population being substantially sicker. While researchers were able to catch this instance, it’s a clear call for health systems to devote the resources to continually monitor both the inputs and outputs of their AI solutions.

    Explainable AI

    AI solutions are enormously complex, ingesting and analyzing massive amounts of structured and unstructured data. The conclusions they produce from this can be surprising – sometimes by doing what they’re meant to exceedingly well, and sometimes by predicting outcomes that are inexplicable.

    Never does a day go by when I don’t have to ask my 7-year-old why he decided to do something completely out of line with the norm. Just the other day, he decided to rush into a toy shop in the mall, leaving his mother and brother frantically searching for him for an hour or so. AI technologies aren’t id-driven like 7-year-olds, but without the proper checks, their conclusions can seem just as capricious.

    When evaluating AI technologies for your healthcare organization, you must ensure that the AI solutions you’re deploying have the element of “Explainable AI” embedded in them. It must be possible to not only spot outliers but trace them back to the data inputs. Without this there will be little or no trust in the outcomes of the predictions produced by the AI model.

    Risk vs. Reward

    While these considerations highlight risks in AI deployment, the potential benefits to patients, providers, and healthcare organizations remain enormous. AI is gaining in importance across a wide array of industries and use cases. It’s even more important in the healthcare industry due to the nature of critical services it provides.

    If you need expertise in developing or implementing an AI solution, there are tools such as the World Economic Forum’s Empowering AI Leadership: AI C-Suite Toolkit (available here) which provides an excellent blueprint for executive leadership.

    Kamran Ali

    Kamran Ali, AI and Analytics Leader – EMEA at GE Healthcare

    Kamran Ali is a guest writer with MDisrupt. With over 15 years of experience in deploying Enterprise level IT solutions, he is currently leading the Commercial Analytics Team for GE Healthcare’s EMEA Region. Certified in both Project Management and Azure AI technologies, Kamran’s passion is to make stakeholders and key opinion leaders understand the nuances of AI deployments, especially when it comes to the healthtech space.

    At MDisrupt we believe that the most impactful health products should make it market quickly. We do this by uniting digital health companies with experts from the healthcare industry to help them accelerate their time to market responsibly.

    Our expert consultants span the healthcare continuum and can assist with all stages of health product development: This includes regulatory, clinical studies and evidence generation, payor strategies, commercialization, and channel strategies. If you are building a health product, talk to us.

    Breaking Down Barriers to Care

    Breaking Down Barriers to Care

    Aaron Shapiro

    MDisrupt Expert Aaron Shapiro, MD, MPH, EDAC, is a primary care physician focused on improving health equity. In a world where many people lack access to appropriate care—whether because they live in underserved areas, face discrimination in accessing care, don’t have the right technological resources, or have been systematically excluded from clinical trials and genetic databases—he is working to bring down the barriers experienced by marginalized populations.

    Building multifaceted expertise

    MDisrupt: Tell us about yourself.

    Aaron Shapiro: I’m a primary care doc finishing up my residency in Primary Care Social Internal Medicine at Montefiore Medical Center in the Bronx, NY. I grew up in Maryland, went to medical school at Brown University, got my Master of Public Health focused in Healthcare Leadership and Management at Johns Hopkins, and got my Evidence Based Design Accreditation and Certification (EDAC) from the Center for Health Design. EDAC is a professional certification awarded to practitioners who have demonstrated competency in applying evidence-based design principles to healthcare contexts.

    I’m moving home to the DC area to settle in as a primary care doctor at an inspiring Federally Qualified Health Center in a high Health Professional Shortage Area, about half of which will be through their Health Care for the Homeless branch.

    Connecting clinicians with industry-changing innovators

    MDisrupt: What’s your perspective on the state of digital health today?

    Aaron Shapiro: I am constantly inspired by the advancements of health technology. But as a primary care doctor working in underserved areas, serving people historically marginalized by our government and capitalist-driven healthcare systems, I am regularly disenchanted that these innovations often don’t make it to the clinics I work in. There are many reasons for this, stemming from the disenfranchisement of communities of color through years of racist redlining policies and exclusively revenue-focused business models that do not identify low-income communities as sufficiently profit-generating.

    MDisrupt: How do you see health technology impact your everyday work?

    Aaron Shapiro: Health technology has become ubiquitous in healthcare. But my profession is slow to change. We still have vestiges of very old technology slowing us down. Our professional culture is far from one that embraces rapid adoption of new workflows. So even when a new technology is introduced, it’s often done in a very targeted, siloed way that mutes its potential for large-scale system wide progress.

    As someone fascinated by healthtech and healthcare innovation, I get very excited learning about the inspiring, innovative work so many are doing to improve healthcare delivery. But so much of this work is done in a traditionally proprietary fashion. So very little makes its way to my patients in under-resourced health systems.

    Bringing innovation where need is greatest

    MDisrupt: Tell us about some solutions you’re working on to make a difference.

    Aaron Shapiro: Nowadays I spend most of my time thinking about how we can adapt and implement high quality health service innovations for those who need them most.

    So I founded an initiative called Differential Design, which seeks to harness the power of healthcare technology, management, and design as tools to advance health equity and justice. There’s this enormous potential to help existing healthcare providers provide better care. But there are so many barriers to them having the resources, time, and experience to be able to identify the appropriate tools to improve the efficiency and quality of their service delivery—let alone implement them, let alone imagine doing that on a shoestring budget. But I think there’s so much potential in this space!

    For example, we recently launched clinici.wiki, a free crowdsourcing initiative to help primary care providers more efficiently practice patient-centered, evidence-based medicine, even in high-volume clinics with limited resources. And after implementing a huge Knowledge Management System project at the clinic I currently work in, we are now in the process of making that work accessible to everyone at no cost through The [Your Clinic] Wiki project, so that any and every clinic can adopt efficient health technology work-flow support regardless of budget, management capacity, or healthtech experience.

    MDisrupt: What got you interested in MDisrupt?

    Aaron Shapiro: I really appreciate MDisrupt’s focus on pragmatically getting tech and innovation-minded practitioners to join these potentially industry-changing teams with the hope to decrease harm and maximize impact.

    And I do see the ecosystem starting to change. I see more and more companies adopting the triple aim—defined as improving the experience of care, improving the health of populations, and reducing per capita healthcare costs—as central to their innovation work. And I think large healthcare systems, including government payers, are starting to listen.

    Toward a more inclusive future

    MDisrupt: What do you see as the future of the healthcare system?

    Aaron Shapiro: I see a future where health technology is used to ensure quality healthcare services for everyone, regardless of income, education level, or historical disenfranchisement by our government and capitalist healthcare-industrial complex. I see a future where health technology allows us to return healthcare to experiences of healing, safety, and comfort.

    Find Aaron on twitter: https://twitter.com/aaronmshapiro

    At MDisrupt, we believe that the most impactful health products should make it to market quickly. We connect digital health innovators to the healthcare industry experts and scientists they need to responsibly accelerate product development, commercialization, adoption, and scale.

    Our experts span the healthcare continuum and can assist with all stages of health product development: This includes regulatory, clinical studies and evidence generation, payor strategies, commercialization, and channel strategies. If you are building a health product, talk to us.