Iteration vs Innovation in Healthcare and Life Sciences

A look into the state of the industry and how to keep up with the speed of life to deliver better solutions and improve patient outcomes.

There’s a crucial difference between iteration and innovation. Iteration builds on established thinking and behaviors, making incremental changes that improve upon—but don’t radically change—the existing model. Innovation asks more of us. Innovation asks us to reimagine what’s possible and discard traditional modes and models in favor of ideas, features, processes, and technology that provide better experiences faster.

Healthcare is an incredibly emotional, personal, and scientifically rigorous field which makes it slow and difficult to change. It’s the poster child for iteration and incremental change because the outcomes of those changes can literally be life or death. But healthcare MUST change to meet the moment and prepare for the future. The pandemic has revealed significant gaps, inefficiencies, and inequities in healthcare, but those challenges are not insurmountable. We have to reimagine what normal looks like instead of relying on small iterations that can’t keep up with the speed of life as we now know it.

The challenges ahead are how to drive these changes and embrace large-scale innovation while ensuring data security, reliability, and equity. How to revolutionize the patient experience and improve outcomes while reducing the stress and burnout of the doctors, nurses, and technicians we rely on to deliver care. How to advance groundbreaking research safely, ethically, and equitably to ensure better treatments for all.

Let’s explore the state of the Health and Life Sciences industry across patient experience, healthcare technology, data and AI, and cybersecurity, and open up deeper conversations about how to overcome challenges and innovate responsibly to move healthcare forward.

Patient Experience

Health Equity

Health Equity is one of the most significant challenges that came to light during the pandemic. COVID-19 showed us that the gaps in access to quality healthcare largely split along racial and economic lines, with low-income people of color facing the biggest barriers to care.

Due to historical and ongoing disparities, trust between disadvantaged communities and the healthcare industry has reached dangerous levels. All healthcare stakeholders—hospitals, doctors, researchers, tech companies, etc.—have to purposefully dismantle unequal systems and rebuild trust with the most vulnerable populations.

It’s crucial to view innovation through a wide intersectional lens to factor ALL patients into the design of new systems, delivery models, and caregiving options. For example, suppose a doctor’s office or a hospital decides to promote new telehealth options as their primary method for first appointments and check-ins. In that case, they need to ensure digital equity and literacy exist in their patient communities before cutting off options to access care in other ways.

Expanding Patient Choices

Patient choice is a broad term that encompasses medical devices and technology, doctors, telehealth, diagnostics, and more. Rapid changes to infrastructure and care delivery due to pandemic conditions now mean more options to meet patients where they are.

While people deserve to be empowered to make their own healthcare decisions, it’s up to healthcare providers to help patients access care based on the condition that best meets their needs. It’s not about the illusion of choice but instead serving up an appropriate slate of options that will guide them to the best choice based on their situation (hospital visits, in-clinic, telehealth, etc.).

Out of all of the care delivery methods, telehealth is the most controversial. While arguably more convenient than in-person care, more research is needed to evaluate when and how to use it most effectively. This type of decision also fits into the discussion around patient trust. If you provide telehealthcare, do patients feel adequately heard and supported? Do they have confidence in the solutions?

Community Health

The pandemic again showed us the critical need for partnerships between the public and private sectors inside and outside the healthcare system (government, churches, business, schools, etc.) to support better health in our communities. Healthcare isn’t just the purview of the medical establishment. It takes an engaged community to provide holistic support, education, and care to people throughout their lives.

One of the biggest questions is how do we expand the net of data we capture, standardize it, and make it safely and securely accessible for analysis? To find innovative solutions that include preventive care, the data needs to go well beyond healthcare and capture demographics, lifestyle choices, economic factors, and more.

If we can securely and ethically break down data silos across industries and sectors to share resources and insights, there’s massive potential for long-term, community-oriented healthcare solutions.

Healthcare Technology

Artificial Intelligence

Out of all the industries currently using AI, HLS might be experiencing the biggest impact, from research to patient communications to administrative workflows.

HLS Administration

Administrative costs have skyrocketed nationwide due to the effort to keep up with the increased complexity of medical technology and care systems, and the need to locate and onboard new employees to replace those who left during the great resignation.

Healthcare administration and record-keeping aren’t just the responsibility of administrators. Administration tasks fall on healthcare providers, hospital staff, researchers, and more. Each healthcare professional spends hours each day inputting data. AI can help shoulder the workload to increase efficiency while saving time and money and reducing errors. This can also help prevent burnout by freeing time to spend on other high-value tasks and lightening their overall workload.

Chatbots and Data Interoperability

Chatbots are quickly becoming indispensable knowledge tools that can actively engage with users. When we talk about patient enablement, building trust, and empowering informed choices, chatbots can be integral to delivering those changes at scale.

Interoperability is the ability of computer systems or software to exchange and use information. In the context of chatbots, this means bots can communicate with multiple systems to pull relevant knowledge and respond to more complex requests with speed and accuracy. They can also take action based on a user’s input and trigger workflows that support people-driven operations.

While the first uses that come to mind are patient-facing, chatbots can also help guide and direct healthcare professionals internally. By having an active AI interface to search for knowledge, data, records, and more, everyone working in the Health and Life Sciences ecosystem stands to gain insight, efficiency, and time, contributing to better outcomes.

Patient Communication

Healthcare can be intimidating for patients. From insurance coverage concerns to diagnoses and treatment, seeking and receiving care isn’t always easy or straightforward. Improving patient communication is crucial to demystifying healthcare and building trust.

AI can go a long way in alleviating patient worries and concerns by providing relevant information (via chatbots, for example), suggesting compassionate yet clear phrasing for written communications from healthcare providers, or helping people identify trustworthy sources vs. misinformation.

Healthcare Data

Healthcare involves hundreds of different data sources—they are the fuel of digital transformation. Just one medium-sized hospital averages over 400 different systems where critical data can be held! These data sources include the hospital information system, EMRs, CRMs, wrist packs, wearables, and diagnostic devices. But the data is only as valuable as the insights it can provide, and integration between data sources is the key to uncovering them.

Healthcare is also becoming increasingly personalized as medical devices monitor patients at home, capturing vital information and helping patients report symptoms without coming to the clinic. This unprecedented level of individualized data collection is enabling better care and powering predictive research.

Medical Device Cybersecurity

Connected devices have the potential to drive great outcomes and better healthcare, but they also expose organizations and individuals to the risk of theft and manipulation. Studies have shown that insulin pumps can be hacked merely by gaining proximity to a device, allowing the hacker to control the device’s mechanisms. Hacks can lead to organizational reputation degradation, financial fraud, and even risk of physical harm to patients.

However, medical device companies can take advantage of TIPPSS, a new cybersecurity paradigm in IoT that can block hacks from bad actors. TIPPSS stands for:

  • Trust: Allow only designated people/services to have device or data access.
  • Identity: Validate the identity of people, services, and “things.”
  • Privacy: Ensure device, personal, and sensitive data are kept private.
  • Protection: Protect devices and users from harm—physical, digital, financial, reputational.
  • Safety: Provide safety for devices, infrastructure, and people.
  • Security: Maintain security of data, devices, people, etc.

Medical device companies can utilize architectural frameworks for clinical IoT data and device interoperability to ensure security and privacy.

As we rely on more sophisticated technologies to evaluate patients, deliver treatment and monitor patient health, we are also exposed to greater risks. Responsible and ethical healthcare extends beyond patients themselves to the sensitive technology and data that power innovative solutions.

What’s Next?

Every healthcare initiative eventually ladders up to one final goal: improving patient outcomes. This could mean reducing waiting times, getting the right care to the right person at the right place, or relieving the data and administrative burdens of healthcare providers.

Find your why. What’s the impact of your project or initiative? Why does it matter to your organization, community, and HLS industry?

Decide how you’ll track and measure your impact. Without data, it’s impossible to understand your progress, solve challenges, and build on your success.

Healthcare innovation is a journey with many stops and forks along the road. It’s critical to build digital solutions alongside a partner who understands how to integrate tech platforms like Salesforce Health Cloud to build flexible, long-lasting solutions that can evolve and grow with you. A partner can also help you contextualize your goals against broader developments and innovations in the HLS industry to design holistic systems that work together to improve conditions, processes, experiences, and outcomes for healthcare staff and patients.

At Wise Wolves, we use our industry experience and deep knowledge of the Salesforce platform to identify, create, and prioritize solutions to help Health and Life Sciences companies deliver quality care and innovation. If you’re ready to embrace innovation over iteration, let’s talk and build something beautiful.

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