Growth Challenges Faced by Healthcare Technology Startups

There are thousands of healthcare tech startups that deliver SaaS solutions, platforms, or medical devices to healthcare delivery organizations (HDOs) and consumers. These HDOs and consumers rely on the startup’s solutions to support them in treating, tracking, monitoring, analyzing data, or interacting with patients and Health Information Technology (HIT) systems. The aim is to deliver improved healthcare outcomes, efficiencies, cost savings, and agility. According to a report, the global health tech market is expected to grow at a CAGR of 18.8% from 2021 to 2028, but many startups face significant hurdles in scaling their operations. This growth trajectory underscores the immense potential within the sector, yet it also highlights the daunting challenges that must be overcome to fully capitalize on these opportunities.

As a healthcare tech startup, you are a crucial yet often unseen force driving innovation in outcomes-based, population, and preventative healthcare. The solutions you develop and implement are often at the forefront of medical advancements, making significant impacts on patient care and operational efficiencies. However, you all encounter a common set of challenges as you grow and provide software and platform solutions to your HDO clients and consumer base. One of the most prevalent health tech startup challenges is a lack of scalability.

Overcoming Scalability Issues in Health Tech Startups

The first significant challenge is when a startup is successful, the speed of growth often outpaces the ability to adjust to the increasing needs of customers (both HDOs and consumers). Your product and services—such as a primary application or platform for a medical device—are clearly filling a niche no one else is serving for a large segment of HDOs needing that service or support. This niche may be as specialized as remote patient monitoring or as broad as telehealth platforms, but regardless of the focus, the scalability issue looms large.

However, scalability becomes an issue when the technology or architecture on which the product is built cannot handle the increased load. The infrastructure that initially supported your product may not be robust enough to handle the growing number of users or the expanding complexity of tasks. So, as you gain new customers, you struggle to serve them efficiently. How can this challenge be overcome? What are some breakpoints, and in which areas are you struggling to fulfill?

The scalability of an application, database system, associated workloads, or general data growth can be at the heart of these challenges. This is all fueled by your success with customer growth or recent mergers and acquisitions (M&A) that stand as proof of that success. As your customer base expands, so does the volume of data and the complexity of the workflows your system needs to manage. This growth can expose weaknesses in your technology stack, from inadequate server capacities to outdated database structures, each of which can hinder your ability to scale effectively.

Managing Data Growth and M&A Challenges

Your rapid growth as a healthcare tech startup is matched by the growing demands from your HDOs or consumers using your software or platform. This growth makes it challenging to keep up with data, application, and platform updates. As a healthcare tech startup, your HDOs often rely on you to deliver software or platform solutions that enable them to turn data into actionable insights and automate processes to increase efficiencies.
As a healthcare technology provider startup, you are often dealing with the data generated by both the HDO and your own solutions. These large and expanding datasets mean you must leverage what's being collected to deliver actionable application improvements, enhance healthcare efficiencies, and improve processes and patient outcomes. The challenge of scalability to meet data demands usually uncovers the bigger issue of technical debt.

Navigating Technical Debt in Health Tech Startups

Another critical challenge is that many successful healthcare startups face technical debt that hampers their ability to scale and grow to meet client needs. You may have legacy systems and technology – from servers and non-scalable databases to mainframes and other infrastructure technology – that cannot adapt to new technologies and the cloud. These systems, while perhaps reliable in the past, now represent a significant barrier to growth, preventing your organization from taking full advantage of modern innovations such as cloud computing, AI, and machine learning.
This technical debt hinders you from scaling faster, cost-effectively, and efficiently to serve your growing HDO and consumer base. Every delay in updating or replacing these systems adds to the overall debt, creating a vicious cycle where the cost of maintaining outdated technology drains resources that could otherwise be invested in innovation. A move to the cloud is the solution, but it also presents its own set of challenges, such as:

• Building a developer environment that enables quick application updates that can be accurately and automatically pushed to your providers without interrupting processes.
• Automating processes to enable legacy technology, like mainframes, to keep up with data and services transfers to and from the cloud platform.
• Leveraging the vast data you receive from HDO and consumer customers to create innovative services and applications while remaining compliant with HIPAA privacy laws and other data privacy regulation.

The transition to cloud-based systems is not just about moving data from one place to another; it involves rethinking how your entire technology stack operates. This shift requires a strategic approach that balances the need for modernization with the realities of existing technical debt. Regardless of whether you face one or all these challenges as a healthcare tech solutions startup, you recognize that the cloud is the answer. But the fear of moving to the cloud becomes another challenge. Concerns about data security, potential downtime, and the cost of migration can make even the most forward-thinking organizations hesitant to take the plunge.

The Dual Nature of the Cloud and Data Analytics

Understanding that achieving application, platform, database system/data scalability, modernization, and service innovation in the cloud may be the solution, but it also brings new challenges. These challenges include how to:

• Migrate applications or platforms to the cloud
• Manage and move vast amounts of data/database systems to the cloud
• Ensure regulatory compliance to keep data safe and anonymous
• Build a cloud landscape that tracks data and stays compliant

Once you have migrated your data to the cloud, the goal is to interpret and make it actionable, which raises several questions, such as how to:

• Utilize AI and ML to advance data to the next level
• Gain insights and learn from the data
• Conduct predictive analytics

Getting these answers typically requires a data scientist, but there is a shortage of data science talent in the marketplace. This lack of talent poses a substantial challenge for healthcare technology providers, prompting the question, "How do we rise above it?"

Addressing Technical Debt to Foster Growth

Technical debt is a significant obstacle to innovation and growth. This debt might stem from M&A activities or from short-term planning and poor choices that failed to account for future IT architecture, database systems, or application scalability needs. For some startups, the technology has simply been around for a long time and is now incompatible with achieving cloud efficiencies and scalability. The longer you delay addressing technical debt, the more entrenched it becomes, making it even more difficult to introduce new technologies or scale your operations effectively.
Technical debt is crippling your ability to innovate and expand. This could mean lacking the capability to provide new services or application/platform features that enable customers to:

• Use limited resources like ICU beds more effectively, ensuring that critical care is available to those who need it most.
• Track ICU patient symptoms and conditions via medical devices to proactively determine potential future conditions and treatments, enhancing patient care and outcomes.
• Provide medical device data and patient/user health tracking based on long-term, large dataset analytics, which can inform treatment plans and improve patient outcomes.
• Enhance data integration and interoperability across HIT systems like Electronic Health Records (EHRs) and other HIT systems, breaking down silos and enabling more coordinated care.
• Manage medications more effectively using dashboards to reduce adverse reactions and increase effectiveness, improving patient safety.
• Aggregate data from thousands of geographically dispersed personal health devices, creating a comprehensive view of patient health that can inform personalized care plans.
• Deliver data analytics as part of patient population platforms for healthcare population and biopharmaceutical studies, contributing to medical research and innovation.
  

The list of challenges and solutions is endless, but for you as a startup serving your HDO customers and their patient populations and consumers, the solutions often begin with addressing technical debt. Whether it’s mainframes, database systems, monolithic applications, server farms, or IT infrastructure, overcoming these challenges is critical.
The good news is you don’t have to undertake costly rip-and-replace strategies. With our modernize-in-place approach, you can improve scalability and address technical debt effectively. Learn more about Application Migration here. Understanding what technical debt truly means and how Techolution helps you manage it will be covered in more depth in an upcoming blog post. If you're ready to improve scalability and resolve technical debt, our team is prepared to assist. Fill out the form to get more information.