There are thousands of healthcare tech startups that deliver SaaS solutions, platforms or are medical device manufacturers (MDM) to healthcare delivery organizations (HDO) and consumers. These HDOs and consumers rely on the startup’s solution’s support in treating, tracking, monitoring, analyzing data, or interacting with patients and HIT to deliver improved healthcare outcomes, efficiencies, cost savings, and agility.

As one of these startups, you are a central unseen force driving healthcare innovation in outcomes-based, population, and preventative-based healthcare. But you all face a common set of challenges as you grow and provide software and platform solutions to your HDO clients and consumer base. This often starts with a lack of scalability.

Common problems for Healthcare Tech companies

The Scourge of Startup Application/Platform Scalability

The first challenge is if you’re a successful startup, you often find your speed of growth is outpacing your ability to adjust to growing customer (HDO and consumer) needs. Your product and services such as the primary application or platform for a medical device is clearly filling a niche no one else is filling for a large segment of HDOs needing that service or support.

When you have a product like that, it’s built on some sort of technology or architecture may not scale well. So, as you gain new customers, you have a problem trying to serve those customers. How can this be overcome? What are some breakpoints and some areas that you’re struggling to fulfill?

The scalability of an application, database system, associated workloads, or general data growth can be at the heart of scalability challenges. This is all fueled by your success with customer growth and/or the recent M&A that stands as proof of that success and growth.

Startup Data Growth and M&A Challenges

Your fast growth as a healthcare tech startup is matched by the growing demands from your HDOs or consumers using your software or platform. This has made it difficult to keep up with serving their data, application, and platform update needs. As a healthcare tech startup, your HDOs often turn to you to deliver software or platform solutions that enable them to turn that data into actionable decisions and automate processes to increase efficiencies.

As a healthcare technology provider startup, you’re often dealing with the data generated by the HDO and your own data being generated from how the HDOs are using your solution/ services. These massive and growing databases mean you’ve got to leverage what’s being collected to deliver actionable application improvements, healthcare efficiencies, and improved processes/patient outcomes. The challenge of scalability to meet data demands usually reveals a bigger connected challenge of technical debt.

Another challenge is when successful healthcare startups are part of an M&A to create synergistic solution offerings to HDOs and consumers. This results in the need to bring legacy technologies and infrastructure stacks into a unified approach. The challenge here is you’re often facing application code, database systems, workloads, and IT infrastructure that harbors technical debt like mainframes and on-prem server architectures.

The Challenges of Healthcare Startup Technical Debt

Another enormous challenge you may have is that you face technical debt that holds back scalability and growth to meet client needs. You likely have legacy systems and technology from servers and non-scalable databases to mainframes and other infrastructure technology and architecture that can’t adapt to new technologies and the cloud.

This means the technology hinders you from scaling faster, cost effectively, and working more efficiently in serving your growing HDO and/or consumer base. A move to the cloud is the answer, but it also poses its own challenges such as:

• Building the developer environment that enables fast application updates that can be accurately and automatically pushed out to your providers without process interruption
• Having a way to automate processes in ways that enable legacy technology like mainframes to keep up with data and services transfers to and from the cloud platform
• How to leverage all that data you’re getting from HDO and consumer customers to create innovative services and applications that will benefit you and them while staying compliant to HIPAA privacy laws and other regulations for data privacy and auditing.

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 how to move to the cloud becomes another challenge.

The Cloud and Data Analytics as Both Solution and Challenge

Understanding that gaining application, platform, database system/data scalability, modernization, analytics, and services innovation in the cloud may be the answer. It may also be another challenge that can grow out of how to:

• Move that application or platform to the cloud
• Manage and move all that data/database systems to the cloud
• Meet regulatory compliance for keeping that data safe and anonymous
• Navigate and build that cloud landscape, track that data, and stay compliant

Once you get your data to the cloud, the goal is to make sense of it and make it actionable, which leads you to ask several questions about how to:

• Leverage AI and ML to figure out how we take that data to the next phase?
• Get insight into the data and learn about it?
• Perform predictive analytics?

Getting those answers has traditionally required a data scientist. This poses another challenge as data scientists are in high demand, rare, and very expensive. Lack of data science talent in the marketplace is an enormous challenge where healthcare technology providers are asking, how do we rise above it?

Technical debt, which is the root of your challenges, may come through acquisition in M&A or through short-term planning and poor choices that failed to look ahead to the need for IT architecture, database system, or application scalability. For some startups, the technology has just been around for a long time and is now incompatible with gaining cloud efficiencies and scalability in a simple way.

Technical debt is crippling your ability to innovate and grow. This could mean not having the ability to provide new services or application/platform features for your customers that enable them to:

• More effectively use limited resources like ICU beds
• Track ICU patient symptoms and conditions via medical devices to proactively determine potential next phase conditions and treatments
• Provide medical device data and patient/user health tracking based on long-term, large data set data analytics
• Create more cost-effective data integration and interoperability across HIT systems like EHRs and other HIT systems
• Provide medication management for dashboards to lower reactions and increase effectiveness
• Providing services and provider connection for data aggregation of thousands of geospatially distant personal health devices
• Deliver data analytics as part of patient population platforms for health population and biopharmaceutical studies

The list is endless and diverse, but the challenges for you as a startup and serving your HDO customers and their patient populations and consumers are all the same. Solving these challenges often starts with solving the challenge of technical debt, whether it be mainframes, database systems, monolithic applications, server farms, or IT infrastructure.

The good news is you don’t have to undertake costly rip and replace with our modernize in place approach. Read more about Application Migration here. This is all rooted in understanding what technical debt really means and how Techolution helps you deal with technical debt, which we’ll go into in more depth in an upcoming blog post. If you ready to improve scalability and solve for technical debt our team is ready to help. Fill out the form to get more information.