Max is Collective Health’s Chief Technology Officer. He is passionate about solving tough problems by building best-in-class technology.

I’ve worked in Silicon Valley and technology my whole career. I’m well acquainted with the “disruptive” mentality espoused by myself and fellow technologists. However, when working with human lives, disruption must be thoughtful and deliberate and include controls. I recently started working with a company that’s solving some of the most pressing healthcare challenges today, and in these past few months, it’s become clear why healthcare lags behind other industries in transforming through technology.

Simply put, it’s complicated.

Healthcare is highly regulated. While other industries have their own unique regulatory and legacy challenges, the complexity of healthcare stems not only from data privacy and tight controls, but also new technology simply layering onto legacy technology — many “digital health” solutions today are simply layered on top of, in some cases, 30-year-old technology. The incentives of these disparate solutions are also not always aligned with desired outcomes and the result is a confusing, fragmented and more costly experience for people and employers, who are often the payers of healthcare.

In healthcare, and when functioning optimally, technology automates processes, identifies trends and scales the necessary human touch. Unlike other industries, technology can’t completely replace the human element — in this case, it enhances it.

While we may be inclined to reduce healthcare down to a series of transactions, the reality is the healthcare system was architected with acute and episodic care in mind, but as consumers, we’ve evolved, and the requisite technology has evolved. The care needs of many individuals occur outside of the clinical setting and involve at least one, if not multiple, chronic conditions. So, while other industries like banking have realized the benefits of transformational technology (virtually overnight), complexity has hampered rapid adoption of technology across healthcare, and in particular, hampered those areas that help drive better transparency and quality health outcomes.

Data: It’s foundational yet controversial.

With all the red tape that surrounds personal health information and the HIPAA guidelines, data is the greatest asset and hindrance healthcare has to offer. Legacy systems built upon dated EDI specifications, coupled with the lack of tooling and documentation to handle what should be basic processing and services, leads innovators in healthcare to spend valuable time and resources on data processing. This sadly distracts from delivering improved health costs and outcomes. There’s a clear opportunity to elevate standards and interoperability to modern structures and protocols. Many members of the new generation of health tech companies will lead the way, as they are more interested in advancing health outcomes than investing in the legacy data formats, which are error-prone and non-descriptive. Enabling innovation through modern practices is key to tackling the daunting challenges associated with healthcare transformation.

Innovators must have access to integrated sets of data that help data scientists identify health and care patterns through artificial intelligence and machine learning that will lead to meaningful improvements in care recommendations, outcomes and cost. With the plethora of data that feeds our healthcare systems, analyzing, organizing and delivering insights that are accurate, meaningful and actionable is the objective. Data normalization and organization, while still ensuring its protection, is the foundation to achieve that goal. This will make practitioners, employers and people more informed, while reducing the friction and drag that has become the industry norm.

And yet, despite the perceived treasure trove of personal health information and the opportunity to make meaningful improvements in healthcare, there’s a significant shortage of data scientists that work in the healthcare industry. Perhaps what keeps data scientists from joining the ranks of those in the healthcare space is lack of access. Most I’ve come to know want to solve hard problems in an effort to create more quality health outcomes, but they also need the data.

Land and expand — even with technology.

Transforming healthcare requires the same thoughtful methodology that many other industries have gone through, with much more patience. Similar to how many consider a “land and expand” go-to market strategy, the same applies to technology and product investments as disruptors enter healthcare and health tech markets. Thoughtfully considering legacy capabilities and the potential for both disruption and differentiation is important. Considering where and when to invest in building technology that ultimately results in meaningful outcomes or differentiation, versus what existing systems can fill needs in the short- or long-term, is core to transforming the industry.

To define what capabilities matter, it’s important to ask in what way investing now will help achieve the vision of transforming healthcare in America. Staying true to the vision and mission helps avoid being overwhelmed by the magnitude of the goals.

This may beg the question: Why is the “technologist” perspective needed in this space? Incumbents just aren’t incentivized to implement new technology. This mentality will continue as long as incentives are aligned with a fee-for-service model versus a system that values meaningful health outcomes.

Additionally, implementation is costly and slow. A significant amount of technology investment is required to participate. That need alone limits the amount of time and resources spent on driving meaningful change.

Despite the headwinds, the opportunities to drive innovation in healthcare are limitless. My hope is that more technologists are motivated to bring their skills and creativity to this space. It is certainly a worthy industry for our attention and transformation.  


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