What Went Wrong for Amazon Care?

By Stephen Dean, Co-Founder, Keona Health
Twitter: @keonahealth

When Amazon Care was first announced in 2019, it was championed as a revolutionary approach to health care delivery. Amazon attempted to combine in-person and telehealth medical services into a pioneering primary and urgent care service. However, the venture failed to gain traction with both users and clinicians, and at the end of 2022, Amazon shuttered Amazon Care.

The armchair quarterbacking began almost immediately. Most analysts blamed health care’s maze of regulations. Or they attributed the failure to the “relational” nature of the industry, concluding that Amazon didn’t earn the trust of providers. These components no doubt contributed, but the reality is a bit more complicated.

Neil Lindsay, senior vice president of Amazon Health Services told employees in an email, “Although our enrolled members have loved many aspects of Amazon Care, it is not a complete enough offering for the large enterprise customers we have been targeting, and wasn’t going to work long-term.” The phrase “complete enough offering” indicated that Amazon’s software did bring all the elements of health care together, yet it didn’t address the reality of what clients needed.

Amazon is far from alone. Recent attempts by Google, Microsoft, and Berkshire Hathaway to enter the health care market have failed, indicating that scaling in health care is very different from scaling in tech, or any other industry for that matter. The standard growth formula simply doesn’t work in health care.

Delivering the best patient care means navigating a complex set of challenges unique to the health care industry. From provider requirements and safety to workflows and, especially, interoperability, there are many barriers to providing care and, ultimately, value. Amazon’s Care’s demise can be attributed to a failure to rise to this unique combination of challenges. And there’s a lot to be learned from Amazon’s experience.

Interoperability barriers

One of the most significant barriers to scaling is interoperability, or the ability to share data and resources among various health systems. To overcome this barrier, any company hoping to enter the health care space must have a comprehensive understanding of the immense variety of protocols, standards, processes, and technology used by different institutions and providers.

The interoperability of Electronic Health Record (EHR) data has been a challenge for providers for many years, even those that have been in the industry for decades. To address this challenge, the Office of the National Coordinator for Health Information Technology (ONC) recently issued a policy statement that outlined principles and strategies to make EHR data more interoperable and accessible.

Adding to the challenge of interoperability – and serving as a major roadblock for any company that wants to enter the health care space – is patient privacy and regulatory compliance. To address this challenge, the ONC policy statement includes standards for the secure exchange of data, guidelines for access to patient records, and other technical measures.

Despite these and other attempts to make EHR data more interoperable, health care leaders are still struggling to effectively implement such recommendations. One of the driving reasons behind this struggle is that EHR data is just a fraction of the information needed to perform complex health care processes. Interoperability also depends upon bringing together information about doctors and practices, patient demographics, insurance, safety, and much more.

Overcoming interoperability challenges

To overcome the challenges of interoperability, organizations must first audit their systems to determine their ability to share data. This audit should focus not only on the EHR system, but also cover the scheduling system, billing system, and communication system.

They should then invest in a workflow management system that aggregates all of this data. Patient-facing systems, like the one that Amazon provided, can best be optimized in a health care CRM, which manages and automates access, communication, and scheduling.

To further improve interoperability, health care organizations can take advantage of numerous recent technological developments. Key new technologies include:

  • Artificial intelligence (AI): AI technologies like natural language processing (NLP) and machine learning (ML) can analyze large volumes of data and create insights that improve patient outcomes. For instance, AI can scan unstructured data like handwritten doctors’ notes and find connections among patient records that have led to breakthroughs in treating diseases. AI can also automate workflows such as patient billing, streamline data analysis and clinical decision support, and enhance the delivery of personalized care.
  • Cloud computing: Cloud-based technologies allow organizations to store, manage, and access data from anywhere. This reduces the cost and complexity of managing data, and it creates enhanced access for remote health care teams. To adhere to strict security compliance outlined by the Health Insurance Portability and Accountability Act (HIPAA), practices must select a HIPAA-compliant cloud system that ensures encryption, permission controls, and data confidentiality.
  • Internet of Things (IoT): IoT technology enables health care organizations to collect, analyze, and act on data from connected devices in real-time. Most promising is the emergence of wearable devices that allow for remote patient monitoring. EHR vendors have partnered with companies like Apple so users can share health app data with their physicians. This coincides with an upward trend in the number of people choosing to purchase wearables like smartwatches in order to better manage their health.
    Of course, the IoT health care market goes much further than smartwatches and can benefit almost every aspect of health care operations. IoT devices can also be used to monitor the whereabouts of patients and staff members, and to track medical inventory while reducing manual labor linked to traditional inventory management.
  • No-code solutions: No-code solutions allow non-technical teams to build systems without knowledge of coding. This is particularly valuable in the health care industry, where staffing shortages are affecting all positions, including IT teams that typically need to hold advanced technological insight and medical understanding.
    No-code solutions mean practitioners can build and integrate applications quickly and efficiently while lowering costs and boosting interoperability. As a result, health care teams can develop systems that specifically work for them and handle all the data collected from and managed by AI, the cloud, and IoT.


While Amazon Care failed to fully grasp what is needed from a robust digital health care platform, the role of digital services in health care will continue to grow. Health care leaders should take advantage of new technologies to ensure their organizations succeed where Amazon Care did not.

By leveraging AI, cloud computing, IoT, and no-code solutions, organizations can quickly and efficiently access and manage data while improving patient outcomes. Amid mounting pressures facing our nation’s health care services, it’s time for health care leaders to act on data interoperability.