All health care problems are data problems

The American health care system is facing a crisis, but at its core, this crisis is fundamentally one tied to data. Preventable medical errors, soaring costs, lack of transparency and insurance woes are driven by inefficiencies in how information is managed, shared and used.

Outdated practices and policies that govern data exchange in health care have created an environment where vital information is siloed, fragmented and often inaccessible at critical moments. It can be particularly burdensome for independent primary care physicians, especially those in smaller and medium-sized practices, to comply with federal privacy and data-sharing regulations. Unlike larger health systems with dedicated IT teams, these practitioners often face the challenge of ensuring compliance with limited resources. While these regulations are well-intentioned and aimed at safeguarding patient care and privacy, they also impose additional administrative burdens that many doctors find difficult to manage.

To address the systemic issues plaguing American health care today, we must first recognize them as data issues that, if solved, could make significant headway toward a more efficient, cost-effective and patient-centered system.

Preventable medical errors

One of the most pressing issues in health care is the prevalence of preventable medical errors. These errors often occur due to incomplete or inaccurate patient information at the point of care. For example, a patient might receive the wrong medication because their allergy history wasn’t shared between different health care providers. Similarly, a lack of access to critical test results in a timely manner could lead to misdiagnoses, delays in treatment and unnecessary complications.

Evidence suggests that implementing robust electronic health record (EHR) systems that are interoperable across different health care providers can significantly reduce the incidence of these errors by ensuring that all relevant patient information is up to date and accessible in real time. The emerging promise of health information exchanges (HIEs) and qualified health information networks (QHINs) also holds the potential to further enhance this interoperability. Participation in these networks helps health care providers consolidate patient data flows, reduce the likelihood of errors and improve patient safety. In general, these systems support more accurate clinical decision-making and enhance patient safety​.

Lack of transparency

Lack of transparency in health care is a significant issue that stems from poor data practices and leads to surprise bills and financial hardship for many patients. Despite federal efforts to improve price transparency, such as the U.S. Centers for Medicare & Medicaid Services rule requiring hospitals to make their chargemasters publicly available, there remains significant variability and inaccessibility in pricing data that are often scattered across multiple systems and obscured by complex billing practices​.

This fragmentation causes confusion and mistrust among patients, who struggle to understand the true cost of their care. Without a clear, centralized source of pricing information, patients are left to navigate a maze of disparate data sources that often leads to unexpected out-of-pocket expenses and perpetuates a cycle of financial insecurity. This confusion is exacerbated by the fact that even when pricing data are available, they are often presented in a way that is difficult for patients to interpret, with medical jargon and complex billing codes further obfuscating the issue.

High cost

The high cost of health care in the United States is indeed closely tied to inefficiencies in data management, particularly in administrative processes. Administrative costs make up a significant portion of health care spending, with outdated methods like manual data exchanges and reliance on paper-based systems such as faxing that contribute to this inefficiency. These manual processes not only add unnecessary time and complexity but also increase the likelihood of errors that further drive up costs.

Automating and standardizing data exchanges — such as those around medical approval and billing processes — could significantly impact providers’ overhead costs. Moreover, streamlined data practices could free up resources that are currently wasted on redundant tasks and allow health care providers to focus more on patient care rather than bureaucratic hurdles. This is where QHINs and HIEs play a crucial role for reducing costs by enabling more efficient data sharing across the health care ecosystem.

What the critics may say

Some may argue that current data practices are necessary to protect patient privacy and security. For example, the Health Insurance Portability and Accountability Act regulations were designed to safeguard sensitive health information, and many believe that changing data-sharing practices could compromise these protections. However, this argument overlooks advancements in technology that allow for secure, encrypted data exchange.

Modern EHR systems and data-sharing platforms are designed with security in mind to ensure that patient information is both accessible and protected. Additionally, the lack of data interoperability can lead to security breaches due to the ad hoc methods providers use to share information, such as unsecured emails or physical media. In turn, modernizing data practices can enhance both the security and efficiency of health care data management.

Where we go from here

When we take a step back and consider the most significant issues plaguing American health care, it’s entirely reasonable to argue these are fundamentally data problems more than social or systemic ones. Of course, data, people and systems are interconnected, but information sharing has become a cornerstone of modern health care. With the promise of HIEs and QHINs, along with cutting-edge tools for data analysis, we’ve reached a point where change is possible. That said, change won’t be easy, but it will be necessary to transform our health care system for the better.

Mika Newton is the CEO of xCures, an artificial intelligence-assisted platform that automatically retrieves and structures medical records from any U.S. care site. He holds over 25 years of leadership experience in the life sciences.