Only 12 percent of health systems and health plans consider their provider data quality to be excellent, according to new findings. The research was conducted by Sage Growth Partners and commissioned by Verato, an identity intelligence company. It surveyed leaders from major healthcare organizations, including those with at least $1 billion in annual net patient revenue. The survey included 101 health system leaders and 50 health plan leaders.
The study found that nearly all health systems and plans experience provider data errors regularly, often multiple times a week, according to insurancebusinessmag.com. Issues include duplicate records, outdated locations, and practitioners listed as active when they are not in the network. These data problems lead to member complaints, billing surprises, and claims rework. Verato reported that 92 percent of health systems and 98 percent of health plans encounter provider data inaccuracies at least monthly.
Employers often end up paying for errors when directories used by plan members are incorrect. Despite the challenges, both health systems and plans agree that accurate provider data is essential for achieving strategic goals. However, only a small number of organizations have fully implemented systems to manage provider data effectively. Only 28 percent of health systems and 36 percent of health plans said they had a fully implemented and maintained single source of truth for provider data.
The root of the issue lies in how healthcare organizations handle data across departments and systems. Each department often builds its own tools, resulting in fragmented information that is hard to keep consistent. This fragmentation leads to inefficiencies and waste in credentialing, panel reconciliation, and claims processing.
Leaders from both sectors see AI as a top technology area for investment in the coming years. Yet, they also acknowledge that the data needed to support AI efforts is unreliable. Fewer than half of health systems and plans currently use data effectively for revenue cycle management or claims adjudication. Verato found that 78 percent of health systems and 70 percent of health plans rank AI as the top technology investment area for the next one to three years.
Jason Bihun, president of commercial operations at Verato, emphasized that provider data is foundational to all strategic initiatives. He noted that network growth plans and claims processing depend heavily on this data, regardless of AI implementation. Governance gaps in AI use further complicate matters for health plans.
A separate survey found that while most health plans are using or piloting AI, few have detailed policies for its use. The 2026 Healthcare AI Readiness Index found that 97 percent of payer respondents were piloting or actively using AI, while fewer than 40 percent of payer and provider organizations had detailed policies governing employee use of generative AI. This lack of governance affects downstream AI applications and analytics that rely on accurate data. Maintaining current information from trusted external sources is important for a reliable data foundation.
Only after this step can organizations build more strategic dimensions of provider data, such as clinical activity and referral patterns. This three-step process distinguishes a durable data foundation from another point solution. Meanwhile, medical technology company Powerful Medical has received rare FDA De Novo authorization for an AI algorithm designed to detect heart attacks, according to a report from inc.com. FDA records show the De Novo decision was granted on September 3.
The model, named the Queen of Hearts, identifies acute arterial blockages in patients with chest pain using ECG readings. It is particularly effective at identifying heart attacks that do not meet classic STEMI criteria on first ECG tests. The algorithm helps first responders make better decisions, reducing delays in treatment and false alarms. The FDA authorization covers detection of STEMI and STEMI-equivalent patterns in patients with suspected acute coronary syndromes.
Under standard STEMI pathways, about 25 to 40 percent of cath lab activations can be false positives. In a 2025 study, Queen of Hearts had a 7.9 percent false-positive cath lab activation rate compared with 41.8 percent under standard decision-making. Heart disease remained the leading cause of death in the United States in 2023, accounting for 22 percent of all deaths. However, there has been progress in reducing heart attack deaths since the 1970s, according to a study in the Journal of the American Heart Association. That study found that heart attack death rates fell by nearly 90 percent over about 50 years.
In another development, Google Cloud and Accenture have formed a joint group to promote the use of Google’s Gemini Enterprise platform, insidermonkey.com reported. The new business group aims to train engineers and implement AI applications for enterprise clients. This collaboration combines Google Cloud’s technology with Accenture’s industry experience and implementation skills. Accenture said the group will establish a 1,000-person forward-deployed engineer workforce and build on its nearly 50,000 Google Cloud-skilled professionals.
Accenture already has a large team of engineers skilled in Google Cloud technologies. The initiative could help Google turn Gemini Enterprise into a more deeply embedded platform for businesses. This would provide Google with additional channels to expand its customer base and cloud usage.
The partnership also strengthens Google’s position against competitors like Microsoft and Amazon in the AI market. Accenture stands to benefit by capturing more of the enterprise AI spending cycle. The companies have previously expanded their collaboration, indicating a broader strategy rather than a one-time effort. The two companies had already announced a Gemini Enterprise Acceleration Program in April.
However, the success of this initiative depends on demonstrating measurable financial returns for Google. Enterprise AI adoption remains challenging due to integration issues and proving return on investment. Google’s investments in AI infrastructure also raise questions about whether current usage can justify those costs.
There is a risk that customers may move toward multi-model strategies, which could reduce the dominance of Gemini Enterprise. For Accenture, the main concern is the upfront investment required before seeing returns. The companies have not disclosed specific financial details about the partnership.
Accenture also faces competition from other firms that offer their own implementation services or AI expertise.
IMAGE: A 12-lead electrocardiogram (ECG) measured in clinical practice. 2012 Peterhcharlton CC4