How Payers Can Identify Providers for High-Performing Networks

Common challenges

While several strategies aid health plans in building successful high-performing networks, it may not always be a simple task.

Data collection can certainly assist with identifying high-quality providers, but there is limited access to comprehensive and reliable data in the healthcare space. Without widespread interoperability, payers may struggle to collect cost and quality data that determine provider performance.

Similarly, not all providers employ the same quality performance measures, meaning it could be challenging for payers to compare providers based on quality metrics.

Health plans could also face data barriers if providers are unwilling to communicate and share data due to security and privacy concerns or due to potentially increased administrative burdens.

Identifying high-quality providers through data collection, analytics, and provider engagement requires significant work on the health plan side. Some health plans may not have the proper resources or enough staff to sufficiently carry out these tasks, creating another challenge to establishing a high-performing network.

Data collection is key

Despite several data access challenges, payers must collect relevant data to determine if providers will fit into their high-performing networks. This includes data that sheds light on provider performance, such as claims data, electronic health records (EHRs), patient feedback, and quality measurement programs.

Data from quality measurement programs can help plans understand how well providers deliver quality care at low costs.

CMS offers several quality reporting programs that aim to improve care quality through payment incentives and reporting requirements. The Agency for Healthcare Research and Quality (AHRQ) also helps collect provider data through initiatives like the Consumer Assessment of Healthcare Providers and Systems (CAHPS) surveys.

Additionally, health plans can consider provider accreditations when seeking high-quality providers, such as those given by the National Committee for Quality Assurance (NCQA).

Technology solutions support payers

Payers can take advantage of technology to help identify high-quality providers. After gathering accurate and current data, payers must analyze it to measure provider performance. Using predictive analytics, they can project which provider will best fit member needs, considering location, medical specialty, and availability.

Additionally, predictive analytics models can help health plans with risk assessment. Through analyzing historical claims data, previous health outcomes, and patient characteristics, plans can determine provider patterns that are likely to lead to high-quality care delivery.

Under the predictive analytics umbrella, machine learning can also help predict provider performance. When payers enter provider data into machine learning algorithms, the predictive models that assess providers’ potential performance can be continuously updated as new data becomes available.

In addition, machine learning processes can help payers categorize members into groups depending on their health needs and the spending required for their care. This information can influence payers and their choices as they consider which providers to add to their networks.

Machine learning and other artificial intelligence algorithms can also make payers aware of providers they shouldn’t include in their networks through fraud detection. Payers can feed medical claims and other documentation related to billing and coding through machine learning algorithms, which will then flag any providers potentially involved in fraudulent activities.

Furthermore, artificial intelligence algorithms can use historical and current provider data to identify in-network providers who are underperforming and should be removed from the network.

Quality measurement considerations

Quality measurement programs offer key data that payers can use to evaluate providers. Quality measures for healthcare providers typically fall into one of three categories: structure, process, or outcome.

Structural measures speak to a provider’s infrastructure, systems, and capacity to provide quality care. These measures include whether a provider uses an EHR, the staff-to-patient ratio in a practice, and the number of board-certified physicians.

Process measures indicate how a provider maintains and improves patients’ health and tend to reflect recommendations for clinical practice. For example, process measures include the share of people receiving preventive services and the share of people with diabetes who had their blood sugar tested and controlled.

Outcome measures are perhaps the most helpful for payers when evaluating providers on high-quality care delivery. These measures assess how healthcare services impact patient health status. Measures like clinical outcomes, patient satisfaction scores, infection rates, readmission rates, and mortality rates can help payers determine if providers deliver high-quality care.

Payers may want to avoid adding providers to their network who have high readmission rates, as it may indicate repeatedly unresolved patient issues, a lack of patient-provider communication, or poor initial care delivery. Similarly, low patient satisfaction scores and high infection rates may also indicate poor quality.

Patient outcomes can differentiate between providers who prioritize patient-centered care and those who do not. They also offer objective data on how safe, effective, timely, efficient, and equitable care delivery is, allowing payers to compare providers.

Another critical quality indicator is how well a provider manages population health. Population health management strategies emphasize preventive care, evidence-based guidelines, health equity, and cost-effective care. Providers often leverage care coordination, data analysis, and care integration to implement population health strategies, which improve health outcomes for a specific group of patients.

Whether or not a provider has implemented successful population health management strategies can help payers decide if they want a provider in their high-performing network.

Open provider communication

Another way payers can identify high-quality providers for their networks is by simply communicating with providers. In addition to data collection, direct engagement can allow payers to gather information about how providers operate their practice and what capabilities they possess.

Payers can interview providers, review documentation, and conduct site visits to learn if they want to include a given provider in their network.

After payers establish their high-performing networks, effective collaboration between payers and providers can also improve provider directories, according to CAQH and the American Medical Association (AMA). Timely communication can help correct address, phone number, and new patient status discrepancies in directories.

Evaluate network adequacy

When building a high-performing provider network, health plans must assess individual providers as well as overall network adequacy.

The National Association of Insurance Commissioners (NAIC) defines network adequacy as a “health plan’s ability to deliver the benefits promised by providing reasonable access to enough in-network primary care and specialty physicians, and all health care services included under the terms of the contract.”

Quantitative network adequacy standards include time and distance standards, minimum number of providers, appointment wait times, and available essential community providers. These standards can vary, with states and plan types setting different guidelines for provider networks.

For example, the Affordable Care Act (ACA) requires qualified health plans (QHPs) offered through the marketplace to maintain a provider network with a sufficient number of providers, including those specializing in mental health and substance use disorder services. In addition, QHPs must provide information to enrollees on the availability of in-network and out-of-network providers.

In 2023, CMS started requiring QHPs to comply with time and distance standards, with standards varying by specialty type and county type. In large metro counties, at least 90 percent of enrollees must live within 10 minutes and 5 miles of at least one primary care physician. The standard is 15 minutes/10 miles for metro counties, 30 minutes/20 miles for micro counties, 40 minutes/30 miles for rural counties, and 70 minutes/60 miles for Counties with Extreme Access Considerations (CEAC).

QHP time and distance standards for all provider and facility types can be found here.

Starting in 2024, CMS will evaluate QHPs on appointment wait times.

Medicare Advantage plans have similar network adequacy standards as QHPs, according to KFF. In the 2024 Medicare Advantage rule, CMS added three specialty types to be subject to time, distance, and minimum number requirements: clinical psychologists, clinical social workers, and prescribers of medication for opioid use disorder.

For Medicaid managed care organizations, states must establish and enforce network adequacy standards for primary and specialty care, behavioral health, OB/GYN, hospital, pharmacy, pediatric dental, and long-term services and supports.

States do not have to use time and distance standards; they can choose other quantitative standards to ensure network adequacy, including minimum provider-to-enrollee ratios, maximum appointment wait times, or minimum percentage of contracting providers accepting new patients.

However, state network adequacy standards must address the ability of providers to communicate with enrollees with limited English proficiency in their preferred language and to accommodate those with disabilities.