Skip to main content
Article

Provider network optimization – Finding value in the details

4 June 2025

Introduction

Timely access to healthcare services is an important enabler of positive health outcomes. Access to care remains a significant challenge in the United States where, historically, approximately 16% of adults Americans have reported long wait times and difficulty getting appointments for routine care as soon as needed.1 Demand for healthcare services has grown over the past decades, although supply of qualified providers and healthcare access points has not kept pace.2 This lagging capacity has contributed to delays in receiving care, often resulting in adverse health outcomes and higher healthcare expenditures.3

As payers and providers work to develop and maintain their provider networks, they often face limited options in how they can meet access standards mandated by state and federal regulators. Selecting the appropriate providers to address geographic network requirements is a crucial strategic decision. Payers must develop a deep understanding of how the often-limited pool of providers in a market can impact the plan’s Medicare star rating and other quality and performance measures.

Meeting minimum requirements

Traditionally, provider network access and adequacy have been assessed through the use of three primary measures:

  • Geographic driving time and distance: Provider networks have historically been measured through a series of quantifiable geographic access standards set forth by a regulator, often Centers for Medicare and Medicaid Services (CMS) and/or a state department of insurance or Medicaid. These classic geographic access measures rely on driving time (minutes) and distance (miles) standards to assess the proximity of a plan’s provider network locations to the plan’s enrollees.
  • Provider to member ratios: Additionally, regulations frequently mandate minimum ratios of providers to members. These requirements are set at the specialty level and can vary based on county designation (metro, micro, rural, etc.)
  • Wait times: Appointment wait time standards serve as another metric for assessing networks and evaluating whether providers are accessible to enrollees within a reasonable time frame. Appointment availability thresholds are standardized in the federal marketplace4 and a minimum standard is established for Medicare Advantage plans.5 These measures are typically assessed using third-party “secret shoppers” who call provider offices posing as members and attempt to schedule an appointment.

These measures provide a standardized view of access and adequacy. However, developing a network that offers optimal accessibility relies on many nuanced factors beyond geographic location and provider ratios.

An analytic approach to adequacy

Organizations providing, facilitating, or financing healthcare delivery must look beyond geographic adequacy to build stronger care delivery systems. This more detailed view requires managing provider capacity and service quality. Building an optimal provider network requires a deeper understanding of both the available providers in the market and the members who utilize their services. An adequate network must be geographically and financially accessible, capable of meeting demand for services, and able to deliver a premium member experience to support good outcomes.6 While building such a network can be challenging, it is achievable in many markets with proper access to reliable, high-quality data.

To create an optimized network that aligns the needs of a patient population with the qualifications and capacity of a provider network, payers and providers should develop a thorough understanding of the following provider attributes:

  • Quality: Quality is commonly measured using methodologies such as the National Committee for Quality Assurance (NCQA) Health Effectiveness Data and Information Set (HEDIS) measures7 or the CMS Merit-Based Incentive Payment System (MIPS).8 MIPS uses a weighted combination score of quality, cost, interoperability, and improvement activity to evaluate provider performance. A provider’s ability to meet or exceed HEDIS quality scores can significantly impact the network’s overall performance. Providers who contribute to meeting or exceeding key HEDIS 90th percentile measures are more likely to support higher overall quality scores and performance of the network. Higher quality scores can translate to lower costs and better health outcomes.9 Additionally, providers’ clinical outcomes, adherence to evidence-based care, and patient safety metrics are central to establishing a strong network. Consistently performing well against standard quality measures, such as HEDIS or similar benchmarks, results in better patient outcomes and effective claims cost management.10
  • Relative cost: Understanding the unit cost of a service is critical. Start by evaluating provider costs at a high level and compare them against other providers in the area. Total cost of care, including negotiated rates and utilization patterns, can vary significantly among providers. A comparative “cost index” or global fee schedule can reveal which providers offer the best blend of cost efficiency and quality clinical care.
  • Patient satisfaction: Patient satisfaction, as reported through surveys (e.g., CAHPS, CG-CAHPs, or other instruments), provides insights into provider performance in areas such as responsiveness, communication, and service quality. High member satisfaction often correlates with better health outcomes and stronger retention rates.11
  • Health system and practice alignment: Coordinated care ensures all providers on a patient’s care team share information and collaborate on a unified treatment strategy, ultimately improving health outcomes and containing costs. By aligning providers within health systems and practices through shared data, standard care protocols, and value-based incentive structures, organizations can avoid unnecessary services, minimize errors, and enhance the patient experience. This integrated approach also facilitates proactive interventions, ensuring patients receive timely and appropriate treatment.
  • Line-of-business mix: Understanding a provider’s patient mix (Medicaid, Medicare, commercial, etc.) helps assess their ability to meet specific product or regulatory criteria. Providers accustomed to a particular line of business may have staff, systems, and processes tailored to serve that line of business effectively. Additionally, understanding the line-of-business mix can narrow the pool of potential provider, as some may opt not to contract with certain payer types, such as Medicaid.
  • Current network contracts:∫ Reviewing providers’ existing contract affiliations with other networks can identify potential synergies or conflicts, such as overlapping discounts or participation in rival networks. In addition, a provider that is contracted with many different networks may be less likely to engage in focused and innovative payment arrangements that usually necessitate more dedicated patient volume aligned with a single payer.
  • Languages spoken: Ensuring providers meet the linguistic needs of the patient population is crucial for accessibility, effective communication, and patient satisfaction. A network with a diverse set of language capabilities can better serve multicultural or multilingual communities. Provider language data is self-reported and is typically found in credentialing files.
  • Wait times: Excessively long wait times can lead to decreased member satisfaction and delayed care, which can worsen outcomes or inflate costs.12 Providers with efficient scheduling and throughput processes can help maintain satisfaction levels and reduce downstream expenses.
  • Number of locations: Understanding the number of locations where a provider practices offers valuable insight into the provider’s true capacity. Traditional geographic network access and adequacy measures incentivize providers to report active practice at multiple locations to assist with satisfying access standards. However, a provider who practices at many locations might have limited availability at each site, affecting their ability to accept new patients.13

Creating intentional networks tailored to the specific needs of members can enable significant market success. These optimized networks can help contain costs, ensure quality care, support timely access to services, and maintain a marketable healthcare network product.

Go to the source—identifying a solid foundation for analytics

A key challenge in developing and acting on a deeper understanding of network providers is the lack of reliable provider data. Inaccurate and outdated information can lead payers and providers to establish flawed conclusions from these analytics. While there are numerous data sources available to inform provider network analytics, there are three that provide a consistent balance of accuracy, completeness, and timeliness.

  • Claims data: Captured from healthcare claims submissions, claims data includes information such as diagnosis codes, procedures performed, sites of service, and billed or paid amounts. Claims data is structured data that may be used to assess provider utilization patterns, patient volumes, treatment costs, and care outcomes. To ensure data integrity, the dataset should be scrubbed by removing duplicates and standardizing ICD and CPT coding. While claims data can be a reliable and well-structured source of information, there is typically a significant length of time or lag between the delivery of a clinical service and the final posting of a claim. This lag introduces some limitations in using claims data for more frequent and timely operational reporting and analytics.
  • Provider registry files: These files detail contracted provider attributes, including names, specialties, locations, tax IDs, and National Provider Identifiers (NPIs). Provider registry files are vital to the verification of network adequacy, access standards, and provider alignment. However, registry files are inconsistent in their format and are frequently out of date.14 These files are often populated by data derived from credentialing activities, which may only be updated on an annual basis.
  • Transparency data: This data includes publicly available files provided by payers and providers that report negotiated rates, service costs, or provider quality measures. Transparency data supports comparative analysis of in-network and out-of-network providers, helping identify opportunities for cost reduction and quality of care improvement. However, these datasets are notoriously large, non-standard, and challenging to manage.

Identifying and maintaining clean, reliable, timely data is essential to unlocking the benefits of an optimized provider network.

Curating a source of truth

A critical component of creating a high-performing provider network is the integration, reconciliation, and cross-referencing of major data sources to establish a single “source of truth” for each provider’s status in the database. Implementing data governance practices can improve data integrity and accuracy, ensuring reliable data structures, confidence ratings, and update schedules for each component of the available data.

Once the necessary data has been identified, payers may choose to optimize their networks by developing aggregate scoring at the provider level. When designed properly, each provider within the network should quantifiably support or detract from the performance of the network. This metric-based approach minimizes ambiguity in a provider’s impact on the overall performance of the network. In addition, payers may identify resources, like Milliman’s Provider Network Optimizer, that provide them with similar insight for noncontracted providers and how those providers could impact network performance if brought into contract. This predictive modeling allows organizations to make proactive decisions about their network composition and contracting strategies.

Conclusion

The definition of adequacy is personal to the needs of the organization building the network and the members it serves. A truly adequate network optimizes financial results while improving access, increasing member satisfaction, and supporting positive health outcomes.

Achieving this deeper understanding requires access to reliable data sources, robust cross-validation of data accuracy across those sources. Payer or provider organizations should intentionally design analytics focused on key strategic priorities that promote network competition. An adequate network encompasses more than just a group of providers meeting geographic driving time and distance requirements.

By harnessing claims, provider, and public data sources, payers and provider organizations can gain a clearer picture of provider performance and capture the potential value of their network. With a comprehensive picture of provider quality, cost, accessibility, and affiliations, payers and providers building or maintaining networks can make informed decisions about which providers to include or exclude from their networks.


1 Agency for Healthcare Research and Quality. (December 2021). 2021 national healthcare quality and disparities report. Retrieved May 28, 2025, from https://www.ncbi.nlm.nih.gov/books/NBK578537.

2 Institute of Medicine National Cancer Policy Forum. (2009). Ensuring quality cancer care through the oncology workforce: Sustaining care in the 21st century: Workshop summary. Retrieved May 28, 2025, from https://www.ncbi.nlm.nih.gov/books/NBK215247.

3 Kraft, A.D., Quimbo, S.A., Solon, O., Shimkhada, R., Florentino, J., & Peabody, J.W. (August 2009). The health and cost impact of care delay and the experimental impact of insurance on reducing delays. The Journal of Pediatrics, 155(2), 281–285.e1. Retrieved May 28, 2025, from https://doi.org/10.1016/j.jpeds.2009.02.035.

4 Centers for Medicare and Medicaid Services. Appointment wait times FAQ. Retrieved May 28, 2025, from https://www.qhpcertification.cms.gov/QHP/faqs/Appointment-Wait-Time-FAQs.

5 Code of Federal Regulations. (May 16, 2025). Title 42. Retrieved May 28, 2025, from https://www.ecfr.gov/current/title-42/chapter-IV/subchapter-B/part-422/subpart-C/section-422.112.

6 Agency for Healthcare Research and Quality. (December 2021). 2021 national healthcare quality and disparities report. Retrieved May 28, 2025, from https://www.ncbi.nlm.nih.gov/books/NBK578537.

7 National Committee for Quality Assurance. HEDIS and performance measurement. Retrieved May 28, 2025, from https://www.ncqa.org/hedis.

8 Centers for Medicare and Medicaid Services. Learn about MIPS. Retrieved May 28, 2025, from https://qpp.cms.gov/mips/mvps/learn-about-mips.

9 Hussey, P.S., Wertheimer, S., & Mehrotra, A. (January 1, 2013). The association between health care quality and cost: A systematic review. Annals of Internal Medicine, 158(1), 27–34. Retrieved May 28, 2025, from https://doi.org/10.7326/0003-4819-158-1-201301010-00006.

10 Kolinski, B. (May 6, 2025). Improving HEDIS performance through benchmarking. National Committee for Quality Assurance. Retrieved May 28, 2025, from https://www.ncqa.org/blog/improving-hedis-performance-through-benchmarking.

11 Ferreira, D.C., Vieira, I., Pedro, M.I., Caldas, P., & Varela, M. (February 21, 2023). Patient satisfaction with healthcare services and the techniques used for its assessment: A systematic literature review and a bibliometric analysis. Healthcare, 11(5), 639. Retrieved May 28, 2025, from https://doi.org/10.3390/healthcare11050639.

12 Kraft, A.D., Quimbo, S.A., Solon, O., Shimkhada, R., Florentino, J., & Peabody, J.W. (August 2009). The health and cost impact of care delay and the experimental impact of insurance on reducing delays. The Journal of Pediatrics, 155(2), 281–285.e1. Retrieved May 28, 2025, from https://doi.org/10.1016/j.jpeds.2009.02.035.

13 Xierali I.M. (March 2018). Physician multisite practicing: Impact on access to care. Journal of the American Board of Family Medicine, 31(2), 260–269. Retrieved May 28, 2025, from https://doi.org/10.3122/jabfm.2018.02.170287.

14 Richards, R. (August 14, 2024). Roses and thorns: The nuanced landscape of healthcare provider data. Milliman. Retrieved May 28, 2025, from https://www.milliman.com/en/insight/roses-and-thorns-landscape-healthcare-provider-data.


Explore more tags from this article

About the Author(s)

John Kasey

Jon Yalcin

DaCoda Love

Gordon Chan

Shrujan Amin

We’re here to help