by Howard Koenig...  

​Provider data management faces growing challenges in the age of digital transformation at a pace that may be difficult for organizations to match. Current data management processes and analytics capabilities may serve as a roadblock to its evolution.
​
A 2016 McKinsey Survey points to data management as the primary challenge for organization, finding that “86 percent of executives say their organizations have been at best only somewhat effective at meeting the primary objective of their data and analytics programs, including more than one-quarter who say they’ve been ineffective.” *

If online search directories, referral sources, or other provider data solutions pull from insufficient provider data sources and inaccurate data, it can set off a chain reaction that impacts consumer and provider experience, as well as clinical and financial outcomes.

Inaccurate provider data along the utilization workflow can lead to:

• Gaps in care (from network leakage and care delays)
• Negative consumer experiences
• Negative provider experiences
• Costly regulatory fines
• Overpayments

The inability to access comprehensive, accurate provider data creates gaps in care and negatively impacts overall satisfaction, health outcomes, and the bottom line due to fines, overpayments, and loss of members and providers.
When network leakage (meaning a patient/member is treated at an out-of-network provider) occurs, critical patient data, such as lab testing, physician notes, and diagnostic imaging studies may be missing from the overall health record, creating a potential gap in care.

Accurate provider data can also lessen delays in care which occur when a member/patient selects a provider who is no longer in business, has moved to a different location, or is no longer in the health plan’s network.

A well-managed, authoritative provider data enterprise helps to prevent leakage and care delays that can lead to gaps in care due to missing patient/consumer information or inaccurate provider information. This includes both provider search directories and referrals management solutions which enable providers, care managers, and other stakeholders to identify the best in-network provider to whom to refer a patient/member.

*  https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/the-need-to-lead-in-data-and-analytics

by Howard Koenig...   
​
To blaze the trail for digital transformation, provider data management requires a transformative approach and technological innovation. What differentiates this approach and defines innovation is the data itself and how it is used. The architectonics of provider data need to be scalable, designed to anticipate change, consumable from many formats and attributes, and discoverable in a valuable way for both business and consumer users.

The role of machine learning (ML) and artificial intelligence (AI)

by Howard Koenig...
It is important to break down data silos to access and transform data that is complete, usable, and standardized to apply advanced analytics to enable more informed decision-making for all stakeholders within the provider network enterprise. The biggest challenge is keeping provider data accessible, secure, and relevant, as it must be managed across multiple clouds, external and internal entities, platforms, applications, and attributes.

By April Stiles... 

For Workers’ Compensation companies, providing immediate access to accurate and quality provider data is a critical step to get injured workers back to work quickly. By establishing an intuitive process to manage provider data, organizations can easily assist injured workers in locating quality providers on site, online or via mobile access so that they can seek medical treatment as soon as possible.
   
It is important to empower claims professionals and case managers with the digital solutions they need to optimize workflow, assist injured workers, and control medical claims costs.
​
Here are eight solutions that can help organizations get injured workers back to work quickly.  

Provider data is a critical revenue generating asset for health plans, health systems, and workers compensation organizations. An essential process for ensuring data accuracy is provider roster management. Roster management enables organizations to associate or disassociate a provider with whom they are currently affiliated with or in the process of contracting, to include within their provider data management ecosystem.

The impact of inaccurate data includes:

• Negative consumer experience
• Bad press within the market
• Provider abrasion
• Undue administrative burden
• Fines or sanctions by regulatory organizations​

Medicare Advantage insurer Zing Health has chosen Perspecta LLC, an innovator in provider data management solutions,  to make its provider directory more accurate and reliable using artificial intelligence and machine learning.  

Zing Health’s advanced approach to health data aims to improve care access and quality for under-resourced populations. Perspecta’s Roster Management 3.0 solution applies machine learning techniques to intuitively distill Zing Health provider data from hundreds of doctors, clinics, and hospitals into an accurate, uniform format. Perspecta’s process employs both digital algorithms and programmatic verification to confirm hospital affiliations, medical specialties, locations, and other essential information; thus automating a previously cumbersome manual process and freeing up valuable IT resources to focus their attention elsewhere. 

by April Stiles... 
​
Provider directories are often riddled with inaccuracies, burdening everyone who attempts to access this crucial data. Whether it is patients, providers, or healthcare personnel, errors in provider data prove to be a major roadblock for everyone in ensuring network accuracy and adequacy.

A 2016 study by a research group at West Virginia University tested California health insurance directories, posing as patients and attempted to make appointments with 743 primary care physicians listed in California health plan directories. These “secret shoppers” were unsuccessful 70% of the time. *
​

by April Stiles...   

Attempting to traverse through the ever-changing, quagmire of provider data can be a resource-intensive, tiresome task. As it is a crucial aspect of the health plan and workers compensation internal operations, it is imperative that provider data be managed efficiently so as not to burden those who rely on its accuracy, such as internal and external stakeholders, regulators, and consumers. 

by Joseph Kennedy... 

The No Surprises Act was signed into law on December 27, 2020 as part of the Consolidated Appropriations Act of 2021 (H.R. 133; Division BB – Private Health Insurance and Public Health Provisions). The No Surprises Act addresses “surprise” medical billing at the federal level. Out-of-network billing, or “surprise medical bills” are usually the balance between what the individual’s insurer pays for the out-of-network care and what the provider charges for the services.

Simply put, the act states that patients should not be responsible for out-of-network costs they did not agree to pay.
​
The Departments of Health and Human Services, Treasury, and Labor will be releasing regulations and guidelines for the implementation of these provisions before the largest sections of the legislation go into effect on January 1, 2022.

by Sean Healy...   
​​
Provider referrals management is a strategic balance of getting the best clinical outcomes while controlling overall claims cost. This starts by creating and managing a high-functioning provider and partner referral network to ensure beneficiaries and members receive the best in-network care when and where they need it.

Ensure a high-performing referral network
Referral networks should be measured on clinical outcomes, ancillary utilization, and proximity to the beneficiary or member. High-quality providers offer the lowest-cost and appropriate, high quality care. As such, claims adjusters and case managers need a way to quickly identify providers that match the beneficiary’s coverage plan to find the best specialists and ancillary providers that offer accessible appointments and locations.

Enable provider & partner referral insights
Data and analytics help to optimize referrals management by continuously assessing the referral network. Analytics data can provide claims managers and care managers with clear insights into why and when beneficiaries should be referred to a particular provider and which partner offers the most efficient and cost-effective service. Prioritization should consider price, location, rating, and outcomes to control costs while improving outcomes and satisfaction.
​
In addition, an intuitive referral management solution can help an organization monitor the time it takes for beneficiaries or patients to obtain an appointment or if there has been a change in the provider practice in order to expand its preferred provider network as demand increases.

Continuously check & update provider information
Accurate provider data is critical in referral management. Inaccuracies are the biggest barrier to care and contribute to higher claims costs and risk. It is essential to know if a provider moves from in-network to out of network, has moved, is no longer accepting patients, has an incorrect phone number or address before making a referral.
​
High performing referral networks maintain access to a centralized repository of provider data to ensure referrals to the right provider. A master provider database should be designed to check, cleanse, and manage complex, dynamic data.

Centralize referral resources
With a provider network varying in specialty, geography, and quality, it is important to keep resources consolidated and centralized in an automated, digital referrals management system. A comprehensive solution should integrate claims systems and provider directory information. Intuitive referral management solutions can even prepopulate provider and claims data to simply the workflow for claims adjusters and case managers.
​
A high-performing provider referral process should eliminate time-consuming administrative tasks and processes to foster better consumer and beneficiary experience and reduce the cost of care.

Learn more by checking out Perspecta's provider referral management solution.

by April Stiles...  

Navigating in the sea of disparate provider data is a tumultuous, tedious, & resource reliant endeavor. With data existing in conflicting formats & fragmented attributes, & across various applications across your organization & partners, how do you efficiently transform, cleanse, standardized, & reconcile provider data? For many healthcare organizations, provider data cleansing is like commanding a paper boat at the price of a luxury cruise ship.

The variations in formats, exchange, content, & intended use create a tsunami of costs related to internal resources, time-consuming workflows, & regulatory fines. This poses unnecessary obstacles for consumers. providers, health plans, & partners who need access to reliable provider information.

So how do you chart a better course?

Benchmark data accuracy.
Before starting your data cleansing voyage, it is important to benchmark the current state of your provider information. Begin by creating a data repository that collects & maps data elements. Use a smart analytics solution that can identify and score your provider network data to pinpoint inconsistencies, duplicates, and errors.

Find an expert provider data profiler.
With no industry-standard format requirement, provider data discrepancy detection becomes difficult. An AI-enabled data profiling process can automate the identification of metadata & provide visibility & data matching right down to the single attribute level. Artificial Intelligence helps to pinpoint inconsistencies to assure comprehensive data cleansing. It optimizes the cleansing process by mapping data from source to transformation & finally to destination using commonly used formats​

Check. Cleanse. Check again.
Your cleansing workflow should include quality checks of the information flow to monitor and correct errors that may occur during processing. Data integrity can be ensured with AI-powered data transformation, scrubbing, validation, and transport. A final check and scoring of your data help you establish a higher benchmark for accuracy moving forward.

Don't go it alone.
Provider data is a critical part of your business, so it is important to find a partner that really knows the industry to control costs and manage the challenges you face. A trusted provider data expert can more efficiently and effectively take on the workload, helping you reduce costs and free up internal resources to focus on other areas of your business.

The goal is to reduce costs by automating workflow to continuously clean enterprise data that can be accessed for consumer searches, integration, reporting, and analyses across your organization and regulatory environment. 

by April Styles...   
The value of accurate & compliant provider network data cannot be overstated. Provider Directories serve as road maps to help consumers and their families decide which health plan to enroll in or how to access care the best care for their needs. According to a 2013 Health Reform Monitoring Survey, almost 56% of consumers consider a health plan’s provider network to be a very important factor when selecting a health insurance plan. 

Data accuracy is not only essential to assist consumer decision-making but it is also an important way for health plans & healthcare organizations to control costs & reduce network leakage. The cost is further compounded by fines from Centers for Medicare & Medicaid Services (CMS) and other government agency reaching as high as $25,000 per beneficiary for data errors.

So how do healthcare organizations manage the overwhelming amount of ever-changing provider information? 

Here are 5 ways to optimize your provider network data for better consumer experience & accuracy compliance.

1. ​Simplify the complexity of provider data
2. Create a single, authoritative source of provider information
3. Regularly check, score, & scrub your data
4. Enable real-time consumer support
5. Obtain consumer/member feedback