Complying with Public Disclosure Requirements
As the dates set for public disclosure requirements, Jan of 2022, draws close with every passing day, it is best for everyone involved if health plans got themselves aligned with these requirements. Compliance would ensure faster delivery of quality care, resulting in reduced visits to the hospital, thereby healthier members.
Disclosure requirements for public files pose a challenge – identifying the required information and converting them into the targeted file formats. Even though the public file generation process is executed every month, the computation and technical complexities involved are rather high.
In-network Negotiated Rates File
As the name suggests, the file will contain negotiation details of the covered services offered by in-network providers. Negotiation arrangements can range from capitation, performance-driven payment, bundled payment, to fee-for-service. These negotiations may not be pre-defined or calculated for each service.
One example is referenced billing, where the amount requested by the provider and the amount paid by the payer will be calculated based on the CMS reference table with a multiplier. Another example of an arrangement is that the payer would pay 80% of the amount, the provider has requested for a service.
All these types of arrangements create complexity while extracting and consolidating information concerning service codes and providers.
One approach would be to identify the service/billing code & negotiation amount before capturing the respective providers. Identification of providers is segregated based on Tax Identification Number (TIN), as one provider can provide their services from multiple locations/facilities. In those scenarios, the same provider would use different TIN.
Out-of-Network Allowed Amounts File
When a member avails of services from an out-of-network provider, there is a maximum fixed amount that a health plan would pay based on the provider’s place of service, and member’s eligibility.
Based on the rule, first and foremost, the solution needs to identify all the adjudicated claims for the first 90 days from the last 180 days, based on the date of service. Once those claims are identified, segregation of records would be based on out-of-network and in-network claims. Once this category is established, the next step would be to create subsets based on the provider’s NPI and TIN. A provider may have billed amounts from different TINs. Once the combination of NPI, TIN, billed amount, and allowed amount has been identified, it would be grouped by their place of service.
In-network Prescription Drugs File
Pharmacy medications provide a different challenge due to changes in market pricing over time. That is why the rule has mandated to include the historical net price as well. However, the historical net price would not be readily available, it needs to be calculated based on the month of the file publication. The solution needs to check all the prices, within a specific timeframe, and compute the historical price. Other than the price itself, medication dispensation comes with an administrative fee, dispensing fee, transactional fee based on the National Drug Classification (NDC) code and the place of service.
As negotiations for medication can apply to a group of providers, such as Independent Practitioner Associations (IPA), it can align with National Council for Prescription Drug Programs (NCPDP) Chain code. In this scenario, all the pharmacies that come under single-chain code would follow the same negotiation contract for drug billing.
The approach would be to club information initially based on the medication name, type, and NDC code. After that, the solution will look for provider details with whom health plans have negotiations based on the medication. The solution would find previously agreed negotiated rate, administrative fee, dispensing fee, and transaction fee within those negotiations. As there are thousands of NDC codes, their combination with innumerable providers would result in an extensive amount of information lined up for publishing.
All the above files will contain plan identifier, plan market type, and the last updated date of files. The format and examples of all JSON and XML files are present at GitHub. Based on the requirement, the volume of records for each file can range from thousands to millions. Even though the file is generated once a month, the solution needs to account for the volume of data as well as the time required to extract and convert it into JSON or XML files.
We Can Help You Out
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Pankaj has vast experience ranging from claims processing engine to application of machine learning algorithms in US Healthcare. As a Healthcare Business Analyst, he is passionate about addressing healthcare data/process related challenges and ideating solutions for clients.All stories by: Pankaj Kundu