By Justin Kozik

Precision Master Data Management (MDM) software enables the critical steps of the mastering process to facilitate downstream analytics across the Drug, HCP, and Healthcare Organization (HCO) domains. This paper addresses some of the key challenges and highlights best practices for connecting datasets and creating a single source of truth in each respective domain.

Drug: Creating a product master enables connections to several other datasets, which allows further analytics vs reworking of the product master for each analytics project.

Too often, we see third-party prescription data products as the product backbone. The source of this problem is an initial focus on the two highest-visibility datasets for commercial teams: customer relationship management (CRM) software data and prescription volume data, which may come from third parties. However, when claims or formulary data are added, the master must be reworked or the product dimension compromised for analytic use.

A sustainable MDM system for drugs should create a true “master key” separate from any source dataset and with key levels of parent/child relationships established. In most cases, granularity should be at the product, form, strength, and package (eg, NDC, RxNorm) levels and connected to key identifiers.  Once drugs are connected to RxNorm it is possible to connect to standard drug libraries and explore their attributes by condition treated, mechanism of action, chemical composition, etc. Precision is a proponent of the National Institutes of Health’s (NIH’s) RxNorm project and recommends that clients explore the value of using its components as a cornerstone of their mastering process. Most analyses are conducted at the “brand” level, which is a custom level that should be actively defined by the manufacturer and informed by the source data granularity. The master’s attributes should be updated and bridges maintained as new source data emerge over time to ensure availability for downstream systems and analytics.

The MDM system must also be able create and maintain user defined groupings of drugs, which are often referred to as “market baskets,” including the ability to maintain attributes such as drug equivalence factors within a market basket. Within these market baskets, custom sub-categories of drugs can be created to enable market share calculations for the market and/or sub-market.

Precision focuses on creating a simple, powerful framework for mastering drugs and managing market baskets and other drug attributes, which simplifies managing the product dimension as organizations grow and become more complex.

Health care professionals (HCPs): Precision believes that overcomplication results in bloated systems that cannot react to changing conditions and inflexibility, leading to challenging commercial operations decisions. Emerging pharmaceutical manufacturers have a distinct advantage in that they initially have limited CRM account history and thus avoid many of the most difficult mastering challenges. Precision believes in a simple, transparent system that allows critical compliance and commercial use mastering. Our system focuses on bringing transparency and process to requirements such as determination of golden record rules and overrides, specialty exclusion, and data entry control on new or changed records.

Selecting the appropriate reference source is a critical component, as it typically forms the starting point for all HCP mastering activities. Many of the traditional challenges associated with MDM systems arise from having a limited set of “subscribed” HCPs from the reference data provider. Rules and processes then need to be developed to determine when HCPs should be added to the subscription.  Selecting an appropriate dataset and clear business rules for the subscription streamlines implementation of the MDM technology solution.

Prescribing HCPs and non-prescribing HCPs generally have different challenges related to mastering. Matching HCPs with prescribing authority (eg, MDs, DOs, NPs) is generally a matter of connecting IDs provided that care is taken to include national provider identifier (NPI) and/or drug enforcement agency (DEA) numbers on all source systems to allow matching. Common challenges with prescribing HCPs generally originate from two sources: data change requests from the field via CRM and compliance-driven requirements such as included/excluded specialties for field calls. Adding and/or switching the primary address of an HCP is the most common request from the field. Most companies use the ZIP code of the HCP’s primary address to assign sales representatives to territories. If an address is added or changed and thus leads to a change in sales representative, ensuring that representatives are communicating with the HCP and receiving credit for subsequent sales is critical.

Companies should generally lean towards simple business rules that can be fully automated in terms of overrides. Changing an address is a good example to highlight the complexity of managing overrides to the reference data and the need for clear rules as emerging pharmaceutical manufacturers scale commercial operations. For instance, an HCP, Dr. Smith, has 8 “active” addresses, one of which is recognized as “primary.” Dr. Smith starts spending some of his time at a new office not yet recognized in the reference data, and the address is in a different territory from the current primary address. A business rule will need to be determined for how these data will be submitted to the MDM system, whether the new address should be “created” in the MDM system, and what happens if the request to add the new address is delayed or denied. If a business rule is created to add the address to the MDM system, a complex cascading process is created to manage and resolve that address over time.  Subsequent steps involve determining whether the address should be marked as primary (eg, sales management approval) and what occurs if that address is later added to the reference dataset.

Importantly, the MDM system can adapt to business rules, but streamlining the process is also critical to ensure scalability as the system evolves over time. Precision can help guide implementation of these rules and provide process feedback on the unintended consequences of seemingly simple decisions.

Health care organizations (HCOs): Precision’s MDM system in terms of HCOs is designed to scale to the complexity required by an organization. We encourage emerging pharmaceutical clients to be prudent regarding the complexity that their organization can realistically support over time, as a one-time effort of mapping and cleaning is a very different endeavor from maintaining a clean master of HCOs with history over time.

HCO mastering needs range from very simple mastering of 852 to 867 distribution data to the very complex task of tracking HCO-to-HCO and HCO-to-HCP relationships across datasets and teams.   The two primary challenges that we encounter in HCO mastering typically arise from defining the HCO and making affiliations more meaningful. Unlike HCPs, where an individual is clearly the unit to master, HCOs can be described in multiple ways based on the source dataset and with a multitude of identifiers such as hospitals with multiple DEA and NPI numbers. Second, most analytics involving HCO-to-HCO and HCO-to-HCP affiliations aim to understand the locus of control. With too many affiliations, control signals are not delivered, and little correlation appears to exist between the influence of a health system and the prescribing of its employed HCPs. Precision has devised several proprietary methodologies that allow manufacturers to narrow their focus on defining the HCO and establishing rules for the locus of control when multiple affiliations exist.

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