Big Data

Addressing Data Challenges in MedTech

Big Data

Data analytics can provide a more streamlined view of your customers and simplify the complex challenges faced by medical device commercial operations teams.

The healthcare landscape in the United States is transforming. There is a shift towards hospital mergers and acquisitions (M&A), the growth of group purchasing organizations (GPOs), integrated delivery networks (IDNs), accountable care organizations (ACOs) and value-analysis committees (VACs). These changes have altered the relationships between medical device sales and marketing teams and their stakeholders, leading to new challenges in data collection, retention and analysis.

Critical Data Challenges

The following data challenges faced by many medical device companies can complicate their commercial analytics:

Customer Data Levels: A medical device company has a diverse need for customer views at the enterprise, sales area, transaction, company code, and relationship level. That leads to multiple levels of classification. Compounding the challenge, these classifications come from different applications and systems (e.g., enterprise resource planning [ERP], customer relationship management [CRM], and contract management systems) as well as syndicated sources. This creates a hurdle when trying to cross-reference between multiple end users and tie different definitions or processes together.

Multiple Definitions: Customer and product definitions and hierarchies may vary depending on the source (e.g., CRM, SAP software solutions, JD Edwards software or legacy master data management (MDM) systems from acquisitions). This is a challenge because customers may be defined differently based on the source. Furthermore, customer identifiers may be labeled differently, such as “sold-to,” “ship-to,” and “bill-to”—all common in the medical device industry. How one connects and understands these relationships ultimately helps define the customers of a medical device company.

It is critical for the various members of a sales force to understand the key stakeholders they need to target to drive their value propositions. Yet, due to the varying identifiers, it can be challenging to get a consolidated commercial viewpoint from the ERP systems or syndicated sources.

Account-Based Sources: Most medical device sales teams transact at an account level with centralized decision-makers (i.e., hospitals and IDNs). Sales can be direct, or indirect through distributors, making it difficult to have visibility of the end customer. In some cases, customer data is received from external sources on a lagging basis. Customer accounts can also cut across various product hierarchies and portfolios, from individual products to complete care-delivery solutions.
These permutations and combinations of customer engagements are challenging to track across multiple product categories, complicating estimating and budgeting decisions. These factors make it difficult to gauge demand-generating channel options.

Customer Identifiers: Healthcare organizations (HCO) use many identifiers, including global location number (GLN), tax ID, healthcare industry number (HIN), American Hospital Association (AHA) ID number and Drug Enforcement Agency (DEA) number. These may differ by business unit (BU)/contracting system. These customer identifiers are not standard across HCOs and are obtained from several sources such as contracts, the client CRM and syndicated sources. Therefore, how a medical device company looks at that data impacts its targeting and marketing efforts.

Timing: The importance of date milestones varies based on product lifecycle and type. Capital equipment will typically last 5 to 10 years, will be used by many patients across different specialties and typically requires a considerable, one-time upfront cost. On the other hand, noncapital equipment, which can range from surgical masks and scalpels to blood glucose monitors and stents, is typically lower cost and single-use. Therefore, the factors to consider when sizing markets and forecasting will often depend on the type of device and the time of its purchase.

Contract Access: Medical device companies may have multiple contracts for quoting/pricing at their disposal, and pricing data shows tremendous variation. Depending on which GPO or IDN a customer belongs to every product is priced differently.

Medical device companies may have access to the contracts through an IDN, which has multiple contracts with several GPOs. Pricing complexity increases further as contracts at the regional planning council (RPC) level are included, especially if the sales rep contracted directly with the hospital at the local level. Hence, setting up business rules and understanding primary contract specifics can help medical device companies determine the base price for each customer based on its GPO or IDN.

Customer Purchase Journey: Medical device companies need to understand product/service offerings by procedure, department, care setting, patient type, connectivity, configurability and channel. Typically, the customer purchase journey ties into the complexity of the patient journey. Understanding the care process is critical in understanding sales opportunities. Medical device companies need to carefully research the care journey for each device area as well as their market footprint to determine their future business opportunities and better connect with customers, patients and consumers.

Pricing Levels: There are several pricing models in the medical device industry, including volume-based, tiered, exceptions, field-based, single list, status, affiliation or strategic. And pricing can vary widely according to contracting schemes. For instance, some individual hospitals receive better prices than the largest IDNs. Even within large IDNs, the average sales price for the same product can vary widely across member hospitals. This complicates average price and margin analyses.

Varying Address Definitions: The complexity of customer addresses, including street-front view, building, room, floor or shipping location, increases the risk of duplicates in your system. The ship-to address might vary within the same facility and with the same customer. Therefore, how medical device companies record the “sold-to” and “ship-to” components from a field or a promotional perspective is critical.

Aggregate GPO/IDN Data: IDNs and GPOs lower costs for healthcare facilities by working with suppliers to lower purchasing prices. In the U.S., national GPOs such as Premier and Vizient negotiate contracts, which must be managed and navigated by medical device companies, which then receive regular updates to the membership lists of GPOs and IDNs.

The aggregate GPO sales data will often be necessary to calculate the administration fee paid back to the GPO for the privilege of being a seller within their network. This is difficult in its own right but is further complicated by ongoing M&A activity. As the customers change, medical device companies must ensure they have the correct pricing and a long-term version of institutional sales. Having standards in place to ingest the data to act as a single source of truth for GPO pricing and contracts is key. Also, with the rapid consolidation of health systems, access to GPO/IDN data can help answer questions such as: What price should a specific hospital get because it was formerly part of another health system, and now under a new health system? Does the spend that it incurred over the last few years migrate with it, or does it start anew?

Procedure Data Book: Depending on the device, procedure count data from claims processing sold by third parties can be critical for targeting and sizing. Medical claims data includes information such as ICD-10-CM codes, current procedural terminology (CPT) codes, healthcare common procedure coding system (HCPCS) codes, patient info/demographics and information about payers, practitioners, and facilities. However, procedure data loses value when the device has multiple indications and can be used in multiple suites within the hospital, as it makes it more difficult to determine market share and target customer base.

Market Share Estimates: Medical device companies are good at staying on top of their account-level data. It’s harder, however, to gather sales data on competitors. They gather product and sales information from syndicated sources, and it helps to have medical device companies’ market baskets precisely apportioned to the total sales to derive accurate market share estimates. However, estimating market share can be difficult as many of the syndicated data sources and publicly available data sets, such as the Medicare Provider Analysis and Review (MEDPAR), only include data from acute inpatient facilities. Therefore, it is important to understand from a market share perspective how medical device companies define their market baskets and their share of total sales.

The Potential of Big Data and Analytics to Address Challenges

Cloud-hosted MDM and its integration with existing enterprise applications can help a medical device company navigate data challenges like the ones outlined above. MDM helps create a master record of customers, products and contracts by ingesting and integrating data from all sources and applications within an organization. That results in enterprise consistency for customer and product definitions, KPIs and metrics.

Axtria Data Challenges
Figure 1: Master Data Management addresses all functions of the medical device supply chain

A robust MDM process helps reduce the amount of data wrangling and preparation needed to generate insights. Various analytics models can then be designed to ensure accurate and timely actionable insights at the point of decision. These insights provide multiple operational and business benefits for commercial effectiveness, reporting, pricing/contract operations, analytics and IT teams looking to adapt to the industry’s new dynamics. Data analysis enables:

  • Identification and sizing of new markets and key competitors
  • Customer segmentation and targeting
  • Greater understanding of the customer and their likely propensity for cross or up-sell with other products
  • Production of data-driven value propositions to support sales messages
  • Logical apportionment of marketing budgets to different channels
  • Development of data-driven models for deploying and compensating the sales force
  • Understanding of the account and territory performance
  • Contract evaluation and the right approach in tactics as contracts expire

Supply chain complexities, massive amounts of data, and adherence to specific guidelines and regulations all create challenges for medical device companies. Developing new capabilities, especially a robust data management system with advanced analytics, can drive value for companies by increasing their operations’ speed, flexibility, efficiency and reliability.



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