Looking back to when some of the major stock indexes plunged in March, it was unclear just how much of an impact COVID-19 would have on the financial markets, let alone on society as a whole. But, as we cross a year into the pandemic, we can now see that while this year’s market volatility has created many challenges, it has also uncovered opportunities and areas ripe for investment.
Notably, there are a few healthcare stocks that are expected to perform well in the coming year, such as Pfizer with the rollout of its vaccine. While COVID-19 has created visibility for Pfizer and other healthcare stocks, there still remains a constant battle being waged against diseases that have yet to be cured and, as innovation in healthcare continues to emerge, the companies behind these cures will provide investors with attractive new opportunities.
Before one can make an investment decision, they must have a complete view of these companies and information on the drugs they make. A few questions that might be raised by investors in regard to each company include:
- How has it performed historically?
- How many drugs of this company have been approved in the past?
- What are the ailments remedied by the drug?
- Which drugs are in which trial stage?
- Have there been any important events and/or announcements associated with the given drug?
Seeking answers to the above questions can be quite the challenge for investors. Oftentimes, information on healthcare companies and their historical performance is provided by some of the more standard market vendors, whereas information on the drugs they make is spread across multiple datasets and sourced from specialist providers. In the below, we review solutions to the various challenges investors face when dealing with healthcare data:
- Integration: Integrating with specialist data providers to bring in datasets is a challenge that is further exacerbated by the fact that each such provider has their own nuances when it comes to accessing data. This integration often results in a time-consuming and costly process if one does not possess out-of-the-box adapters required for these sources.
- Complete View: In order to build a clear narrative, one must be able to properly stitch together disparate datasets. For example, one dataset may hold the brand name of the drug, another may hold the companies that are involved with the drug, a third may hold the ailments solved by the drug, while yet another dataset may hold all of the important events pertaining to that drug. With this, users must be able to master the data in such a way that they can begin their analysis by looking at the company as a whole and from there, drill down into its drugs, the various ailments it treats and event details.
- Deduplication: Another challenge arises from the fact that the same drug might have different names in different provider systems. For example, the antisense agent Affinitak in one source might be referred to as Affinitac in another. It is important that users don’t end up creating duplicate records for what is essentially the same drug. Because of this, the master data management process must support smart reconciliation/deduplication across multiple sources.
- Data Governance: Even after the above challenges have been addressed, there is still a chance that the data provided by the source is incorrect or incomplete. For example, the brand name of the drug could be missing, in which case the data must be governed to ensure that users are accessing clean and accurate data.
- Real-Time Access: When it comes to mastering data from different providers, the frequency of changes poses yet another challenge. Some datasets, like those pertaining to exchange data of companies, change almost every minute. Because of this, users must be able to easily access the latest data available in real-time.
While there are many more challenges, like source prioritization and data discovery from third-party applications, we believe the above five are the most important to keep in mind when dealing with healthcare data. By leveraging IVP’s Master Data Management suite, managers can address these challenges with:
- Out-of-the-box configurable adapters to most major specialist data providers like Biomedtracker, GlobalData etc.
- The capability to link different datasets from the user interface
- A built-in Reconciliation module to prevent duplication of records and create a golden copy
- Clean and accurate data using the Data Governance module
- Connectors to source systems that allow for real-time data pulls