What to Know When Sourcing Data
Beyond the Surface: Understanding Your Data Sources’ Impact on Healthcare Marketing Strategy
If insights are the foundation of strategy, then data stands as the very bedrock of those insights. Thus, an innate connection exists between the quality of data and the caliber of strategic decisions. In the current business landscape, a considerable portion of companies are funneling resources into analytics, and many are delving into the promises of AI. Surprisingly, however, less attention is dedicated towards data input. This is especially true in the healthcare marketing space.
When navigating the realm of data options, two prevailing paths come into view: an inclination toward arbitrary brand preferences or a perception of data as a mere commodity. Nonetheless, the truth is that while data origins might share similarities, disparities in acquisition methods, sources, and quantity are rife. Amid the evaluation of data for commercial analytics, a comprehensive consideration of the following factors is essential:
Source: Open or Closed Source
Closed-source data is captured at the payer level, one payer at a time. While it encompasses all or most claims from a given payer, it is confined to the patient subset of that payer’s plans which leads to smaller data sets. Moreover, closed-source data inherently carries biases toward the formularies and networks covered by the plan. For these reasons, closed source data tends to be less favored for marketing endeavors.
Open-source data, in contrast, is captured during the adjudication process between providers (HCPs or pharmacies) and payers. This type of data encompasses a wider array of payers and, consequently, captures a broader patient pool, larger practitioner volumes, and more claims spanning all plans. The result is a more comprehensive dataset primed for commercial analytics.
Data Capture: More is Better
Healthcare data capture wields substantial influence over shaping commercial operations. The increasing digitization of healthcare processes and increased volume of data being generated is expanding the opportunities for analysis and insights. This has spurred a range of new data company entrants. These emerging players often possess limited samples of claims data sourced from only one or two data sources.
While these new players can present enticing platforms and promise economic advantages, it is crucial to acknowledge the pivotal role that data depth and the breadth of underlying data assets play in ensuring the accuracy and reliability of outcomes. Limited data samples may inadvertently lead to incomplete insights, hindered trend identification, and less-informed decision-making. In a world where precision matters, healthcare stakeholders must balance the allure of platforms and economic efficiencies with the critical need for comprehensive data capture.
Data Linking: 1+1 > 2
Within the current landscape of healthcare analytics, the ability to correlate medical and prescription claims has taken on heightened significance. The proliferation of drugs with multiple indications underscores the importance of understanding not only the prescriber but also the purpose of prescription. This contextual insight is as vital as the prescription itself. Linking medical and prescription claims provides a comprehensive narrative of a patient's journey, shedding light on the conditions being treated, the efficacy of interventions, and effectiveness of commercial activities.
In the absence of robust data capture that seamlessly intertwines prescriptions with diagnoses, a critical risk arises: the potential oversight of insights pivotal to informed commercial decision-making. It's through understanding this interconnection that marketers can craft strategies that resonate with patients' experiences and needs.
Data Rights: Unleash Your Insights
Gaining a firm grasp of your data suppliers' rights is fundamental for responsible data utilization. The terms governing data access, usage, and sharing can differ vastly among suppliers. Certain companies may be confined to using the data solely for analytical purposes, lacking the ability to disseminate the foundational data itself. Others might be restricted to using data access within the confines of their platform and prevented from releasing the core-level data such as claims, patient details, and HCP information.
Sourcing data from suppliers with restrictions can pose challenges. The ability to export and blend healthcare data outside of the supplier's platform becomes pivotal for comprehensive analysis and informed decision-making. As the landscape of data suppliers continues to diversify, ensuring that analysts possess the necessary freedom and flexibility to work with the data efficiently and holistically becomes an imperative cornerstone for maximizing the value of healthcare data-driven insights.
The relationship between data and strategic decision-making is indisputable. As companies invest in analytics and AI, the pivotal role of data input cannot be downplayed. This is particularly relevant in healthcare marketing. While data origins may appear uniform, the disparities in availability, depth, and sources can wield significant influence over the insights generated.
In the process of evaluating data for commercial analytics, it's imperative to consider the four foundational pillars: the source, capture process, linking potential of prescription and medical claims, and access and usage rights. In a world where precision matters, the freedom to explore, combine, and analyze data that is connected, thorough, and comprehensive plays a critical role in generating the most informed insights.
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