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Until now, developing health care insights and understanding a product’s real-world value proposition have been developed primarily from claims data. Research scientists have also anchored much of their insight-generation on the slices of information related to billable activity.

Claims-only data, although crucial, doesn’t provide the most complete representation of the human activity and clinical complexities that impact drug or medical device performance.

By their nature, the most common approaches can provide only limited insight. They don’t include information captured in a clinical environment, such as: disease severity, symptomology, health measurements, and laboratory values. 

Integrated data breaks through limits of traditional analysis to complete the value story

Using the traditional model, value is frequently measured on cost reduction or avoidance and analysis is conducted by leveraging a claims-only data foundation. This is understandable given the availability and familiarity of claims data. Common outcomes of interest tend to be health care utilization metrics. It’s what claims data captures and what it’s able to return to us as insight. Using these data to make decisions on coverage, benefit design or other engagement models is straightforward. They can guide recommendations about shifting the site of service.

But here’s where it gets more difficult: assessing the full impact of other decisions, such as switching medications or comparing the efficacy of treatment options. Measuring clinical benefits in these cases has usually been derived from clinical trials, which are also limited in their inputs. While the assessment is valuable, it’s still using only one dimension to assess impact.

True value, and the value upon which a growing number of contracts and formularies are based, is not just lower cost. It’s the combination of improved clinical outcomes and reduced cost — the net value of the treatment.

Life sciences research: Adding new dimensions to complete the value story

Today, clinical data has reached the level of maturity where it can be a powerful addition to life sciences intelligence gathering. Information is now collected from electronic health records (EHR) and unstructured clinical notes. It’s a new way of looking at data that provides richer and more valuable information for life sciences researchers.

This clinical information includes: diagnosis codes, signs and symptoms, observations, measurements, biomarkers, and lab and other test results.

Natural language processing and advanced analytics pull meaning from provider notes and add a rich layer of insight into patient journeys and clinical outcomes.

Reliable calculations of the cost and clinical outcome equations are what value-based or risk-bearing arrangements should be built upon. That is, if we truly want to change the trajectory of health care expenditures. And this is where health care is clearly moving.

Asking the right questions to gain richer insights

As researchers continue to evolve their real-world data and evidence strategy, three key questions arise:

  1. Does our approach address the challenges of an evolving health care system?

To participate in new payment arrangements that are driving a shift from fee-for-service to fee-for-value, health organizations must be able to predict clinical and financial performance. They can look to their life sciences partners and the products and service  these partners provide to contribute to their ability to manage that risk.

  1. Do I have the right sets of real-world data to evaluate cost and clinical outcomes?

This is a vital question because the current standard approach cannot help you best prepare for head-to-head clinical trials, recognize changes in clinician behavior or measure clinical outcomes. Without these inputs, it’s nearly impossible to calculate a path to the most improved outcomes at the lowest cost.

  1. What will it mean to amend my process?

The process of using integrated data is not dramatically different from the current approach. Working with clinical data does add a rich new layer of information, and therefore, another layer of evaluation and complexity. But it builds rationally on the current claims-only approach, which we can delve into further.

Become more targeted in your research with clinical and cost insights  

The potential impact that integrated data can have on the issues plaguing the health care system is significant. And the system is at a tipping point.

The pressure to reduce cost and improve outcomes is present in every conversation. Integrated data is now available to use at scale. It’s a powerful new tool that collects the level of insight needed to make more precise business decisions, creates more comprehensive value stories, and delivers the low-cost, quality outcomes that the market demands.

Read the Optum whitepaper to learn more about Integrated data: Creating a dimensional view of outcomes and cost