Real-World Data for Healthcare: A Practical Handbook

Written by: Amanda Cohen, MPH

Real-world data (RWD) holds great promise for organizations in the healthcare industry. For example, during the COVID-19 pandemic, life sciences organizations used RWD to generate evidence on vaccine effectiveness, model localized strategies for controlling the spread of the illness, identify potential symptoms using smartphones, study how lockdowns influenced mental health, and assist in policymaking.

Practical uses of RWD during the pandemic are just the beginning of the possibilities for this abundant source of information. This handbook provides an overview of where to find real-world data and how RWD is used in the healthcare industry, from developing treatments and therapies to improving biopharmaceutical safety to refining marketing messaging.

What Is Real-World Data in Healthcare?

According to the United States Food and Drug Administration (FDA), RWD includes routinely collected "data relating to patient health status and/or the delivery of health care." This broad definition encompasses everything from health outcomes to diagnostic trends to treatment costs. Healthcare RWD comes from various sources, such as electronic health records (EHRs), disease and product registries, digital health technologies, and even social media (Figure 1).

Figure 1. Common Sources of Real-World Data in Healthcare

Specific examples of RWD in healthcare include physician notes from annual check-ups, vitals readings from wearable devices, lab results, health-related social media posts, information from patients enrolled in a metabolic disease registry, claims for services provided, reported service costs, and much, much more.

3 Ways Real-World Data Is Used in Healthcare

Real-world data presents new opportunities for the life sciences and healthcare organizations involved in developing treatments and providing patient care. In clinical research, RWD unlocks new ways to study diseases and can help researchers evaluate treatment effectiveness for broader populations. In medication safety, RWD can improve how physicians track adverse events. Additionally, RWD gives healthcare marketers methods for directed promotion.

RWD Expands Clinical Research

Life science organizations can use real-world data to answer research questions, uncover clinical patterns, and test hypotheses. RWD expands the breadth and length of studies, allowing researchers to see the effects of treatments and therapies on more patients for longer periods of time. Using RWD for clinical research has challenges, but as data processing technology continues to improve, the opportunities for RWD to transform research continue to grow.

Randomized Clinical Trials vs. Real-World Data vs. Real-World Evidence

Unlike the highly controlled data gathered during randomized clinical trials (RCTs), RWD in healthcare is not generated specifically for research. However, RWD can generate real-world evidence (RWE). RWE is a trusted source of information used in regulatory and clinical decision-making. Where RCTs may show the efficacy of a new treatment, RWE can show whether or not it is effective for a wider population over a longer amount of time.

For example, consider a trial of a new medication for controlling glucose levels in patients with diabetes. Researchers conduct multiple RCTs to demonstrate the medication's safety and efficacy. However, results from the RCTs only show how well the medication worked for patients with the time and opportunity to participate in the trial. Researchers then use RWE generated from the RWD in patient registries and EHRs to evaluate the medication's effectiveness for a much larger, more demographically diverse population.

RCTs and RWE studies are complementary yet very different. Table 1 provides a brief overview of the differences between RCTs and RWE studies.

Table 1. Real-World Evidence Compared with Randomized Clinical Trials

RWD in Prospective and Retrospective Cohort Studies

In addition to building the RWE to supplement information from RCTs, RWD can be used in prospective and retrospective cohort studies. These studies analyze data collected from select groups of people to find insights into how diseases develop (prospective cohort studies) or how a certain factor influences health outcomes (retrospective cohort studies). Prospective and retrospective cohort studies provide valuable insights for developing new treatments and improving patient health.

RWD Sources Used in Clinical Research

The RWD used in clinical research comes from EHRs, disease and patient registries, and financial data, such as claims and remits. RWD must be used with the patient's permission and de-identified before use. Often data undergoes tokenization-replacing protected data with unique identifiers that can't be tracked back to an individual-before use. Examples of RWD used in clinical research include:

• Medical, environmental, and social data from the point of care
• Clinical notes
• Diagnoses
• Lab results
• Longitudinal views of specific populations
• Costs incurred
• Medical procedures performed
• Admission type and discharge status

RWD sources provide clinically rich data with the potential to understand diseases from all angles. For example, clinical notes could reveal social or environmental factors influencing symptom development. RWE generated from RWD research sources helps researchers better understand health trends, disease burden, and product effectiveness and meet post-market regulatory requirements.

Veradigm Real-World Data Solutions for Clinical Research

Veradigm offers many solutions to help life sciences organizations use RWD in their research. Veradigm Network EHR Data allows access to over 154 million patient records gathered during a five-year period. This data from Veradigm is sourced from ambulatory clinics across the country and includes geographically, demographically, and socially diverse patient populations. To simplify data use, Veradigm uses standardized organization and definitions of variables across sources.

Veradigm proprietary Natural Language Processing (NLP) models extract crucial clinical insights from semi-structured and unstructured EHR data and transform them into research-ready data, offering a more comprehensive understanding of therapy decisions, disease progression, and patient outcomes.

Veradigm also offers NLP-enriched EHR data tailored towards therapeutic areas of interest such as Cardiovascular, Metabolic, Immunology, and Central Nervous System. Veradigm Cardiology and Metabolic Registries are curated databases with cross-sectional, geographically dispersed patient populations ready to use for prospective, protocol-driven research.

RWD alone can't generate valuable insights. Datasets require organization and evaluation before use. The Veradigm Real World Evidence service team can help life sciences organizations analyze RWD and navigate the research process. Researchers can also use the Veradigm Real-World Evidence analytics platform to analyze RWD on a granular level.

RWD Improves Pharmacovigilance

In addition to enhancing clinical research, real-world data has practical implications for expanding pharmacovigilance-the practice of monitoring the adverse effects of prescription medications. Adverse effect reporting is mostly done by healthcare providers. Reports help life science organizations refine treatments to improve patient comfort and safety. In some cases, adverse effect reporting data also informs regulators when to remove a medication from the market.

Unfortunately, reporting adverse events is easier in theory than in practice for busy healthcare providers. Often, reports for adverse events require separate forms than those used in everyday visits, and healthcare providers don't have the time to complete them or follow up with patients. A recent systematic review found that underreporting of adverse drug reactions was a massive problem worldwide; in many countries, over 90% of adverse events went unreported.

How Technology and RWD Improve Safety Reporting

Simplifying identification and documentation for adverse events will help increase the percentages of adverse events reported. Technology using innovative artificial intelligence solutions like NLP can help identify potential safety events in RWD sources like EHRs. NLP-equipped software does the work of noting a potential adverse event and pulling together medications taken by the patient to help healthcare providers make informed decisions.

Technology using RWD can integrate directly into EHRs so that providers can identify and report adverse events at the point of care instead of waiting to complete reports later. There are two approaches to this task: either unidirectionally, where the technology sends an alert about a potential adverse event to a physician, or bi-directionally, where technology sends an alert, and the physician provides additional information. Figure 2 outlines the process.

Figure 2. Enhancing Pharmacovigilance Through RWD

Veradigm Real-World Data Solutions for Pharmacovigilance

The Veradigm Network includes a large healthcare provider base-ambulatory clinics nationwide that rely on Veradigm solutions to meet clinical, financial, administrative, and revenue cycle needs. Providers connect to Veradigm at the point of care, when patients are sitting in provider's offices and talking about medication adverse events. Technology-enabled pharmacovigilance programs require this type of connection and alignment between technology, clinical research expertise, and the user experience.

RWD Improves Focused Healthcare Marketing

Real-world data has the potential to help healthcare marketers inform providers about new treatments, therapies, patient support and tools. Data-driven approaches to marketing are not new-most marketers recognize the value of using information to form insights into who they are trying to reach. However, the level of detail and accuracy of data sources impact the quality of the insights formed. Surface-level or inaccurate data makes for ineffective marketing strategies.

Real-world data in healthcare, in contrast, provides the in-depth information that marketers need to reach exactly the right healthcare providers at their decision-making point. RWD for healthcare marketing comes from EHR systems and includes:

• Demographics
• Lab tests and results
• Vitals
• Co-morbidities and diagnoses
• Existing treatments
• Insurance
• Provider engagement velocity

Analyzing these data gives marketers insight into where brand exposure will yield the most benefit. Take this scenario, for example. A marketer for a pharmaceutical company is researching channels for increasing healthcare professional exposure to a new hypertension medication. RWD helps them identify providers who frequently diagnose hypertension and/or co-morbid conditions and prescribe anti-hypertension treatments. When the marketer promotes to these providers, awareness of the new medication tends to increase.

Focused marketing benefits healthcare providers and patients as well. Busy healthcare providers will know what appropriate medications are available to them without doing additional research, and patients can become aware treatments demonstrated to address their health needs.

Case Study: Medication Marketing for Major Depressive Disorder

Although the vast majority of medications for major depressive disorder (MDD) are prescribed by primary care providers, the manufacturers of MDD medications tend to focus primarily mental health specialists in promotion which may omit healthcare providers who could prescribe their products, and patients were missing out on learning about new medications.

The pharmaceutical company worked with Veradigm Digital Health Media to find primary care providers prescribing MDD medications, diagnosing MDD, and working with patients with MDD. Then they advertised to the highly targeted audience via their EHR platform. The healthcare providers most likely to benefit from new information on MDD medications received the advertisements directly on the platform they used for everyday work.

Veradigm Real-World Data Solutions for Healthcare Marketing

Biopharmaceutical marketers can use RWD to develop targeted messaging for healthcare providers through the Veradigm Digital Health Media solution. Veradigm Digital Health Media provides messaging via EHRs so providers can see ads when they are making decisions about patient care. The solution is safe and compliant and allows access to the Veradigm Network of EHR platforms, the largest ambulatory EHR user base in the US.

Veradigm Bridges Real-World Data Solutions

Veradigm is uniquely positioned to help make the promise of the value of real-world data in healthcare a reality. Our services lie at the intersection of healthcare providers, payers, and life sciences organizations, and our solutions have the integration capabilities to work with other systems. Whether you are considering RWD for research, marketing, or improving patient safety, we have the services to help. Experience Veradigm's solutions by scheduling a call with a Veradigm expert today.

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