The Importance of Data Collection in Public Health

In today’s world, the significance of data for an industry is essential for decision-making, innovation, and more. It’s especially true for organizations operating in the field of public health. As the healthcare sector increasingly relies on data-driven solutions, the efficient collection of public health data has become a paramount concern.

Nevertheless, stakeholders involved in research often encounter challenges in gathering and evaluating data, hindering their ability to derive meaningful insights from it. This predicament underscores the immense value of data collection in public health and its potential to deliver tangible benefits to communities.

To dive into why it’s so vital, let’s look at the role data plays in public health, why the field relies on it, and how to close the gaps in its collection and use.

What Role Does Real-World Data Play in Public Health?

The inclusion of real-world data delivers value in any research application. In public health, real-world data’s (RWD) role is becoming more prominent.

Data can fuel this mission to enable:

Improving HEOR model accuracy: Health economics measures and values the outcomes of healthcare interventions. Outcomes research evaluates the effect of healthcare interventions on patients. Access to quality RWD is critical for enabling these disciplines.
Increasing predictability of models for emerging public health emergencies: Healthcare data is pivotal to public agencies gaining more confidence in their projections of public health issues, from the next pandemic to the impact of environmental changes on human health.
Addressing social determinants of health (SDOH): These environmental conditions impact the health of citizens and their access to care. If public health organizations can obtain diverse healthcare data, they can draw more conclusions about how SDOH influences a population’s ability to receive care and develop programs to address the needs of these underserved groups.
Accelerated research for new drugs and treatments: Collecting healthcare data related to a specific disease and how it affects different people, including symptoms and responses to therapy, can be crucial in public health defenses to these ailments. The more data available across a diverse population, the more information life sciences researchers have to improve drugs and treatments.

How Is Global RWD Currently Used?

Global healthcare data drives outcomes in the healthcare ecosystem in many ways, including research, policies, investigations, and planning. However, many use cases are still hungry for more of it.

In order for healthcare data to have a positive impact on public health outcomes, it must create actionable information. This requires proper context, completeness, and accuracy.

However, many public health data sources do not follow a specific standard, creating challenges for how the information can be used and questions about its transportability across borders. Ideally, there would be interoperability and standardization in sharing global public health data. Unfortunately, experts in the field have identified multiple barriers to achieving this, including technical, motivational, economic, political, legal, and ethical challenges.

Despite these obstacles, global RWD usage has been effective, particularly during the pandemic. Data played a critical role in helping public health agencies understand the virus and provide recommendations to citizens on protecting themselves and others.

The World Health Organization (WHO) collected and analyzed such data, benefiting many worldwide. For example, WHO issued weekly Situation Reports regarding the virus, delivering global, regional, and country-level information about cases and deaths. These epidemiological reports also highlighted trends to inform decision-making by public health authorities. In addition, WHO also operates the World Health Data Hub, which is a digital platform involving the collection, storage, analysis, and sharing of global health data.

Similar to the WHO, the Centers for Disease Control and Prevention (CDC) also emphasizes the importance of data collection in public health. The CDC states that consistent and detailed data helps identify and address public health issues. They seek better coordination of data across the US from states and healthcare providers and have determined that data modernization and data authority are areas in need of improvement. These efforts are necessary to support use cases such as:

Prevention and mitigating the spread of future outbreaks
The empowerment of localized agencies to act more efficiently
Delivery of more timely insights for action
The identification and monitoring of outbreaks
Forecasting how outbreaks and public health conditions could progress

As the world becomes increasingly interconnected and complex, access to varied sources of quality RWD will be essential to better enable these use cases.

Why Do We Rely on Data?

Healthcare and life sciences are reliant on data as a means to drive better decision-making. It’s an objective source that paints the reality of what’s happening in population health, investigating outbreaks, spurring innovation in treatments, preventing diseases, and much more.

Without data, public health would only be able to respond to the present with no way to look at the past and future.

Reliance on data is a proven process for healthcare to improve and evolve. However, much of the genomic data available isn’t global. By rethinking how we rely on data and what makes it complete and high-quality, public health can gain more clarity, with implications for five distinct areas of public health.

Epidemic and Outbreak Investigation

Responding rapidly to epidemics and outbreaks is critical for public health entities. It allows the delivery of precise and accurate recommendations to their communities. It was a crucial component in the COVID-19 pandemic, as the WHO already had an Outbreak Toolkit in place for epidemiologists and investigators to source updated data and tools.

Investigations also collect genomic sequencing data to track the spread of a virus and how it mutates. These insights then feed into public health procedures.

Identifying data sources and collecting information from them is a critical step in any investigation. Ensuring the data is accurate, enriched, and diverse will continue to be crucial to accelerating investigations and creating action plans.

Health Promotion and Disease Prevention

Public health agencies have a mission to promote healthy living and prevent diseases. Data that provides a holistic view of populations and their associated SDOH can help deliver relevant messaging and drive people to make lifestyle changes, such as smoking cessation, exercising more, and eating a balanced diet.

A good example of this is the prevention of chronic diseases, such as diabetes, that can be mitigated or controlled through lifestyle modifications. If a public health organization can gain knowledge about specific populations with elevated disease rates influenced by SDOH, it can strategically direct programs toward those individuals.

Health Policy and Planning

This area of public health addresses the development, implementation, and assessment of policies to improve patient outcomes. These policies often include guidelines for the benefit of patients, providers, and health systems.

In this realm, data holds significant importance as policies are constantly evolving and require regular updates. Data plays a leading role in assessing the effectiveness of existing policies and identifying emerging challenges and issues. It helps ensure that policies remain responsive and adaptable to the evolving healthcare landscape.

Emergency Preparedness and Response

Public health organizations are responsible for being prepared to act quickly in emergencies and work with many other stakeholders and agencies to plan for worst-case scenarios.

All parties involved need data to improve these responses, and analyzing data from previous episodes is essential for assessing and improving performance. In addition, trends in population data could also impact how an area prepares and what type of emergency might have an increased probability of occurring.

Drug and Therapy Development

Lastly, drug and therapy development depends on plentiful data to inform all steps of the process. Public health data can significantly contribute to life sciences researchers and drug makers.

These processes are often inefficient and slow; data can close some of these gaps. Real-world data, which public health collects, has become essential and is a focus of the 21st Century Cures Act, emphasizing its value for the life sciences industry.

While there are massive amounts of different types of data in public health, and the entire ecosystem agrees on its value, it often falls short of the promise.

How Global RWD Often Falls Short

Interoperability issues, lack of standardization, and compliance and privacy concerns are continuing challenges in global healthcare data. In addition, available data tends to have a US and European bias, while sources of data outside these regions may be incomplete or inaccurate.

The WHO is trying to diversify its real world data sources. Their data collection efforts include population-based sources, including household surveys and civil registrations. They also gather from institution-based sources. The WHO states it has data from 198 countries, which it uses for its World Statistics Report.

It’s a rich dataset but doesn’t contain information from every nation. As of 2023, 195 independent sovereign nations, 60 dependent areas, and several disputed territories exist. The reportIt includes 58 health-related indicators but isn’t complete for every country. There are gaps, for example, in life expectancy, new HIV infections, Malaria incidence, neonatal mortality rate, maternal mortality, and more.

The ultimate objective is to ensure that healthcare diagnostics and treatments are both effective and inclusive, catering to the global patient population. To shape the future of care and treatment, it’s crucial to generate research insights that go beyond the traditional focus on US and European cohorts in clinical trials. By harnessing real-world data from underrepresented or unknown populations, we can bridge the gap and pave the way for significant breakthroughs.

The Future of Healthcare Depends on Global Data

The importance of data collection in public health is critical for action, response, and innovation. It serves as the backbone for enabling the investigation of outbreaks, prevention of diseases, improvement of policies, preparation for emergencies, and development of drugs and therapies.

Sources of data including electronic health records (EHRs) maintained by healthcare providers and hospitals, genomic data, payer and claims data, and other sources provide vital pieces of the puzzle. When combined on a global scale, these sources can revolutionize global health equity and improve patient outcomes.

Syndesis is building such a community to propel research and innovation through unified access to global real-world clinical data from untapped sources. Contact our team today for more information on becoming part of this network.