Big data is a big topic for healthcare
Big data analytics in healthcare is crucial for improving national health equity and promoting positive health outcomes. Both the standard medical data points (think medical research data, as well as patient-specific chart data) and lifestyle factors are important to unlock new use cases and opportunities.
When merged, medical and non-medical data points showcase a patient’s ability to thrive outside a traditional healthcare setting.
The new Comprehensive Patient Profile analysis includes more than it used to
When we think of ourselves as patients, it’s clear that medical data can only paint a portion of the picture of our health. Many of our everyday lifestyle choices and the characteristics of the community we live in, have an incredible impact on our health.
In fact, 80% of an individual’s health is determined outside of the doctor’s office.
The healthcare industry is taking action in data collection and analysis with non-medical data, which is critical to reimagining how to best support patients. With big data at the forefront of the health equity movement, access to consumer data can be transformational as healthcare providers seek to better serve their communities.
Social Determinants of Health — not optional in modern healthcare
Even with a robust treatment plan in place, social factors have an incredible impact on the outcome for a patient. Some may even argue – without evaluating the patient’s Social Determinants of Health (SDOH), it can be difficult to build a treatment plan that will yield a best-case outcome.
Here are examples of SDOH data points:
- Access to Care & Health Barriers
- Access to Technology
- Core Demographics
- Economic Insecurity
- Food Insecurity
- Geography (e.g., urban vs. rural)
- Housing Insecurity
- Language Proficiency & barriers
- Social Isolation
- Substance Abuse (including smoking)
- Transportation Barriers
Data comes first. Understanding is next.
Big data analytics in healthcare provides a three-dimensional view. This new viewpoint gives organizations new insights, including life circumstances and differences that may play a role in a patient’s health and wellness.
Predictable, scalable, and reliable data fuses individual data points to form new insights. These new insights, when applied with real-world action, are what is required to progress health equity. Without large-scale data – providers may not have the information they need to effectively serve their communities and address unique healthcare needs individually.
SDOH: A major factor in pandemic research
Research conducted using AnalyticsIQ data showed that the COVID-19 pandemic disproportionately impacted disadvantaged communities and ethnic groups. Ultimately, the pandemic revealed what was true even before 2020: there is still much more to be done. We have a great deal to accomplish to address the ever-present gaps in the healthcare system.
Dozens of research organizations, including Northwestern Medicine, Johns Hopkins, and UC Berkeley, all conducted independent research using AnalyticsIQ data. They found that the effects of COVID-19 mirror some of the existing disparities we’ve seen in the healthcare system.
The studies were conducted during the height of the pandemic, with over 1,500 researchers participating. Although many organizations conducted independent research and focused on multiple niche topics, they continually confirmed some larger findings. Two key insights from the research include:
- Households with an annual income of less than $49k show higher representation in both COVID-19 cases and death
- Hispanic Americans were 4x more likely to contract COVID-19
Data use cases: the science of going from Pandemic to Endemic
As we look back at this research in a post-pandemic world, it is important to recognize the impact of granular level, non-medical data. These insights are powerful as we aim to be better prepared to overcome healthcare challenges in the future. Consider the endemic struggles your patient population is facing today. How is your organization applying non-medical data to identify better solutions?
Like COVID-19, although the opioid epidemic affects people of all races and ethnicities, certain minority groups have been disproportionately impacted. For example, African Americans and Hispanics have historically had lower rates of opioid misuse. However, they are more likely to die from opioid overdoses due to limited access to addiction treatment and other factors.
Obesity and related diseases (Type 2 Diabetes, Cardiovascular disease, etc.)
Rates of obesity and related chronic diseases such as diabetes and heart disease are higher among certain minority groups, including African Americans, Hispanics, and Native Americans. These disparities are often linked to structural factors such as poverty and limited access to healthy food options.
Environmental health issues
People of certain ethnicities are often disproportionately impacted by environmental hazards such as air pollution, which can contribute to higher rates of respiratory illnesses and other health problems.
Mental health crisis
Mental health disparities exist across race and ethnicity. Still, minorities are less likely to receive care to address them due to cultural stigma, lack of insurance, and other factors. In addition, certain minority groups face unique stressors related to discrimination and racism that can impact mental health.
Big data analytics in healthcare can have a very direct impact on patient care
Overall, big data analytics in healthcare can improve existing use cases that are currently operating with a less-than-complete picture:
- Identify patient needs and habits
- Create plans to improve patient adherence
- Track population health across communities
- Uncover gaps and biases present in patients or study participants
- Develop the correct devices and treatments
Clearly, evidence-based information is necessary for the advancement of the healthcare sector. A patient’s health and genetic predispositions, race, ethnic background, and life events should all be considered.
AnalyticsIQ data is a powerful tool for outcome-driven healthcare organizations
We believe in using big data for good and are proud to partner with amazing healthcare research organizations, major health systems, retail healthcare brands, and Pharmaceutical brands that are focused on delivering better outcomes.
With data-driven insights at the crux of healthcare innovation, equity, and access – the possibilities are endless.
AnalyticsIQ data is highly effective and predictive. This is due to our coverage of the overall population, as well as the depth of attributes that deliver a full view of the patient population. With 1500+ people-based data variables, healthcare teams are armed with the data they need to provide exceptional, accessible, and affordable care to their communities.
For more information on AnalyticsIQ and how HealthIQ can help your organization to better serve your community, please visit our Health & Wellness center. We love to partner to solve complex issues with the power of predictive data.