Healthcare inequity is a pervasive issue plaguing our society, driving a divide in access and quality of care that negatively impacts patients. The reality is that many people cannot receive quality medical care due to factors such as type of insurance, (in)ability to pay, and location. These factors are identified as social determinants of health, or SDoH.
While SDoH can play a significant role in limiting patient access to high-quality healthcare, one solution may lie in utilizing data and technology to bridge this gap. From suggesting appointment times based on the patient’s address to monitoring digital health data to identify interventions, intelligent and AI-driven automation can help streamline essential complex processes that lead to the best care for patients.
When Investment Rhymes with Canada
Canada has a proud history of achievement in the areas of science and technology, and the field of biomanufacturing and life sciences is no exception.
Automation is a powerful tool with the potential to revolutionize healthcare and improve accessibility and patient engagement. To better understand the benefits of using automation in healthcare, it is essential to understand common problems that prevent patients from accessing quality healthcare today. Common hurdles include:
- Transportation concerns: Lack of reliable transportation can be a significant barrier when accessing healthcare. This is particularly true in cases where individuals depend on public transport, have to travel long distances to access care, or aren’t able to drive.
- Geographical barriers: Accessing healthcare may be especially difficult for people who live in rural areas. These patients may have limited choices for speciality care, and may require significant travel time to access premier medical systems.
- Insurance disparities: Underinsured patients or those on Medicaid often face challenges when accessing high-quality care. Unfortunately, not all healthcare providers accept Medicaid, causing limited specialty care options.
- The digital divide: Lack of access to reliable internet connections and other technology can create a significant divide in treatment and consistency of care. Those who live in rural or underserved communities with limited access to Wi-Fi or other broadband services are less able to get remote telehealth, connect with their patient portal, or utilize a remote monitoring device.
- Socioeconomic realities: Patients from lower-income backgrounds, underserved communities, and areas with marginalized populations may also experience problems finding and accessing healthcare.
- Cultural and religious beliefs: Many patients’ beliefs and cultural norms are important to ensure appropriate treatment planning and may create barriers for typical scheduling norms.
Knowing how to improve access to healthcare is the next critical step to providing individuals who face inequalities with the ability to seek quality healthcare services. One of the best ways we can increase access for those facing inequities is by assessing patients for their specific needs then using that data and technology to drive appropriate interventions.
How data and technology help bridge the gap
Unlocking Transparency in PBM Pricing
The TSX Venture Exchange has a strong history of helping early-stage health and life sciences companies raise patient capital for research and development.
To identify health inequities in a given community, you must collect SDoH data at the patient level. This approach helps identify patterns and common SDoH issues within specific patient populations. Electronic or AI-driven systems can track patients’ SDoH data which, when referenced by automated workflows, ensure that appropriate resources are offered to address those patients’ needs.
Healthcare providers can also use the collected data to track factors, such as whether they have access to adequate transportation, if there is abuse or food scarcity in their homes, or if their insurance is a roadblock to getting the care they need. Automation and AI make it easy to analyze comprehensive population data and reveal patterns at the patient and community levels.
Data collection and analysis allow healthcare providers to think differently about patients’ communities, understand vulnerable populations, and develop ideas for targeting health inequalities first-hand. By taking this comprehensive approach, medical providers can better serve their patient population and improve the overall quality of healthcare in the local community.
Unfortunately, data analysis cannot begin until the data itself is collected and organized. Using automation can significantly improve healthcare providers’ ability to merge all of the data and issue real solutions that will improve patients ability to access and engage in their healthcare (offering an appointment at the time of the public bus drop off, for example).
How automation can address equity issues
Being able to analyze patterns at the population level is a powerful tool for healthcare providers. If they can see a correlation between certain health issues and SDoH — or a high rate of a certain SDoH — they can then target interventions at the source, working within the community where they can make the most impact.
The first step is gathering this data; you can’t gain insights if you don’t have the information. Automated workflows can facilitate gathering this data through patient forms that can be taken at home. Also, collecting digital forms at the provider’s office is efficient and useful. Full access to a patient’s health data is crucial to providing the best possible care.
In rural and urban areas where healthcare systems might be sparse or disconnected, tracking and sharing patient data can be a time-consuming and frustrating task without the right tools. Many healthcare processes involve multiple systems, where sharing data or triggering subprocesses can expedite the overall process automatically. With access to more data, providers can better treat individual patients and gather more population-level data to contribute to improved analytics.
As an example, analytics may reveal that the patient population in a neighborhood has a high rate of obesity. This may lead providers to determine that this health issue may be related to a lack of access to fresh, healthy food. To address this, providers could work with community partners to set up a food pantry in the area to target the SDoH of food scarcity. Automation could then help push out messages to these patients to inform them about this new resource so they can take advantage of it.
An analysis of SDoH data could reveal a high population of patients who do not speak English. This could lead patients to avoid regular check-ups because they are uncomfortable with the language barrier or worried that they will not be able to properly communicate with their provider. With this information, the provider could set up specific clustered times when staff are available to speak the native languages, making the patients feel more comfortable and understood (and hopefully encouraging them to engage in their health).
Patients with limited access to transportation or those who do not drive can be at high risk for a no-show. Starting with scheduling the visit, automated technologies could pull in the bus schedule for their area so they can ensure the appointment time lines up with access to transportation, reducing the chance of a missed appointment. They can then automatically remind them about the appointment and provide the bus schedule or even schedule an Uber Health ride. This system also saves providers time; by automating reminders, a human no longer has to spend time calling each patient with this information, and there is a reduced risk that providers will waste time waiting for a no-show.
Automation can be a powerful tool to bring together all the pieces needed to provide optimal care that can be scattered across various systems and apps. Whether it’s to exchange patient data quickly and easily, identify communities in need of programs to address food inequity, or reduce no-shows by sending automatic reminders, using the right technology is an essential tool for achieving better patient care. By leveraging its capabilities coupled with AI technologies, healthcare providers have access to incredible new ways of working smarter and faster.
Jeanette Ball, Solution Architect for Population Health and Value-Based Care at CTG, brings an extensive clinical, population health, and healthcare administrative background to CTG. As a senior consultant and Registered Nurse, Ms. Ball has more than 35 years of experience in the healthcare industry, including a more than 10-year history of outpatient medical center executive administration and 15 years as a senior consultant in clinical application design, population health strategies, and overall health system preparation for responding to health care reform and value-based care.
As Director of CTG’s Application and Information Solutions (AIS) and Testing Solutions in North America, Rick Cruz has executive responsibility for the ongoing development of CTG’s AIS and Testing offerings and teams to deliver innovative, global services that help clients strategically address their business challenges. Rick is an accomplished IT leader and TOGAF Certified Enterprise Architect with 25+ years of IT experience, specializing in global solution delivery, enterprise digital transformation platform and solution development, quality assurance, and data integration.
This post appears through the MedCity Influencers program. Anyone can publish their perspective on business and innovation in healthcare on MedCity News through MedCity Influencers. Click here to find out how.
