Health care disparities are a pervasive problem that plagues our society, creating a divide in access and quality of care that negatively impacts patients. The reality is that many people cannot get 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 using data and technology to bridge this gap. From offering appointment times based on a patient’s address to monitoring digital health data to identify interventions, intelligent and AI-driven automation can help streamline core complex processes that lead to the best patient care.
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 the common issues preventing patients from accessing quality healthcare today. Common obstacles include:
- Transportation issues: Lack of reliable transportation can be a significant barrier to accessing health care. This is particularly true where people depend on public transport, have to travel long distances to access care, or are unable to drive.
- Geographical barriers: Access to healthcare can be particularly difficult for people who live in rural areas. These patients may have limited choices for specialty care and may require significant travel time to access first-class medical systems.
- Insurance differences: Underinsured or Medicaid patients often face challenges accessing high-quality care. Unfortunately, not all healthcare providers accept Medicaid, resulting in limited options for specialty care.
- The digital divide: Lack of access to reliable Internet connections and other technologies can create a significant divide in treatment and continuity of care. Those who live in rural or underserved communities with limited access to Wi-Fi or other broadband services are less able to receive remote telehealth, connect to their patient portal, or use a remote monitoring device.
- Socio-economic realities: Lower-income patients, underserved communities, and areas with marginalized populations may also experience problems finding and accessing health care.
- Cultural and religious beliefs: Many patients’ beliefs and cultural norms are important in ensuring appropriate treatment planning and can create barriers to typical planning norms.
Knowing how to improve access to health care is the next critical step toward enabling people who face inequities to seek quality health services. One of the best ways we can increase access for those facing disparities is by assessing patients for their specific needs, then using that data and technology to drive appropriate interventions.
How data and technology are helping to bridge the gap
To identify health inequities in a community, you need to collect SDoH data at the patient level. This approach helps to identify patterns and common problems of SDoH within specific patient populations. Electronic or AI-driven systems can track patients’ SDoH data, which, when used by automated workflows, ensures that appropriate resources are offered to meet those patients’ needs.
Health care providers can also use the collected data to track factors such as whether they have access to adequate transportation, whether there is abuse or food shortages in their homes, or whether their insurance is a barrier to getting the care they need . Automation and AI make it easy to analyze comprehensive population data and uncover patterns at the patient and community level.
Data collection and analysis allows health care providers to think differently about patient communities, understand vulnerable populations, and develop ideas for targeting health care disparities firsthand. By taking this comprehensive approach, medical providers can better serve their patients and improve the overall quality of health care in the local community.
Unfortunately, data analysis cannot begin until the data itself has been collected and organized. The use of automation can greatly improve the ability of healthcare providers to bring together all the data and issue real solutions that will improve the ability of patients to access and engage with their healthcare (offering an appointment during the public shutdown bus, for example).
How automation can solve equity problems
The ability to analyze patterns at the population level is a powerful tool for healthcare providers. If they can see a link between certain health problems and SDoH—or a high rate of a certain SDoH—then they can target interventions at the source, working in the community where they can have the greatest impact.
The first step is to collect this data; you can’t gain insights if you don’t have the information. Automated workflows can facilitate the collection of this data through patient forms that can be taken home. Also, collecting digital forms at the provider’s office is efficient and useful. Full access to a patient’s health data is critical to providing the best possible care.
In rural and urban areas where healthcare systems may 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 sub-processes can automatically speed up the overall process. With access to more data, providers can better treat individual patients and collect more population-level data to contribute to improved analytics.
As an example, analyzes may reveal that the patient population in a given neighborhood has a high rate of obesity. This may lead providers to determine that this health problem may be related to a lack of access to fresh, healthy food. To address this, suppliers could work with community partners to set up a food pantry in the area to target the SDoH of food shortages. Automation could then help send messages to those patients to inform them of this new resource so they can take advantage of it.
Analysis of SDoH data may reveal a large number of non-English speaking patients. This can cause patients to avoid regular checkups because they feel uncomfortable with the language barrier or worry that they won’t be able to communicate properly with their provider. With this information, the provider can set up specific clustered times when staff are available to speak in native languages, making patients feel more comfortable and understood (and hopefully encouraging them to engage with their health).
Patients with limited access to transportation or those who do not drive may be at high risk of no-show. Starting with planning a visit, automated technologies can download the bus schedule for their area so they can ensure meeting times coincide with transportation access, reducing the chance of a missed appointment. They can then automatically remind them of the appointment and provide the bus schedule or even schedule a ride with Uber Health. This system also saves suppliers time; by automating reminders, one no longer has to spend time calling each patient with this information, and there is a reduced risk of providers wasting time waiting for no-shows.
Automation can be a powerful tool for bringing together all the pieces needed to deliver optimal care that can be spread across different systems and applications. Whether it’s quickly and easily sharing patient data, identifying communities in need of programs to address food inequity, or reducing no-shows by sending automated reminders, using the right technology is an essential tool for achieving better outcomes. -good patient care. Using its capabilities combined with AI technologies, healthcare providers have access to incredible new ways to work smarter and faster.
