How Analytics Increase Patient Access to Care: 3 Insights

Data analysis provides valuable insights into measuring patient risk, ensuring adequate insurance coverage, and planning timely interventions. This allows providers to predict and meet patient needs. However, to increase patient access to health services, providers must understand healthcare analytics and how to leverage it properly. 

To help put your healthcare organization on the right track, this guide explores three insights into the ways that data analytics increases patient access to care.

1. Identifying and addressing care gaps

Care gaps, or missed opportunities to provide patients with necessary health care, are direct results of limited access to care. Whether a condition went undiagnosed or treatment was delayed, care gaps can be detrimental to a patient’s overall health. 

Analytics enables providers to identify gaps in patient care and develop a plan for closing those gaps. To do this, providers must take a holistic view of population health by connecting various sources of information, such as personal information and medical records kept in electronic health records (EHRs). 

For example, gaps in care may include:

• Being overdue for a recommended screening
• Failing to adhere to a medication regimen
• Geographical disparities that make it difficult to visit healthcare facilities

Analytics not only plays a powerful role in uncovering obstacles to receiving care, but it also helps providers understand why such gaps exist. Using the examples above, providers may learn that: 

• A lack of medical literacy leaves at-risk populations unaware of the need for regular preventive screenings for certain conditions
• Financial blockers, such as a lack of insurance coverage or an inability to cover high out-of-pocket costs, make it difficult for a patient to afford medicine
• Certain patients are unable to visit healthcare facilities because of geographic barriers, including the distance to a facility or a lack of transportation

After identifying any disparities, healthcare providers can design targeted interventions to address these gaps. For example, populations facing economic instability may benefit from receiving information about affordable healthcare options or financial assistance programs, such as the Affordable Care Act. Additionally, providers will be better equipped to adhere to billing compliance requirements to ensure patients understand what they’re paying for.

Using analytics, providers can even address potential gaps proactively by stratifying patients based on their risk levels, forecasting their care needs, and taking steps to ensure that these needs can be met when the time comes. 

2. Optimizing resource allocation

Effective resource allocation ensures supplies, staffing, funding, and other necessities are available where and when needed most. This way, patients can access care in a timely — or even proactive — manner to optimize their health outcomes.

The key to allocating resources efficiently is predicting ahead of time where they’ll be needed and addressing issues before they become adverse health events. According to Arcadia, predictive analytics helps providers forecast future events using statistical modeling, data mining, artificial intelligence (AI), and machine learning techniques. This supports patient access to care by:

• Enabling preventive care: Early diagnosis is vital to addressing care needs before they escalate, which is why predictive analytics is essential to ensuring patients can access proactive interventions. This is especially important for addressing chronic conditions such as cancer or heart disease, which are the leading causes of death and disability in the U.S. 
• Coordinating intensive interventions: For individuals with complex health needs, such as polychronic patients, predictive analytics can help identify the need for specialized services to help providers plan resource allocation appropriately. 
• Targeting treatment plans: Providers can use predictive analytics to develop personalized treatment plans, ensuring each patient receives care according to their specific needs. Be sure to comply with HIPAA regulations to protect patient data and personal information.

Implementing predictive analytics increases both access to care and operational efficiency, making it a win-win situation for providers and patients. For example, preventive care may help patients avoid unnecessary complications and hospital admissions, resulting in significant cost savings for providers. 

3. Improving patient outreach

Patient engagement affects not only an individual’s willingness to seek care, but also their ability to receive care and, as a result, their overall health outcome. In other words, to increase patient access to care, providers must improve patient outreach and maximize engagement.

Analytics provides key insights into patients’ behaviors and preferences needed to identify barriers to patient engagement, such as: 

• Language barriers: Patients may struggle to communicate their symptoms or understand providers’ instructions if a language barrier exists
• Low health literacy: The inability to navigate hospital paperwork, complex diagnoses, or other aspects of the health field can limit a patient’s efforts to seek care
• Limited access to technology: As access to care becomes increasingly digital with the prevalence of telehealth, patients can be left behind if they have limited access to technology

Identifying these barriers to patient engagement can help providers adjust their communications and effectively reach patients according to their needs. For example, a provider may offer multilingual resources or simplified health information on their website to reach a wider audience of individuals facing such barriers. 

Data is the backbone of the healthcare industry, so providers must learn how to utilize analytics — not only to increase patient access to care but also to improve overall patient outcomes. As healthcare and technology merge, the need for innovative tools to draw meaningful insights from health databases is ever-increasing. 

Adopt a data platform that converts data into actionable conclusions by connecting data sources and surfacing meaningful insights. As a result, your organization can improve both clinical and operational decisions, driving value to patients and providers alike.