Could AI be the Answer to Lowering Healthcare’s $17B Patient Readmission Rates Problem?

High patient readmission rates for chronic diseases are a significant concern in healthcare, as they indicate that patients with chronic conditions are returning to the hospital after an initial discharge. 

Each Year 2M Patients are Readmitted to Hospital within 30 Days of Procedure 

Reducing preventable hospital readmissions is a national priority for payers, providers, and policymakers seeking to improve health care and lower care costs. In 2012, the Centers for Medicare & Medicaid Services began processes to reduce Medicare payments for certain hospitals with excess of 30-day readmissions for patients with several conditions. Each year, more than 2 million patients are readmitted, this unfortunate circumstance is costing Medicare $27 billion, of the total amount,  $17 billion is spent on readmissions that could be classified as potentially avoidable. 

What are the Factors that Contribute to these High Readmission Rates?

Poorly Managed Chronic Conditions: Inadequate management of chronic diseases, such as diabetes, heart failure, and chronic obstructive pulmonary disease (COPD), can lead to worsening symptoms and complications, prompting patients to seek readmission.

Medication Non-Adherence: Many patients with chronic diseases struggle with adhering to prescribed medication regimens. Failure to take medications as directed can lead to uncontrolled symptoms and exacerbations, necessitating hospitalization.

Lack of Follow-Up Care: Insufficient access to or utilization of follow-up care, including post-discharge appointments with healthcare providers, can result in patients not receiving the ongoing support needed to manage their conditions effectively.

Limited Health Literacy: Patients with low health literacy may not fully understand their condition, treatment plan, or self-care instructions, leading to difficulties in managing their health and an increased likelihood of readmission.

Socioeconomic Factors: Social determinants of health, such as poverty, lack of access to nutritious food, unstable housing, and transportation issues, can make it challenging for patients to manage their chronic diseases outside of the hospital, contributing to readmissions.

Psychosocial Factors: Mental health issues, including anxiety and depression, can affect a patient's ability to manage their chronic disease and make them more vulnerable to readmissions.

Inadequate Care Transitions: Poorly coordinated transitions of care between hospital and home or other healthcare settings can result in gaps in treatment and follow-up, making readmission more likely.

Complications and Comorbidities: Chronic diseases can lead to acute complications or the development of other comorbid conditions, necessitating readmission for specialized care.

Patient Education and Empowerment: Lack of patient education and involvement in self-management strategies can hinder a patient's ability to make informed decisions about their health.

Access to Healthcare Services: Limited access to healthcare services, including primary care and specialty care, can impede a patient's ability to manage their chronic disease effectively.

How Can AI Help This Healthcare Epidemic? Here’s 6 Ways…

Reducing readmission rates for chronic diseases requires a holistic approach that encompasses medical care, patient education, social support, and improved healthcare system coordination. Attempting to successfully manage all parties without the support of automation and computational intelligence results in the dynamics populations are experiencing within today’s healthcare system: 

• Sick patient populations that are increasing. 

• Patients that are not health literate. 

• Healthcare administrators that are too slow to adopt innovation. 

• Care teams that are overwhelmed by the volume of patient care service demands. 

To reduce high readmission rates for chronic diseases, healthcare systems and providers can  implement a range of strategies that leverage AI to automate repeatable care workflows to scale care in a more efficient way. AI aides all parties involved in the patient’s healthcare journey. Here’s how AI can help:

Care Coordination: Enhance care coordination to ensure a smooth transition between inpatient and outpatient care.

Patient Education: Educate patients about their conditions, treatment plans, and self-care strategies to empower them to manage their health effectively.

Medication Management: Simplify medication regimens, provide adherence aids, and conduct medication reconciliation during care transitions.

Support for Social Determinants of Health: Address social determinants of health by connecting patients to community resources that can help with housing, transportation, and access to healthy food.

Mental Health Support: Address mental health issues and provide access to counseling or support services for patients with comorbid mental health conditions.

Health Literacy Initiatives: Implement health literacy initiatives to ensure patients understand their health information.

Tammy McMiller is the Co-Founder and CEO of Plan Heal , an AI platform that supports the patient and care team by capturing and analyzing real-time patient health data to detect disease risks earlier.