Patient Readmission Analytics Software to Reduce Readmissions by Hundreds

Readmission Analytics tools are widely used now by large healthcare systems that serve millions of patients. These health systems operate dozens of hospital campuses, primary care clinics and urgent care/same-day centers, and at least one hundred specialty practices in the communities they serve. They report improvements like a high percentage of patients completed follow-up within the target number of days which significantly reduces the likelihood of hospital readmissions. What strategies do these health systems implement to drive sustainable results?

If healthcare organizations are able to effectively implement improvements in discharge and follow-up activities, they are rewarded with avoidance of hundreds of readmissions and, as a result, save millions of dollars in total variable costs.

However, a lack of relevant tools often prevents healthcare organizations from consistently performing hospital discharge and follow-up procedures across the organization which results in increased readmissions and decreased overall variable cost savings. Using data analytics and other organizational actions helps address such issues.

Challenges with Hospital Readmissions

Even if organizations significantly reduce the number of readmissions, they still do not use all the ways to reduce them.

• Follow-up after discharge is problematic. Clinics experience uncertainty about whether virtual and phone visits could effectively prevent hospital readmissions.
• Organizations experience lack of expertise and tools to learn from the data, to scale their analytics-based readmission reduction drivers, and to improve their patient care transition.
• Gaps in follow-up are identified for patients who aren’t discharged directly home. Patients who go through a third-party facility like a rehab center, do not always receive timely follow-up after being discharged from this center.

Organizational Measures to Implement Readmission Analytics

Simply using analytics software to automate workflows isn’t enough. Many organizational efforts are needed.

• Providers and care managers work together to create effective discharge and transition plans for each patient.
• Redesign when discharge planning happens by starting it right at the time of the patient's admission.
• Accurate medication reconciliation is a crucial part of discharge planning, and the organization needs to make sure it happens within 24 hours of the patient's admission.
• Add telehealth options, like virtual and phone visits, to the analytics application to see and evaluate how different visit types affect timely follow-ups and hospital readmissions.
• Providers who discharge a patient need to leverage a standardized discharge note and an order in the electronic healthcare records to document and communicate medication changes and patient needs. This measure ensures that primary care providers (PCPs) have the crucial information to manage the patient effectively and avoid unnecessary readmissions.

What Benefits Can Be Expected from Using Readmission Risk Analytics Tools

Care managers and providers report the following improvements:

• Identifying patients at the highest risk of readmission and focusing interventions on them. It allows care managers to contact the patient in the days following discharge to schedule their next appointment with their primary care physician to adjust care and avoid readmission.
• Receiving from the analytics app a list of patients who go to a third-party facility such as a rehab center and aren’t always getting timely follow-up after leaving this center. This list ensures care managers invite patients to an appointment within the optimal app-determined time period after leaving the third-party facility.
• Positive impact on readmissions of virtual and telephone visits. The provider can engage care teams in ensuring discharged patients receive timely follow-up via telehealth and contribute to better patient outcomes.
• Creating a tailored serious disease risk framework via an analytics platform and a specialized data mart, that is specific to this framework to apply the risk score to all patients. This framework spots patients before their health worsens and helps providers know the best time to have a serious disease conversation with them.
• The app helps determine the optimal period from discharge day to follow-up appointments. Providers can use this info to adjust their target and reduce unnecessary readmissions.

How Belitsoft Can Help

Belitsoft is an outsourcing company that specializes in custom healthcare software development. We help top healthcare data analytics companies build robust data operating systems.

For integrated data platforms developed to collect, store, process, and analyze large volumes of data from various sources (Electronic Medical Records, clinic management systems, laboratory systems, financial systems, etc.), we:

• Automate processes for data cleansing, standardization, and normalization.
• Configure scalable data warehouses.
• Set up and implement analytical tools for creating dashboards, reports, and data visualizations.
• Ensure a high level of data security and compliance with healthcare regulations such as HIPAA.
• Integrate machine learning and AI into analytics.

We also help build specialized analytical applications like the Readmission Risk Analytics tool to:

• find and understand the factors behind patient readmissions
• identify specific areas where improvements can be made and which improvements can be made
• create a visual representation of readmission performance that includes risk-based identification and grouping of patients with risk of readmission
• see quickly how many inpatient visits each patient has had over a specific period
• display readmissions based on the care unit where patients were discharged, the level of care, the main issue, the provider, the discharge plan, or the insurance payer
• calculate and track the ratio of actual-to-expected (A/E) for potentially preventable readmissions (PPR) basing on risk-adjusted data
• use data in the analytics app and the PPR A/E to spot and address changes in performance
• monitor the PPR A/E both in the entire large network and in each clinic of this network
• keep track of how changes affect balance measures such as death rates, length of stay, and patient satisfaction
• assess how changes affect the outcome measures that matter.

If you're looking for expertise in data integration, data infrastructure, data platforms, HL7 interfaces, workflow engineering, AWS development, or data analytics, we are ready to serve your needs. Contact us today to discuss your project needs.