How Patient Readmission Analytics Software Helps Significantly Cut Hospital Readmissions 

Readmission analytics tools are extensively utilized today by serious healthcare systems that care for millions of patients. These healthcare networks manage multiple hospital campuses, primary care clinics, same-day centers, as well as urgent care centers, along with at least a hundred specialty practices within the areas they serve. They report enhancements, such as a high percentage of patients finishing follow-ups within the designated time frame, which markedly decreases the chance of hospital readmissions. What approaches do these healthcare systems adopt to achieve sustainable outcomes?

If healthcare organizations can efficiently execute enhancements in discharge and follow-up processes, they are able to prevent hundreds of readmissions and, consequently, achieve savings of millions of dollars in total variable costs.

However, the absence of appropriate tools often hinders healthcare systems from consistently executing hospital release and follow-up processes throughout the organization, leading to higher readmissions and reduced overall savings in variable costs.

Leveraging data analytics and other organizational measures helps resolve such challenges.

Challenges with Hospital Readmissions 

Even if organizations substantially diminish the number of readmissions, they still don’t utilize all the methods available to further lower them.

• Healthcare organizations face a shortage of tools and expertise to learn from the data, scale their analytics-driven readmission minimization strategies, and enhance their patient care
• Post-discharge follow-up is complicated. Clinics face uncertainty about whether phone and virtual consultations could efficiently avoid rehospitalizations.
• Voids in follow-up are pinpointed for patients who are not released from the hospital to their homes. Patients who pass through a rehabilitation center or another third-party facility, get a follow-up in time after their discharge from the center not in all cases.

Organizational Measures to Apply Readmission Analytics 

Merely using analytics software to make processes automated isn’t sufficient. Certain organizational initiatives are necessary.

• Providers and care coordinators collaborate to develop efficient discharge and transition strategies for each patient.
• Restructure when discharge planning takes place by beginning it precisely at the time of the patient’s admission.
• Exact medication reconciliation is a crucial element of discharge planning, and the healthcare system must ensure it takes place within 24 hours of the patient’s admission.
• Incorporate telehealth options, such as virtual and phone consultations, into the analytics platform to observe and assess how various visit types influence timely patient follow-ups and the frequency of hospital readmissions.
• Providers who release a patient must utilize a standardized discharge report and an order in the electronic health records to record and convey medication adjustments and patient requirements. This measure guarantees that primary care physicians (PCPs) possess the essential information to manage the patient effectively and prevent needless readmissions.

What Benefits Can Be Anticipated from Utilizing Readmission Risk Analytics Tools

Care coordinators and providers report the following enhancements:

• Recognizing patients at the greatest risk of readmission and targeting interventions toward them. It enables care coordinators to reach out to the patient in the days after discharge to arrange their next appointment with their primary care physician to modify care and prevent readmission.
• Obtaining from the analytics application a list of patients who transfer to a third-party facility, such as a rehabilitation center, and do not consistently receive prompt follow-up after being discharged from that facility. This list enables care managers to arrange patient appointments within the optimal period determined by the application after their discharge from the third-party facility.
• The beneficial effect of virtual and phone consultations on reducing readmissions. The provider can involve care teams to ensure that released patients receive well-timed follow-up care through telehealth, thereby supporting improved patient outcomes.
• Establishing a tailored serious disease risk model through an analytics solution and a specialized data store designed specifically for this model to utilize the risk score for all patients. This model identifies patients before their condition deteriorates and assists providers in determining the optimal time to discuss serious health issues with them.
• The app aids in identifying the best time span from discharge day to follow-up appointments. Providers can utilize this information to modify their goals and minimize needless readmissions.

How a Healthcare Software Development Company Can Aid

An outsourcing company like Belitsoft that specializes in healthcare software development assists top healthcare data analytics companies in building 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.), the healthcare software development companies:

• Automate data processing workflows (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.

They also assist in developing specialized analytical applications such as the Readmission Risk Analytics tool for:

• Identify and comprehend the factors driving patient readmissions
• Pinpoint particular areas for enhancement and determine which improvements can be implemented
• Generate a visual depiction of readmission performance that features risk-based identification and categorization of patients at risk for readmission
• Quickly view the number of hospital visits each patient has had during a defined period
• Show rehospitalizations based on the care department where patients were released, the level of patient care, the patient’s primary issue, the provider, the released plan, or the insurance carrier
• Compute and follow the ratio of actual-to-expected (A/E) for potentially preventable readmissions (PPR) utilizing risk-adjusted information
• Utilize data in the analytics tool and the potentially preventable readmissions actual-to-expected ratio to identify and address shifts in performance
• Track the potentially preventable readmissions actual-to-expected ratio across the entire network and within each clinic of the network
• Control how changes impact balance metrics such as patient satisfaction, length of stay (LOS), and fatality rates
• Estimate how changes influence the key result measures.

If you are looking for expertise in data analytics, data infrastructure, data platforms, HL7 interfaces, workflow engineering, and development within cloud (AWS, Azure, Google Cloud), hybrid, or on-premises environments, a healthcare software development company like Belitsoft also can serve these needs.