By Jamie Leachman, RN BSN, Senior Product Line Manager, DSS, Inc.
LinkedIn: Jamie Leachman
LinkedIn: DSS, Inc.
When it comes to advancing Veteran care, effectively assessing patients when they leave hospitals can play a vital role in reducing readmissions.
A recent NIH study found that hospital readmissions within 30 days point to potential care quality issues, along with increased mortality risks. The study also highlighted how high readmission rates can also harm patient outcomes and financially strain care hospitals, as well as invite penalties and discourage potential patients from seeking care.
Readmissions are often the result of insufficient pre-discharge planning and post-discharge management, such as incomplete instructions, medication errors and gaps in follow-up care, which can all put Veterans at unnecessary risk.
Fortunately, there are emerging precision medicine-focused solutions that enhance patient care coordination that can prevent readmissions, while also minimizing admissions through effective inpatient and post-discharge care. These solutions can harness algorithms, virtual learning and predictive analytics to anticipate health outcomes and personalize Veteran care.
Discharge Management at the Department of Veterans Affairs (VA)
In May, the VA Office of Inspector General (OIG) issued a report around how the Veterans Health Administration (VHA) can best incorporate social determinants of health (SDOH) and health-related social needs (HRSN) into inpatient medical unit discharge assessments, planning, and policies.
Specifically, the report highlighted how there were no national policies or procedures that integrated SDOH/HRSN into discharge assessment and planning. The report advocated for the creation of this national policy for establishing the inclusion of social determinants of health/health-related social needs into discharge assessment and planning.
In addition, a recent VA Health Systems Research study found that Veterans living in rural settings experienced higher rates of readmission than those living in urban settings. It also found that, regardless of where Veterans lived, readmission after a VA hospitalization was more common than readmission after being treated at a non-VA hospital.
Key Solutions for More Effective Discharge Management
New suites of healthcare solutions allow VA care providers to focus on enhancing patient care coordination, optimizing workflow efficiency, and mitigating health care risks with a key focus on prevention of readmissions.
With effective care coordination being front-and-center, these solutions provide effective inpatient and post-discharge care management, while making patient risk identification a critical priority.
It is possible to leverage dashboards that are designed with the team workflows and care coordination in mind, allowing the various team members effective patient status evaluation, while also enhancing team communication. Ultimately, this comprehensive approach enhances overall decision-making and improves patient outcomes across diverse care settings.
In addition, a dashboard for emergency departments identifies both actively registered and discharged patients with emphasis on identification of patients with prior hospital discharge within 30 days of an emergency department visit.
Precision Medicine and Discharge Management
One of the core tenets of precision medicine is allowing care practitioners to predict more accurately which treatment and prevention strategies for a particular disease will work in which groups of people.
Precision medicine also often considers differences in people’s genes, environments, and lifestyles, which is why the VA is moving more towards leveraging SDOH and HRSN data for reducing readmissions.
By analyzing comprehensive patient data and integrating it with predictive models, these new solutions will be able to enable health care providers to move from reactive to proactive care strategies. This approach not only improves patient outcomes, but also optimizes resource allocation and makes health care delivery more efficient.
These solutions often include algorithms at the patient level to assess risk factors and predict outcomes. For instance, the algorithms may analyze patient data in real-time to identify high-risk individuals who may require timely and proactive interventions. This could include predicting the likelihood of readmission based on clinical data, socio-economic factors, previous healthcare utilization patterns and mortality risks.
As precision medicine continues to come more into the forefront, it will play a critical role in helping the VA to enhance care coordination and ultimately prevent unnecessary hospital readmissions.