Armed with granular data and knowledge of factors that contribute to the readmission cycle, EDs can make the best possible decisions and action plans.

Pushing Improvement With Data Clarity

Health care organizations are continuously seeking to improve processes. It’s particularly important in light of the guidelines and mandates of the Patient Protection and Affordable Care Act (ACA) and the Centers for Medicare & Medicaid Services’ value-based purchasing programs like the Hospital Readmissions Reduction Program (HRRP).

Patients who use the emergency department (ED) for routine care, so-called high utilizers, are both costly and challenging for case managers. One aspect of reducing readmissions is treating patients in the most appropriate care setting for their illness. It provides better continuity and follow-up for the patient and is more cost-effective for the entire health care system. And, using a data-driven approach can help organizations reach this goal.

Safe and Effective Emergency Department Discharges

A portion of readmissions happens because of a failed discharge plan. The components of a safe and effective discharge plan must be tailored to each patient’s circumstances, and carefully communicated prior to discharge. After the discharge, timely follow-up by the care team is important to address issues early on and to answer questions that might arise from home.

EDs can turn to electronic health records (EHRs) for important insights into why their patients are returning. Analyzing this data carefully can answer questions such as:

  • Which patient demographics and characteristics create a higher risk for readmission?
  • Are patients attending follow-up appointments, and if not, why?
  • Are patients filling prescriptions, and if not, what are the barriers?
  • Which discharge interventions seem most effective?

When an organization is below benchmark, managers may receive a directive to “improve,” but exactly how to do this can be baffling. This is when d2i can help. Insights revealed by d2i’s Emergency Medicine Performance Analytics help lead to tailored, detailed strategies that make a difference in outcomes.

Basing an improvement plan on sound planning and structured data is vital. By using data to identify patterns and causes of readmissions, hospitals can more effectively target hospital resources and partner with community resources, leading to both better patient care and a healthier bottom line.

Care Transitions

Transitions of patient care from one setting to another is another area where missteps and suboptimum care are all too common. Transitions often are complex, and the patients themselves may have complicated cases. A long list of interventions must be completed and accurately handed off to the next care team. Because of the tendency for patients to bounce back and forth from long-term care and community care facilities to the ED, CMS has instituted penalties for both hospitals and care facilities.

How can EDs stop this cycle and provide the best outcomes for these patients? Once again, the answer lies in data. Much research has been done over the past decade or so to determine best practices for effective care transitions. This has led to many toolkits and protocols available to hospitals and EDs, but these processes are only effective if they are applied well and consistently.

Analyzing in-process data can help find opportunities for targeted training and staff improvement, and help EDs streamline the amount of time spent on care transitions.

Evaluating Hospital Admission Criteria

Sometimes ED physicians see patients who fall into a gray area when it comes to hospital admission. In these cases, decision-making can be helped by analyzing historical data.

For instance, when a patient has several characteristics that are known to contribute to readmissions, hospital admission may the best decision. This decision can ensure that treatment plans are followed, medications are taken, and social factors can be worked on with a case management team.

Admission may not be the best course for a patient who is not typically a high-utilizer and who has a good support system, self-awareness, and engagement in the care plan.

There’s no one-size-fits-all answer to preventing readmissions, which is why individualized solutions are so important. Armed with granular data and knowledge of factors that contribute to the readmission cycle, EDs can make the best possible decisions and action plans. Contact d2i for more information about how data analysis can help you lower readmission.