Avoiding Readmissions: Using the Electronic Medical Record to Predict Who’s at Risk

American Sentinel brings you this report from the frontlines of nursing research, the NICHE 2012 Conference!  It was held in New Orleans from March 7 to 9, and was a wonderful opportunity to learn how nurses are rising to the challenge of lowering high readmission rates in their facilities.

(NICHE is an acronym for Nurses Improving Care for Healthsystem Elders. While NICHE’s mandate is to improve care among the elderly, much of the research that was presented can easily be applied to more diverse populations.)

We’ve blogged here before about how nurse case managers can prevent unnecessary readmissions (those defined as occurring within 30 days of a discharge and being directly related to the original complaint.) And we’ve given an example of how information technology can help bring down readmission rates, through the use of a virtual discharge assistant.

Now, here’s a brilliant example of a way to use the electronic medical record to prevent readmissions.

A pilot project to identify high-risk patients

At the NICHE conference, Patti Pagel, MSN, RN, GCNS-BC, from Aurora Health Care System in eastern Wisconsin and northern Illinois, presented a pilot project using ACE tracking and electronic medical records (EMR) to predict the risk of 30-day readmission among 83 patients who were 65 years or older. They were in one of seven medical/surgical units in three acute care urban hospitals.

ACE tracking is a tool developed by Aurora Health Care. You can read about it here, but the excerpt below is a good summary:

Twelve years ago the geriatrics physicians at Aurora Health Care in Wisconsin became frustrated with the need to provide safe care to vulnerable older hospitalized patients.  We developed and implemented an evidence-based model of care, Acute Care for Elders (ACE). We found that using health information technology greatly helped us to spread this model of care.

We observed that health care workers were entering information into the electronic record of every patient, but that no one was systematically using the information.  The key component of the ACE model is the ACE Tracker report — a real-time checklist report of key clinical indicators for all of the older patients on a med-surgical unit.  The report is available on a tab in the electronic medical record of each hospitalized patient in every hospital, and is generated without any additional work from the nursing staff.

Pagel and her team identified risk factors for readmission gleaned from the EMR and the nursing assessment. These risk factors were each assigned a number of points, for a total point level of 20. These were then divided into four categories:

  • Admitting diagnosis
  • Comorbidities
  • Demographics (such as prior hospital admissions, current length of stay, etc.)
  • Social factors (such as educational barriers, Medicaid status, lack of family support, etc.)

The ACE tracker played an important role – it could pull the necessary data on request and generate it in real time, so scores were available to the health care team throughout the patients’ hospitalization.

When working on discharge planning, case managers would refer patients who had scores of seven or more to the senior resource nurse (SRN). The SRN would then schedule a follow-up call or home visit within 72 hours of discharge, to assess how well patients were managing and to provide any necessary assistance.

Impressive outcomes

Prior to the pilot project, the facilities’ 30-day readmission rate was 17.4 percent. At the end of the project, the readmission rate had dropped to 5.4 percent, as a direct result of post-discharge interventions – and this was despite the fact that 44 percent of the patients were at high risk of readmission, according to the scoring module!

There are still things to learn though, Pagel said. With the cut-off for post-discharge monitoring set at seven points out of 20, the tool was more successful at predicting the patients who would not be readmitted than those who would.

However, when Pagel’s team moved the cut-off to eight points, the tool was significantly more successful at determining who may be readmitted. The project is now going through another testing phase, this time with 273 patients, using the cut-off of eight points or higher for follow-up care.

Good for all patients

While this project was done with elderly patients in mind, there is potential for similar programs to be used among patients of all ages and health status. A tool like this allows resources to be directed to the appropriate patients, saving money in the long run. Nurses can give necessary discharge information to all patients, but can allocate their time to supply additional information and post-discharge strategies for those who seem to be at high risk for readmission.

Nursing research is becoming a more important and integral part of the health care system. You can develop the necessary critical thinking skills through an online RN to BSN or RN to MSN degree program.

American Sentinel University is an innovative, accredited provider of online nursing degrees, including programs that prepare you to specialize in nursing informatics and nursing case management, fields that are the wave of the nursing future!

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