Automated messaging system may reduce acute care resource usage after hospital discharge

Automated text-messaging systems supporting primary care patients following hospital discharge were associated with reductions in the use of acute care resources, a study found.

Noting the criticalness of post-discharge periods, Eric Bressman, MD, MSHP, a fellow in the National Clinician Scholars Program at the University of Pennsylvania, and colleagues wrote in JAMA Network Open that a commonly utilized post-discharge care management approach has been “a single primary care–based, nurse-led telephone call to identify needs shortly after discharge.”

“This approach has proven effective in some settings in reducing unplanned readmissions; however, the calls are limited in scope and present a significant operational burden,” they wrote. “In our experience, the calls can be time intensive, often go unanswered and generally connect with patients only once, early in the course of their recovery.”

Looking to improve upon these limitations, the researchers developed a 30-day intervention based on an automated text-messaging system with two-way capability.

Bressman and colleagues implemented the system in a primary care practice from Jan. 27, 2021, to Aug. 27, 2021. Patients who used it received automated check-in text messages from the practice on a tapering schedule after discharge. Staff members used an electronic medical record inbox to follow up with patients who had any needs that were identified by the automated messaging platform. The outcomes of patients in the intervention group were compared with those of a control group.

The study included 1,885 patients, 58.4% (n = 1,101) of whom were women. A total of 2,617 discharges occurred: 404 before and 604 after the intervention in the intervention group, and 613 before and 953 after the intervention in the control group.

Bressman and colleagues found that the odds of any use of acute care resources in the control group increased from 15.2% to 19.8% following the implementation of the intervention, while the odds in the intervention group decreased from 20.3% to 16.5%.

After adjustments, the odds in the intervention group were 41% lower (aOR = 0.59; 95% CI, 0.38-0.92) than the control group. Readmission within 30 days was also 55% lower (aOR = 0.45, 95% CI, 0.23-0.86) for the intervention group compared with its counterpart.

The study limitations reported by the researchers included the system being deployed at a single site and patients being potentially excluded due to considerations not readily identified by EMR data.

Bressman and colleagues noted that the way in which the automated system helps relieve resource usage is “complex,” and they hypothesized that more frequent check-ins and lower mediums for patient-initiated outreach leads to earlier detection of a patient’s needs, increasing the odds that the issue will be handled by the practice.

The researchers pointed out that in addition to improving hospital resources, the intervention also saw patient responsiveness.

Overall, “82.8% of patients responded to at least one of our introductory messages — far higher than rates of response to our traditional transitions calls. This outcome is consistent with other work that has compared text messaging with traditional call-based approaches,” they wrote.

The system’s integration into the daily workflows of staff resulted in a mean of 1.4 escalations per day, a “manageable” workload, Bressman and colleagues reported.

“Although the staff continued to place the standard telephone calls during this pilot, future work can test replacement of these calls with messaging entirely,” they wrote.