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Related Experiment Video

Updated: Feb 2, 2026

Author Spotlight: Developing a Point-of-Care Hemoglobin Estimation Method for Anemia Management
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Using a Decision Support Algorithm for Referrals to Post-Acute Care.

Kathryn H Bowles1, Sarah J Ratcliffe2, John H Holmes2

  • 1University of Pennsylvania School of Nursing, New Courtland Center for Transitions and Health, Philadelphia, PA.

Journal of the American Medical Directors Association
|November 12, 2018
PubMed
Summary
This summary is machine-generated.

Clinical decision support (CDS) via the DIRECT algorithm improved post-acute care (PAC) referrals, significantly reducing inpatient readmissions by identifying high-risk patients, even without changing overall referral rates.

Keywords:
Patient dischargedecision support systemshome healthcarelong-term carenursing informaticspost-acute carereadmissionskilled nursing facility

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Area of Science:

  • Health Informatics
  • Healthcare Management
  • Clinical Decision Support Systems

Background:

  • Hospital discharge planning for post-acute care (PAC) is often inconsistent and lacks evidence-based practices.
  • Effective referral to PAC is crucial for patient outcomes but challenging for clinicians.
  • Existing processes may not optimally identify patients who would benefit most from PAC services.

Purpose of the Study:

  • To evaluate the impact of the Discharge Referral Expert System for Care Transitions (DIRECT) algorithm on PAC referral processes.
  • To assess the effect of DIRECT's clinical decision support (CDS) on patient selection for PAC and subsequent readmission rates.
  • To determine if automated CDS can improve the efficiency and effectiveness of discharge planning.

Main Methods:

  • A quasi-experimental study using a pre-/postdesign was conducted in two hospitals.
  • The DIRECT algorithm provided CDS for PAC referrals during the post-intervention period; clinicians were blinded to advice in the pre-period.
  • Propensity modeling was used to control for patient characteristic differences between the control and intervention cohorts.

Main Results:

  • While the DIRECT algorithm recommended 24%-25% more PAC referrals, overall referral proportions did not significantly change.
  • The characteristics of patients referred for PAC services differed significantly between periods.
  • Inpatient readmission rates significantly decreased across all measured time intervals (same-day to 30-day) with DIRECT CDS implementation.

Conclusions:

  • Automated, timely discharge CDS, like the DIRECT algorithm, holds significant value for optimizing PAC referrals.
  • The algorithm appears effective in identifying high-need patients, leading to reduced readmissions, despite not altering overall referral volume.
  • Further research should explore clinician agreement with CDS recommendations and its impact on outcomes.