How a dedicated postdischarge unit can reduce hospital congestion and costs
Corresponding Author
Maryam Khatami
Department of Information Technology and Decision Sciences, G. Brint Ryan College of Business, University of North Texas, Denton, Texas, USA
Correspondence
Maryam Khatami, Department of Information Technology and Decision Sciences, G. Brint Ryan College of Business, University of North Texas, Denton, TX, USA.
Email: [email protected]
Search for more papers by this authorJon M. Stauffer
Department of Information and Operations Management, Mays Business School, Texas A&M University, College Station, Texas, USA
Search for more papers by this authorMark A. Lawley
Department of Industrial and Systems Engineering, Texas A&M University, College Station, Texas, USA
Search for more papers by this authorCorresponding Author
Maryam Khatami
Department of Information Technology and Decision Sciences, G. Brint Ryan College of Business, University of North Texas, Denton, Texas, USA
Correspondence
Maryam Khatami, Department of Information Technology and Decision Sciences, G. Brint Ryan College of Business, University of North Texas, Denton, TX, USA.
Email: [email protected]
Search for more papers by this authorJon M. Stauffer
Department of Information and Operations Management, Mays Business School, Texas A&M University, College Station, Texas, USA
Search for more papers by this authorMark A. Lawley
Department of Industrial and Systems Engineering, Texas A&M University, College Station, Texas, USA
Search for more papers by this authorAbstract
Depending on the patient's condition, up to 60% of inpatients are discharged to post–acute care facilities (PACFs). These patients may experience several days of nonmedical inpatient stay until the hospital finds a facility that fits their needs, contributing to overcrowding in upstream units. This article studies the feasibility of creating a “postdischarge unit” (PDU) for medically ready-for-discharge patients who experience transfer delays, to improve access to inpatient beds. We use a multistage stochastic program, solved with a dual dynamic programming algorithm, to address the PDU size and capacity question. The random variable is the number of bed requests from upstream units (e.g., emergency department). Our numerical analysis, using data from a large hospital, shows that a PDU can reduce costs and significantly reduce the number of patients waiting for transfer to PACFs that are occupying inpatient beds, as long as the percentage of these patients in the hospital is more than 4%. Compared to current practice in our partner hospital, a PDU could increase access to inpatient beds by up to 13% and result in 2%–21% cost savings. Results show that PDU capacity in hospitals with a larger number of patients waiting for transfer is more sensitive to variation in PDU renovation and operational costs. In addition to using fewer medical staff, a PDU can improve discharge transitions to lower levels of care and more efficiently utilize social workers and physical therapists assisting these patients.
Supporting Information
| Filename | Description |
|---|---|
| deci12624-sup-0001-SuppMat.pdf1.2 MB | Figure EC.1 Relative Frequency for Number of Accepted Transfer Requests from Other IUs During Intervals 1 (6 a.m.-12 p.m.), 2 (12 p.m.-6 p.m.), 3 (6 p.m.-12 a.m.), and 4 (12 a.m.-6 a.m.) Figure EC.2 Relative Frequency for Number of Accepted Bed Requests to IU from Direct Admissions During Intervals 1 (6 a.m.-12 p.m.), 2 (12 p.m.-6 p.m.), 3 (6 p.m.-12 a.m.), and 4 (12 a.m.-6 a.m.) Figure EC.3 Relative Frequency for Number of Accepted Bed Requests to IU from the ICU During Intervals 1 (6 a.m.-12 p.m.), 2 (12 p.m.-6 p.m.), 3 (6 p.m.-12 a.m.), and 4 (12 a.m.-6 a.m.) Figure EC.4 SDDP Forward Pass Figure EC.5 SDDP Backward Pass Table EC.1 A Lower Bound (in $) for the PDU Renovation Cost Below Which a PDU Reduces Costs Figure EC.6 PDU Optimal Capacity with and without Cost Discounting and Various Planning Horizons Table EC.2 Upper and Lower Bounds for the Number of Days to Recover the Renovation Cost in T15 Hospital Table EC.3 Upper and Lower Bounds for the Number of Days to Recover the Renovation Cost in T30 Table EC.4 Upper and Lower Bounds for the Number of Days to Recover the Renovation Cost in T60 Figure EC.7 The Stage-wise Cost With and Without a PDU in Our Partner Hospital (With 15% Transfer to PACFs): Three Shades from Lighter to Darker Represent the Occurrence Percentiles of 0-100%, 10%-90%, and 25%-75%, Respectively, and the Solid Line is the Median. Figure EC.8 The Stage-wise Medically Needed Stays in IU With and Without a PDU in Our Partner Hospital (With 15% Transfer to PACFs): Three Shades from Lighter to Darker Represent the Occurrence Percentiles of 0-100%, 10%-90%, and 25%-75%, Respectively, and the Solid Line is the Median. Figure EC.9 The Stage-wise Number of Declined Bed Requests from ED With and Without a PDU in Our Partner Hospital (With 15% Transfer to PACFs): Three Shades from Lighter to Darker Represent the Occurrence Percentiles of 0-100%, 10%-90%, and 25%-75%, Respectively, and the Solid Line is the Median. Figure EC.10 The Stage-wise ALC Population in IU With and Without a PDU, and the PDU Occupancy in Our Partner Hospital (With 15% Transfer to PACFs): Three Shades from Lighter to Darker Represent the Occurrence Percentiles of 0-100%, 10%-90%, and 25%-75%, Respectively, and the Solid Line is the Median. Figure EC.11 Comparing the Median and 75th Percentile of the Stage-wise Number of Declined Bed Requests from the ED for Current Practice Without a PDU vs. the PDU Optimal Policy in a T15 Hospital Figure EC.12 The Stage-wise Transfer and Direct Admission Request Rejections With and Without a PDU in Our Partner Hospital (With 15% Transfer to PACFs): Three Shades from Lighter to Darker Represent the Occurrence Percentiles of 0-100%, 10%-90%, and 25%-75%, Respectively, and the Solid Line is the Median. Table EC.5 Total Number of Declined Transfers and Direct Admissions to the IU in the Current Practice Without a PDU vs. the PDU Optimal Policy in a T15 Hospital. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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