The Interrelationships between the length of stay, readmission, and post-acute care referral in cardiac surgery patients
Prolonged hospital stays, and readmission contribute to substantial healthcare cost. Hence, an assessment of the optimal inpatient length of stay (LOS) associated with lower readmission rate is important for healthcare providers. Post-acute care (PAC) facilities have promising potential to shorten t...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-11-01
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| Series: | Healthcare Analytics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772442522000247 |
| _version_ | 1828120102082445312 |
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| author | Ineen Sultana Madhav Erraguntla Hye-Chung Kum Dursun Delen Mark Lawley |
| author_facet | Ineen Sultana Madhav Erraguntla Hye-Chung Kum Dursun Delen Mark Lawley |
| author_sort | Ineen Sultana |
| collection | DOAJ |
| description | Prolonged hospital stays, and readmission contribute to substantial healthcare cost. Hence, an assessment of the optimal inpatient length of stay (LOS) associated with lower readmission rate is important for healthcare providers. Post-acute care (PAC) facilities have promising potential to shorten the LOS; however, currently their influence on overall patient outcomes is not well understood. The primary goal of this study is to highlight the interrelated risk factors of LOS and readmission for cardiac patients. The study also examines the influence of PAC referral on LOS and readmission. In this paper, a cohort of 13,982 Coronary Artery Bypass Graft (CABG) and Valve Replacement (VR) patients from 49 hospitals in the U.S. were analyzed with respect to the association of healthcare delivery, demographics, PAC referral, and clinical conditions with LOS and readmission. A generalized linear mixed model and multinomial logistic regression model were developed to evaluate the readmission and LOS associative risk factors, respectively. Referral to PAC was included as a vital predictor in both models to examine its impact on optimal LOS and improving patient outcomes. The results indicate a non-uniform care distribution across census divisions and an inverse relationship between LOS and readmissions. The analytics showed that higher LOS patients were more often referred to PAC and yet they were more prone to readmission except for the patients who were referred to Long Term Care (LTC). This study identifies the effects of healthcare delivery, demographic, comorbidity, and PAC referral factors on readmission and LOS, so that personalized acute and post-acute care coordination can be achieved to improve overall patient outcomes. Interventions such as treating CABG and VR patients with multiple comorbidities for longer time in acute hospitals and increasing LTC referral can result in significant improvement. |
| first_indexed | 2024-04-11T13:58:27Z |
| format | Article |
| id | doaj.art-bb63f4d3540f4b92bb3d5ae254162a4c |
| institution | Directory Open Access Journal |
| issn | 2772-4425 |
| language | English |
| last_indexed | 2024-04-11T13:58:27Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Healthcare Analytics |
| spelling | doaj.art-bb63f4d3540f4b92bb3d5ae254162a4c2022-12-22T04:20:11ZengElsevierHealthcare Analytics2772-44252022-11-012100062The Interrelationships between the length of stay, readmission, and post-acute care referral in cardiac surgery patientsIneen Sultana0Madhav Erraguntla1Hye-Chung Kum2Dursun Delen3Mark Lawley4Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, United States of America; Data Scientist, WVU Research Corporation, West Virginia University, United States of America; Correspondence to: 135 Donna Ave, Morgantown, WV 26505, United States of America.Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, United States of AmericaSchool of Public Health, Texas A&M University, College Station, TX, United States of AmericaDepartment of Management Science and Information Systems, Spears School of Business, Oklahoma State University, United States of America; Faculty of Engineering and Natural Sciences, Istinye University, Istanbul, TurkeyDepartment of Industrial and Systems Engineering, Texas A&M University, College Station, TX, United States of AmericaProlonged hospital stays, and readmission contribute to substantial healthcare cost. Hence, an assessment of the optimal inpatient length of stay (LOS) associated with lower readmission rate is important for healthcare providers. Post-acute care (PAC) facilities have promising potential to shorten the LOS; however, currently their influence on overall patient outcomes is not well understood. The primary goal of this study is to highlight the interrelated risk factors of LOS and readmission for cardiac patients. The study also examines the influence of PAC referral on LOS and readmission. In this paper, a cohort of 13,982 Coronary Artery Bypass Graft (CABG) and Valve Replacement (VR) patients from 49 hospitals in the U.S. were analyzed with respect to the association of healthcare delivery, demographics, PAC referral, and clinical conditions with LOS and readmission. A generalized linear mixed model and multinomial logistic regression model were developed to evaluate the readmission and LOS associative risk factors, respectively. Referral to PAC was included as a vital predictor in both models to examine its impact on optimal LOS and improving patient outcomes. The results indicate a non-uniform care distribution across census divisions and an inverse relationship between LOS and readmissions. The analytics showed that higher LOS patients were more often referred to PAC and yet they were more prone to readmission except for the patients who were referred to Long Term Care (LTC). This study identifies the effects of healthcare delivery, demographic, comorbidity, and PAC referral factors on readmission and LOS, so that personalized acute and post-acute care coordination can be achieved to improve overall patient outcomes. Interventions such as treating CABG and VR patients with multiple comorbidities for longer time in acute hospitals and increasing LTC referral can result in significant improvement.http://www.sciencedirect.com/science/article/pii/S2772442522000247ReadmissionPost-acute careLength of stayCardiac surgeryLogistic regression |
| spellingShingle | Ineen Sultana Madhav Erraguntla Hye-Chung Kum Dursun Delen Mark Lawley The Interrelationships between the length of stay, readmission, and post-acute care referral in cardiac surgery patients Healthcare Analytics Readmission Post-acute care Length of stay Cardiac surgery Logistic regression |
| title | The Interrelationships between the length of stay, readmission, and post-acute care referral in cardiac surgery patients |
| title_full | The Interrelationships between the length of stay, readmission, and post-acute care referral in cardiac surgery patients |
| title_fullStr | The Interrelationships between the length of stay, readmission, and post-acute care referral in cardiac surgery patients |
| title_full_unstemmed | The Interrelationships between the length of stay, readmission, and post-acute care referral in cardiac surgery patients |
| title_short | The Interrelationships between the length of stay, readmission, and post-acute care referral in cardiac surgery patients |
| title_sort | interrelationships between the length of stay readmission and post acute care referral in cardiac surgery patients |
| topic | Readmission Post-acute care Length of stay Cardiac surgery Logistic regression |
| url | http://www.sciencedirect.com/science/article/pii/S2772442522000247 |
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