EURO-Online login
- New to EURO? Create an account
- I forgot my username and/or my password.
- Help with cookies
(important for IE8 users)
2423. Prevalence and costs of delayed discharge in a tertiary Indian hospital
Invited abstract in session WA-18: OR for Medical Services in Developing Countries, stream OR for Development and Developing Countries.
Wednesday, 8:30-10:00Room: 42 (building: 116)
Authors (first author is the speaker)
| 1. | Georg Gutjahr
|
| Department of Health Science Research, Amrita Institute of Medical Sciences and Research Center, Kochi, Kerala, India | |
| 2. | Merin Mathew
|
| Mathematics, Amrita Vishwa Vidyapeetham | |
| 3. | Malavika Krishnakumar
|
| Health Sciences Research, Amrita Vishwa Vidyapeetham | |
| 4. | Rejitha P S
|
| Infectious Disease, Amrita Institute of Medical Sciences | |
| 5. | Preetha P
|
| Infectious Disease, Amrita Institute of Medical Sciences Hospital | |
| 6. | Binil Babu
|
| Infectious Disease, Amrita Institute of Medical Sciences | |
| 7. | Ajitha Aniyappan
|
| Infectious Disease, Amrita Institute of Medical Sciences | |
| 8. | Merlin Moni
|
| Infectious Disease, Amrita Institute of Medical Sciences | |
| 9. | Dipu T. S.
|
| Infectious Disease, Amrita Institute of Medical Sciences |
Abstract
In India and other low and middle-income countries, delays in the approval of medical procedures from insurance companies often lead to extended hospital stays. Patients can not be discharged until the insurance company approves all procedures.
In this talk, we study the prevalence of the problem and the financial implications by analyzing all discharge summaries from 2021 to 2023 in a tertiary hospital in Kerala, South India. Unnecessary hospital stays will cause substantial economic loss to the hospitals. They will also lead to patient dissatisfaction and reduced bed availability for patients with medical needs.
If the hospital allocates additional resources, it can improve discharge planning through system-level approaches. In this talk, we investigate the implications of different hospital policies. We use counting processes to model patients’ arrival on each day, survival models for the length of hospital stays, and a Markov decision process to model the effects of different policies. The decision variables can be optimized by approximate dynamic programming. We find that policies that prioritize a timely discharge should be recommended. Beyond costs, these policies also increase patients’ satisfaction and the overall efficiency of the health care system.
Keywords
- Developing Countries
- Health Care
- Programming, Dynamic
Status: accepted
Back to the list of papers