New Drug Approval

The U.S. Food and Drug Administration (FDA) decides whether to approve or reject new drug applications based on statistical evidence of safety and efficacy determined through clinical trials. The tension between providing sick patients with potentially beneficial remedies, while protecting consumers from adverse events, plays an important role in the FDA's decision-making, yet the agency typically applies a 2.5% significance threshold across all diseases.  We model the drug approval process--from development through evaluation, approval, and market exit—as a network of queues which allow for the arrival, abandonment, and service rates to vary by disease. With an objective of maximizing expected net benefits, the optimal approval policy should be less stringent for diseases with low R&D intensity—due to low investment in novel drug formulation, lengthy clinical trials, or high rates of attrition--to increase the number of drugs available to patients. Given high degrees of obsolescence or substitution among available treatments, approval standards should be stricter as the market cannot support a large number of similar therapies. Using publicly available clinical trial data, we estimate model parameters and calculate the optimal significance levels for drugs targeting HIV, hypertension, or breast cancer.

Flexible Drug Approval Policies [Appendix]
Fernanda Bravo, Taylor C. Corcoran, Elisa F. Long
Manufacturing & Service Operations Management, 2021

• First place, 2018 INFORMS Public Sector OR Paper Competition
• Third place, 2019 POMS Healthcare Paper Competition
• Finalist, 2018 Pierskalla Best Paper Award
• Finalist, 2018 M&SOM Student Paper Competition

​​​     featured in UCLA Anderson Review

Hospital ICU Operations

I am interested in understanding the relationship between operational metrics (e.g., wait time for admission, discharge delays) and patient outcomes (e.g., mortality, hospital disposition, readmission) in the intensive care unit (ICU), which has the highest mortality rate in the hospital and costs the U.S. health care system more than $100 billion annually. Many hospitals experience chronic ICU bed shortages, exacerbated by poor coordination with the emergency department and wards. Using 2 years of patient-level data on ICU length-of-stay (LOS) and hourly bed occupancy at 2 major academic medical centers, we empirically examine the relationship between bed occupancy levels and LOS, 30-day readmissions, and mortality rates. Unlike prior studies, we split LOS into a medically-necessary "service time" and a discretionary "boarding time", during which a patient is deemed clinically ready for transfer to a lower level of care but physically remains in the ICU, potentially due to a lack of available ward beds. We find that boarding time is accelerated during periods of high ICU occupancy and, conversely, prolonged when the receiving ward faces bed shortages, after controlling for patient covariates including severity-of-illness, primary diagnoses, age, insurance, etc.

The Boarding Patient: Effects of ICU and Hospital Occupancy Surges on Patient Flow
Elisa F. Long, Kusum S. Mathews
Production & Operations Management, 2018, 27(12):2122-2143
​     featured in UCLA Anderson Review

Hospital managers decide how to assign ICU beds among waiting patients and choose among different triage policies (e.g., priority-based, FIFO). We use our empirical results to formulate a priority queuing model with exogenous service times but endogenous (state-dependent) boarding times, and we simulate a queue of multi-class patients arriving to an ICU with multiple server types. We compare policies, such as achieving 1-6 hour boarding times or building 4 additional ICU beds. Our simulation results closely mimic actual wait times collated by the hospital. This modeling framework could be used by other hospitals who wish to compare expansion, targeted transfer times, or other policies.

A Conceptual Framework for Improving Critical Care Patient Flow and Bed Use
Kusum S. Mathews, Elisa F. Long
Annals of the American Thoracic Society, 2015, 12(6):886-894