Understanding Patient Wait Times at the LV Prasad Eye Institute

Figure 1. Service time variability at LVPEI.Figure 2. Patient arrivals by time of day.Figure 3. Patient's adherence to appointments.Dmitriy Lyan, SDM '11, right, meets with two ophthalmologists at the LVPEI retina clinic in Hyderabad, India..Dmitriy Lyan, SDM '11, receives a free consultation from an LVPEI optometrist in Hyderabad, India.Ben Levitt By Ali Kamil, SDM ’12, and Dmitriy Lyan, SDM ’11
October 4, 2013

The challenge presented in this project was to reduce patient wait times and variability at LV Prasad Eye Institute (LVPEI) in Hyderabad, India. Since its inception, LVPEI has served more than 15 million patients, of which more than 50 percent were served at no charge. Each outpatient department (OPD) clinic sees 65 to 120 patients in a given day, with the average wait time ranging from 45 minutes to 6 hours. This variability in service time and associated long delays is a source of angst for patients, stress for hospital staff—who consistently work overtime, and damage to the reputation of the clinic in the region (see Figure 1). The MIT Sloan team was tasked with applying management and engineering principles to investigate the source of the variability and delays at LVPEI.

Figure 1. Service time variability at LVPEI.

The process

To understand the problem holistically, the team attempted to build a reference model of the problem experienced at LVPEI. From January through March 2013, the team:

  • Communicated with the leads from LVPEI’s clinical and administrative operations staff;
  • Conducted interviews with key stakeholders to understand patient flow dynamics; and
  • Focused on qualitative metrics, due to constraints in accessing actual data points.

To identify existing best practices in managing patient flows and reducing variability, the team also conducted research at Boston-area eye clinics—Massachusetts General Hospital, Massachusetts Eye and Ear Hospital, and Mount Auburn Hospital.

The team traveled to Hyderabad, India, in March 2013 to conduct on-the-ground research and collect quantitative metrics for patient service and wait times. Operating from the hospital, the team:

  • Conducted time and motion studies in four of LVPEI’s OPD clinics, including two cornea and two retina clinics;
  • Collected time stamps as patients and corresponding medical folders moved through the clinics;
  • Interviewed stakeholders, including faculty ophthalmologists in each of the studied clinics, administrators who oversee appointment scheduling and resource allocation, and operations professors from the Indian School of Business in Hyderabad, to understand their prior work on patient wait time trends at LVPEI;
  • Conducted patient surveys at walk-in counters to understand the motivation for choosing the walk-in option, and surveyed patients at the checkout counter to gauge patient satisfaction levels and concerns about their LVPEI experiences;
  • Constructed a system dynamics model—based on the qualitative data gathered from numerous interviews and observations—that reflects the core structure of LVPEI OPD operations and simulates patient flow in a given day; the model was then validated by key stakeholders and calibrated to the data collected on site (see Figure 2); and
  • Worked with key stakeholders to validate and calibrate the data collected on site.

Figure 2. Patient arrivals by time of day.

Figure 3. Patient’s adherence to appointments.

The findings

Based on our work on the ground and subsequent application of system dynamics to determine the cause for variability and long service times, we showed that:

  • Given a fixed OPD capacity, patient wait times are largely a function of service demand, scheduling, and resource-specific factors;
  • Demand and scheduling factors include the complexity of patient cases, their volume, and the way they are scheduled in a given day; factors impacting resource allocation and utilization include patient workup time, patient investigation time, and the operating hours of the OPD clinic;
  • To accommodate larger daily volumes of patients, providers reduce the time they spend with each patient, thereby undermining the quality of care provided and increasing the likelihood of medical errors; and
  • Walk-in patients are the source of variability in the system and cause the established schedule at LVPEI to deviate.

Given the fixed OPD capacity and service staff, we recommended that LVPEI consider allocating blocks of time in the day dedicated specifically for walk-in patients and follow-up patients. Increasing awareness and enforcing adherence to an appointment-based scheduling system will enable predictable patient wait and service times.

Next steps

Further analysis is needed to study the relationship between the volume of patients, the number of incorrect diagnoses, and the number of patients that return to the clinic to receive additional treatment as a result of error. The team is continuing its work with LVPEI to obtain additional data on patient check-in and checkout times. Additionally, the team is working to make the system dynamics model robust under extreme scenarios and able to delineate among patient types—i.e. walk-in, appointment-based, or follow-up patients.

About the Authors

Ali Kamil is a graduate student at the MIT Sloan School of Management and the Harvard Kennedy School of Government. His research focuses on understanding managerial and organizational effectiveness in low-resource settings—specifically developing and emerging markets. His expertise lies in employing system dynamics–based modeling and tools to simulate complex operations and devise effective policy measures. Prior to MIT, Kamil was an engagement manager at Deloitte Consulting LLP, where he advised leading media, entertainment, and telecom clients in matters of competitive strategy, operations, and technology implementation/outsourcing. He holds a B.S. in computer science and economics from the Georgia Institute of Technology.

Dmitriy Lyan is a senior product manager of technical product at Amazon. He is a graduate of the MIT System Design and Management program, where he specialized in the development of performance management systems for shared value-focused organizations. In his thesis work, Lyan applied system dynamics methodology to explore performance dynamics in US military behavioral health clinics. Prior to MIT, he worked in the investment management and software development industries. He holds an M.S. in financial engineering from Claremont Graduate University/Peter F. Drucker School of Management and a B.S. in computer engineering from the University of California, San Diego.

Dmitriy Lyan, SDM ’11, right, meets with two ophthalmologists at the LVPEI retina clinic in Hyderabad, India.

Dmitriy Lyan, SDM ’11, receives a free consultation from an LVPEI optometrist in Hyderabad, India.

Children wait to be seen at the LV Prasad Eye Institute in Hyderabad, India.