Jeremy Nighohossian | Managing Director | FTI Consulting
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Jeremy Nighohossian

Jeremy Nighohossian, Ph.D.

  • Managing Director
  • Economic Consulting
  • T: +1 202 589 2389
  • F: +1 202 312 9101
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Office
    • 555 12th Street, NW
    • Suite 700
    • Washington, DC, 20004
    • United States
    • T: +1 202 312 9100
    • F: +1 202 312 9101
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Jeremy Nighohossian is a Managing Director at FTI Consulting and is based in Washington, DC. Mr. Nighohossian is in the Center for Healthcare Economics and Policy practice in the Economic Consulting segment.

At FTI Consulting, Mr. Nighohossian has led and participated in several projects in which he employed his talents and expanded them. He has conducted many analyses using discrete choice methods to help predict where patients would seek treatment among several alternatives. Mr. Nighohossian has done so within the context of antitrust analysis to estimate bargaining power, damages analysis to calculate revenues lost from changes in payer networks, and in areas where falling demand threatened to close hospitals.

Mr. Nighohossian also has extensive experience with demand modeling. He used time series methods to forecast demand for hospitals in the UK, and he has also used microsimulation to predict the prevalence of cancer and the eventual demand for medical services that those patients would require. In several of those projects, Mr. Nighohossian also conducted research into the payments involved in order to project the revenue that those facilities could expect. Mr. Nighohossian has experience applying a multitude of econometric and forecasting techniques to provide insights to hospitals and communities about healthcare. In addition to those mentioned above, he has used stochastic frontier estimation and conditional and multinomial logit models.

Mr. Nighohossian has worked extensively on NY DSRIP projects and with New York data. He led the analysis team that supported the Niagara Falls PPS’s grant application and continued in that role supporting the Millennium PPS’s DSRIP application. In doing so, Mr. Nighohossian worked extensively with the NY SPARCS data as well as became especially familiar with the structure of the DSRIP initiative and the metrics involved. As part of that experience, Mr. Nighohossian also worked with many of NY’s data sources in order to extract relevant information for the region including additional calculations using the data when needed. These sources included CAHPS data, the New York Vital Statistics, and the Expanded Behavioral Risk Factor Surveillance System.

These New York sources augmented other sources including the US Census, which is used often to obtain a number of metrics for various geographies, including ZIP, county, and state level data using the ACS 1-, 3-, and 5- year estimates. Mr. Nighohossian has worked in general topics such as population estimates as well as the more granular information provided within the surveys and the census itself. Mr. Nighohossian has also conducted research using the Medicare Beneficiary Survey and the Medicare Standard Analytic File which provides IP discharge data and outpatient visit information similar to the SPARCS data but for the entirety of the Medicare population.

In addition, Mr. Nighohossian has worked to provide analysis for the NY DOH regarding two PPS’s COPA applications. This project required him to calculate market shares using both inpatient and outpatient SPARCS data. Mr. Nighohossian has also used SPARCS data in consumer discrete choice models to understand how patients would choose hospitals should certain hospitals in New York close. Mr. Nighohossian has set up and maintained the SPARCS data held onsite, including inpatient and the full outpatient files from 2011 to 2014.

Mr. Nighohossian holds a B.S. in chemical engineering from the University of Illinois Urbana Champaign. Mr. Nighohossian also holds a Ph.D. in economics from Texas A&M University, under Dr. Li Gan. Mr. Nighohossian’s dissertation focused on various topics at the intersection of Health Economics and Public Policy—how ownership affects hospital efficiency, how ownership influences insurance companies’ participation in the Medicare Advantage market, and the consumer welfare benefits of the Medicare Advantage program.

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