In our research, we distinguish between policy and network interventions. A policy intervention is a type of an action that involves design, revision, implementation or translation of a health policy for reducing costs and for improving health outcomes, healthcare access and quality. A network intervention refers to an action that involves altering an existing network of care, including networks consisting of medical facilities. For instance a network intervention could be designed to achieve more equitable access and better healthcare coverage.

Resources

What We Do

The Three Es Framework: Efficiency, Effectiveness and Equity

One important aspect in the discourse of attainment of equity in health and healthcare is the trade-off between the three Es: Efficiency, Effectiveness and Equity. Generally, efficiency measures how well the system is utilizing its resources and effectiveness is a measure of how well the system meets a need or achieves an objective. In our research projects, we use optimization models to account for the trade-off between the three Es in designing policy and network interventions to improve healthcare access and health outcomes.

Network interventions for Improving Access

Network interventions for improving healthcare access include opening new facilities or expanding the capacity at some of the existing facilities given an expanded budget. The set of decisions to be made in a network intervention can be complex as the principal objectives to be achieved can be conflicting. For instance, facilities may be opened or expanded to provide the best benefit for the society. However, this result could lead to specific geographic areas to have inadequate access to healthcare. We investigate the impact of such decisions and consider the impact of designing network interventions for efficiency, equity, or a combination of factors.

Cost-Effectiveness

A value-based model for designing interventions requires assessment of their cost-effectiveness, which is an analysis of the benefits of an intervention given the costs, including not only financial costs but also number of years of life saved or quality of life. We consider cost-effectiveness analysis in which costs, benefits, and effectiveness of various components of the network interventions are weighted in quantifying the value added by the interventions. Within our current research, we have particularly focused on telemedicine programs, which are becoming common network interventions in improving geographic access to care.

Publications

Published by the Health Analytics Group

  • Ma, S., Serban, N., Dehaghnian, A., Tomar, S. (2023), "The Impact of Dentists’ Availability in Delivering Dental Care in Florida Elementary Schools", Journal of Public Health Dentistry, 83 (1), Pages 60-68.

  • Cummings, J., Shellman, M., Stein, B., Asplund, J., Lin, H., Serban, N. (2022) "Association between in-home services and engagement in psychosocial services among Medicaid-enrolled youth", Journal of the American Academy of Child & Adolescent Psychiatry, 61(11), pages 1351-1361.

  • Baxter, A., Oruc, B.E., Keskinocak, P, Asplund, A., Serban, N.(2022) "Evaluating Scenarios for School Reopening under COVID19", BMC Public Health, 22 (496).

  • Oruc, B.E., Baxter, A., Keskinocak, P., Asplund, J., Serban, N. (2021) "Homebound by COVID19: The Benefits and Consequences of Intervention Strategies",  BMC Public Health, 21, 655.

  • Yildirim, F.M., Shih, J., Keskinocak, P., Serban, N. (2021) "Reflecting on Prediction Strategies for Epidemics: Preparedness and Public Health Response",  Annals of Allergy, Asthma & Immunology, 126(4):338-349.

  • Serban, N., Harati, P., Munoz Elizondo, J.M., Sharp, W. (2020) "An Economic Analysis of Intensive Multidisciplinary Interventions for Treating Medicaid-insured Children with feeding disorders", Medical Decision Making, vol 4, issue 5.

  • Keskinocak, P., Oruc, B.E., Baxter, A., Asplund, J., Serban, N. (2020) "The Impact of Social Distancing on COVID19 Spread: State of Georgia Case Study", PLOS One, 15 (8), e0236455.

  • Serban, N. (2019). Healthcare System Access: Measurement, Inference and Intervention, John Wiley & Sons, NJ.

  • Pujol, T., Serban, N., Swann, J., Kottke, M. (Accepted August 2018) Determining the Uptake of CDC MEC Guidelines for Contraceptive Usage of Chronically Ill Women, Preventive Disease Control, in press.

  • Gentili, M., Serban, N., Harati, P., O'Connor, J., Swann, J. (2018) Quantifying Disparities in Accessibility and Availability of Pediatric Primary Care with Implications for Policy, Health Services Research, 53(3), 1458-1477.

  • Johnson, B., Serban, N., Griffin, P., Tomar, S. (Submitted March 2018) Does Silver Diamine Fluoride Reduce Caries Treatment Expenditures in US Children? Journal of Public Health Dentistry, under 2nd review.

  • Johnson, B., Serban, N., Griffin, P., Tomar, S. (2017) The Cost-Effectiveness of Three Interventions for Providing Preventive Services to Low-Income Children, Community Dentistry and Oral Epidemiology, 45(6), 522-528.

  • Bastian, N.D., Griffin, P.M., Spero, E., and Fulton, L. (2015), “Multi-Criteria Logistics Modeling for Military Humanitarian Assistance and Disaster Relief Aerial Delivery Operations”, Optimization Letters.

     

  • Bennett-Milburn, A., Hewitt, M., Griffin, P.M., Savelsbergh, M. (2014). “The Value of Remote Monitoring Systems for Treatment of Chronic Disease”, IIE Transactions on Healthcare Systems Engineering, Vol. 4, pp. 65-79

  • Rouse, W.B., Serban, N. (2014). Understanding and Managing the Complexity of Healthcare, MIT Press.

  • Kirkizlar E., Serban N., Sisson J.A., Swann J.L., Barnes C.S., Williams M.D. (2013) ``Evaluation of telemedicine for screening of diabetic retinopathy in the Veterans Health Administration." Ophtamology, 120(12) 2604-2610.

  • Griffin, J., P. Keskinocak, and J. Swann (2013). “Allocating Scarce Healthcare Resources in Developing Countries,” Handbook of Healthcare Operations Management: Methods and Applications (International Series in Operations Research and Management Science), B. Denton (editor) and F. Hillier (senior editor), Springer.

  • Faissol, D.M., Griffin, P.M., Kirkizlar, E., and Swann, J.L. (2010). “Timing of Testing and Treatment for Asymptomatic Diseases”, Mathematical Biosciences, Vol. 226, pp. 28-37

  • Shi, P., P. Keskinocak, J. Swann, and B. Lee (2010). “The Impact of Mixing Pattern Changes from Holidays and Traveling on Outcomes during an Influenza Pandemic.” BMC Public Health 10:778.  

  • Faissol, D., J. Swann, B. Kolodziejski, P. Griffin and T. Gift (2007). “The Role of Bathhouses and Sex Clubs in HIV Transmission: Findings from a Mathematical Model.”  Journal of AIDS.  44(4): 386-394. 

  • Scherrer, C., P. Griffin, J. Swann (2007). “Public Health Sealant Delivery Programs: Optimal Delivery and the Cost  of Practice Acts.”  Medical Decision Making. 27:762. 

  • Griffin, S.O., Griffin, P.M., Beltran-Aguilar, E.B., Malvitz, D.M., and Heiden, K.D. (2004), “Estimating Prevalence and Severity of Caries in the Mixed Dentition: A Comparison of Two Screening Protocols,” Journal of Public Health Dentistry, Vol. 64, 14-19

  • Griffin, S.O., Griffin, P.M., Gooch, B.F., and Barker, L.K. (2002), “Comparing the Costs of Three Sealant Delivery Strategies,” Journal of Dental Research, Vol. 81, 641-645

"We use the CT scan because it’s a great defense," says the CEO of another hospital not far from Stamford. "For example, if anyone has fallen or done anything around their head — hell, if they even say the word head — we do it to be safe. We can’t be sued for doing too much."
Bitter Pill