Emergency Medicine 2020 Projects

Project Title: Patient Factors in Readmission for Sepsis

Faculty Mentor:Dr. Elizabeth DeVos
Phone: 904-244-4405
Email: elizabeth.devos@jax.ufl.edu

Student: Kristin Smith
Email: kris07@ufl.edu

Research Project Description:

Sepsis occurs when an infection triggers a dysregulated immune response that leads to organ dysfunction or death. With clinical advances in resuscitation and improved sepsis screening, early mortality and late-onset multiple organ failure rates have improved. Nationwide, sepsis accounts for the greatest percentage of hospital readmissions when compared to MI, CHF, COPD and pneumonia1 and in California, was shown to cost over $500 million/year (far more than CHF ($229m) and MI ($142m))2. In a recent review of UFH-J sepsis data, sepsis readmissions occur at a rate of approximately 20% regardless of payer status. However unfunded patients, who upon initial admission had fewer comorbidities and less likelihood to suffer in hospital death, have differences in characteristics of their sepsis readmissions. Unfunded patients’ readmissions are notable for lower median charges per admission, significantly shorter median lengths of stay, and show a trend towards earlier readmission for sepsis than readmissions from other payer groups. We hypothesize that some of these hospital readmissions may be preventable and specifically related to: 1) socioeconomic status, 2) health literacy, 3) limited post-discharge support, and 4) sepsis-associated organ dysfunction. This project aims to create a score for prospective risk assessment at the time of discharge from the index sepsis admission. We will extensively characterize potential risk factors for readmission at the time of index hospital discharge for sepsis and address factors contributing to readmission within 6 months of index sepsis discharge. The UF Health-Jacksonville Faculty Dean’s Grant funds this project. The medical student will participate in data collection, analysis, and other projects relating to emergency department sepsis and/or health equity research and education as assigned.
Mayr FB, Talisa VB, Balakumar V, Chang CCH, Fine M, Yende S. Proportion and Cost of Unplanned 30-Day Readmissions After Sepsis Compared With Other Medical Conditions. JAMA. 2017:317(5)530-531.
2. Chang DW, Tseng CH, Shapiro MF. Rehospitalizations Following Sepsis: Common and Costly. Crit Care Med. 2015; 43(10)2085-93.

Project Title: Adapting the Mobile Clinic Care Coordination Program in the Emergency Department

Faculty Mentor:Dr. Caroline Srihari and Dr. Liam Holtzman
Email: corbyons@ufl.edu and lholtzman@ufl.edu

Student: Genesys Giraldo
Email: gengirald@ufl.edu 

Research Project Description:

The use of the Emergency Department (ED) for nonurgent care has been documented for decades (1,2). In 1992, more than half of the ED visits across the country were related to nonurgent care, and misuse of the ED has been previously reported as a major contributor to excess health spending (3). Although the use of the emergency department for nonurgent matters has continued to increase over the years, this pattern of ED use is most prominent among minorities, individuals of low socio-economic status (SES), and people who lack access to primary care (4,5). Individuals that identify as homeless are three times more likely to use the ED in a year than individuals that are not homeless (6). Increasing access to primary care for the uninsured and underserved can potentially address the public health concern that is overcrowding in the ED. Furthermore, expansion of primary care services for individuals of low SES can provide them with continuity of care. A study documenting the reasons for medically nonurgent ED visits found that the increased propensity of certain individuals to use the ED was tied to availability of resources or information about such resources. However, the authors report that simply expanding primary care services or educational interventions was not enough to decrease the nonemergent use of the ED (7).

In the Gainesville area, the Mobile Outreach Clinic caters to uninsured and underserved patients by offering free continuous medical care and promoting health equity by addressing the patients’ social determinants of health. The Mobile Clinic Care Coordination Program was established with the purpose of bridging health care teams together for the benefit of the patient. The program relies on undergraduate volunteers, termed care coordinators, that are trained to connect patients with the resources they need and to aid patients in overcoming the barriers associated with low SES, poor health, and poor health literacy. The volunteers also employ motivational interviewing, facilitate goal setting with patients, and empower patients to make better lifestyle choices (8). The resources offered by the Mobile Clinic Care Coordination Program can positively impact the uninsured patients that recur to the ED for primary care health concerns.

  1. Gavaler, J. S., & Van Thiel, D. H. (1980). The non-emergency in the emergency room. Journal of the National Medical Association, 72(1), 33.
  2. Jaffe, T. A., Kocher, K. E., & Ghaferi, A. A. (2018). Potentially avoidable emergency department use: when policy expects patients to be physicians. Annals of emergency medicine, 72(3), 256-258.
  3. Baker, L. C., & Baker, L. S. (1994). Excess cost of emergency department visits for nonurgent care. Health Affairs, 13(5), 162-171.
  4. Grumbach, K., Keane, D., & Bindman, A. (1993). Primary care and public emergency department overcrowding. American Journal of Public Health, 83(3), 372-378
  5. Gandhi, S. O., Grant, L. P., & Sabik, L. M. (2014). Trends in nonemergent use of emergency departments by health insurance status. Medical Care Research and Review, 71(5), 496-521.
  6. Kushel, M. B., Perry, S., Bangsberg, D., Clark, R., & Moss, A. R. (2002). Emergency department use among the homeless and marginally housed: results from a community-based study. American journal of public health, 92(5), 778-784.
  7. Guttman, N., Zimmerman, D. R., & Nelson, M. S. (2003). The many faces of access: reasons for medically nonurgent emergency department visits. Journal of Health Politics, Policy and Law, 28(6), 1089-1120.
  8. Nguyen, T., Ng, Y., Lehenaff, R., McCoy, D., Laughrey, M., Grigg, J., … & Hardt, N. S. (2019). A Mobile Clinic Care Coordination Program: Enhancing Patient Care with Innovative Roles for Undergraduate Students. Journal of health care for the poor and underserved, 30(2), 510-518.

Project Title: Understanding Patient Factors with Readmission for Sepsis

Faculty Mentor: Dr. Elizabeth DeVos
Phone: 904-244-4405
Email: elizabeth.devos@jax.ufl.edu

Student: Dimitrios Kampouris
Email: dkampouri95@ufl.edu 

Research Project Description:

Sepsis is a condition that occurs when the body’s inflammatory and immune processes become dysregulated. This escalated host response to infection leads to life threatening organ dysfunction, which ultimately leads to shock. Shock is due to the increasing direct endothelial injury, leading to a loss of integrity. Plasma leakage into the interstitium leads to reduced blood volume, decreased cardiac output, and impaired tissue perfusion. (1)
Sepsis is one of the leading diagnosis of patients admitted to the ED, and comprises the leading cause of hospital readmissions. Readmission for sepsis is dependent on certain risk factors. Young age, male, Black or Native American, low income, urban residence, and increased co-morbid factors are the most predisposing risk factors to sepsis readmissions. (2,3) University of Florida Health Jacksonville (UFHJ) in Duval County, is ranked 55/67 counties in health outcomes despite high health rankings. (4) It is a Health Zone 1, with 80% of residents being minorities, unemployment more than double the next least employed zone, and 30% falling below the poverty line. Only 36% of Duval County has achieved a greater than high school education, indicating a population with predominantly poor health literacy. (5) The county’s high unemployment and large low socioeconomic population leads to a lack of post discharge care access. Patients who fall into these predisposing risk factors were readmitted earlier for sepsis, and had greater rates of organ dysfunction. The significance of all this information and the focus of this research will be to use the factors that influence sepsis and sepsis readmission, and create a sepsis readmission risk score for prospective risk assessment. (6)

1) Gyawali B, Ramakrishna K, Dhamoon AS. Sepsis: The evolution in definition, pathophysiology, and management. SAGE Open Med. 2019;7:2050312119835043. Published 2019 Mar 21. doi:10.1177/2050312119835043
2) Chang DW, Tseng CH, Shapiro MF. Rehospitalizations Following Sepsis: Common and Costly. Crit Care Med. 2015;43(10):2085-93.
3) Norman BC, Cooke CR, Ely EW, Graves JA. Sepsis-Associated 30-Day Risk-Standardized Readmissions: Analysis of a Nationwide Medicare Sample. Crit Care Med. 2017;45(7):1130-1137
4) RWJF /University of Wisconsin Population Health Institute. County Health Rankings 2017. Available online at http://www.countyhealthrankings.org/sites/default/files/state/downloads/CHR2017_FL.pdf. Accessed May 21, 2017.
5) Duval County, Florida. Community Health Assessment and Community Health Improvement Plan. 2012. Available online at http://duval.floridahealth.gov/programs‐and‐services/community‐health‐planning‐and‐ statistics/_documents/chip.pdf. Accessed May 20, 2017.
6) Guirgis FW, Brakenridge S, Sutchu S, et al. The long-term burden of severe sepsis and septic shock: Sepsis recidivism and organ dysfunction. J Trauma Acute Care Surg. 2016;81(3):525-32.

Project Title: Efficacy and Safety of High-Sensitivity Troponin I Assay for Ruling Out Myocardial Infarction

Faculty Mentor’s Name:Dr. Brandon Allen
Email: brandonrallen@ufl.edu 

Students: Justin Raman and Jacob Sammon 
Email: justin.raman@ufl.edu jsammon96@ufl.edu 

Research Project Description:

Since patients with acute myocardial infarction (AMI) presentation comprise up to 10% of total emergency visits, there is great need to rapidly identify a life-threatening AMI (1 ).Patients with acute coronary syndrome (ACS)–which includes ST-elevation myocardial infarction (STEMI), non-ST elevation myocardial infarction (NSTEMI), and unstable angina–require continued observation and medical management in order to appropriately classify and treat. Myocardial infarctions have traditionally been ruled in or out using electrocardiograms and levels of cardiac troponins. Cardiac troponins are small proteins found within sarcomeres of cardiac myocytes. Recent development and utilization of high-sensitivity troponin I and T (hs-TnI and hs-TnT, respectively) have improved the ability to measure relatively low blood levels of these proteins unique to cardiac muscle, helping to better rule in or out myocardial infarction as well as other cardiac events in patients both with and without known cardiovascular disease (CVD) (2).
There have been several hs-Tn assays developed, each with varying cut-points for ruling in or out patients for ACS and specifically AMI. For example, a hs-TnT assay was shown to rule out faster (requiring only 1 hour compared to 3 hours) and rule out more patients suspected of MI than the existing protocol of not-high-sensitive troponin assay (3). Specific to the hs-TnI assays, recommendations made include establishing different cut points based on sex as well as tracking hs-TnI levels over time as they fluctuate (4). Assay recommendations include getting a hs-TnI level at the initial time point (T0), then at 1 hour later (T1) and at 3 hours later (T3). Through utilization of hs-Tn assays, earlier rule out for MI and earlier detection of MI are major advantages (5). Although many assays proposals have been developed, there is a significant need to determine the safety and efficacy of each so as to improve healthcare utilization and improve patient-care outcomes.

  1. Boeddinghaus J, Twerenbold R, Nestelberger T, Badertscher P, Wildi K, Puelacher C, du Fay de Lavallaz J, Keser E, Rubini Giménez M, Wussler D, Kozhuharov N, Rentsch K, Miró Ò, Martin-Sanchez FJ, Morawiec B, Stefanelli S, Geigy N, Keller DI, Reichlin T, Mueller C. Clinical Validation of a Novel High-Sensitivity Cardiac Troponin I Assay for Early Diagnosis of Acute Myocardial Infarction. Clin Chem. 2018 Sep;64(9):1347-1360. doi: 10.1373/clinchem.2018.286906. Epub 2018 Jun 25. PubMed PMID: 29941469.
  2. Jia X, Sun W, Hoogeveen RC, Nambi V, Matsushita K, Folsom AR, Heiss G, Couper DJ, Solomon SD, Boerwinkle E, Shah A, Selvin E, de Lemos JA, Ballantyne CM. High-Sensitivity Troponin I and Incident Coronary Events, Stroke, Heart Failure Hospitalization, and Mortality in the ARIC Study. Circulation. 2019 Jun 4;139(23):2642-2653. doi: 10.1161/CIRCULATIONAHA.118.038772. Epub 2019 Apr 29. PubMed PMID: 31030544; PubMed Central PMCID: PMC6546524.
  3. Vigen R, Kutscher P, Fernandez F, Yu A, Bertulfo B, Hashim IA, Molberg K, Diercks DB, Metzger JC, Soto J, Alzubaidy D, Thibodeaux L, Joglar JA, de Lemos JA, Das SR. Evaluation of a Novel Rule-Out Myocardial Infarction Protocol Incorporating High-Sensitivity Troponin T in a US Hospital. Circulation. 2018 Oct 30;138(18):2061-2063. doi: 10.1161/CIRCULATIONAHA.118.033861. PubMed PMID: 30372140.
  4. Tan JWC, Lam CSP, Kasim SS, Aw TC, Abanilla JM, Chang WT, Dang VP, Iboleon-Dy M, Mumpuni SS, Phommintikul A, Ta MC, Topipat P, Yiu KH, Cullen L. Asia-Pacific consensus statement on the optimal use of high-sensitivity troponin assays in acute coronary syndromes diagnosis: focus on hs-TnI. Heart Asia. 2017;9(1):81-87. doi: 10.1136/heartasia-2016-010818. eCollection 2017. PubMed PMID: 28466882; PubMed Central PMCID: PMC5388929.
  5. Kontos MC, Turlington JS. High-Sensitivity Troponins in Cardiovascular Disease. Curr Cardiol Rep. 2020 Mar 30;22(5):30. doi: 10.1007/s11886-020-01279-0. Review. PubMed PMID: 32232671.

Project Title: Influence of comorbidities on the rates of infection and reinfection of COVID19 in Alachua County

Faculty Mentor: Dr. Matthew Ryan 
Email: mfryan@ufl.edu 

Students: David Jablonski and Charles Sarria
Email:  davidjablonski@ufl.edu charlesjsarria@ufl.edu 

Research Project Description:

In the midst of an evolving pandemic, looking for clues as to factors that make an individual more or less likely to contract an illness is vital. This allows for more efficient allocation of healthcare workers and testing in order to slow and eventually stop the spread. One of the most important factors influencing the infectivity and severity thus far in the COVID-19 pandemic has been the prevalence of comorbidities among patients. Early studies have shown that patients concurrently affected by comorbidities such as hypertension, obesity, and diabetes have higher rates of infection as compared to patients who are not afflicted with these conditions (2,5). In addition to infectivity, it has been shown that the presence of the aforementioned comorbidities puts a patient into a higher risk category for severe complications from the disease (1,4,6). This understanding allows us to target specific populations with an increased level of attention. Our project aims to study these relationships in Alachua County so that we can determine if the disease is following the same trends as it has elsewhere.
A vital question that will continue to shape our treatment of COVID-19 and the world’s response to the pandemic, is whether an initial infection will make a patient immune from reinfection. This will guide our public policy, healthcare decisions, and will help to determine when the world can start it’s return to normality. Unfortunately, the research behind whether immunity is developed due to an initial infection with COVID-19 is widely unknown and inconclusive. The reason for the gap in knowledge is principally due to the fact that not enough time has elapsed for adequate data to present itself for analysis. Over the course of the coming months we plan to follow the development of our understanding of reinfection, and if it is determined that reinfection is occuring in Alachua County, we aim to reveal the trends and factors that make an individual more likely to become inflicted with the disease for a second time. This information will help the medical community to identify patients who are at an increased risk of reinfection, so that we may alter their treatment and follow up in an effort to diminish the prevalence and severity of the disease.
In addition to the importance of understanding how a patient’s medical history can affect the infectivity and progression of COVID-19, identifying social trends such as location of residence and socioeconomic status that are playing roles in the pandemic is extremely important. If we are able to accurately pinpoint locations across Alachua County where the disease is most prevalent, we can work to provide increased care and attention. It is well understood through research of both COVID-19 and previous diseases that a higher population density leaves the individuals living in the area at an increased risk of infection (3). This increased risk may be due to the inability to adequately socially distance from one another or due to social trends in an area such as low socioeconomic status. The answer most likely lies as a combination of the two. If we are able to locate areas across Alachua County that have clusters of infection, we can investigate whether this is due to proximity, social trends, or a combination of factors.

  1. Guan, Wei-jie, et al. “Comorbidity and Its Impact on 1590 Patients with Covid-19 in China: A Nationwide Analysis.” The European Respiratory Journal, Mar. 2020. PubMed Central, doi:10.1183/13993003.00547-2020.
  2. Richardson, Safiya, et al. “Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area.” JAMA, Apr. 2020. jamanetwork.com, doi:10.1001/jama.2020.6775.
  3. Rocklöv, Joacim, and Henrik Sjödin. “High Population Densities Catalyse the Spread of COVID-19.” Journal of Travel Medicine. academic.oup.com, doi:10.1093/jtm/taaa038. Accessed 11 May 2020.
  4. Wang, Bolin, et al. “Does Comorbidity Increase the Risk of Patients with COVID-19: Evidence from Meta-Analysis.” Aging (Albany NY), vol. 12, no. 7, Apr. 2020, pp. 6049–57. PubMed Central, doi:10.18632/aging.103000.
  5. Yang, Jing, et al. “Prevalence of Comorbidities and Its Effects in Patients Infected with SARS-CoV-2: A Systematic Review and Meta-Analysis.” International Journal of Infectious Diseases, vol. 94, May 2020, pp. 91–95. ScienceDirect, doi:10.1016/j.ijid.2020.03.017.
  6. Zhang, Jin-jin, et al. “Clinical Characteristics of 140 Patients Infected with SARS-CoV-2 in Wuhan, China.” Allergy, vol. n/a, no. n/a. Wiley Online Library, doi:10.1111/all.14238. Accessed 11 May 2020.