Tiffany Cadwallader

Ms. Tiffany Cadwallader


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 December 2021 in Cancers
Verified
Journal Article
Open access
PDF file
CMCassidi C. McDaniel
Cassidi C. McDaniel
HHHayleigh Hallam
Hayleigh Hallam
TCTiffany Cadwallader
Tiffany Cadwallader
HLHee Yun Lee
Hee Yun Lee
CCChiahung Chou
Chiahung Chou
Background: Due to diabetes being linked with poorer cervical cancer prognosis, this study aimed to evaluate HPV testing behaviors among females with and without diabetes across the U.S. by geographic area in 2016, 2018, and 2020. Methods: This cross-sectional study used the Behavioral Risk Factor Surveillance System (BRFSS) from 2016, 2018, and 2020. The study population included females aged 25–69 years old, stratified by self-reported diabetes status. The primary outcome measure was cervical cancer screening behavior, which was evaluated by self-reported HPV test uptake/receipt (yes/no). Results: A total of 361,546 females from across the U.S. were sampled. Within the study population combined from all study years, the overall likelihood of receiving an HPV test was significantly lower among females with diabetes [37.95% (95% CI: 36.87–39.04)] compared to those without diabetes [46.21% (95% CI: 45.84–46.58)] (p < 0.001). Screening rates with HPV tests were lowest among females with diabetes in the South in 2016 (29.32% (95% CI: 26.82–31.83)), 2018 (39.63% (95% CI: 36.30–42.96)), and 2020 (41.02% (95% CI: 37.60–44.45)). Conclusions: Females with diabetes are screening with HPV tests less frequently than females without diabetes, and females living in the South, particularly states in the Deep South, report the lowest rates of HPV testing.

29 July 2022 in Exploratory Research in Clinical and Social Pharmacy
Verified
Journal Article
Open access
KFKaren B Farris
Karen B Farris
TCTiffany Cadwallader
Tiffany Cadwallader
JFJoel F. Farley
Joel F. Farley
KGKatie Gatwood
Katie Gatwood
EMEmily Mackler
Emily Mackler
Justin GatwoodJustin Gatwood
Justin Gatwood
Improvements in chronic myeloid leukemia (CML), chronic lymphocytic leukemia (CLL), and multiple myeloma (MM) treatment options have increased the 5-year survival rates for patients with these hematologic malignancies. In addition to cancer management, these patients may need help to manage multiple chronic conditions (MCC). The overall objective of this study is to examine the impact and implementation of a model that coordinates care between oncology and primary care pharmacists for people taking an oral anti-cancer agent (OAAs) and medications for comorbid chronic conditions. This is a multi-center, prospective, single-arm pilot study that will recruit up to 40 patients from Michigan Medicine and Vanderbilt University Medical Center (VUMC). Eligible participants will be 18 years of age or older, prescribed an OAA, have a diagnosis of either CML, CLL or MM, and be diagnosed with and taking medication for at least two specified chronic conditions. The Pharmacists Coordinated Care Oncology Model (PCOM) is a two-month intervention that builds upon current pharmacist clinical responsibilities. Generally, participants will complete a patient-reported outcome measure at 2 and 6 weeks post-OAA initiation that is sent to their oncology pharmacist, and they will also receive a comprehensive medication review at week 4 from a primary care pharmacist for their chronic medications. The pharmacists will communicate about the results via electronic medical record (EMR) and intervene if necessary. The primary endpoints are (1) dose-adjusted OAA proportion of days covered (PDC), and (2) PDC for chronic condition medications. PDCs will be determined via prescription records. The association of OAA and chronic medication PDCs will be quantified via correlation and chi-squared tests. The association between symptom experience and OAA adherence will be examined via correlation analyses. For implementation, characteristics of patient participants, feasibility, acceptability, adoption, fidelity, and trialability will be described. Data will be collected via EMR and pharmacist and patient interviews. Median/IQR for acceptability, adoption and fidelity will be reported, and patient interviews will be analyzed using a grounded theory approach and pharmacist interviews will be analyzed using thematic analyses.