scholarly journals The Boston Medical Center Experience: An Achievable Model for the Delivery of Transgender Medical Care at an Academic Medical Center

2018 ◽  
Vol 3 (1) ◽  
pp. 136-140 ◽  
Author(s):  
Pamela Klein ◽  
Supraja Narasimhan ◽  
Joshua D. Safer
Keyword(s):  
Medical Care ◽  
Medical Center ◽  
Academic Medical Center ◽  
Academic Medical ◽  
Boston Medical

Millennials Seeking Healthcare: Examining the Degree to Which Patients Utilize Online Resources (Preprint)

2021 ◽  
Author(s):  
Landon Arensberg ◽  
Jessica Kalender-Rich ◽  
Jaehoon Lee ◽  
Cheryl Gibson
Keyword(s):  
Medical Care ◽  
Baby Boomers ◽  
Medical Center ◽  
Academic Medical Center ◽  
Age Groups ◽  
Online Reviews ◽  
Online Resources ◽  
Cross Sectional ◽  
Academic Medical ◽  
Us Census

BACKGROUND According to the 2020 US Census, a Silver Tsunami is looming with more than 75.4 million persons aged 57-75 (known as “Baby Boomers”) expected to need more costly medical care. Future estimates, however, indicate a much larger wave of individuals is imminent, given the 83.1 million Millennials approaching adulthood who will be seeking medical care. Because Millennials differ from Baby Boomers in several ways, it is important to understand how this population finds their physician to gain insight into what might influence this decision. OBJECTIVE To determine the extent and influence online resources and reviews have on the younger generation as compared to elder generations. METHODS Between the months of May and July 2020 a cross-sectional paper-based survey was conducted at primary care and geriatric clinics located within a large urban academic medical center in the Midwest. RESULTS A sample of 284 patients completed the survey (44.35 ± 17.54 yrs old [range=18-90], 60.6% female, 57.4% white). Of Millennials (respondents aged 22-38 yrs), 67.2% read online reviews before choosing a physician. Millennials were significantly more likely to read online reviews before choosing a physician (P=0.004) and utilize online resources to search for a new physician (P<.001) than older patients. The majority of millennials were likely to be influenced by both negative reviews (59%) and positive reviews (71.3%). Female patients were more likely to read online reviews and use online resources compared to men, but the differences were not significant. CONCLUSIONS Overall, Millennials are much more likely to research online reviews before choosing a physician. Other generations also use online resources to an extent but tend to use personal referrals. Across all age groups, negative online reviews were less influential in decision-making compared to positive ones. Therefore, a presence on review websites and search engines seems to only benefit one’s medical practice to capture the new wave of patients.

Gender differences in career progress and satisfaction in an academic medical center

2002 ◽  
Vol 2 (3) ◽  
pp. 95-104 ◽  
Author(s):  
JoAnn Manson ◽  
Beverly Rockhill ◽  
Margery Resnick ◽  
Eleanor Shore ◽  
Carol Nadelson ◽  
...  
Keyword(s):  
Gender Differences ◽  
Medical Center ◽  
Academic Medical Center ◽  
Academic Medical ◽  
Career Progress

Mo1760 Assessment of Postoperative Complications in Patients With IBD. A Single Academic Medical Center Experience

2013 ◽  
Vol 144 (5) ◽  
pp. S-1109 ◽  
Author(s):  
Samantha J. Quade ◽  
Joshua Mourot ◽  
Anita Afzali ◽  
Mika N. Sinanan ◽  
Scott D. Lee ◽  
...  
Keyword(s):  
Postoperative Complications ◽  
Medical Center ◽  
Academic Medical Center ◽  
Academic Medical

scholarly journals Deferring Routine Wrist Radiography Does Not Affect Management of de Quervain Tendinopathy Patients

2017 ◽  
Vol 07 (02) ◽  
pp. 115-120 ◽  
Author(s):  
Tiffany Liu ◽  
Chia Wu ◽  
David Steinberg ◽  
David Bozentka ◽  
L. Levin ◽  
...  
Keyword(s):  
Physical Examination ◽  
Medical Center ◽  
Academic Medical Center ◽  
Diagnostic Study ◽  
Level Of Evidence ◽  
Radiographic Findings ◽  
Academic Medical ◽  
De Quervain ◽  
Clinical Records ◽  
Surgical Release

Background Obtaining wrist radiographs prior to surgeon evaluation may be wasteful for patients ultimately diagnosed with de Quervain tendinopathy (DQT). Questions/Purpose Our primary question was whether radiographs directly influence treatment of patients presenting with DQT. A secondary question was whether radiographs influence the frequency of injection and surgical release between cohorts with and without radiographs evaluated within the same practice. Patients and Methods Patients diagnosed with DQT by fellowship-trained hand surgeons at an urban academic medical center were identified retrospectively. Basic demographics and radiographic findings were tabulated. Clinical records were studied to determine whether radiographic findings corroborated history or physical examination findings, and whether management was directly influenced by radiographic findings. Frequencies of treatment with injection and surgery were separately tabulated and compared between cohorts with and without radiographs. Results We included 181 patients (189 wrists), with no differences in demographics between the 58% (110 wrists) with and 42% (79 wrists) without radiographs. Fifty (45%) of imaged wrists demonstrated one or more abnormalities; however, even for the 13 (12%) with corroborating history and physical examination findings, wrist radiography did not directly influence a change in management for any patient in this series. No difference was observed in rates of injection or surgical release either upon initial presentation, or at most recent documented follow-up, between those with and without radiographs. No differences in frequency, types, or total number of additional simultaneous surgical procedures were observed for those treated surgically. Conclusion Wrist radiography does not influence management of patients presenting DQT. Level of Evidence This is a level III, diagnostic study.

scholarly journals Clinical Team Distribution and Antibiotic Use Patterns at a Tertiary-Care Academic Medical Center

2020 ◽  
Vol 41 (S1) ◽  
pp. s168-s169
Author(s):  
Rebecca Choudhury ◽  
Ronald Beaulieu ◽  
Thomas Talbot ◽  
George Nelson
Keyword(s):  
Medical Center ◽  
Academic Medical Center ◽  
Tertiary Care ◽  
Antibiotic Use ◽  
Care Hospital ◽  
Hospital Units ◽  
Antibiotic Utilization ◽  
Academic Medical ◽  
Level Data ◽  
Utilization Data

Background: As more US hospitals report antibiotic utilization to the CDC, standardized antimicrobial administration ratios (SAARs) derived from patient care unit-based antibiotic utilization data will increasingly be used to guide local antibiotic stewardship interventions. Location-based antibiotic utilization surveillance data are often utilized given the relative ease of ascertainment. However, aggregating antibiotic use data on a unit basis may have variable effects depending on the number of clinical teams providing care. In this study, we examined antibiotic utilization from units at a tertiary-care hospital to illustrate the potential challenges of using unit-based antibiotic utilization to change individual prescribing. Methods: We used inpatient pharmacy antibiotic use administration records at an adult tertiary-care academic medical center over a 6-month period from January 2019 through June 2019 to describe the geographic footprints and AU of medical, surgical, and critical care teams. All teams accounting for at least 1 patient day present on each unit during the study period were included in the analysis, as were all teams prescribing at least 1 antibiotic day of therapy (DOT). Results: The study population consisted of 24 units: 6 ICUs (25%) and 18 non-ICUs (75%). Over the study period, the average numbers of teams caring for patients in ICU and non-ICU wards were 10.2 (range, 3.2–16.9) and 13.7 (range, 10.4–18.9), respectively. Units were divided into 3 categories by the number of teams, accounting for ≥70% of total patient days present (Fig. 1): “homogenous” (≤3), “pauciteam” (4–7 teams), and “heterogeneous” (>7 teams). In total, 12 (50%) units were “pauciteam”; 7 (29%) were “homogeneous”; and 5 (21%) were “heterogeneous.” Units could also be classified as “homogenous,” “pauciteam,” or “heterogeneous” based on team-level antibiotic utilization or DOT for specific antibiotics. Different patterns emerged based on antibiotic restriction status. Classifying units based on vancomycin DOT (unrestricted) exhibited fewer “heterogeneous” units, whereas using meropenem DOT (restricted) revealed no “heterogeneous” units. Furthermore, the average number of units where individual clinical teams prescribed an antibiotic varied widely (range, 1.4–12.3 units per team). Conclusions: Unit-based antibiotic utilization data may encounter limitations in affecting prescriber behavior, particularly on units where a large number of clinical teams contribute to antibiotic utilization. Additionally, some services prescribing antibiotics across many hospital units may be minimally influenced by unit-level data. Team-based antibiotic utilization may allow for a more targeted metric to drive individual team prescribing.Funding: NoneDisclosures: None

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