Literature DB >> 32926984

Understanding the impact of teledermatology on no-show rates and health care accessibility: A retrospective chart review.

Ellen B Franciosi1, Alice J Tan1, Bina Kassamali2, Daniel M O'Connor3, Mehdi Rashighi1, Avery H LaChance4.   

Abstract

Mesh:

Year:  2020        PMID: 32926984      PMCID: PMC7484689          DOI: 10.1016/j.jaad.2020.09.019

Source DB:  PubMed          Journal:  J Am Acad Dermatol        ISSN: 0190-9622            Impact factor:   11.527


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At the onset of the COVID-19 pandemic, emergency legislation expanding the coverage of telehealth service swept across the nation to allow for continued access to medical care despite strict shelter-in-place guidelines. In the wake of this, telehealth usage has increased dramatically. Dermatology, in particular, is uniquely amenable to virtual visits, and teledermatology has the potential to become a permanent platform from which we provide specialty care. As telehealth expands, additional data are needed on the impact of telehealth on health equity. Missed appointments, or no-shows, are a measure of health disparity, with low-income, Medicaid, and minority patients traditionally having the highest no-show rates. Given the ability of teledermatology to theoretically improve patient convenience and eliminate potential barriers to care, we sought to investigate the impact of telehealth on no-show rates and patient access at a large academic medical center. The institutional review board of the University of Massachusetts designated this study exempt from institutional review as a quality improvement project. A retrospective chart review was conducted on all patients with completed or no-show appointments with a dermatologist at the UMass Memorial Hahnemann Campus during the months of May and June of 2019 and 2020. Procedural appointments were excluded. In-person visits and televisits, which were conducted using Doximity (San Francisco, CA) or AmWell (Boston, MA) software, were included. Clinic and televisit no-show rates were calculated using data from 2019 and 2020, respectively. Statistical analysis was performed with the Fisher exact test and 2-tailed P values < .05 were considered statistically significant. The Bonferroni method was applied to correct P values where indicated. Compared with clinic visits, televisits had significantly lower no-show rates, with the greatest reductions seen for Black or African American, LatinX, and primary non–English-speaking patients (Fig 1 , Table I ). Compared with clinic visits, televisits served a greater percentage of Medicaid enrollees and patients under 50 years of age (Table I). There was no significant difference in the racial/ethnic background of patients seen via the 2 platforms, with a similar proportion of minority patients seen in televisits versus clinic visits (504 of 1568 [32.1%] vs 1581 of 5315 [29.7%]; P = .19).
Fig 1

No-show rates between clinic and teledermatology visits for all patients and stratified by patient demographic subgroups: gender, primary language, and race/ethnicity. Error bars show the standard error of the mean.

Table I

Comparison of patient composition and no-show rates in clinic versus teledermatology visits for all patients and stratified by patient demographic subgroups

Patient demographicsPercent no-show (no-show visits/total visits)
TelevisitsClinic visitsP value
All4.0% (63/1568)13.4% (711/5315)<.0001
Gender
 Female4.9% (47/969)14.2% (423/2992)<.0001
 Male2.7% (16/599)12.4% (288/2322)<.0001
Primary language
 Non-English5.6% (8/143)12.5% (174/742)<.0001
 English3.9% (55/1425)11.8% (538/4573)<.0001
Race/EthnicityAdjusted P value
 Asian2.9% (2/69)14.2% (24/169).15
 Black or African American2.6% (2/77)30.4% (68/224).0006
 LatinX7.0% (17/242)27.7% (229/826).0006
 Other6.6% (4/61)25.1% (53/211).04
 Unknown1.8% (1/55)13.3% (20/151).18
 White3.5% (37/1064)8.5% (318/3734).0006
Age, y
 <504.3% (41/964)18.7% (423/2268)<.0001
 ≥503.6% (22/604)8.6% (289/3372)<.0001
Insurance payerCompleted televisitsCompleted clinic visitsAdjusted P value
 Private60.6% (975/1607)54.5% (2462/4514).08
 Medicaid25.5% (410/1607)19.6% (885/4514).0003
 Medicare13.8% (222/1607)25.9 % (1167/4514).0003
 Total16074514

Statistically significant.

No-show rates between clinic and teledermatology visits for all patients and stratified by patient demographic subgroups: gender, primary language, and race/ethnicity. Error bars show the standard error of the mean. Comparison of patient composition and no-show rates in clinic versus teledermatology visits for all patients and stratified by patient demographic subgroups Statistically significant. The data show a particularly striking reduction in no-show rates for minority patients seen via teledermatology. At the same time, both platforms served a similar population of patients with respect to race/ethnicity, while televisits saw a greater percentage of Medicaid but smaller percentage of Medicare enrollees, possibly reflecting age-dependent differences in comfort with virtual visits. Lack of private transportation, access to childcare, and inflexible work schedules contribute to higher no-show rates in minority patients and patients with Medicaid. , Significant reductions in no-show rates with teledermatology suggest that televisits may help mitigate barriers to care and improve access for these patients. Limitations of this study include its small sample size and single institution experience. However, this study provides early evidence that teledermatology may play an important role in mitigating no-show rates and improving access to our most vulnerable populations. Further investigation into the impact of telehealth on health inequity is vital to informing future policy making regarding continued insurance coverage of telemedicine moving forward.
  3 in total

1.  The Impact of Telehealth Implementation on Underserved Populations and No-Show Rates by Medical Specialty During the COVID-19 Pandemic.

Authors:  Ellen B Franciosi; Alice J Tan; Bina Kassamali; Nicholas Leonard; Guohai Zhou; Steven Krueger; Mehdi Rashighi; Avery LaChance
Journal:  Telemed J E Health       Date:  2021-04-07       Impact factor: 5.033

Review 2.  Teledermatology During COVID-19: An Updated Review.

Authors:  Morgan A Farr; Madeleine Duvic; Tejas P Joshi
Journal:  Am J Clin Dermatol       Date:  2021-04-09       Impact factor: 6.233

Review 3.  Teledermatology in the COVID-19 pandemic: A systematic review.

Authors:  Chee Hoou Loh; Steve Yew Chong Tam; Choon Chiat Oh
Journal:  JAAD Int       Date:  2021-08-02
  3 in total

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