Quality Of Care For Acute Respiratory Infections During Direct-To-Consumer Telemedicine Visits For Adults

Shi, Zhuo; Mehrotra, Ateev; Gidengil, Courtney A.; Poon, Sabrina J.; Uscher‐Pines, Lori; Ray, Kristin N.

doi:10.1377/hlthaff.2018.05091

Cited by 87 publications

(127 citation statements)

References 33 publications

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“…Most research has been conducted on data derived from synchronous virtual visits in American health care settings, where antibiotic prescription is historically higher [6], possibly due to a more market-controlled health care system with incentives for high patient satisfaction [7]. Consequently, there have been mixed results regarding antibiotic prescribing following virtual visits in various contexts [4,[8][9][10][11][12][13][14][15][16][17][18], with most studies focusing on urinary tract infections (UTIs) and upper respiratory infections. For example, depending on the health care provider, virtual visits for sinusitis have been associated with both higher [14] and lower [10,13] prescriptions rates compared with office visits.…”

Section: Introductionmentioning

confidence: 99%

Antibiotic Prescription Rates After eVisits Versus Office Visits in Primary Care: Observational Study

Entezarjou¹,

Calling²,

Bhattacharyya³

et al. 2021

JMIR Med Inform

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Background Direct-to-consumer telemedicine is an increasingly used modality to access primary care. Previous research on assessment using synchronous virtual visits showed mixed results regarding antibiotic prescription rates, and research on assessment using asynchronous chat-based eVisits is lacking. Objective The goal of the research was to investigate if eVisit management of sore throat, other respiratory symptoms, or dysuria leads to higher rates of antibiotic prescription compared with usual management using physical office visits. Methods Data from 3847 eVisits and 759 office visits for sore throat, dysuria, or respiratory symptoms were acquired from a large private health care provider in Sweden. Data were analyzed to compare antibiotic prescription rates within 3 days, antibiotic type, and diagnoses made. For a subset of sore throat visits (n=160 eVisits, n=125 office visits), Centor criteria data were manually extracted and validated. Results Antibiotic prescription rates were lower following eVisits compared with office visits for sore throat (169/798, 21.2%, vs 124/312, 39.7%; P<.001) and respiratory symptoms (27/1724, 1.6%, vs 50/251, 19.9%; P<.001), while no significant differences were noted comparing eVisits to office visits for dysuria (1016/1325, 76.7%, vs 143/196, 73.0%; P=.25). Guideline-recommended antibiotics were prescribed similarly following sore throat eVisits and office visits (163/169, 96.4%, vs 117/124, 94.4%; P=.39). eVisits for respiratory symptoms and dysuria were more often prescribed guideline-recommended antibiotics (26/27, 96.3%, vs 37/50, 74.0%; P=.02 and 1009/1016, 99.3%, vs 135/143, 94.4%; P<.001, respectively). Odds ratios of antibiotic prescription following office visits compared with eVisits after adjusting for age and differences in set diagnoses were 2.94 (95% CI 1.99-4.33), 11.57 (95% CI 5.50-24.32), 1.01 (95% CI 0.66-1.53), for sore throat, respiratory symptoms, and dysuria, respectively. Conclusions The use of asynchronous eVisits for the management of sore throat, dysuria, and respiratory symptoms is not associated with an inherent overprescription of antibiotics compared with office visits. Trial Registration ClinicalTrials.gov NCT03474887; https://clinicaltrials.gov/ct2/show/NCT03474887

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Section: Introductionmentioning

confidence: 99%

Antibiotic Prescription Rates After eVisits Versus Office Visits in Primary Care: Observational Study

Entezarjou¹,

Calling²,

Bhattacharyya³

et al. 2021

JMIR Med Inform

View full text Add to dashboard Cite

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“…Learning about the duration of hospitalisation among COVID-19 patients and its associated factors could provide a better understanding of its impact on medical interventions as well as hospital capacities to cope with the surge of COVID-19 patients. To date, studies of COVID-19 mostly focused on epidemiological investigation, prevention and control, diagnosis and treatment [3,[6][7][8]. Fewer studies have investigated the duration of COVID-19 patients' hospital stays during the epidemic.…”

Section: Introductionmentioning

confidence: 99%

Factors associated with the duration of hospitalisation among COVID-19 patients in Vietnam: A survival analysis

et al. 2020

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Background The median duration of hospital stays due to COVID-19 has been reported in several studies on China as 10−13 days. Global studies have indicated that the length of hospitalisation depends on different factors, such as the time elapsed from exposure to symptom onset, and from symptom onset to hospital admission, as well as specificities of the country under study. The goal of this paper is to identify factors associated with the median duration of hospital stays of COVID-19 patients during the second COVID-19 wave that hit Vietnam from 5 March to 8 April 2020. Method We used retrospective data on 133 hospitalised patients with COVID-19 recorded over at least two weeks during the study period. The Cox proportional-hazards regression model was applied to determine the potential risk factors associated with length of hospital stay. Results There were 65 (48.9%) females, 98 (73.7%) patients 48 years old or younger, 15 (11.3%) persons with comorbidities, 21 (16.0%) severely ill patients and 5 (3.8%) individuals with life-threatening conditions. Eighty-two (61.7%) patients were discharged after testing negative for the SARS-CoV-2 virus, 51 were still in the hospital at the end of the study period and none died. The median duration of stay in a hospital was 21 (IQR: 16–34) days. The multivariable Cox regression model showed that age, residence and sources of contamination were significantly associated with longer duration of hospitalisation. Conclusion A close look at how long COVID-19 patients stayed in the hospital could provide an overview of their treatment process in Vietnam, and support the country's National Steering Committee on COVID-19 Prevention and Control in the efficient allocation of resources over the next stages of the COVID-19 prevention period.

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“…For example, a recent analysis of a Minnesota All-Payers Claims Database elucidated a comprehensive picture of telemedicine use across multiple payer types and patient geographies [5]. Other studies used administrative data to study telemedicine for mental health services [6], substance use disorder treatments [7], primary care [8], and acute respiratory infections [9]. Prior analyses have also highlighted trends in telemedicine use among specific populations, such as rural communities [10] and children [11].…”

Section: Introductionmentioning

confidence: 99%

Validation of use of billing codes for identifying telemedicine encounters in administrative data

Yeramosu

Kwok

Kahn

et al. 2019

BMC Health Serv Res

Self Cite

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BackgroundTelemedicine is the use of telecommunication technology to remotely provide healthcare services. Evaluation of telemedicine use often relies on administrative data, but the validity of identifying telemedicine encounters in administrative data is not known. The objective of this study was to assess the accuracy of billing codes for identifying telemedicine use.MethodsIn this retrospective study of encounters within a large integrated health system from January 2016 to December 2017, we examined the accuracy of billing codes for identifying live-interactive and store-and-forward telemedicine encounters compared to manual chart review. To further examine external validity, we applied these codes and assessed patient and visit characteristics for identified live-interactive telemedicine encounters and store-and-forward telemedicine encounters in a second data set.ResultsIn manual review of 390 encounters, 75 encounters were live-interactive telemedicine and 158 were store-and-forward telemedicine. In weighted analysis, the presence of the GT modifier in the absence of the GQ modifier or CPT code 99444 yielded 100% sensitivity and 99.99% specificity for identification of live-interactive telemedicine encounters. The presence of either the GQ modifier or the CPT code 99444 had 100% sensitivity and 100% specificity for identification of store-and-forward telemedicine encounters. Applying these algorithms to a second data set (n = 5,917,555) identified telemedicine encounters with expected patient and visit characteristics.ConclusionsThese findings provide support for use of CPT codes to perform telemedicine research in administrative data, aiding ongoing work to understand the role of non-face-to-face care in optimizing health care delivery.

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Quality Of Care For Acute Respiratory Infections During Direct-To-Consumer Telemedicine Visits For Adults

Cited by 87 publications

References 33 publications

Antibiotic Prescription Rates After eVisits Versus Office Visits in Primary Care: Observational Study

Antibiotic Prescription Rates After eVisits Versus Office Visits in Primary Care: Observational Study

Factors associated with the duration of hospitalisation among COVID-19 patients in Vietnam: A survival analysis

Validation of use of billing codes for identifying telemedicine encounters in administrative data

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