Assessment of diabetic teleretinal imaging program at the Portland Department of Veterans Affairs Medical Center

Tsan, Grace L.; Hoban, Keely L.; Riedel, Kevin J.; Pedersen, Amy L.; Hayes, John L.

doi:10.1682/jrrd.2014.03.0077

Cited by 10 publications

(4 citation statements)

References 10 publications

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“…Thirty (18.2%) papers have indicated a two-step implementation and evaluation process that was not based on any formal structured planning strategy. Of those papers six (n=6) (66,86,89,(114)(115)(116) reported that the rationale for the implementation of the telemedicine services was based on the success of their research project or the pilot study.…”

Section: Planning Based On Need Assessmentmentioning

confidence: 99%

A systematic review of the methodologies used to evaluate telemedicine service initiatives in hospital facilities

AlDossary

Martin‐Khan

Bradford

et al. 2017

International Journal of Medical Informatics

106

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Our systematic review identified only 137 telemedicine services. This suggests either telemedicine service implementation is still not a part of mainstream clinical services, or it is not being reported in the peer-reviewed literature. The depth and the quality of information were variable across studies, reducing the generalisability. The reporting of service implementation and planning strategies should be encouraged. Given the fast paced technology driven environment of telemedicine, this may enable others to learn and understand how to implement sustainable services. The key component of planning was underreported in these studies. Studies applying and reporting more rigorous methodology would contribute greatly to the evidence for telemedicine.

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Section: Planning Based On Need Assessmentmentioning

confidence: 99%

A systematic review of the methodologies used to evaluate telemedicine service initiatives in hospital facilities

AlDossary

Martin‐Khan

Bradford

et al. 2017

International Journal of Medical Informatics

106

View full text Add to dashboard Cite

show abstract

“…This is pivotal since many countries in the world adopted trained graders for their screening programs for DR. These include the United States, 9,10 United Kingdom, 11 India, 12 Malaysia, 13 South Africa, 14 Singapore, 15 and China 16 among others. Furthermore, according to the statement by American Academy of Ophthalmology (AAO), 14,17 there is a strong (level 1) evidence that single-field retinal photography with interpretation by trained graders can serve as a screening tool to identify patients with DR where ophthalmologists are not readily available for referral for further ophthalmic evaluation and management.…”

Section: Discussionmentioning

confidence: 99%

Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program

et al. 2019

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Deep learning algorithms have been used to detect diabetic retinopathy (DR) with specialist-level accuracy. This study aims to validate one such algorithm on a large-scale clinical population, and compare the algorithm performance with that of human graders. A total of 25,326 gradable retinal images of patients with diabetes from the community-based, nationwide screening program of DR in Thailand were analyzed for DR severity and referable diabetic macular edema (DME). Grades adjudicated by a panel of international retinal specialists served as the reference standard. Relative to human graders, for detecting referable DR (moderate NPDR or worse), the deep learning algorithm had significantly higher sensitivity (0.97 vs. 0.74, p < 0.001), and a slightly lower specificity (0.96 vs. 0.98, p < 0.001). Higher sensitivity of the algorithm was also observed for each of the categories of severe or worse NPDR, PDR, and DME ( p < 0.001 for all comparisons). The quadratic-weighted kappa for determination of DR severity levels by the algorithm and human graders was 0.85 and 0.78 respectively ( p < 0.001 for the difference). Across different severity levels of DR for determining referable disease, deep learning significantly reduced the false negative rate (by 23%) at the cost of slightly higher false positive rates (2%). Deep learning algorithms may serve as a valuable tool for DR screening.

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“…Given the important role of integrated behavioral health in enhancing mental health care continuity 1 , 14 and widespread use of telehealth, there is an urgent need to develop strategies to facilitate warm handoffs and greater real-time communication between primary care and mental health providers over telehealth. For example, past research has shown that training providers on the tenets of PC-MHI increases the use of mental health assessment tools among primary care providers.…”

Section: Discussionmentioning

confidence: 99%

Association Between Virtual Care Use and Same-Day Primary Care Access in VA Primary Care-Mental Health Integration

Haderlein

Dobalian

Raja

et al. 2022

J Prim Care Community Health

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Introduction: Same-day referrals from primary care to mental health increase subsequent mental health treatment engagement. VA Primary Care-Mental Health Integration (PC-MHI) clinics offer integrated mental health services embedded in primary care clinics, providing a key entry point to mental health care. Although telehealth use expanded rapidly after the onset of COVID-19, the impact of telehealth on same-day primary care access among new PC-MHI mental health patients is unknown. To address this knowledge gap, we examined associations between telehealth use and same-day primary care access in VA PC-MHI. Methods: We examined electronic health record data to identify same-day primary care appointments among PC-MHI patients who initiated care during 3/1/2018 to 10/29/2021. We used logistic regression analyses to evaluate the effect of telehealth on same-day primary care access. Time, demographic characteristics, mental health diagnoses (PTSD and depression), and substance use disorder diagnosis were evaluated as covariates. Results: New PC-MHI patients who were seen via telehealth were less likely to receive same-day primary care access than patients seen in person (OR: 0.54; 95% CI: 0.41-0.71; P < .001). Conclusions: Despite the potential advantages of using telehealth to increase access, VA patients with an initial PC-MHI visit via telehealth were less likely than patients seen in person to be referred from primary care. Telehealth may adversely affect primary care referrals to mental health services, an outcome that could ultimately reduce specialty mental health care continuity. There is an urgent need to identify strategies to facilitate PC-MHI care coordination in the telehealth context.

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Assessment of diabetic teleretinal imaging program at the Portland Department of Veterans Affairs Medical Center

Cited by 10 publications

References 10 publications

A systematic review of the methodologies used to evaluate telemedicine service initiatives in hospital facilities

A systematic review of the methodologies used to evaluate telemedicine service initiatives in hospital facilities

Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program

Association Between Virtual Care Use and Same-Day Primary Care Access in VA Primary Care-Mental Health Integration

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