3 artigos com a tag "Referral"

Conclusions​

Legit.Health significantly enhanced primary care physicians' diagnostic accuracy, increasing it from 72.96% to 82.22%.

The impact of Legit.Health varied across different skin conditions, demonstrating significant improvements in hidradenitis suppurativa, urticaria, and actinic keratosis. However, p-values were not statistically significant for all cases, due to the low number of samples per pathology.

Approximately 49% of cases did not necessitate a referral. Additionally, 60.74% of cases across all specialities could be effectively managed remotely.

Reduction of referral and use of remote consultation​

Previous studies reported that 66% of patients visiting primary care HCPs are referred to dermatology, with very low (1%) remote consultation rates (González-López et al., 2019). In terms of urgent referral and triage, some institutions have reported that 76.8% of patients referred from primary HCPs to dermatology result in benign diagnoses (Pagani et al., 2023).

In this experiment, we found that 49% of cases should be referred according to the primary HCP with the information provided by the device, which is 17% lower than the aforementioned referral rates. Additionally, our results improve the remote consultation rates, suggesting that diagnostic support tools can help foster remote consultations.

Summary​

• Code: LEGIT.HEALTH_PH_2024
• Status: Finished
• Start date: June 4th, 2024
• Finish date: September 13th, 2024
• Acceptance criteria:
  • An improvement of diagnostic accuracy on both primary care physicians and dermatologists.
  • A reduction of 30% of referrals to dermatology (Warshaw et al. 2011).
  • An improvement in remote consultations.

Conclusions​

Legit.Health significantly enhanced primary care physicians' diagnostic accuracy, increasing it from 72.96% to 82.22%.

The impact of Legit.Health varied across different skin conditions, demonstrating significant improvements in hidradenitis suppurativa, urticaria, and actinic keratosis. However, p-values were not statistically significant for all cases, due to the low number of samples per pathology.

Approximately 49% of cases did not necessitate a referral. Additionally, 60.74% of cases across all specialities could be effectively managed remotely.

Reduction of referral and use of remote consultation​

Previous studies reported that 66% of patients visiting primary care HCPs are referred to dermatology, with very low (1%) remote consultation rates (González-López et al., 2019). In terms of urgent referral and triage, some institutions have reported that 76.8% of patients referred from primary HCPs to dermatology result in benign diagnoses (Pagani et al., 2023).

In this experiment, we found that 49% of cases should be referred according to the primary HCP with the information provided by the device, which is 17% lower than the aforementioned referral rates. Additionally, our results improve the remote consultation rates, suggesting that diagnostic support tools can help foster remote consultations.

Summary​

• Code: LEGIT.HEALTH_PH_2024
• Status: Finished
• Start date: June 24th, 2022
• Finish date: January 10th, 2024
• Acceptance criteria:
  • An improvement of diagnostic accuracy of 10% (Ferri et al. 2020) in primary care physicians and dermatologists.

Conclusions​

Primary care doctors exhibit a notably low sensitivity of approximately 25% when it comes to the crucial task of deciding whether to refer a patient to secondary care. This is especially true in referrals in the field of Dermatology.

On the other hand, they maintain a high specificity rate of 96%, meaning that when they do decide to make a referral, they are highly likely to be correct in their judgment that specialist care is necessary.

This pattern reflects a cautious approach, as primary care physicians seem to prefer minimizing the risk of false negatives, even if it means that some patients who could benefit from secondary care might not be promptly referred. This cautiousness impedes an optimal utilization of specialist resources.

This study reveals that approximately 29% of the referrals involve common and easily diagnosable conditions, even those from teledermatology. About half of them are related to seborrheic keratosis. Another example of conditions that can be confidently identified and managed without referrals includes skin tags, which the device can reliably confirm, and other entities are unlikely to misdiagnose.

The quality of the images significantly influences the performance of the system. This is a well-established fact in the field because image quality not only impacts the effectiveness of algorithms but also hinders dermatologists from making diagnoses through teledermatology systems. Specifically, poor-quality images of nevi often require an in-person consultation, causing unnecessary delays for specialists.

It is typically complex to calculate precise costs, but we can estimate that algorithms like the device could have a substantial impact on cost optimization while simultaneously reducing waiting times and expediting urgent cases.

In terms of the waiting list, the analysis assumes that patients could have received treatment earlier, and the appointment delays were a result of the hospital's waiting list.

The current analysis primarily focuses on malignancy, but there may be other criteria to consider when referring patients. While not addressed in this study, the device incorporates additional algorithms that focus on the severity of chronic skin conditions. Moreover, in certain cases, referrals can be based on the possibility of a specific disease that may be complex to manage.

Summary​

• Code: LEGIT.HEALTH_DAO_Derivación_O_2022
• Status: Ongoing
• Start date: April 7th, 2022
• Acceptance criteria:
  • Improve the adequacy of referrals to dermatology
  • A reduction of waiting lists (at least 30% Warshaw et al. 2011)
  • A reduction of the costs in secondary care