Benefícios Clínicos e Declarações de Desempenho

Esta seção descreve os benefícios clínicos pretendidos do dispositivo e as declarações de desempenho que fundamentam cada benefício. Cada benefício clínico é apoiado por métricas de desempenho específicas validadas através de estudos clínicos.

Identificadores de Benefícios Clínicos

Cada benefício clínico é identificado por um código único de 3 caracteres utilizado de forma consistente nas Instruções de Utilização, no dossiê técnico, na avaliação clínica e na documentação de gestão de riscos. A tabela abaixo define cada código e a respectiva descrição do benefício clínico.

Code	Clinical Benefit Description
7GH	The device improves the accuracy of healthcare professionals in the diagnosis of dermatological conditions across a broad spectrum of clinical presentations, including rare diseases and lesions suspicious for skin cancer. This has a positive impact on patient management and health outcomes related to diagnosis, enabling more appropriate clinical decision-making, earlier identification of rare conditions, and, in cases of suspected malignancy, reducing the risk of delayed diagnosis and the need for unnecessary invasive procedures.
5RB	The device measures the degree of involvement of disease objectively, quantitatively, and reproducibly. This increases the precision of healthcare providers during the monitoring of patients. This has a positive impact on patient management and outcomes related to the monitoring of patients and treatment.
3KX	The device improves the precision of healthcare professionals in managing dermatological care pathways, encompassing referral decisions, resource allocation, and clinical assessment in remote care settings. This has a positive impact on patient management and outcomes related to the diagnosis and monitoring of patients, resulting in reduced waiting times for specialist consultation, improved adequacy of referrals, and expanded access to dermatological assessment across in-person and remote care settings.

Como Ler as Declarações de Desempenho

Cada benefício clínico listado abaixo é apoiado por métricas de desempenho de estudos de validação clínica. Ao ler os dados de desempenho, tenha em conta o seguinte:

• Os códigos de estudo (p. ex., IDEI_2023, BI_2024) identificam o estudo de validação clínica que gerou a métrica. Os detalhes bibliográficos completos de cada estudo — incluindo título, investigadores principais, centros de investigação, tamanho da amostra, período do estudo e estado de publicação — são fornecidos na seção Estudos de Validação Clínica.
• O dispositivo produz sempre uma distribuição de probabilidade em todas as categorias CID-11 validadas para cada imagem processada. O dispositivo não diagnostica condições específicas; fornece uma representação de distribuição interpretativa das possíveis categorias CID para apoiar a tomada de decisões clínicas. A lista completa de categorias CID-11 cobertas pelo dispositivo é especificada na seção Finalidade prevista.
• A população do estudo apresentada para cada métrica (p. ex., "Multiple conditions", "Rare diseases", "Melanoma") indica o contexto clínico em que o estudo de validação foi conduzido — ou seja, a composição de imagens utilizadas no estudo. O mecanismo de saída do dispositivo é idêntico independentemente da condição apresentada: cada imagem recebe a mesma distribuição de probabilidade CID-11 completa. No entanto, o benefício clínico realizado pelo profissional de saúde varia consoante o contexto clínico, porque a precisão diagnóstica de base difere entre categorias de condições. Por exemplo, os profissionais de saúde têm menor precisão de base para condições dermatológicas raras, pelo que a melhoria atribuível ao dispositivo é proporcionalmente maior nesse contexto.
• As métricas de desempenho medem a melhoria na precisão diagnóstica, na precisão de referenciação ou na avaliação da gravidade do profissional de saúde ao utilizar a saída distribucional do dispositivo, em comparação com o desempenho sem o dispositivo.

Definições de Métricas e Terminologia

Para garantir clareza, são utilizadas as seguintes definições para as métricas de desempenho:

• Precisão Top-K: Mede com que frequência o diagnóstico correto (o padrão de referência clínica) aparece entre as K previsões com maior probabilidade fornecidas pelo algoritmo.
• Precisão Top-1: A previsão é considerada bem-sucedida apenas se o diagnóstico mais provável (a primeira previsão) gerado pelo algoritmo corresponder exatamente ao diagnóstico correto.
• Precisão Top-3: A previsão é considerada bem-sucedida se o diagnóstico correto estiver incluído em qualquer lugar das três previsões com maior probabilidade.
• Precisão Top-5: A previsão é considerada bem-sucedida se o diagnóstico correto aparecer entre as cinco previsões com maior probabilidade.
• AUC (Área Sob a Curva ROC): Mede a capacidade da saída do dispositivo para discriminar entre duas classes (p. ex., maligno vs. não maligno). Utilizado para o subcriterio de malignidade no âmbito do Benefício 7GH, uma vez que a questão clínica é a discriminação entre apresentações malignas e não malignas, para a qual a AUC é a métrica metodologicamente adequada. A AUC e a precisão Top-1 medem aspectos diferentes da mesma saída de classificação subjacente e não são intercambiáveis.

Benefícios Clínicos

7GH The device improves the accuracy of healthcare professionals in the diagnosis of dermatological conditions across a broad spectrum of clinical presentations, including rare diseases and lesions suspicious for skin cancer. This has a positive impact on patient management and health outcomes related to diagnosis, enabling more appropriate clinical decision-making, earlier identification of rare conditions, and, in cases of suspected malignancy, reducing the risk of delayed diagnosis and the need for unnecessary invasive procedures.

Estimated Magnitude of Benefit

• 97.06% Specificity:
  • 6EP 97.06%. Study: IDEI_2023 (Multiple malignant conditions). User Group: Dermatologists.
• 97.06% Negative predictive value(NPV):
  • V2U 97.06%. Study: IDEI_2023 (Multiple malignant conditions). User Group: Dermatologists.
• 97.00% Area under the ROC curve(AUC):
  • FIQ 97.00%. Study: IDEI_2023 (Multiple malignant conditions). User Group: Dermatologists.
• 96.00% Negative predictive value(NPV):
  • 7ZI 96.00%. Study: DAO_Derivación_O_2022 (Multiple malignant conditions). User Group: Primary care practitioners.
• 93.95% Top-5 sensitivity:
  • ZM8 93.95%. Study: MC_EVCDAO_2019 (Melanoma). User Group: Dermatologists.
• 93.53% Specificity:
  • R9P 93.53%. Study: DAO_Derivación_O_2022 (Multiple malignant conditions). User Group: Primary care practitioners.
• 92.47% Positive predictive value(PPV):
  • 9G4 92.47%. Study: MC_EVCDAO_2019 (Multiple malignant conditions). User Group: Dermatologists.
• 90.72% Specificity. Weighted average across the following studies:
  • B4N 90.72%. Study: SAN_2024 (Multiple conditions). User Group: Dermatologists.
  • YIO 90.72%. Study: SAN_2024 (Multiple conditions). User Group: Dermatologists.
• 90.32% Top-3 sensitivity:
  • T3S 90.32%. Study: MC_EVCDAO_2019 (Melanoma). User Group: Dermatologists.
• 89.83% Area under the ROC curve(AUC):
  • 9OD 89.83%. Study: MC_EVCDAO_2019 (Multiple malignant conditions). User Group: Dermatologists.
• 89.29% Top-3 accuracy:
  • 7V9 89.29%. Study: IDEI_2023 (Multiple conditions). User Group: Dermatologists.
• 89.29% Top-5 accuracy:
  • 1S5 89.29%. Study: IDEI_2023 (Multiple conditions). User Group: Dermatologists.
• 87.50% Sensitivity:
  • GS5 87.50%. Study: IDEI_2023 (Multiple malignant conditions). User Group: Dermatologists.
• 87.50% Positive predictive value(PPV):
  • PZD 87.50%. Study: IDEI_2023 (Multiple malignant conditions). User Group: Dermatologists.
• 87.08% Specificity. Weighted average across the following studies:
  • QX8 89.91%. Study: PH_2024 (Multiple conditions). User Group: Primary care practitioners.
  • VCN 89.91%. Study: PH_2024 (Multiple conditions). User Group: Primary care practitioners.
  • FBJ 84.15%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners.
  • N2E 84.15%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners.
• 86.84% Specificity. Weighted average across the following studies:
  • FEH 86.84%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
  • VFV 86.84%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
• 86.00% Specificity:
  • VFY 86.00%. Study: MC_EVCDAO_2019 (Multiple malignant conditions). User Group: Dermatologists.
• 85.00% Area under the ROC curve(AUC):
  • 6U1 85.00%. Study: MC_EVCDAO_2019 (Melanoma). User Group: Dermatologists.
• 84.22% Top-5 accuracy:
  • EYP 84.22%. Study: MC_EVCDAO_2019 (Multiple conditions). User Group: Dermatologists.
• 84.20% Area under the ROC curve(AUC):
  • EAC 84.20%. Study: DAO_Derivación_PH_2022 (Multiple malignant conditions). User Group: Primary care practitioners.
• 81.50% Area under the ROC curve(AUC):
  • DX7 81.50%. Study: DAO_Derivación_O_2022 (Multiple malignant conditions). User Group: Primary care practitioners.
• 81.00% Top-1 accuracy:
  • JFM 81.00%. Study: MC_EVCDAO_2019 (Melanoma). User Group: Dermatologists.
• 80.88% Sensitivity:
  • BRI 80.88%. Study: MC_EVCDAO_2019 (Multiple malignant conditions). User Group: Dermatologists.
• 80.00% Specificity:
  • 4JY 80.00%. Study: MC_EVCDAO_2019 (Melanoma). User Group: Dermatologists.
• 77.86% Top-1 accuracy. Weighted average across the following studies:
  • GU0 70.87%. Study: BI_2024 (Multiple conditions). User Group: Dermatologists.
  • 47J 70.87%. Study: BI_2024 (Multiple conditions). User Group: Dermatologists.
  • LXJ 82.14%. Study: IDEI_2023 (Multiple conditions). User Group: Dermatologists.
  • 8V3 86.93%. Study: SAN_2024 (Multiple conditions). User Group: Dermatologists.
  • UC7 86.93%. Study: SAN_2024 (Multiple conditions). User Group: Dermatologists.
• 76.41% Sensitivity. Weighted average across the following studies:
  • A76 73.90%. Study: BI_2024 (Multiple conditions). User Group: Dermatologists.
  • CUC 73.90%. Study: BI_2024 (Multiple conditions). User Group: Dermatologists.
  • Q5G 85.08%. Study: SAN_2024 (Multiple conditions). User Group: Dermatologists.
  • 3GH 85.08%. Study: SAN_2024 (Multiple conditions). User Group: Dermatologists.
• 75.69% Top-3 accuracy:
  • 6R7 75.69%. Study: MC_EVCDAO_2019 (Multiple conditions). User Group: Dermatologists.
• 75.10% Top-1 accuracy. Weighted average across the following studies:
  • GZS 68.78%. Study: BI_2024 (Multiple conditions). User Group: Primary care practitioners.
  • 31Q 68.78%. Study: BI_2024 (Multiple conditions). User Group: Primary care practitioners.
  • CZR 81.85%. Study: PH_2024 (Multiple conditions). User Group: Primary care practitioners.
  • F16 81.85%. Study: PH_2024 (Multiple conditions). User Group: Primary care practitioners.
  • 5XF 89.92%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners.
  • R7X 89.92%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners.
• 74.45% Sensitivity. Weighted average across the following studies:
  • 37G 71.23%. Study: BI_2024 (Multiple conditions). User Group: Primary care practitioners.
  • 19H 71.23%. Study: BI_2024 (Multiple conditions). User Group: Primary care practitioners.
  • HUG 83.15%. Study: PH_2024 (Multiple conditions). User Group: Primary care practitioners.
  • JZ1 83.15%. Study: PH_2024 (Multiple conditions). User Group: Primary care practitioners.
  • KPM 76.53%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners.
  • 2W5 76.53%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners.
• 74.07% Specificity:
  • CH0 74.07%. Study: PH_2024 (Rare diseases). User Group: Primary care practitioners.
• 73.90% Sensitivity. Weighted average across the following studies:
  • 5IT 71.94%. Study: BI_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
  • ASM 71.94%. Study: BI_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
  • 5UM 80.64%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
  • S2C 80.64%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
• 73.79% Top-1 sensitivity:
  • T1S 73.79%. Study: MC_EVCDAO_2019 (Melanoma). User Group: Dermatologists.
• 73.73% Top-1 accuracy. Weighted average across the following studies:
  • 9D7 69.36%. Study: BI_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
  • ZKC 69.36%. Study: BI_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
  • YJC 88.78%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
  • ME3 88.78%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
  • M2A 65.07%. Study: MAN_2025 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
• 70.56% Top-1 accuracy. Weighted average across the following studies:
  • KW3 78.57%. Study: IDEI_2023 (Multiple conditions). User Group: Dermatologists.
  • WGP 55.00%. Study: MC_EVCDAO_2019 (Multiple conditions). User Group: Dermatologists.
• 67.89% Negative predictive value(NPV):
  • Z96 67.89%. Study: MC_EVCDAO_2019 (Multiple malignant conditions). User Group: Dermatologists.
• 57.14% Sensitivity:
  • LU4 57.14%. Study: DAO_Derivación_O_2022 (Multiple malignant conditions). User Group: Primary care practitioners.
• 51.85% Specificity:
  • 5W2 51.85%. Study: PH_2024 (Rare diseases). User Group: Primary care practitioners.
• 44.44% Sensitivity:
  • REV 44.44%. Study: PH_2024 (Rare diseases). User Group: Primary care practitioners.
• 42.00% Positive predictive value(PPV):
  • 0L2 42.00%. Study: DAO_Derivación_O_2022 (Multiple malignant conditions). User Group: Primary care practitioners.
• 31.28% Sensitivity. Weighted average across the following studies:
  • 8PG 34.00%. Study: BI_2024 (Rare diseases). User Group: Primary care practitioners.
  • 6YW 22.22%. Study: PH_2024 (Rare diseases). User Group: Primary care practitioners.
• 30.39% Specificity:
  • ZGT 30.39%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
• 29.80% Sensitivity:
  • NK7 29.80%. Study: BI_2024 (Rare diseases). User Group: Primary care practitioners, Dermatologists.
• 25.61% Top-1 accuracy. Weighted average across the following studies:
  • JBB 28.30%. Study: BI_2024 (Rare diseases). User Group: Primary care practitioners.
  • I7Y 16.66%. Study: PH_2024 (Rare diseases). User Group: Primary care practitioners.
• 24.70% Top-1 accuracy:
  • DII 24.70%. Study: BI_2024 (Rare diseases). User Group: Primary care practitioners, Dermatologists.
• 22.25% Sensitivity. Weighted average across the following studies:
  • 81T 23.76%. Study: BI_2024 (Multiple conditions). User Group: Primary care practitioners.
  • 09O 14.60%. Study: PH_2024 (Multiple conditions). User Group: Primary care practitioners.
  • 7YC 24.95%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners.
• 22.22% Top-1 accuracy:
  • Z90 22.22%. Study: PH_2024 (Rare diseases). User Group: Primary care practitioners.
• 21.87% Sensitivity. Weighted average across the following studies:
  • 02A 20.08%. Study: BI_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
  • A84 28.03%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
• 20.71% Top-1 accuracy. Weighted average across the following studies:
  • O4L 19.65%. Study: BI_2024 (Multiple conditions). User Group: Primary care practitioners.
  • 6KX 18.15%. Study: PH_2024 (Multiple conditions). User Group: Primary care practitioners.
  • AR8 27.00%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners.
• 20.70% Specificity. Weighted average across the following studies:
  • VEF 11.90%. Study: PH_2024 (Multiple conditions). User Group: Primary care practitioners.
  • 9YX 29.80%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners.
• 18.20% Sensitivity:
  • TG6 18.20%. Study: BI_2024 (Rare diseases). User Group: Dermatologists.
• 17.47% Top-1 accuracy. Weighted average across the following studies:
  • MRT 16.73%. Study: BI_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
  • 61I 20.00%. Study: SAN_2024 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
  • M2N 23.27%. Study: MAN_2025 (Multiple conditions). User Group: Primary care practitioners, Dermatologists.
• 15.80% Top-1 accuracy:
  • 4KO 15.80%. Study: BI_2024 (Rare diseases). User Group: Dermatologists.
• 11.03% Sensitivity. Weighted average across the following studies:
  • W8N 9.96%. Study: BI_2024 (Multiple conditions). User Group: Dermatologists.
  • BHO 14.70%. Study: SAN_2024 (Multiple conditions). User Group: Dermatologists.
• 9.53% Top-1 accuracy. Weighted average across the following studies:
  • 6FT 9.25%. Study: BI_2024 (Multiple conditions). User Group: Dermatologists.
  • O0B 10.50%. Study: SAN_2024 (Multiple conditions). User Group: Dermatologists.
• 8.37% Specificity:
  • N50 8.37%. Study: SAN_2024 (Multiple conditions). User Group: Dermatologists.

Means of Measure

Top-1 accuracySensitivityArea under the ROC curveSpecificityPositive predictive valueNegative predictive valueTop-3 accuracyTop-5 accuracyTop-1 sensitivityTop-3 sensitivityTop-5 sensitivity

Associated Performance Claims

MRT9D7ZKC02A5ITASMO4LGZS31Q81T37G19H6FTGU047JW8NA76CUCDIINK7JBB8PG4KOTG6EACDX7LU4R9P0L27ZILXJKW37V91S5FIQGS56EPPZDV2UWGP6R7EYP6U1JFMT1ST3SZM84JY9ODBRIVFY9G4Z966KXCZRF1609OHUGJZ1VEFQX8VCNI7YZ906YWREV5W2CH061IYJCME3A845UMS2CZGTFEHVFVAR85XFR7X7YCKPM2W59YXFBJN2EO0B8V3UC7BHOQ5G3GHN50B4NYIOM2NM2A

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5RB The device measures the degree of involvement of disease objectively, quantitatively, and reproducibly. This increases the precision of healthcare providers during the monitoring of patients. This has a positive impact on patient management and outcomes related to the monitoring of patients and treatment.

Estimated Magnitude of Benefit

• 81.50% Expert consensus(CUS). Weighted average across the following studies:
  • 3OA 80.00%. Study: COVIDX_EVCDAO_2022 (Multiple conditions). User Group: Dermatologists.
  • EZ1 83.00%. Study: COVIDX_EVCDAO_2022 (Multiple conditions). User Group: Dermatologists.
• 72.70% Accuracy against the expert-consensus gold standard:
  • LL5 72.70%. Study: AIHS4_2025 (Hidradenitis suppurativa). User Group: Dermatologists.
• 59.00% Correlation. Weighted average across the following studies:
  • JWQ 77.00%. Study: IDEI_2023 (Androgenetic alopecia). User Group: Dermatologists.
  • 284 47.00%. Study: IDEI_2023 (Androgenetic alopecia). User Group: Dermatologists.
  • 7TS 53.00%. Study: IDEI_2023 (Androgenetic alopecia). User Group: Dermatologists.
• 53.47% Unweighted Kappa. Weighted average across the following studies:
  • A1Q 73.97%. Study: IDEI_2023 (Androgenetic alopecia). User Group: Dermatologists.
  • 3OB 32.97%. Study: IDEI_2023 (Androgenetic alopecia). User Group: Dermatologists.

Means of Measure

Accuracy against the expert-consensus gold standardExpert consensusCorrelationUnweighted Kappa

Associated Performance Claims

LL53OAEZ1JWQA1Q2843OB7TS

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3KX The device improves the precision of healthcare professionals in managing dermatological care pathways, encompassing referral decisions, resource allocation, and clinical assessment in remote care settings. This has a positive impact on patient management and outcomes related to the diagnosis and monitoring of patients, resulting in reduced waiting times for specialist consultation, improved adequacy of referrals, and expanded access to dermatological assessment across in-person and remote care settings.

Estimated Magnitude of Benefit

• 213.46% Reduction in the number of days. Weighted average across the following studies:
  • KPQ 84.37%. Study: DAO_Derivación_O_2022 (Multiple conditions). User Group: Primary care practitioners.
  • 1M1 56.00%. Study: DAO_Derivación_O_2022 (Multiple conditions). User Group: Primary care practitioners.
  • UGS 5 days. Study: DAO_Derivación_O_2022 (Multiple conditions). User Group: Primary care practitioners.
• 100.00% Expert consensus:
  • P30 100.00%. Study: COVIDX_EVCDAO_2022 (Multiple conditions). User Group: Dermatologists.
• 100.00% Expert consensus:
  • 8MV 100.00%. Study: SAN_2024 (Multiple conditions). User Group: Dermatologists.
• 80.00% Expert consensus:
  • VCT 80.00%. Study: DAO_Derivación_PH_2022 (Multiple conditions). User Group: Primary care practitioners.
• 74.01% Expert consensus. Weighted average across the following studies:
  • ZGP 50.00%. Study: COVIDX_EVCDAO_2022 (Multiple conditions). User Group: Dermatologists.
  • RND 100.00%. Study: COVIDX_EVCDAO_2022 (Multiple conditions). User Group: Dermatologists.
  • 3BD 67.00%. Study: COVIDX_EVCDAO_2022 (Multiple conditions). User Group: Dermatologists.
  • NVT 76.67%. Study: COVIDX_EVCDAO_2022 (Multiple conditions). User Group: Dermatologists.
  • LYP 87.00%. Study: SAN_2024 (Multiple conditions). User Group: Dermatologists.
• 74.00% Sensitivity. Weighted average across the following studies:
  • CST 74.00%. Study: DAO_Derivación_O_2022 (Multiple conditions). User Group: Primary care practitioners.
  • 6H0 74.00%. Study: DAO_Derivación_O_2022 (Multiple conditions). User Group: Primary care practitioners.
• 73.10% Adequacy of referrals during in-person care. Weighted average across the following studies:
  • DCH 78.60%. Study: DAO_Derivación_O_2022 (Multiple conditions). User Group: Primary care practitioners.
  • DZC 67.60%. Study: DAO_Derivación_O_2022 (Multiple conditions). User Group: Primary care practitioners.
• 67.00% Specificity. Weighted average across the following studies:
  • H4U 67.00%. Study: DAO_Derivación_O_2022 (Multiple conditions). User Group: Primary care practitioners.
  • 04D 67.00%. Study: DAO_Derivación_O_2022 (Multiple conditions). User Group: Primary care practitioners.
• 60.70% Reduction in the number of days:
  • IP4 60.70%. Study: PH_2024 (Multiple conditions). User Group: Primary care practitioners.
• 56.00% Increase in patients that can be managed remotely:
  • WL4 56.00%. Study: SAN_2024 (Multiple conditions). User Group: Dermatologists.
• 50.00% Adequacy of referrals during remote care. Weighted average across the following studies:
  • LHF 33.00%. Study: DAO_Derivación_O_2022 (Multiple conditions). User Group: Primary care practitioners.
  • 4BO 67.00%. Study: DAO_Derivación_O_2022 (Multiple conditions). User Group: Primary care practitioners.
• 49.00% Increase in patients that can be managed remotely:
  • WOI 49.00%. Study: PH_2024 (Multiple conditions). User Group: Primary care practitioners.
• 42.00% Reduction in the number of days:
  • V2J 42.00%. Study: SAN_2024 (Multiple conditions). User Group: Dermatologists.
• 38.00% :
  • D62 38.00%. Study: DAO_Derivación_O_2022 (Multiple conditions). User Group: Primary care practitioners.
• 25.00% Increase in the adequacy of referrals:
  • 8H5 25.00%. Study: DAO_Derivación_PH_2022 (Multiple conditions). User Group: Primary care practitioners.

Means of Measure

Expert consensusIncrease in the adequacy of referralsSensitivitySpecificityAdequacy of referrals during in-person careAdequacy of referrals during remote careReduction in the number of daysIncrease in patients that can be managed remotely

Associated Performance Claims

ZGPRNDP303BDNVT8H5VCTD62CST6H0H4U04DDCHDZCLHF4BOKPQ1M1UGSIP4WOIV2JWL4LYP8MV

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