PDF(Pubmed)
Abstract：
UNASSIGNED: Artificial intelligence deployed to triage patients post-cataract surgery could help to identify and prioritise individuals who need clinical input and to expand clinical capacity. This study investigated the accuracy and safety of an autonomous telemedicine call (Dora, version R1) in detecting cataract surgery patients who need further management and compared its performance against ophthalmic specialists.
UNASSIGNED: 225 participants were recruited from two UK public teaching hospitals after routine cataract surgery between 17 September 2021 and 31 January 2022. Eligible patients received a call from Dora R1 to conduct a follow-up assessment approximately 3 weeks post cataract surgery, which was supervised in real-time by an ophthalmologist. The primary analysis compared decisions made independently by Dora R1 and the supervising ophthalmologist about the clinical significance of five symptoms and whether the patient required further review. Secondary analyses used mixed methods to examine Dora R1\'s usability and acceptability and to assess cost impact compared to standard care. This study is registered with ClinicalTrials.gov (NCT05213390) and ISRCTN (16038063).
UNASSIGNED: 202 patients were included in the analysis, with data collection completed on 23 March 2022. Dora R1 demonstrated an overall outcome sensitivity of 94% and specificity of 86% and showed moderate to strong agreement (kappa: 0.758-0.970) with clinicians in all parameters. Safety was validated by assessing subsequent outcomes: 11 of the 117 patients (9%) recommended for discharge by Dora R1 had unexpected management changes, but all were also recommended for discharge by the supervising clinician. Four patients were recommended for discharge by Dora R1 but not the clinician; none required further review on callback. Acceptability, from interviews with 20 participants, was generally good in routine circumstances but patients were concerned about the lack of a \'human element\' in cases with complications. Feasibility was demonstrated by the high proportion of calls completed autonomously (195/202, 96.5%). Staff cost benefits for Dora R1 compared to standard care were £35.18 per patient.
UNASSIGNED: The composite of mixed methods analysis provides preliminary evidence for the safety, acceptability, feasibility, and cost benefits for clinical adoption of an artificial intelligence conversational agent, Dora R1, to conduct follow-up assessment post-cataract surgery. Further evaluation in real-world implementation should be conducted to provide additional evidence around safety and effectiveness in a larger sample from a more diverse set of Trusts.
UNASSIGNED: This manuscript is independent research funded by the National Institute for Health Research and NHSX (Artificial Intelligence in Health and Care Award, AI_AWARD01852).
UNASSIGNED: 225 participants were recruited from two UK public teaching hospitals after routine cataract surgery between 17 September 2021 and 31 January 2022. Eligible patients received a call from Dora R1 to conduct a follow-up assessment approximately 3 weeks post cataract surgery, which was supervised in real-time by an ophthalmologist. The primary analysis compared decisions made independently by Dora R1 and the supervising ophthalmologist about the clinical significance of five symptoms and whether the patient required further review. Secondary analyses used mixed methods to examine Dora R1\'s usability and acceptability and to assess cost impact compared to standard care. This study is registered with ClinicalTrials.gov (NCT05213390) and ISRCTN (16038063).
UNASSIGNED: 202 patients were included in the analysis, with data collection completed on 23 March 2022. Dora R1 demonstrated an overall outcome sensitivity of 94% and specificity of 86% and showed moderate to strong agreement (kappa: 0.758-0.970) with clinicians in all parameters. Safety was validated by assessing subsequent outcomes: 11 of the 117 patients (9%) recommended for discharge by Dora R1 had unexpected management changes, but all were also recommended for discharge by the supervising clinician. Four patients were recommended for discharge by Dora R1 but not the clinician; none required further review on callback. Acceptability, from interviews with 20 participants, was generally good in routine circumstances but patients were concerned about the lack of a \'human element\' in cases with complications. Feasibility was demonstrated by the high proportion of calls completed autonomously (195/202, 96.5%). Staff cost benefits for Dora R1 compared to standard care were £35.18 per patient.
UNASSIGNED: The composite of mixed methods analysis provides preliminary evidence for the safety, acceptability, feasibility, and cost benefits for clinical adoption of an artificial intelligence conversational agent, Dora R1, to conduct follow-up assessment post-cataract surgery. Further evaluation in real-world implementation should be conducted to provide additional evidence around safety and effectiveness in a larger sample from a more diverse set of Trusts.
UNASSIGNED: This manuscript is independent research funded by the National Institute for Health Research and NHSX (Artificial Intelligence in Health and Care Award, AI_AWARD01852).
摘要：
■用于白内障手术后患者分诊的人工智能可以帮助识别和优先考虑需要临床投入的个人，并扩大临床能力。这项研究调查了自主远程医疗呼叫的准确性和安全性(多拉，版本R1）检测需要进一步管理的白内障手术患者，并将其性能与眼科专家进行比较。
■在2021年9月17日至2022年1月31日进行常规白内障手术后，从两家英国公立教学医院招募了225名参与者。符合条件的患者在白内障手术后约3周接到多拉R1的电话进行随访评估。由眼科医生实时监督。主要分析比较了多拉R1和监督眼科医生独立做出的关于五种症状的临床意义以及患者是否需要进一步检查的决定。二次分析使用混合方法来检查DoraR1的可用性和可接受性，并评估与标准护理相比的成本影响。本研究已在ClinicalTrials.gov（NCT05213390）和ISRCTN（16038063）注册。
■202名患者被纳入分析，数据收集于2022年3月23日完成。DoraR1显示出94％的总体结果敏感性和86％的特异性，并且在所有参数中与临床医生显示出中等到强的一致性（κ：0.758-0.970）。通过评估后续结果验证了安全性：多拉R1建议出院的117例患者中有11例（9％）发生了意外的管理变化，但监督临床医生也建议全部出院.DoraR1建议4名患者出院，但不建议临床医生出院；没有人需要在回调时进行进一步检查。可接受性,从对20名参与者的采访中，在常规情况下通常良好，但患者担心在有并发症的情况下缺乏“人为因素”。自主完成的呼叫比例很高（195/202，96.5％）证明了可行性。与标准护理相比，多拉R1的员工成本福利为每名患者35.18英镑。
■混合方法分析为安全性提供了初步证据，可接受性,可行性,以及临床采用人工智能对话代理的成本效益，DoraR1，对白内障术后进行随访评估。应在实际实施中进行进一步评估，以在更多不同信托的更大样本中提供有关安全性和有效性的更多证据。
■这份手稿是由国家健康研究所和NHSX（健康与护理人工智能奖，AI_AWARD01852)。
■在2021年9月17日至2022年1月31日进行常规白内障手术后，从两家英国公立教学医院招募了225名参与者。符合条件的患者在白内障手术后约3周接到多拉R1的电话进行随访评估。由眼科医生实时监督。主要分析比较了多拉R1和监督眼科医生独立做出的关于五种症状的临床意义以及患者是否需要进一步检查的决定。二次分析使用混合方法来检查DoraR1的可用性和可接受性，并评估与标准护理相比的成本影响。本研究已在ClinicalTrials.gov（NCT05213390）和ISRCTN（16038063）注册。
■202名患者被纳入分析，数据收集于2022年3月23日完成。DoraR1显示出94％的总体结果敏感性和86％的特异性，并且在所有参数中与临床医生显示出中等到强的一致性（κ：0.758-0.970）。通过评估后续结果验证了安全性：多拉R1建议出院的117例患者中有11例（9％）发生了意外的管理变化，但监督临床医生也建议全部出院.DoraR1建议4名患者出院，但不建议临床医生出院；没有人需要在回调时进行进一步检查。可接受性,从对20名参与者的采访中，在常规情况下通常良好，但患者担心在有并发症的情况下缺乏“人为因素”。自主完成的呼叫比例很高（195/202，96.5％）证明了可行性。与标准护理相比，多拉R1的员工成本福利为每名患者35.18英镑。
■混合方法分析为安全性提供了初步证据，可接受性,可行性,以及临床采用人工智能对话代理的成本效益，DoraR1，对白内障术后进行随访评估。应在实际实施中进行进一步评估，以在更多不同信托的更大样本中提供有关安全性和有效性的更多证据。
■这份手稿是由国家健康研究所和NHSX（健康与护理人工智能奖，AI_AWARD01852)。
