Hansen Heike, Menzel Agata, Oltrogge-Abiry Jan Hendrik, Lühmann Dagmar, Scherer Martin, Schäfer Ingmar
Department of Primary Medical Care, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.
BMC Med Inform Decis Mak. 2025 Mar 31;25(1):151. doi: 10.1186/s12911-025-02970-4.
Use of emergency departments has increased in recent years. Different efforts address this problem, eg, medical on-call services. The basis of the DEMAND intervention is computer-assisted initial telephone assessment implemented at regional associations of statutory health insurance physicians in Germany. In this intervention, recommendations for healthcare settings were given over the telephone by medical staff. Recommendations were provided using the software SmED which calculates neural networks. This study aimed to analyse if patient characteristics are associated with the output of the intervention, ie, specific setting recommendations.
Between January 2020 and March 2021, patients aged 18 years and older of the DEMAND intervention from eight intervention sites received a standardised postal survey. Recommended and used settings, and data on sociodemography, health status at the time of the emergency call, past health service use, and health literacy were collected by self-report. Multilevel, multivariable logistic regression models adjusted for random effects at the level of regions and months of observation within regions were conducted.
Of 9473 contacted individuals, 1756 (18.5 %) participated in the survey. Median age was 66 years, 59.0% were women and 30.2% living alone. The most frequently recommended service was emergency home visits (40.1%). Recommendations for this setting were associated with worse self-rated health (odds ratio 0.67, 95% confidence interval: 0.55/0.81, p < 0.001). Telephone counselling was associated with lower age (0.71, 0.59/0.85, p < 0.001), lower subjective treatment urgency (0.65, 0.51/0.82, p < 0.001) and health problems not classified as symptoms and complaints (0.41, 0.25/0.68, p = 0.001) or infections (0.22, 0.09/0.57, p = 0.002). Emergency departments were associated with better self-rated health (1.37, 1.11/1.70, p = 0.003) and health problems classified as injuries (3.12, 1.67/5.83, p < 0.001). Rescue service were associated with higher age (1.44, 1.15/1.81, p = 0.002) and higher subjective treatment urgency (2.51, 1.83/3.43, p < 0.001). General practices were associated with lower subjective treatment urgency (0.58, 0.44/0.76, p < 0.001) and health problems not classified as injuries (0.26, 0.10/0.68, p = 0.006). Emergency practices were associated with lower age (0.60, 0.48/0.74, p < 0.001), and specialist practices were associated with health problems classified as symptoms or complaints (3.75, 1.49/9.45, p = 0.005).
Most associations between patient characteristics and recommendations were comprehensible and in line with the aim of the intervention. However, it should be clarified why patients with better self-rated health were more likely to receive recommendations for emergency departments.
近年来，急诊科的使用有所增加。人们采取了不同的措施来解决这一问题，例如医疗值班服务。“需求”干预措施的基础是在德国法定医疗保险医生区域协会实施的计算机辅助初始电话评估。在这种干预措施中，医护人员通过电话给出医疗保健机构的建议。这些建议是使用计算神经网络的软件SmED提供的。本研究旨在分析患者特征是否与干预措施的结果相关，即特定的机构建议。
在2020年1月至2021年3月期间，来自八个干预地点的“需求”干预措施中年龄在18岁及以上的患者接受了标准化的邮政调查。通过自我报告收集推荐和使用的机构，以及社会人口统计学、紧急呼叫时的健康状况、过去的医疗服务使用情况和健康素养数据。进行了多层次、多变量逻辑回归模型，并对区域层面和区域内观察月份的随机效应进行了调整。
在9473名被联系的个体中，1756人（18.5%）参与了调查。中位年龄为66岁，59.0%为女性，30.2%独自生活。最常被推荐的服务是紧急家访（40.1%）。对这种机构的推荐与较差的自我健康评价相关（优势比0.67，95%置信区间：0.55/0.81，p<0.001）。电话咨询与较低的年龄（0.71，0.59/0.85，p<0.001）、较低的主观治疗紧迫性（0.65，0.51/0.82，p<0.001）以及未归类为症状和不适的健康问题（0.41，0.25/0.68，p=0.001）或感染（0.22，0.09/0.57，p=0.002）相关。急诊科与较好的自我健康评价（1.37，1.11/1.70，p=0.003）以及归类为损伤的健康问题（3.12，1.67/5.83，p<0.001）相关联。救援服务与较高的年龄（1.44，1.15/1.81，p=0.002）和较高的主观治疗紧迫性（2.51，1.83/3.43，p<0.001）相关。全科诊所与较低的主观治疗紧迫性（0.58，0.44/0.76，p<0.001）以及未归类为损伤的健康问题（0.26，0.10/0.68，p=0.006）相关。急诊诊所与较低的年龄（0.60，0.48/0.74，p<0.001）相关，专科诊所与归类为症状或不适的健康问题（3.75，1.49/9.45，p=0.005）相关。
患者特征与建议之间的大多数关联是可以理解的，并且与干预措施的目标一致。然而，需要阐明为什么自我健康评价较好的患者更有可能收到前往急诊科的建议。
