Singh Navdeep, Hess Erik, Guo George, Sharp Adam, Huang Brian, Breslin Maggie, Melnick Edward
Medical College of Georgia, AU/UGA Medical Partnership, Athens, GA, United States.
Department of Emergency Medicine, Yale School of Medicine, New Haven, CT, United States.
JMIR Mhealth Uhealth. 2017 Sep 28;5(9):e144. doi: 10.2196/mhealth.8732.
The Concussion or Brain Bleed app is a clinician- and patient-facing electronic tool to guide decisions about head computed tomography (CT) use in patients presenting to the emergency department (ED) with minor head injury. This app integrates a patient decision aid and clinical decision support (using the Canadian CT Head Rule, CCHR) at the bedside on a tablet computer to promote conversations around individualized risk and patients' specific concerns within the ED context.
The objective of this study was to describe the use of the Concussion or Brain Bleed app in a high-volume ED and to establish preliminary efficacy estimates on patient experience, clinician experience, health care utilization, and patient safety. These data will guide the planning of a larger multicenter trial testing the effectiveness of the Concussion or Brain Bleed app.
We conducted a prospective pilot study of adult (age 18-65 years) patients presenting to the ED after minor head injury who were identified by participating clinicians as low risk by the CCHR. The primary outcome was patient knowledge regarding the injury, risks, and CT use. Secondary outcomes included patient satisfaction, decisional conflict, trust in physician, clinician acceptability, system usability, Net Promoter scores, head CT rate, and patient safety at 7 days.
We enrolled 41 patients cared for by 29 different clinicians. Patient knowledge increased after the use of the app (questions correct out of 9: pre-encounter, 3.3 vs postencounter, 4.7; mean difference 1.4, 95% CI 0.8-2.0). Patients reported a mean of 11.7 (SD 13.5) on the Decisional Conflict Scale and 92.5 (SD 12.0) in the Trust in Physician Scale (both scales range from 0 to 100). Most patients were satisfied with the app's clarity of information (35, 85%), helpfulness of information (36, 88%), and amount of information (36, 88%). In the 41 encounters, most clinicians thought the information was somewhat or extremely helpful to the patient (35, 85%), would want to use something similar for other decisions (27, 66%), and would recommend the app to other providers (28, 68%). Clinicians reported a mean system usability score of 85.1 (SD 15; scale from 0 to 100 with 85 in the "excellent" acceptability range). The total Net Promoter Score was 36.6 (on a scale from -100 to 100). A total of 7 (17%) patients received a head CT in the ED. No patients had a missed clinically important brain injury at 7 days.
An app to help patients assess the utility of CT imaging after head injury in the ED increased patient knowledge. Nearly all clinicians reported the app to be helpful to patients. The high degree of patient satisfaction, clinician acceptability, and system usability support rigorous testing of the app in a larger multicenter trial.
“脑震荡或脑出血”应用程序是一款面向临床医生和患者的电子工具,用于指导急诊科(ED)中因轻度头部受伤前来就诊的患者是否使用头部计算机断层扫描(CT)的决策。该应用程序在平板电脑上于床边集成了患者决策辅助工具和临床决策支持(使用加拿大头部CT规则,CCHR),以促进在急诊科环境下围绕个体风险和患者具体担忧展开对话。
本研究的目的是描述“脑震荡或脑出血”应用程序在高流量急诊科的使用情况,并对患者体验、临床医生体验、医疗保健利用情况和患者安全建立初步疗效评估。这些数据将指导规划一项更大规模的多中心试验,以测试“脑震荡或脑出血”应用程序的有效性。
我们对因轻度头部受伤后到急诊科就诊的成年(18 - 65岁)患者进行了一项前瞻性试点研究,参与研究的临床医生根据CCHR将这些患者识别为低风险患者。主要结局是患者对损伤、风险和CT使用的了解。次要结局包括患者满意度、决策冲突、对医生的信任、临床医生的可接受性、系统可用性、净推荐值评分、头部CT使用率以及7天时的患者安全情况。
我们纳入了由29名不同临床医生护理的41名患者。使用该应用程序后患者的知识有所增加(9个问题中正确回答的数量:就诊前为3.3个,就诊后为4.7个;平均差异为1.4,95%置信区间为0.8 - 2.0)。患者在决策冲突量表上的平均得分为11.7(标准差13.5),在对医生的信任量表上的平均得分为92.5(标准差12.0)(两个量表的范围均为0至100)。大多数患者对应用程序信息的清晰度(35名,85%)、信息的有用性(36名,88%)和信息量(36名,88%)感到满意。在41次就诊中,大多数临床医生认为这些信息对患者有些帮助或非常有帮助(35名,85%),希望在其他决策中使用类似的工具(27名,66%),并会向其他医疗人员推荐该应用程序(28名,68%)。临床医生报告的系统可用性平均评分为85.1(标准差15;量表范围为0至100,85分在“优秀”可接受范围内)。总净推荐值评分为36.6(范围为 - 100至100)。共有7名(17%)患者在急诊科接受了头部CT检查。7天时没有患者漏诊具有临床重要意义的脑损伤。
一款帮助患者评估急诊科头部受伤后CT成像效用的应用程序增加了患者的知识。几乎所有临床医生都报告该应用程序对患者有帮助。高度的患者满意度、临床医生可接受性和系统可用性支持在更大规模的多中心试验中对该应用程序进行严格测试。