PDF(Pubmed)
Abstract：
BACKGROUND: Pregnancy-related death is on the rise in the United States, and there are significant disparities in outcomes for Black patients. Most solutions that address pregnancy-related death are hospital based, which rely on patients recognizing symptoms and seeking care from a health system, an area where many Black patients have reported experiencing bias. There is a need for patient-centered solutions that support and encourage postpartum people to seek care for severe symptoms.
OBJECTIVE: We aimed to determine the design needs for a mobile health (mHealth) patient-reported outcomes and decision-support system to assist Black patients in assessing when to seek medical care for severe postpartum symptoms. These findings may also support different perinatal populations and minoritized groups in other clinical settings.
METHODS: We conducted semistructured interviews with 36 participants-15 (42%) obstetric health professionals, 10 (28%) mental health professionals, and 11 (31%) postpartum Black patients. The interview questions included the following: current practices for symptom monitoring, barriers to and facilitators of effective monitoring, and design requirements for an mHealth system that supports monitoring for severe symptoms. Interviews were audio recorded and transcribed. We analyzed transcripts using directed content analysis and the constant comparative process. We adopted a thematic analysis approach, eliciting themes deductively using conceptual frameworks from health behavior and human information processing, while also allowing new themes to inductively arise from the data. Our team involved multiple coders to promote reliability through a consensus process.
RESULTS: Our findings revealed considerations related to relevant symptom inputs for postpartum support, the drivers that may affect symptom processing, and the design needs for symptom self-monitoring and patient decision-support interventions. First, participants viewed both somatic and psychological symptom inputs as important to capture. Second, self-perception; previous experience; sociocultural, financial, environmental, and health systems-level factors were all perceived to impact how patients processed, made decisions about, and acted upon their symptoms. Third, participants provided recommendations for system design that involved allowing for user control and freedom. They also stressed the importance of careful wording of decision-support messages, such that messages that recommend them to seek care convey urgency but do not provoke anxiety. Alternatively, messages that recommend they may not need care should make the patient feel heard and reassured.
CONCLUSIONS: Future solutions for postpartum symptom monitoring should include both somatic and psychological symptoms, which may require combining existing measures to elicit symptoms in a nuanced manner. Solutions should allow for varied, safe interactions to suit individual needs. While mHealth or other apps may not be able to address all the social or financial needs of a person, they may at least provide information, so that patients can easily access other supportive resources.
OBJECTIVE: We aimed to determine the design needs for a mobile health (mHealth) patient-reported outcomes and decision-support system to assist Black patients in assessing when to seek medical care for severe postpartum symptoms. These findings may also support different perinatal populations and minoritized groups in other clinical settings.
METHODS: We conducted semistructured interviews with 36 participants-15 (42%) obstetric health professionals, 10 (28%) mental health professionals, and 11 (31%) postpartum Black patients. The interview questions included the following: current practices for symptom monitoring, barriers to and facilitators of effective monitoring, and design requirements for an mHealth system that supports monitoring for severe symptoms. Interviews were audio recorded and transcribed. We analyzed transcripts using directed content analysis and the constant comparative process. We adopted a thematic analysis approach, eliciting themes deductively using conceptual frameworks from health behavior and human information processing, while also allowing new themes to inductively arise from the data. Our team involved multiple coders to promote reliability through a consensus process.
RESULTS: Our findings revealed considerations related to relevant symptom inputs for postpartum support, the drivers that may affect symptom processing, and the design needs for symptom self-monitoring and patient decision-support interventions. First, participants viewed both somatic and psychological symptom inputs as important to capture. Second, self-perception; previous experience; sociocultural, financial, environmental, and health systems-level factors were all perceived to impact how patients processed, made decisions about, and acted upon their symptoms. Third, participants provided recommendations for system design that involved allowing for user control and freedom. They also stressed the importance of careful wording of decision-support messages, such that messages that recommend them to seek care convey urgency but do not provoke anxiety. Alternatively, messages that recommend they may not need care should make the patient feel heard and reassured.
CONCLUSIONS: Future solutions for postpartum symptom monitoring should include both somatic and psychological symptoms, which may require combining existing measures to elicit symptoms in a nuanced manner. Solutions should allow for varied, safe interactions to suit individual needs. While mHealth or other apps may not be able to address all the social or financial needs of a person, they may at least provide information, so that patients can easily access other supportive resources.
摘要：
背景：妊娠相关死亡在美国呈上升趋势，黑人患者的预后存在显着差异。大多数解决妊娠相关死亡的解决方案都是基于医院的，这依赖于患者识别症状并寻求卫生系统的护理，许多黑人患者报告经历过偏见的地区。需要以患者为中心的解决方案，以支持和鼓励产后患者寻求严重症状的护理。
目的：我们旨在确定移动健康（mHealth）患者报告结果和决策支持系统的设计需求，以帮助Black患者评估何时寻求严重产后症状的医疗护理。这些发现也可能支持其他临床环境中不同的围产期人群和小型人群。
方法：我们对36名参与者-15名（42%）产科健康专业人员进行了半结构化访谈，10名（28%）精神卫生专业人员，11名（31%）产后黑人患者。访谈问题包括：目前的症状监测做法，有效监测的障碍和促进者，以及支持监测严重症状的mHealth系统的设计要求。访谈是录音和转录的。我们使用定向内容分析和恒定的比较过程分析了转录本。我们采用了主题分析方法，使用健康行为和人类信息处理的概念框架演绎主题，同时也允许新的主题从数据中产生。我们的团队让多个程序员通过共识过程来提高可靠性。
结果：我们的研究结果揭示了与产后支持相关症状输入相关的考虑因素，可能影响症状处理的驱动程序，以及症状自我监测和患者决策支持干预的设计需求。首先,参与者认为躯体和心理症状输入对捕获都很重要。第二,自我感知；以前的经验；社会文化，金融,环境,和卫生系统层面的因素都被认为会影响患者的处理方式，做出决定，并根据他们的症状采取行动。第三，参与者为允许用户控制和自由的系统设计提供了建议。他们还强调了谨慎措辞决策支持信息的重要性，这样，建议他们寻求护理的信息传达了紧迫性，但不会引起焦虑。或者，建议他们可能不需要护理的信息应使患者感到听到和放心。
结论：产后症状监测的未来解决方案应包括躯体和心理症状，这可能需要结合现有的措施，以微妙的方式引发症状。解决方案应该允许多种多样，安全互动，以满足个人需求。虽然mHealth或其他应用程序可能无法满足个人的所有社会或财务需求，他们至少可以提供信息，以便患者可以轻松获得其他支持资源。
目的：我们旨在确定移动健康（mHealth）患者报告结果和决策支持系统的设计需求，以帮助Black患者评估何时寻求严重产后症状的医疗护理。这些发现也可能支持其他临床环境中不同的围产期人群和小型人群。
方法：我们对36名参与者-15名（42%）产科健康专业人员进行了半结构化访谈，10名（28%）精神卫生专业人员，11名（31%）产后黑人患者。访谈问题包括：目前的症状监测做法，有效监测的障碍和促进者，以及支持监测严重症状的mHealth系统的设计要求。访谈是录音和转录的。我们使用定向内容分析和恒定的比较过程分析了转录本。我们采用了主题分析方法，使用健康行为和人类信息处理的概念框架演绎主题，同时也允许新的主题从数据中产生。我们的团队让多个程序员通过共识过程来提高可靠性。
结果：我们的研究结果揭示了与产后支持相关症状输入相关的考虑因素，可能影响症状处理的驱动程序，以及症状自我监测和患者决策支持干预的设计需求。首先,参与者认为躯体和心理症状输入对捕获都很重要。第二,自我感知；以前的经验；社会文化，金融,环境,和卫生系统层面的因素都被认为会影响患者的处理方式，做出决定，并根据他们的症状采取行动。第三，参与者为允许用户控制和自由的系统设计提供了建议。他们还强调了谨慎措辞决策支持信息的重要性，这样，建议他们寻求护理的信息传达了紧迫性，但不会引起焦虑。或者，建议他们可能不需要护理的信息应使患者感到听到和放心。
结论：产后症状监测的未来解决方案应包括躯体和心理症状，这可能需要结合现有的措施，以微妙的方式引发症状。解决方案应该允许多种多样，安全互动，以满足个人需求。虽然mHealth或其他应用程序可能无法满足个人的所有社会或财务需求，他们至少可以提供信息，以便患者可以轻松获得其他支持资源。
