In an era where mental health care increasingly intersects with digital innovation, a groundbreaking pilot randomized controlled trial has explored the use of electronic Measurement-Based Care (eMBC) to address perinatal depression and anxiety. Published in BMC Psychiatry, this study pioneers the integration of symptom monitoring directly within an electronic health record (EHR) framework, marking a significant step forward in personalized, data-driven mental health interventions for pregnant and postpartum individuals.
Perinatal depression and anxiety represent a substantial public health concern, affecting a significant proportion of individuals during pregnancy and the first year postpartum. Yet, despite their prevalence, treatment to full remission remains elusive for as few as 20% of these patients. Traditional approaches to mental health care often rely on episodic clinical impressions rather than continuous, quantitative symptom tracking, which can limit the precision and responsiveness of treatment plans. This study sought to evaluate whether embedding electronic measurement tools into routine clinical practice could enhance the management of perinatal mood disorders.
The study enrolled 42 participants, all perinatal people who scored 13 or higher on the Edinburgh Postnatal Depression Scale (EPDS), an established screening tool identifying likely cases of perinatal depression. These individuals were randomized evenly to receive either the novel eMBC intervention or usual care over a span of 12 weeks post-randomization. The core of the intervention involved regular administration of standardized symptom and functioning scales within the EHR system, presented at each clinical visit to facilitate informed discussion and treatment adjustment.
Importantly, the primary focus of the trial was feasibility rather than efficacy. Researchers prioritized assessing recruitment capacity, acceptability to patients and providers, and adherence to the trial protocol. These foundational parameters are critical for determining whether a larger, fully powered clinical trial could be realistically undertaken and whether the intervention would integrate smoothly into clinical workflows without imposing undue burden.
Results showed promising signs of feasibility. Recruitment rates demonstrated sufficient interest and willingness to engage with digital measurement tools. Among 42 enrolled participants, 76.2% completed the follow-up questionnaires, indicating acceptable engagement over the trial duration. Impressively, 87.5% of clinical encounters included at least one completed symptom scale. However, only about two-thirds (68.8%) of encounters documented a discussion between provider and participant regarding these measurements, highlighting an area ripe for enhancement in provider training or system prompts to encourage utilization of collected data.
Both participants and health care providers reported good acceptability of the eMBC protocol, citing its potential to clarify symptom trajectories and provide objective data to supplement clinical judgment. Nonetheless, constructive feedback revealed opportunities for refining the interface and the clinical integration to better support patient-provider communication and shared decision-making processes. These insights will inform minor modifications ahead of any larger efficacy trial.
Preliminary clinical outcome data suggested non-significant trends favoring the eMBC group, with marginally lower scores on both the Montgomery-Asberg Depression Rating Scale (MADRS) and Hamilton Anxiety Scale (HAM-A) at 12 weeks post-randomization. Although these differences did not reach statistical significance—understandable given the pilot nature and small sample size—the directional findings provide a tantalizing hint of clinical potential warranting further exploration.
From a technical standpoint, the integration of digital scales into the EHR represents a sophisticated advance in mental health informatics. The system captured standardized symptom metrics longitudinally, enabling clinicians to visualize symptom changes over time alongside treatment modifications. This capability may address a critical gap in perinatal mental health care where symptom fluctuations can be rapid, nuanced, and challenging to capture accurately in typical episodic visits.
Moreover, embedding MBC directly into clinical workflows ensures that data collection is streamlined and less prone to the fragmentation or attrition that can occur with separate digital applications. The seamless interface within the clinician’s existing EHR environment minimizes disruption and leverages familiar platforms, which may enhance adoption and sustainability in routine care settings.
The trial also underscored the importance of provider engagement with measurement data. Despite high rates of scale completion, discussions referencing these results were absent in nearly one-third of visits. This gap suggests that technology alone is insufficient; successful digital mental health interventions must be coupled with targeted provider education, clinical prompts, or automated alerts to translate data into actionable care modifications.
Importantly, the eMBC model aligns with the broader shift towards precision medicine and patient-centered care in psychiatry. By systematically measuring symptom burden and functional impairment, treatment plans can be tailored dynamically rather than relying on static, impressionistic assessments. This iterative feedback loop holds promise for optimizing outcomes not only in perinatal populations but across diverse mental health conditions.
Given the complexity of perinatal mental health, characterized by unique biological, psychological, and social dynamics during pregnancy and postpartum, innovative tools such as eMBC may revolutionize how care is delivered. Early identification of symptom exacerbations and timely treatment adjustments could mitigate the profound impacts of maternal mental illness on both parent and child.
The investigators advocate for a larger randomized controlled trial with minor protocol refinements to rigorously assess the clinical efficacy of eMBC. If subsequent trials demonstrate meaningful improvements in depression and anxiety remission rates, this EHR-integrated intervention could become a scalable model adopted by perinatal care providers globally.
In an increasingly digital medical landscape, the study exemplifies how thoughtfully designed technological interventions can bridge gaps in mental health care access and quality. While initial findings are preliminary, they illuminate a pathway towards smarter, evidence-based treatment strategies that empower providers and patients alike through real-time data and collaborative care.
As healthcare systems strive to reduce the burden of perinatal mental illness, this pilot study offers a compelling proof-of-concept for electronic measurement-based care embedded within routine clinical practice, heralding a new frontier in maternal mental health treatment.
Subject of Research: Measurement-based care for perinatal depression and anxiety using an electronic health record-integrated intervention.
Article Title: Electronic Measurement-based care (eMBC) for perinatal depression and anxiety: a pilot randomized controlled trial.
Article References:
Askari, N., Gupta, R., Hussain-Shamsy, N. et al. Electronic Measurement-based care (eMBC) for perinatal depression and anxiety: a pilot randomized controlled trial. BMC Psychiatry 25, 437 (2025). https://doi.org/10.1186/s12888-025-06876-3
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