Characterizing primary care for patients with major depressive disorder using electronic health records of a US-based healthcare provider

Background: Major depressive disorder (MDD) is predominantly managed in primary care. However, primary care providers (PCPs) may not consistently follow evidence-based treatment algorithms, leading to variable patient management that can impact outcomes. Methods: We retrospectively analyzed adult patients with MDD seen at Geisinger, an integrated health system. Utilizing electronic health record (EHR) data, we classified patients as having MDD based on International Classification of Disease (ICD)-9/10 codes or a Patient Health Questionnaire (PHQ)-9 score ≥5. Outcomes assessed included time to first visit with a PCP or behavioral health specialist following diagnosis, antidepressant medication switching, persistence, healthcare resource utilization (HRU), and treatment costs. Results: Among the 38,321 patients with MDD managed in primary care in this study, significant delays between diagnosis with antidepressant prescribing and follow-up PCP visits were observed. There was also considerable variation in care following diagnosis. Overall, 34.9% of patients with an ICD-9/10 diagnosis of MDD and 41.3% with a PHQ-9 score ≥15 switched antidepressants. An ICD-9/10 diagnosis, but not moderately severe to severe depression, was associated with higher costs and HRU. More than 75% of patients with MDD discontinued antidepressant medication within 6 months. Limitations: The study population was comparable with other real-world studies of MDD, but study limitations include its retrospective nature and reliance on the accuracy of EHRs. Conclusions: Management of patients with MDD in a primary care setting is variable. Addressing these gaps will have important implications for ensuring optimal patient management, which may reduce HRU and treatment medication costs, and improve treatment persistence

The safety and tolerability of vortioxetine: analysis of data from randomised placebo-controlled trials and open-label extension studies

The safety and tolerability of vortioxetine in adults with major depressive disorder (MDD) was assessed. Tolerability was based on the nature, incidence and severity of treatment-emergent adverse events (TEAEs) during acute (6/8) week treatment in 11 randomised, double-blind placebo-controlled short-term studies in MDD: 6 with an active reference. Symptoms following discontinuation were assessed through the Discontinuation-Emergent Signs and Symptoms (DESS) checklist in 3 studies. Long-term (?52 weeks) tolerability was evaluated in 5 open-label extension studies. 5701 patients were acutely treated with either placebo (n=1817), vortioxetine (5-20mg/day) (n=3018), venlafaxine XR (225mg/day) (n=113), or duloxetine (60mg/day) (n=753). The withdrawal rate due to TEAEs during treatment with vortioxetine (5-20mg/day) was 4.5-7.8%, compared to placebo (3.6%), venlafaxine XR (14.2%) or duloxetine (8.8%). Common TEAEs (incidence ?5% and >2x placebo) with vortioxetine (5-20mg/day) were nausea (20.9-31.2%) and vomiting (2.9-6.5%). For vortioxetine (5-20mg/day), the incidence of TEAEs associated with insomnia was 2.0-5.1% versus 4.0% for placebo, and with sexual dysfunction 1.6-1.8% versus 1.0% for placebo. Discontinuation symptoms as assessed by the mean DESS total score after abrupt discontinuation were comparable to placebo in the first and second week. Vortioxetine had no effect relative to placebo on clinical laboratory parameters, body weight, heart rate, or blood pressure. Vortioxetine showed no clinically relevant effect on ECG parameters, including the QTcF interval. In long-term treatment, no new types of TEAEs were seen; the mean weight gain was 0.7-0.8kg. Thus, vortioxetine (5-20mg/day) appears safe and generally well tolerated in the treatment of MDD

User-centered design of a digitally enabled care pathway in a large health system: Qualitative interview study

Background: Major depressive disorder (MDD) is a leading cause of disability worldwide. Management of chronic conditions such as MDD can be improved by enhanced patient engagement, measurement-based care (MBC), and shared decision-making (SDM). A user-centered design approach can improve the understanding of the patient journey and care team workflows and thus aid the development of digital health care innovations optimized for the needs of patients living with MDD and their primary care teams. Objective: This study aims to use qualitative research methods for the user-centered design of a digitally enabled MDD care platform, PathwayPlatform, intended to enhance patient engagement, MBC, and SDM. Methods: Insights were gathered through 2 stages of qualitative interviews by a study team with expertise in qualitative research and user-centered design methods. Thematic analysis was used to generate an overarching understanding of a set of shared experiences, thoughts, or behaviors across a broad qualitative data set, including transcripts of interviews, to allow both inductive and deductive insights to emerge. Thematic analysis of interviews was supported by Dedoose (SocioCultural Research Consultants, LLC), a qualitative data analysis software tool that enables systematized coding. Findings and insights were presented based on code frequency, salience, and relevance to the research project. Results: In stage 1, interviews were conducted with 20 patients living with MDD and 15 health care providers from September 2018 to January 2019 to understand the experiences with and perceptions about the initial functionality of the Pathway app while also exploring the perceptions about potential additional features and functionality. Feedback about care team workflows and treatment approaches was collected in stage-2 interviews with 36 health care providers at 8 primary care sites. Inductive and deductive thematic analyses revealed several themes related to app functionality, patient-provider engagement, workflow integration, and patient education. Both patients and their care teams perceived the remote tracking of patient-reported outcomes via digital tools to be clinically useful and reliable and to promote MBC and SDM. However, there was emphasis on the need to enhance the flow of real-time data shared with the care team, improve trend visualizations, and integrate the data within the existing clinical workflow and educational programs for patients and their care teams. User feedback was incorporated into the iterative development of the Pathway app. Conclusions: Ongoing communication with patients living with MDD and their care teams provided an opportunity for user-centric developmental iterations of the Pathway Platform. Key insights led to further development of the patient-facing and care team-facing visit preparation features, collaborative goal-setting and goal-tracking features, patient-reported outcome summaries, and trend visualizations. The result is an enhanced digital platform with the potential to improve treatment outcomes and provide patients living with MDD additional support throughout their treatment journey

Design and implementation of a digitally enabled care pathway to improve management of depression in a large health care system: Protocol for the implementation of a patient care platform

Background: Major depressive disorder (MDD) is a serious public health concern worldwide. A treatment approach that incorporates measurement-based care (MBC) and shared decision-making between patients with MDD and their providers may foster patient engagement and improve clinical outcomes. While digital tools such as mobile apps show promise for expanding health interventions, these apps are rarely integrated into clinical practice. Objective: The primary objective of this ongoing study is to determine whether implementation of a digital tool-the Pathway Platform-in primary care improves adherence to MBC practices; here, we present the study methods. Methods: This large-scale, real-world implementation study is based on a pilot study of an earlier iteration of a mobile app (the Pathway app) that confirmed the feasibility of using the app in patients with MDD and showed a positive trend in patient engagement in the app arm. In addition, a user-centered design approach that included qualitative assessments from patients and providers was used to improve understanding of the patient journey and care team workflows. User feedback highlighted the need for enhanced features, education modules, and real-time data sharing via integration with the electronic health record. The current iteration of the Platform includes the newest version of the Pathway app, education modules for both patients and providers, and real-time patient-level data sharing with the electronic health record. The study takes place in primary care sites within the Advocate Aurora Health system in Illinois and includes adult patients with MDD who were recently prescribed monotherapy antidepressant medication (defined as a new start, medication switch, or dose change in the past 3 months). Clinical performance and selected patient outcomes will be compared before and after the implementation of the Platform. Results: Patient recruitment was completed in July 2022, with initial results expected in mid-2023. Conclusions: This study will provide useful insights into real-world integration of a digital platform within a large health system. The methods presented here highlight the unique user-centric development of the Pathway Platform, which has resulted in an enhanced digital tool with the potential to foster MBC and shared decision-making, improve patient-provider communication, and ultimately lead to optimized treatment outcomes for patients with MDD. Trial registration: ClinicalTrials.gov NCT04891224 ; https://clinicaltrials.gov/ct2/show/NCT04891224. International registered report identifier (irrid): DERR1-10.2196/43788

An App-Based Digit Symbol Substitution Test for Assessment of Cognitive Deficits in Adults With Major Depressive Disorder: Evaluation Study

BackgroundCognitive dysfunction is an impairing core symptom of depression. Among adults with major depressive disorder (MDD) treated with antidepressants, residual cognitive symptoms interfere with patient-reported outcomes. The foregoing characterization of cognitive symptoms provides the rationale for screening and assessing the severity of cognitive symptoms at point of care. However, clinical neurocognitive assessments are time-consuming and difficult, and they require specialist expertise to interpret them. A smartphone-delivered neurocognitive test may offer an effective and accessible tool that can be readily implemented into a measurement-based care framework. ObjectiveWe aimed to evaluate the use of a smartphone-delivered app-based version of the established Cognition Kit Digit Symbol Substitution Test (DSST) neurocognitive assessment compared to a traditional paper-and-pencil version. MethodsConvergent validity and test-retest reliability of the 2 versions were evaluated. Patient satisfaction with the app was also assessed. ResultsAssessments made using the app-based Cognition Kit DSST were highly correlated with the standard paper-and-pencil version of the test, both at the baseline visit (r=0.69, df=27; P<.001) and at the end-of-study visit (r=0.82, df=27; P<.001), and they were positively evaluated by 30 patients as being user-friendly, easy to navigate, and preferable over the paper-and-pencil version of the DSST. However, although the app-based Cognition Kit DSST was validated in patients with MDD, it still needs to be evaluated in healthy controls. ConclusionsApp-based DSST may facilitate a more personalized, convenient, and cost-effective method of cognitive assessment, helping to guide measurement-based care and psychotherapeutic and pharmacologic treatment options for patients with MDD. Trial RegistrationClinicalTrials.gov NCT03999567; https://tinyurl.com/2p8pnyv