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.

No Recurrence in Primary Invasive Stage 1a and 1b Melanoma and Melanoma in Situ Treated With Serial Disk Staged Excision

BACKGROUND

Optimal surgical treatment modality for invasive melanoma (IM) and melanoma in situ (MIS) has been debated with proponents for standard wide local excision (WLE), serial disk staged excision, and Mohs micrographic surgery.

OBJECTIVE

The purpose of this study is to identify the recurrence rates and surgical margins of invasive stage 1 melanoma and MIS lesions using serial disk staged excision technique with rush permanent processing and "bread loafing" microscopic analysis.

MATERIALS AND METHODS

Recurrence rates and surgical margins of 63 IM and 207 MIS at the University of California Dermatology Surgery Unit were retrospectively reviewed.

RESULTS

No recurrences were observed with average follow-up of 34 and 36 months for IM and MIS, respectively (range, 10-92 months). Average surgical margins were 19.8 mm (SD 9.7) for IM and 12.1 mm (SD 12.2) for MIS.

CONCLUSION

This SSE technique for the treatment of IM and MIS is comparable in efficacy to other SSE techniques, and it offers physicians a simple and accessible alternative to WLE and MMS.

A randomized controlled trial of an innovative, user-friendly, interactive smartphone app-based lifestyle intervention for weight loss

OBJECTIVES

Most electronically delivered lifestyle interventions are labor intensive, requiring logging onto websites and manually recording activity and diet. Cumbersome technology and lack of a human coach may have contributed to the limitations of prior interventions. In response, the current program of research created a comprehensive electronically delivered lifestyle intervention using a user-friendly, interactive, smartphone app-based model, and evaluated it in a randomized controlled trial.

METHODS

Twenty-eight adults, body mass index 25-42 kg/m2, with smartphones and sedentary jobs, were randomized to the intervention, along with conventional outpatient weight-management visits every 3 months, or to a wait-listed control group that received only weight-management visits. The intervention included wearable activity trackers, smartscales, food photography logs, physician-driven app-based behavioral coaching, and peer support via the app. The prespecified primary outcome was a comparison of change in weight in kilograms, in the intervention versus control group at 6 months.

RESULTS

At 6 months, the intervention group experienced a statistically significant weight change of -7.16 ± 1.78 kg (mean ± SE, 95% CI -11.05 to -3.26, p < 0.01), which differed from the weight change in controls by -4.16 ± 2.01 kg (95% CI -8.29 to -0.02, p < 0.05, prespecified primary outcome). Weight change in the control group was -3.00 ± 1.05 kg (95% CI -5.27 to -0.73, p < 0.05). Waist circumference and hemoglobin A1c significantly improved (intervention vs. control: p < 0.01, p < 0.05, respectively, prespecified secondary outcomes). Weight change in the intervention group correlated with numbers of food photographs participants shared (rho = -0.86, p < 0.01), numbers of their text messages (rho = -0.80, p < 0.01), number of times and days each participant stepped on the smartscale (rho = -0.73, p < 0.01; rho = -0.608, p < 0.05, respectively), and mean daily step counts (rho = -0.55, p < 0.05).

CONCLUSION

This app-based electronically delivered lifestyle intervention produced statistically significant, clinically meaningful weight loss and improved metabolic health. Engagement with the intervention correlated strongly with weight loss. Given the limited sample size, larger and longer studies of this intervention are needed.