This study investigated whether screening primary care patients for major depression, electronically informing PCPs of the diagnosis, and providing evidence-based treatment recommendations for depression using an EMR system could improve the quality of patient care and 6-month clinical outcomes. We found no improvement in the depression recovery rate for our entire cohort, or any subgroup of it, when compared to previously reported outcomes for “usual care” in primary care randomized clinical trials for treating major depression.7,32,33,35
Varying the intensity of electronic feedback to study PCPs did have a statistically significant effect on the mean number of follow-up visits at 6 months. However, we found no differential impact on recovery or on various depression care process measures compared to the impact of simple screening and feedback of the diagnosis alone. Thus, our findings are consistent with trials of other screening and non-electronic feedback strategies to improve the quality of primary care for major depression.36–38
It is generally accepted that feedback delivered via a well-implemented EMR system can improve the process of care by prompting receptive physicians to perform “1-time” actions such as ordering a mammogram, lipid profile, or flu vaccine, particularly when the feedback must be acknowledged.39,40
Yet, as in this report, investigators attempting to improve outcomes for such chronic conditions as congestive heart failure21
using EMR systems and repeated reminders also found little or no measurable impact on clinical outcomes despite earlier positive reports on the effectiveness of these systems.41
We previously reported that PCPs respond quickly to electronic feedback of their patients' diagnosis of major depression, and that response rates and agreement with the diagnosis increased with repeated electronic reminders and as PCPs became more comfortable with feedback.24
That finding was consistent with another report that electronic feedback increases the rate at which PCPs document depression in their clinical notes compared to PCPs who are not electronically informed of the diagnosis.23
However, even valid and pertinent EMR reminders for appropriate depression care must compete for physician attention with overt patient concerns (e.g., fatigue, insomnia, and back pain) plus the routine primary care tasks (e.g., cancer screening and managing cardiovascular disease) to be performed within the limitations of the typical 15-minute primary care encounter. Addressing these presenting complaints and somatic symptoms can distract busy PCPs from counseling their patients for depression or from delivering appropriate care.42
Indeed, if the 6-month clinical outcomes or care processes measures for patients of PCPs randomized to either guideline exposure condition were significantly improved compared to those of “usual care” patients, one might conclude that repeated electronic reminders are necessary to alter PCP behavior and improve patient outcomes beyond that which occurs within 1 month.24
Management of a chronic medical condition also typically requires the physician to adjust initial treatment in keeping with the patient's subsequent experience and clinical outcome. Unfortunately, contemporary EMR systems cannot collect such data and subsequently present the physician with new treatment recommendations at the time of a follow-up clinical encounter. Effective treatment of chronic conditions requires a greater level of patient participation than does passive receipt of a 1-time recommendation for an immunization or a blood test.43
However, depressed individuals are often nonadherent with recommended care8,44
and EMR systems that typically provide feedback to the physician are unable to directly activate patients to participate in their own treatment.
To the best of our knowledge, this is the first report of clinical outcomes and care processes resulting from providing PCPs with electronic feedback and ongoing treatment advice for patients with major depression or any other psychiatric condition. The validity and generalizability of our findings are strengthened by: (1) application of an evidence-based treatment guideline intended for use in primary care settings and converted to an electronic format30
; (2) use of a commercially available EMR system running on the widely available Windows-PC computer platform; (3) administration of a depression case-finding instrument designed for use in a busy primary care setting27
; (4) rapid feedback of the depression diagnosis to the PCP shortly after each patient's visits; (5) requiring that physicians electronically acknowledge receipt of the depression diagnosis and respond appropriately40
; (6) limiting study participation to board-certified physicians and their patients; and (7) sufficient sample size to address our research hypothesis with adequate power and consideration of the dependence of observations under each physician.34
Despite these design strengths, our negative findings must be interpreted cautiously, since our study was conducted within a single, large, academically affiliated primary care practice. Yet, we are unaware of any published report indicating that patients with psychiatric distress treated by “academic” PCPs achieve clinical outcomes dissimilar to those of patients managed by “nonacademic” PCPs. We also note that although only 5 to 6 PCPs were assigned to each EMR exposure condition, we found no evidence that a single PCP unduly weighted the results for any study group.
It is also unclear whether our findings were related to the EMR's lack of effectiveness, a problem with the guideline's translation into an electronic form,45
competing patient and provider agendas within a limited time encounter, nonadherence with our electronic prompts and reminders for care or another barrier to the use of computers by study clinicians, failure by study patients to accept their PCPs' treatment recommendations for depression, or some other limitation. Still, few PCPs documented discussing depression with their patients 3 or more times, counseling them, or advising them to see a mental health specialist for care at either 3 or 6 months following screening with the PRIME-MD. Although PCPs may deliberately choose not to document such behavior in the medical record because of stigma or some other reason,46
our chart review indicated that the majority of patients were prescribed an antidepressant at both 3- and 6-month follow-up. Further analyses of specific PCP behaviors in response to the electronic prompts and of patients' responses to PCP recommendations are needed to address these issues.
It is conceivable that contamination of our intervention by PCPs randomized to different guideline exposure conditions compromised our ability to detect significant intergroup differences. For example, although encouraged by the investigators not to do so, study PCPs may have discussed our treatment advice with each other. Still, the recovery rate of UC patients was similar to that experienced by the UC cohort in a report from Schulberg et al.47
Patients may also have seen a PCP on the date of the PRIME-MD who was not their usual PCP, may have switched providers within the group practice, or may have seen another PCP, who had been randomized to a different study condition, when their own PCP was unavailable (e.g., on vacation). However, we found that just 8% of study patients saw a PCP other than their usual provider on the date of the PRIME-MD's administration, and switching PCPs while remaining within the group practice was uncommon (<10%). Moreover, one third of those who switched providers when their own PCP was unavailable met with a PCP randomized to the same EMR exposure condition as their assigned PCP.
Given rapid advances in the capabilities of computer software and hardware systems, investigators using newer and more powerful EMR systems might obtain a different result than ours. Contemporary EMR systems cannot automatically identify a mental illness, as they can an abnormal laboratory result or drug–drug interaction. Therefore, the need to systematically screen patients for depression either in person,48
or following initiation of treatment is necessary, unless the EMR is programmed to expose physicians to treatment advice following entry of critical information into the system (e.g., physician prescribes antidepressant pharmacotherapy).32
Still, it is difficult to convert the subtleties of a paper-based treatment guideline to algorithmic form that can be interpreted by a computer system.30
Contemporary EMR systems, such as the one used in our study site, are unable to interpret uncoded information entered as unstructured text (e.g., clinical impressions, oral recommendations, etc). To be clinically feasible, algorithm branch points must hinge on information routinely entered in the EMR system (e.g., medications, appointment dates, etc.). Although our use of the EMR was a hybrid, in that some functions were automated while others were simulated to meet the needs of a clinical trial and overcome the limitations of our EMR system, this requirement may limit the patient specificity and pertinence of computer-generated recommendations to typical care.30,45
Future EMR systems might overcome this challenge and better involve patients in their own care43
by requiring them to enter data into the EMR such as weight, blood pressure, blood glucose, and self-reported depressive symptoms via e-mail or over a secure Internet connection prior to their encounter with a physician. Nevertheless, despite developments in artificial intelligence, it will be difficult to imbue a computer with clinical reasoning or the logic to interpret human emotion and provide patient-specific empathy and counseling at the time of the clinical encounter comparable to that of a trained physician.
In conclusion, we were unable to demonstrate that screening patients for major depression, electronically informing PCPs of the diagnosis, and exposing them to evidence-based treatment recommendations for depression via an EMR system improved either clinical outcomes or various care processes for depression at 6 months following our screening procedure. Our findings are consistent with other recent reports suggesting that contemporary EMR systems are more effective at triggering “1-time” events than for ongoing management of a chronic medical condition. Given the persistent need for physicians to remain current and to provide high-quality care, and given steady declines in the real costs of computer technology, studies attempting to improve the effectiveness of care for chronic medical conditions with increasingly sophisticated EMR systems remain necessary. We encourage efforts that incorporate the key principles of delivering effective chronic illness care, particularly improved care coordination and patient self-management support that activates patients to participate in their own care.43