See past highlights of MHRN activity in our Fall Newsletter.
The Latest from MHRN
Where do patients first present with psychotic symptoms and what is the overall incidence?
When a patient presents with psychotic symptoms, research suggests that comprehensive intervention is effective if it is delivered at the first onset. For this reason it is important to have population-based data on the overall incidence of psychotic symptoms as well as data on where patients make their first presentation.
A recently published MHRN study found, that contrary to conventional wisdom, half of first episodes occur after age 30, and up to 25% present in primary care. Results also indicate that, when comprehensive data from large integrated health systems is used, the incidence of first-episode psychosis is higher than generally believed.
These population-based data have important implications for the design of early detection and early intervention programs and will be part of forthcoming analyses examining patterns of care, both before and after diagnoses.
Be careful when coding self-harm or possible suicidal behavior because of the transition to ICD-10
While health systems are actively looking at suicide risk and how to prevent it, researchers should be vigilant when assessing if these programs work because a recently published MHRN study indicates that coding of “self-harm” or “possible suicidal behavior” changed significantly with the transition from ICD-9-CM to ICD-10-CM.
For example, the study found that diagnoses of self-inflicted injury and poisoning appeared to increase abruptly with the coding transition, and this pattern was consistent across the ten MHRN participating health systems. Likewise, changes in coding of intent for injuries and poisonings during the fall of 2015 almost certainly represent artifacts of coding changes rather than true changes in suicidal behavior.
Although these specific findings may not generalize to other health systems, it’s important to be aware that the transition from ICD-9-CM to ICD-10-CM may affect research, surveillance, and quality improvement related to preventing suicidal behavior, and should be considered when interpreting trends during this period.
Check out our online repository for MHRN diagnoses codes!
The Mental Health Research Network (MHRN) created an online repository for MHRN diagnoses codes on GitHub and posted various specifications and codes. Everything is downloadable and free to the public.
MHRN Suicide Prevention Trial: new study site and 6,500 patients enrolled!
In September 2014, an MHRN-affiliated study began ground-breaking work on suicide prevention , with a goal to enroll 15,000 patients. We have now enrolled 6,500 participants and added a fourth data collection site: Kaiser Permanente Northwest.
This pragmatic trial of selective prevention should fill a major gap in current suicide prevention efforts, and the methods developed should dramatically accelerate future suicide prevention research
What is the extent of psychotropics use among children with autism spectrum disorder?
Psychotropics are frequently prescribed to children with autism spectrum disorder despite weak evidence supporting their effectiveness for such individuals. To examine the extent of psychotropic medication use, Jeanne Madden, PhD, led a study examining the health records of 7,901 children aged 1–17 with autism spectrum disorder in five health systems and compared them to matched cohorts without the disorder.
Study findings indicate that psychotropic treatment was far more prevalent among children with autism spectrum disorder, compared to children without it (48.4% versus 7.7% with some use in the study year). The finding of widespread and intensive use held whether or not other psychiatric diagnoses were present The most common classes of prescribed psychotropic drugs in the study population with autism spectrum disorder were:
- Stimulants, alpha-agonists, or atomoxetine (30.2 %)
- Antipsychotics (20.5 %)
- Antidepressants (17.8 %)
This research highlights the challenges in the treatment of children with autism spectrum disorder as well as the need for greater investment in its evaluation.
MHRN-affiliated health systems receive funding to lead a research consortium as part of NIH's All of Us Precision Medicine Initiative Cohort Program
A team of MHRN-affiliated health systems and investigators recently received NIH funding to lead a five-member Healthcare Provider Organization research consortium to expand the geographic reach and diversity of enrollment and engagement in the NIH's All of Us Precision Medicine Initiative (PMI) Cohort Program.
The consortium, led by co-PIs Brian K. Ahmedani, PhD and Christine Johnson, PhD, is a landmark research effort with a goal to advance personalized health care by studying how individual differences in lifestyle, clinical history, environment and genetics influence a person's health, disease risk, and optimal prevention and treatment approaches.
MHRN study is first to test effectiveness of behavior activation for depression in pregnant women
An MHRN study is the first to test of the effectiveness of behavior activation for depression among pregnant women, as compared with usual treatment. Since depression among pregnant women is a prevalent public health problem and associated with poor mother and child development, behavior activation may be a good intervention given that it does not require pharmaceuticals.
The study found that, compared to treatment as usual, behavioral activation was effective for pregnant women and may offer significant benefits for depression, anxiety, and stress.
A new study, funded by NIMH and implemented at the Kaiser Permanente Colorado MHRN site, aims to develop and test the effectiveness of disseminating behavioral activation using peer delivery for pregnant women with depression.
MHRN analysis looks at depression trajectories using electronic health record data
A recent analysis using MHRN data led by researchers at the University of Washington looked at depression trajectories using electronic health record data. The study team analyzed patterns in depression trajectories in a treated population of over 3,000 patients, and compared several methods to predict individual trajectories for monitoring treatment outcomes.
They found five broad trajectory patterns: stable high, stable low, fluctuating moderate, an increasing and a decreasing group. The authors also found that collaborative modeling outperformed other established methods. These findings indicate that a trajectory-based framework for depression assessment and prognosis is adaptable to model population heterogeneity using electronic health record data.