Are AMI patients with comorbid mental illness more likely to be admitted to hospitals with lower quality of AMI care?

Coverage mandates and market dynamics: employer, insurer and patient responses to parity laws

Parity in coverage for mental health services has been a longstanding policy aim at the state and federal levels and is a regulatory feature of the Affordable Care Act. Despite the importance and legislative effort involved in these policies, evaluations of their effects on patients yield mixed results. I leverage the Employee Retirement Income Security Act and unique claims-level data that includes information on employers’ self-insurance status to shed new light in this area after the implementation of two state parity laws in 2007 and federal parity a few years later. My empirics reveal evidence of strategic avoidance on behalf of insurers in both states prior to the passage of state parity, as well as positive increases in mental health care utilization after parity laws are implemented – but context matters. Policy heterogeneity across states and strategic behaviors by employers and commercial insurers substantively shape the benefits that ultimately flow to patients. Insights from this research have broad relevance to ongoing health policy debates, particularly as states retain great discretion over many health coverage decisions and as federal policy continues to evolve.

Internal Medicine Residents' Attitudes Toward Simulated Depressed Cardiac Patients During an Objective Structured Clinical Examination: A Randomized Study

BACKGROUND

Physician biases toward mental conditions such as depression have been shown to adversely affect medical outcomes.

OBJECTIVE

To explore the relationship between residents' explicit bias toward depressed patients and their clinical skills on a cardiac case during an objective structured clinical exam (OSCE).

DESIGN

Prospective parallel randomized controlled study.

PARTICIPANTS

One hundred eighty-five internal medicine residents from three residency programs in two states.

INTERVENTION

During October-November 2015, residents were randomized to either a depressed or non-depressed standardized patient (SP) presenting with acute chest pain.

MAIN MEASURES

The Medical Condition Regard Scale (MCRS) assessed residents' explicit bias toward patients with depression. Their clinical skills (history-taking, physical examination, patient counseling, patient-physician interaction (PPI), differential diagnosis, and workup plan) and facial expressions were rated during an OSCE.

KEY RESULTS

No significant relationships were found between resident explicit bias and clinical skill measurements. Residents who examined the depressed SP scored lower, on average, on history-taking (t [183] = -2.77, p < 0.01, Cohen's d = 0.41) and higher on PPI (t [183] = 2.24, p < 0.05, Cohen's d = 0.33) than residents examining the non-depressed SP. There were no differences, on average, between stations on physical examination, counseling, correct diagnosis, workup plan, or overall SP satisfaction. Facial recognition software demonstrated that residents with a non-depressed SP had more neutral expressions than depressed-SP residents (t [133] = -2.46, p < 0.05, Cohen's d = 0.46), and residents with a depressed SP had more disgusted expressions than non-depressed-SP residents (t [83.52] = 2.10, p < 0.05, Cohen's d = 0.28).

CONCLUSIONS

Extrinsic bias did not predict OSCE performance in this study. Some differences were noted in the OSCE performance between the two stations. Further study is needed to examine the effects of patient mental health conditions on physician examination procedures, diagnostic behaviors, and patient outcomes.

Big data for bipolar disorder

The delivery of psychiatric care is changing with a new emphasis on integrated care, preventative measures, population health, and the biological basis of disease. Fundamental to this transformation are big data and advances in the ability to analyze these data. The impact of big data on the routine treatment of bipolar disorder today and in the near future is discussed, with examples that relate to health policy, the discovery of new associations, and the study of rare events. The primary sources of big data today are electronic medical records (EMR), claims, and registry data from providers and payers. In the near future, data created by patients from active monitoring, passive monitoring of Internet and smartphone activities, and from sensors may be integrated with the EMR. Diverse data sources from outside of medicine, such as government financial data, will be linked for research. Over the long term, genetic and imaging data will be integrated with the EMR, and there will be more emphasis on predictive models. Many technical challenges remain when analyzing big data that relates to size, heterogeneity, complexity, and unstructured text data in the EMR. Human judgement and subject matter expertise are critical parts of big data analysis, and the active participation of psychiatrists is needed throughout the analytical process.

Inpatient and outpatient costs in patients with coronary artery disease and mental disorders: a systematic review

Background

To systematically review in- and outpatient costs in patients with coronary artery disease (CAD) and comorbid mental disorders.

Methods

A comprehensive database search was conducted for studies investigating persons with CAD and comorbid mental disorders (Medline, EMBASE, PsycINFO, Psyndex, EconLit, IBSS). All studies were included which allowed a comparison of in- and outpatient health care costs (assessed either monetarily or in terms of health care utilization) of CAD patients with comorbid mental disorders (mood, anxiety, alcohol, eating, somatoform and personality disorders) and those without. Random effects meta-analyses were conducted and results reported using forest plots.

Results

The literature search resulted in 7,275 potentially relevant studies, of which 52 met inclusion criteria. Hospital readmission rates were increased in CAD patients with any mental disorder (pooled standardized mean difference (SMD) = 0.34 [0.17;0.51]). Results for depression, anxiety and posttraumatic stress disorder pointed in the same direction with heterogeneous SMDs on a primary study level ranging from −0.44 to 1.26. Length of hospital stay was not increased in anxiety and any mental disorder, while studies on depression reported heterogeneous SMDs ranging from −0.08 to 0.82. Most studies reported increased overall and outpatient costs for patients with comorbid mental disorders. Results for invasive procedures were non-significant respectively inconclusive.

Conclusions

Comorbid mental disorders in CAD patients are associated with an increased healthcare utilization in terms of higher hospital readmission rates and increased overall and outpatient health care costs. From a health care point of view, it is requisite to improve the diagnosis and treatment of comorbid mental disorders in patients with CAD to minimize incremental costs.

Mental health-related stigma in health care and mental health-care settings

This Review considers the evidence for mental-health-related stigma in health-care and mental-health-care settings. Do mental-health-care and other health-care professionals stigmatise people using their services? If so, what are the effects on quality of mental and physical health care? How can stigma and discrimination in the context of health care be reduced? We show that the contact mental-health-care professionals have with people with mental illness is associated with positive attitudes about civil rights, but does not reduce stigma as does social contact such as with friends or family members with mental illness. Some evidence suggests educational interventions are effective in decreasing stigma especially for general health-care professionals with little or no formal mental health training. Intervention studies are needed to underpin policy; for instance, to decrease disparity in mortality associated with poor access to physical health care for people with mental illness compared with people without mental illness.