Bipolar Support Groups.com blog

In the run-up to the Presidential election in America, we’re examining the candidates’ views on mental health and mental illness. Last month, we examined what little Donald Trump, the Republican candidate, had to say on mental health. He has spoken using terms for mental illness that most people have long since abandoned in order to insult others — that’s been the gist of his policy statements about mental illness.

This month, we’ll examine the proposed mental health policy agenda of the Democrat’s nominee for President, Hillary Clinton.

At the end of August, she released a detailed policy statement describing her approach to mental health. The fact that she even has a policy statement is a far cry from Donald Trump’s campaign, which has only a few sentences about mental illness on his website. And this introductory statement pretty clearly states her position: “Hillary Clinton strongly believes we have to bring mental and behavioral health care on par with physical health care—and end the shame and stigma associated with treatment.”

Her main agenda for mental health while President will be to:

• Promote early diagnosis and intervention.
• Launch a national initiative for suicide prevention.
• Integrate our nation’s mental and physical health care systems so that health care delivery focuses on the “whole person” and expand community-based treatment.
• Prioritize treatment over jail for low-level, nonviolent offenders and help train law enforcement officers in responding to conflicts involving persons with mental illness.
• Enforce mental health parity to the full extent of the law.
• Improve access to housing and job opportunities.
• Invest in brain behavioral science research.

That’s a pretty full agenda. The actual briefing document goes into much detail about each of these initiatives.

Here are some of the things I especially like about the proposals she is promoting.

• Fostering integration of behavioral healthcare into the regular healthcare system.
  Long the forgotten, ugly, not-talked-about stepchild of healthcare, bringing mental health care into primary care physicians’ offices will help promote its equality with physical health issues.
• Support the creation of high-quality, comprehensive community behavioral health centers in every state.Expanding on the vision of John F. Kennedy decades ago, these centers could help fill the dangerous gap left by the closing of so many inpatient psychiatric hospitals in the past decade.
• Launch a nationwide strategy to address the shortage of mental health providers.Ask any mental health professional in practice today, and they’ll acknowledge that it’s hard to get their patients in to see a psychiatrist when needed. Ask any person on a private pay health insurance plan, and they’ll tell you that if you can find a psychiatrist’s office who even return your phone calls, the first appointment available to see them will often be months out. There is a real shortage of certain mental health professionals, and this needs to be addressed.
• Prioritize treatment over punishment for low-level, non-violent offenders with mental illnesses.We need to move from imprisoning people for aberrant behavior and get them into treatment instead. Our prisons should not be the new psychiatric hospitals of the 21st century. It appears that Clinton understands this problem and will work to help encourage more people into treatment, instead of our jails.
• Strengthen federal monitoring of health insurer compliance with network adequacy requirements.Mental health parity laws mean nothing if the health insurance provider doesn’t actually offer enough providers within their network that offer mental health services. They can do this because the pay for mental health services is so low, it’s chasing professionals out of accepting insurance. When insurance companies start reimbursing professionals at rates consistent with their services, their networks will once again expand.
• Commit to brain and behavioral science research based on open data.Open data is the future, but some scientists, universities, and publishers object to making raw research data readily available to anyone who wants it. By being a proponent of open data in the behavioral sciences, Clinton appears to be on the right side of the debate.

I have more of mixed feelings about early diagnosis and screening, realizing that all too often children are misdiagnosed by well-meaning pediatricians and parents. We should continue to promote existing programs and work harder to ensure any healthcare provider who makes such diagnoses does so with proven, solid psychiatric training and experience. One or two courses in medical school hardly qualifies most physicians to make such diagnoses.

All of these policy ideas are generally good ideas with solid backing in the research for them. However, most of them would require significant new funding. And one thing we’ve learned from past administrations is that good intentions will generally amount to little without bipartisan support and a clear, sensible funding strategy. Missing from this briefing is such a strategy, suggesting that most of these initiatives would remain nothing more than proposed good ideas.

That’s too bad. Because the mental health care system in America is clearly broken, a patchwork of care that nobody is really overseeing very effectively or reliably. Until something big is done, it’s likely to remain that way no matter who’s elected President in 2016.

Talented and thoughtful, she was a successful non-profit executive. She was well-known throughout the region for her philanthropic endeavors. She had founded three businesses in separate niche industries.

To the outsider, my client was a skilled entrepreneur, a connector between the business and arts communities. She was a self-made woman. When she spoke, others listened — and followed.

Now in a transitional phase, her confidence had plummeted. Self-doubt wracked her. She discredited her previous successes, attributing them to fortuitous circumstances. I listened as she belittled herself in a contemptuous tone.

“Matt, I don’t know why anybody would hire me. I am too old; I can’t learn new technology. Employers must know that,” she complained, a hint of bitterness creasing her voice.

Here was a worldly executive riddled with disabling doubt. The self-limiting language, not her skillset, was the real obstacle.

“Let’s challenge those defeating statements. Look at your career. You have been a catalyst for change. How many people have founded a successful boutique in Los Angeles and then, switching industries, established a thriving non-profit in a different part of the country? Look at your personal relationships. How many people value your opinion?” I gently admonished.

She paused, startled to hear such lavish praise.

“Well, I guess I have never thought about it that way, “ she conceded.

Her self-confidence shattered, my client dismissed with a disdainful shrug her multitude of accomplishments.

I pressed forward. “Look at the self-defeating language. You define yourself before you even start. How many times do you say ‘I can’t’ or ‘I won’t?’ Those words are self-fulfilling prophecies. Let’s change the negative language.”

Bracing for her backlash, instead the line was silent. In the silence, she understood: self-limiting language sabotages. Her destructive language, not her abilities, undercut her career aspirations. Her limiting beliefs fueled her paralyzing self-doubt.

If we inject truth serum, we acknowledge how self-doubt derails us from achieving our goals. When faced with relationship or job uncertainty, how many of us endlessly question whether we are capable? Am I smart enough? Am I skilled enough? Am I likable enough? The questions pummel us into cowering self-doubt.

Challenge the thoughts. If a bully constantly mocked you, castigating you as a failure or fraud, you would respond. Thesecognitive distortions cheat you out of a rich, fulfilling life. So why are you permitting your bullying brain to disparage you? Respond with a measured, accurate response. I am capable; I can achieve; I am deserving. Your default response: I can.

Achieving self-acceptance requires diligence and determination. Whenever a negative thought pollutes my mind, I challenge it. My unwanted, intrusive thoughts, like my client’s, center on my own self-competence. Like that fearsome seventh grade bully, the mind feeds off fear and loathing. When you challenge the bully, the towering giant crumbles. The taunting mind, like the seventh grade bully, is more imposter than imposing.

As you put the self in self-care, remember that inferiority is only a complex. The only limitations are the ones we create.

There are a variety of methods you can use to help yourself with bipolar disorder (also known as manic depression). Individuals should take an active role in their own treatment and self-care because feeling better and getting better is an active, daily process. While medications and psychotherapy are usually recommended to treat bipolar disorder, there are additional steps a person can take to improve their condition.

1. Learn More

Learning more about bipolar disorder is the easiest thing a person can do to help themselves. There is a wealth of information online, but there are also some very good self-help books that provide an in-depth understanding of bipolar disorder and techniques that can be used to improve your daily life.

2. Get Support and Understanding

During a manic phase you may be quite unaware that your actions are distressing or damaging to other people. Later, you may feel guilty and ashamed. It can be especially difficult if those around you seem afraid or hostile. It helps if you provide people with information about bipolar disorder.

After going through a manic depressive episode you may find it difficult to trust others, and may want to cut yourself off. These feelings are to be expected after experiencing such difficulties, but it may be far more helpful to talk through your emotions and experiences with friends, family, careers or a counselor.

There are now many support groups — both in the real world and online — where people who have gone through similar problems can come together to support each other. For instance, check out Psych Central’s Bipolar Support Group or theNeuroTalk Bipolar Support Group.

3. Manage Your Own Condition

Self-management involves finding out about bipolar disorder and developing the skills to recognize and control mood swings early, before they become full blown.

It can be very difficult at first to tell whether a bipolar “high” is really the beginning of a manic episode or whether you are just feeling more confident, creative and socially at ease. It can be a strain watching out for symptoms all the time, particularly when you are first learning about the effect bipolar disorder might have on your life.

There are various guides to self-managing bipolar disorder. They may feature checklists and exercises to help you recognize and control mood swings, like mood diaries, tips on self-medication, and practical tips for dealing with depression andmania. Self management is by no means instant, and can take some time to use effectively. However, you may find you need to rely less on professionals, and have more control over mood swings. This can lead to greater self-confidence and lessens relapse.

The easiest thing you can do today to begin better managing your own condition is by keeping a daily journal of your moods in the morning, afternoon, and evening. Write it down on a piece of paper, day after day. There are even tools like ourdepression quiz and our mania quiz that can you track these moods online.

4. Get Routine in Your Day-to-day Life

Routine is important, as well as good diet, enough sleep, exercise and enough vitamins, minerals and fatty acids. Gentle stress free activities also help, like yoga or swimming. You could also try complementary therapies, such as reflexology and massage.

People sometimes underestimate the importance of a daily routine. They feel, “What’s the use?” The use is that it keeps your body active, which in turn helps you feel better emotionally. The mind and body are interconnected — ignoring one will have an effect on the other.

5. Keep Work Life at Bay

While work is important to many of us, if for no other reason than it helps to pay our rent and food bills, it also needs to be placed into proper perspective with regards to your health and well being. When we are emotionally out of balance, it can affect our work performance (as well as many other areas in our lives, such as relationships with our significant other, family and friends).

It’s important to take things slowly and avoid stressful situations. If you already have a job, you might want to find out if you can return on a part-time basis to start with. If you are a student, most colleges and universities will offer good support and advice. Give yourself time and space to get back into the full world of job stresses and such.

Recovery

Bipolar disorder need not be chronic and it can be possible to recover. There is a growing recovery movement among bipolar disorder survivors. Developing countries have a far higher non-relapse rate than industrialized countries. Great recovery tools are hope, love, support and work.

Objective: Marijuana has been approved for a number of psychiatric conditions in many states in the US including posttraumatic stress disorder (PTSD), agitation in Alzheimer’s disease, and Tourette’s disorder. In this systematic review, we examine the strength of evidence for the efficacy of marijuana and other cannabinoids for these psychiatric indications.

Data Sources: The literature (MEDLINE) was searched for studies published between January 1980 and March 2015 using search terms related to marijuana and other cannabinoids and the specific diagnosis.

Study Selection: The best quality of evidence, namely placebo-controlled, randomized clinical trials (RCTs) and meta-analyses, was sought per PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. In the absence of RCTs, the next best available evidence (eg, observational studies, case reports) was reviewed. Of 170 publications that were screened, 40 were related to the topic, 29 were included in the qualitative synthesis, and 13 studies examined the efficacy of cannabinoids in humans.

Data Extraction: The evidence was rated using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) method.

Results: No RCTs have thus far examined the efficacy of marijuana for Tourette’s disorder, PTSD, or Alzheimer’s disease. Lower-quality studies examined the efficacy of marijuana, Δ9-tetrahydrocannabinol, and nabilone; the strength of evidence for the use of cannabinoids for these conditions is very low at the present time. The consequences of chronic cannabinoid exposure includes tolerance, dependence, and withdrawal. Early and persistent marijuana use has been associated with the emergence of psychosis. Marijuana impairs attention, memory, IQ, and driving ability.

Conclusions: Given its rapidly changing legal status, there is an urgent need to conduct double-blind, randomized, placebo- or active-controlled studies on the efficacy and safety of marijuana or its constituent cannabinoids for psychiatric conditions. Physicians and policy-makers should take into account the limited existing evidence and balance that with side effects before approving medical marijuana for psychiatric indications.

ABSTRACT

Objective: To compare health care resource utilization and costs in veterans with schizophrenia treated with paliperidone palmitate (PP) versus oral atypical antipsychotics (OAAs).

Methods: A retrospective longitudinal study was conducted using electronic health record data from the Veterans Health Administration. Veterans with schizophrenia (identified using ICD-9-CM 295.x) initiating PP or OAAs between January 2010 and October 2014, with ≥ 12 months of benefits enrollment prior to treatment initiation and ≥ 6 months of enrollment after treatment initiation, and with ≥ 1 Global Assessment of Functioning measurement at baseline were included. Inverse probability of treatment weighted regression models were used to estimate incidence rate ratios (IRRs) and cost differences (CDs) for the impact of PP versus OAAs on health care resource utilization and costs.

Results: Among 10,290 eligible veterans, 2,285 and 8,005 were initiated on PP and OAAs, respectively. After adjustment, PP was associated with less frequent all-cause inpatient hospitalizations (IRR = 0.89, P < .001) and more frequent mental health intensive case management visits (IRR= 1.81, P < .001) compared to OAAs. PP treatment was associated with higher likelihood of increased income (odds ratio [OR] = 1.20, P = .027) and lower likelihood of homelessness (OR = 0.82, P < .001). While mean annual pharmacy and outpatient costs were higher among PP users (CD =$3,417 pharmacy, $2,527 outpatient, P< .001), mean annual inpatient costs were lower (CD = –$14,456, P <.001), resulting in average annual total health care (medical and pharmacy) cost savings associated with PP (CD =–$8,511, P = .012) relative to OAAs.

Conclusions: PP treatment was associated with significantly lower total health care costs attributable to reduced inpatient admissions compared to OAAs. Higher mental health intensive case management participation among PP users may have contributed to the differences observed.

Schizophrenia is a chronic mental illness that limits patients’ capacity for self-care, employment, and maintaining personal relationships.1 A systematic review estimated the incidence of schizophrenia to be about 15.2 per 100,000 persons in the United States, with an annual cost of approximately $30,000 per patient.2

As the largest integrated health care system in the United States, the Veterans Health Administration (VHA) cares for more than 6.9 million veterans annually, providing integrated and comprehensive services including primary, specialty, and inpatient care, rehabilitation services, long-term and home care, and other services to US military veterans.3 The number of veterans dealing with mental health issues has increased over time, and veterans with schizophrenia occupy more hospital beds than veterans with any other illness.4–6

When treating schizophrenia with oral antipsychotics, nonadherence often undermines the effectiveness of pharmacotherapy.7 Long-acting injectable antipsychotic therapies (LATs) are administered less frequently, thus providing extended medication coverage, which may improve adherence.8 Among injectable antipsychotics, paliperidone palmitate (PP) is an atypical LAT dosed monthly and approved by the US Food and Drug Administration (FDA) in 2009 for acute and maintenance treatment of schizophrenia. PP has demonstrated effectiveness for treating schizophrenia, though the drug cost is greater than that of oral atypical antipsychotics (OAAs).9–11 While some meta-analyses of randomized controlled trials (RCTs) comparing LATs to oral antipsychotics found no significant difference in clinical outcomes of patients receiving either treatment, the controlled environment of RCTs may not accurately reflect routine practice and real-world outcomes among schizophrenia patients.12,13 For instance, RCTs may enroll patients who are more likely to be adherent to their prescribed treatment regimens or have less severe disease.13 Requiring regular follow-up in RCTs may also increase adherence to prescribed regimens.

The objective of this study was to compare treatment patterns, health care resource utilization (HRU), and economic outcomes in US veterans treated with PP versus OAAs.

METHODS

Study Design and Patient Selection

A retrospective longitudinal cohort study was conducted using electronic medical record data from the VHA. The VHA Corporate Data Warehouse is an integrated and unified medical record system that contains data from all outpatient visits, hospital stays, treatments, prescriptions, laboratory results, billing, benefits information, demographics, socioeconomic information, and estimated costs of hospital stays and health care encounters.

The study design scheme is presented in SupplementaryeFigure 1. Since PP was approved by the FDA on July 21, 2009, the study observation period began on January 1, 2010, to allow for uptake of the drug. The study population included veterans 18 years or older who had at least 2 schizophrenia diagnoses (ICD-9-CM code 295.x) during the observation period (at least 1 of which occurred during the baseline period) and at least 2 dispensings of PP or OAA within 90 days between January 1, 2010, and October 31, 2014, the first of which defined the index date. Patients were also required to be enrolled with VA benefits at least 12 months before (ie, baseline) and 6 months after the index date, have at least 1 Global Assessment of Functioning (GAF)14,15 measurement during baseline, and show evidence of at least 1 health care–related activity at least 6 months prior to the end of observation or a record of death. Patients receiving OAA were not allowed to have evidence of PP during the follow-up period but were still included in the study if they used other LATs during this period. Health care resource utilization and cost outcomes were assessed during the 12-month post-index period and annualized to 12 months for patients with less than 12 months of follow-up data.

Treatment, Outcomes, and Covariates

PP and OAAs were identified using NDC codes from inpatient and outpatient pharmacy and procedure records. The 9 OAAs included in the study were aripiprazole, asenapine maleate, iloperidone, lurasidone, olanzapine, quetiapine fumarate, risperidone, ziprasidone, and oral paliperidone.

Demographic, economic, and clinical characteristics were assessed during the 12-month pre-index baseline period including age, gender, race, region, marital status, homelessness, income, time since the availability of PP, Quan Charlson Comorbidity Index (CCI) score,16–18 previous treatment with antipsychotics, concomitant medications, HRU, health care costs, physical comorbidities, mental health comorbidities, and GAF score. Income values were based on means-testing data, which is conducted periodically to determine whether veterans are eligible for care at no or reduced out-of-pocket costs due to lower incomes. Information about veterans’ source of income was not available.

The outcomes of interest were treatment patterns, HRU, and health care costs. Treatment patterns assessed included days of persistence, proportion of patients with a gap in treatment from the date of dispensing plus days’ supply greater than 30 or 60 days, proportion of days covered (PDC), antipsychotic use (other than the index drug), and concomitant medication use. Persistence was defined conservatively using the minimum number of days a patient was observed to receive treatment, allowing a maximum gap of 30 days following the date of dispensing plus days’ supply. Proportion of days covered is defined as the proportion of days during the measurement period “covered” by prescription dispensings for the same medication. Antipsychotic polypharmacy was defined as having at least 60 consecutive days with overlapping coverage of at least 2 unique antipsychotic agents. Psychiatric polypharmacy was defined as having at least 60 consecutive days with overlapping coverage of at least 1 antipsychotic agent and at least 1 anxiolytic, antidepressant, or mood stabilizer. All-cause HRU and health care cost outcomes were annualized, assessed, and reported overall (ie, medical and pharmacy) and by type of services. Cost values were inflated to US $2014 using the Medical Services component of the Consumer Product Index.19 VHA Decision Support System data were used to evaluate costs.

Statistical Analysis

Inverse probability of treatment weighting. Inverse probability of treatment weighting was used to adjust for baseline differences between PP and OAA patients. Inverse probability of treatment weights (IPTWs) are defined as the inverse of the conditional probability of receiving a patient’s own treatment.20 Applying the IPTW creates a pseudopopulation in which the distribution of baseline confounders used to create the weights is balanced between cohorts.20,21

IPTWs were calculated for each patient in the PP and OAA cohorts. The propensity score (PS) was calculated using a pooled logistic regression model adjusting for the following baseline variables: index year, age, gender, race, region, marital status, homelessness, income, number of mental health diagnoses, CCI, antipsychotic use, concomitant medication use, schizophrenia diagnoses, mental and physical comorbidities with greater than 10% prevalence in baseline, GAF score, and the number and cost of inpatient and outpatient visits. IPTWs were then constructed as 1/PS for the PP cohort and 1/(1 – PS) for the OAA cohort. Normalized IPTWs were calculated by dividing each IPTW by the overall mean IPTW, and were examined for extreme values.22

Descriptive analyses. Unadjusted and IPTW-weighted baseline patient characteristics, treatment patterns during the observation period, and HRU following a mental health inpatient visit were summarized and compared between the PP and OAA cohorts using χ2 tests for categorical variables and Wilcoxon nonparametric tests for continuous variables. Imbalances in unadjusted and adjusted baseline covariates between the PP and OAA cohorts were assessed using standardized differences (std diff), with a threshold of > 10% indicating an imbalance.23

Regression models. IPTW-weighted linear and Poisson regression models were used to estimate the mean cost difference (CD) and incidence rate ratios (IRRs) for the impact of PP versus OAA on health care costs and HRU. The weighted models included a binary indicator for the index treatment variable; linear regression models for cost outcomes also included an adjustment covariate for total baseline costs to account for residual confounding. A nonparametric bootstrap procedure was used to calculate confidence intervals and P values based on 499 resamples of the dataset for health care cost outcomes to account for nonnormality. No adjustment was made for multiplicity. All analyses were conducted in SAS version 9.4 (SAS Institute, Cary, NC).

Sensitivity analysis. A sensitivity analysis was conducted to assess whether mental health intensive case management (MHICM, a VA program similar to assertive community treatment24consisting of a multidisciplinary team of professionals using a client-centered, community-based approach to assist veterans with mental illness to live independently in the community) participation25 modified the association between treatment and outcomes. All statistical analyses were repeated in subgroups stratified by MHICM participation at baseline.

In addition, weighted logistic regression models were used to assess the impact of PP versus OAA on an increase in income (a binary variable based on whether a veteran’s income increased from baseline) and homelessness during the 12-month study period. Odds ratios, 95% confidence intervals, and P values were reported.

RESULTS

A total of 2,285 PP patients and 8,005 OAA patients were included in this study (Figure 1). Applying IPTW (weight range of 0.51–42.3, mean = 1.0, standard deviation = 1.67) to these treatment cohorts created a pseudopopulation of 5,052 PP patients and 5,238 OAA patients.

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Baseline Demographic and Clinical Characteristics

Unadjusted and IPTW-adjusted baseline characteristics of the study population are reported in Table 1. Before adjustment, on average, PP patients were younger than OAA patients (mean age of 50.2 vs 53.7 years, std diff = 27.2%). The proportions of male OAA and PP patients appeared similar, though PP patients were more likely to be single and homeless compared to OAA patients (single: 46.8% vs 39.3%, std diff = 15.2%; homeless: 34.0% vs 29.0%, std diff = 10.6%). After applying IPTW, standardized differences greater than 10% were observed for only a few covariates, suggesting that the distribution of baseline confounders between the PP and OAA cohorts were balanced. Notably, PP patients were more likely to have received a greater number of unique antipsychotic agents (2.4 vs 1.3, std diff = 57.0%) than patients treated with OAAs. PP patients were also more likely to have used atypical oral and short-term injectable antipsychotics (87.6% vs 58.0%, std diff = 70.6%) and atypical LATs (33.5% vs 6.4%, std diff = 71.9%) than OAA patients.

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Treatment Patterns During Follow-Up

Treatment patterns evaluated during the annualized 12-month study period (after PP or OAA initiation) are presented in Table 2. Compared to OAA patients, patients treated with PP were persistent for a longer mean duration of time (209.6 days vs 165.0 days, P < .001) and a lower proportion of PP patients had a treatment gap of at least 30 days or at least 60 days (71.2% vs 83.0%, P < .001 and 60.6% vs 74.0%, P < .001). A higher proportion of PP patients had PDC ≥ 0.8 for their index drug (35.8% vs 23.3%, P < .001) compared to their OAA counterparts. In addition, a lower proportion of PP patients had psychiatric polypharmacy during the observation period compared to OAA patients (40.3% vs 47.8%, P < .001).

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Association Between Treatment and HRU

As shown in Table 3, treatment with PP was associated with a lower rate of inpatient stays (IRR= 0.89, P < .001) and days in an inpatient setting (IRR = 0.82, P < .001) compared to treatment with OAAs. PP was also associated with a 3% increase in the incidence rate of outpatient visits per patient (IRR = 1.03, P < .001). This was driven primarily by the fact that PP patients had more frequent MHICM visits (IRR = 1.81, P < .001).

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Among patients with a mental health inpatient stay, PP patients were less likely to be rehospitalized within 30 days of discharge compared to OAA patients (26.6% vs 29.1%, P = .010). HRU following a mental health inpatient visit is presented in Supplementary eTable 1.

Association Between Treatment and Health Care Costs

Adjusted, annualized mean health care costs evaluated during the 12-month study period and adjusted mean cost differences between treatment cohorts are presented in Table 4. Compared to treatment with OAAs, treatment with PP was associated with a mean total all-cause health care (medical and pharmacy) cost difference of –$8,511.36 (P = .012). Though PP treatment was associated with greater total outpatient visit costs ($2,527.44, P < .001) and higher pharmacy costs ($3,416.96, P < .001), this was offset by lower total inpatient stay costs (–$14,455.76, P < .001) resulting in total overall cost savings associated with PP relative to OAAs.

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In addition, patients treated with PP were 20% more likely to experience an increase in income (OR = 1.20, P = .027) and 18% less likely to be homeless (OR = 0.82, P < .001) during the 12-month study period compared to patients treated with OAAs (Supplementary eFigure 2). With respect to GAF, patients treated with PP were more likely to experience an improvement in GAF score of at least 10 points (OR = 1.15, P = .055).

Results From Sensitivity Analysis Stratified by MHICM Participation at Baseline

With respect to HRU, the benefits of PP persisted in patients who participated in MHICM at baseline and those who did not, though the magnitudes of association were greater among patients with MHICM visits compared to patients without MHICM visits at baseline. Patients without MHICM visits at baseline treated with PP had fewer inpatient stays (IRR = 0.94, P < .001), mental health stays (IRR = 0.94, P < .001), and long-term care stays (IRR = 0.85, P = .040) per patient compared to OAA patients. However, PP patients had a greater number of MHICM visits (IRR = 1.52, P < .001). Similar results were seen in patients with MHICM visits at baseline.

As shown in Table 4, the difference in mean total (medical and pharmacy) health care costs between PP and OAA patients was not statistically significant (–$5,221.68, P = .265) among non-MHICM patients. While significant total health care cost savings associated with PP are not observed among patients who are not enrolled in MHICM during the baseline period, total health care costs were similar between the PP and OAA cohorts, with significant total inpatient stay cost savings (–$9,718.38, P = .016) fully offsetting higher total pharmacy costs ($3,772.64, P < .001) in PP patients relative to OAA patients. Among patients with MHICM visits at baseline, however, PP patients had significantly lower total all-cause health care costs (–$22,584.16, P < .001) compared to OAA patients. Thus, lower total health care costs associated with PP are apparent in patients with MHICM visits at baseline, but the evidence for total health care cost savings is not as definitive for patients who are not enrolled in MHICM during the baseline period.

DISCUSSION

This study found that PP was associated with less frequent all-cause inpatient hospitalizations, more frequent MHICM visits, and improved socioeconomic status during the annualized 12-month follow-up period compared to OAAs. While mean annual pharmacy and outpatient costs were higher among PP users, mean annual inpatient costs were lower, resulting in significant mean annual total cost savings associated with PP relative to OAAs. This is the largest study to examine health care costs and HRU associated with PP use among veterans to date. Given the difficulty of designing generalizable randomized trials of LATs in which improved adherence and persistence is the hypothesized mechanism of incremental benefit relative to oral antipsychotics, observational data are useful to demonstrate the benefit associated with PP and for informing clinical practice.

While PS matching is often used in studies to adjust for differences in baseline confounders, it may result in smaller sample size when appropriate matches between treated and control patients are not found, thus decreasing power. Furthermore, incomplete matching may make it difficult to describe the population of patients for whom matched results apply. The IPTW method applied in this study allows for the preservation of the total sample size while adjusting for baseline confounding, making the results more generalizable to the total population. While some residual confounding may remain after weighting by IPTW, this would result in more conservative estimates of association as the PP cohort has a higher proportion of patients with polypharmacy and a greater number of unique AP agents received at baseline (after weighting), suggesting that severity of disease is slightly greater for the PP cohort than the OAA cohort.

Results from this study are consistent with previous research.27–30 For instance, Xiao et al27found that PP patients had lower medical costs attributable to reduced inpatient and long-term care admissions compared to OAA patients. These lower medical costs offset the higher pharmacy expense for PP-treated patients, resulting in comparable total overall costs and suggesting enhanced clinical management of schizophrenia. Similarly, Baser et al28 found that PP treatment was associated with lower mean inpatient costs, lower hospitalization rates, and a shorter length of stay in inpatient days versus OAA treatment.

In our study, patients treated with PP had higher persistence and lower proportions of patients with 30 or 60 day gaps in treatment than patients treated with OAAs. This may explain the differences observed since improved medication coverage is especially important for schizophrenia patients who are more likely to experience relapse or rehospitalization when they discontinue therapy. LATs like PP provide longer and more persistent medication coverage, and allow clinicians to confirm adherence as the medication is administered via injection by a health care provider. For this reason, it was expected that PP treatment might be associated with greater frequency of outpatient visits and higher outpatient costs compared to treatment with OAAs. The increased frequency of outpatient visits, and especially MHICM visits, also indicates that PP patients may be more engaged in their health and experience greater continuity of care. This is a positive outcome among schizophrenia patients, who often fail to follow-up with health care providers and skip health care visits.

While the incremental increase is small, the greater proportion of patients experiencing an increase in income and the lower proportion of patients experiencing homelessness during the 12 months following initiation of treatment with PP is promising. Treating schizophrenia patients with PP may give them better opportunities for future employment and positively affect patients’ socioeconomic status, which is important as patients with schizophrenia often find themselves in more difficult economic circumstances than the general population.

The general conclusions of the study held in the sensitivity analysis examining subgroups of patients stratified by MHICM participation status at baseline. Statistically significant savings in total health care costs associated with PP were observed only in patients with MHICM visits at baseline, though statistically significant reductions in total inpatient stay costs associated with PP were also observed for patients who were not enrolled in MHICM at baseline. Thus, MHICM participation may be modifying the effect of or interacting with PP (compared to OAA) and contributing to the lower health care costs observed, especially since previous research has demonstrated that MHICM is a cost effective treatment among veterans.31 In addition, post-baseline MHICM participation may have also impacted the results of this study as a greater number of MHICM visits were observed among PP patients in the post-baseline period for both baseline MHICM stratified groups (ie, patients participating in MHICM visits at baseline and patients not participating in MHICM visits at baseline). While a time-varying analysis of post-index MHICM participation was not part of the current study, this is an important topic that merits exploration in future research.

Limitations

This study has several limitations. For instance, all patients were required to have a GAF score recorded during baseline, which reduced our sample size. Furthermore, the majority of GAF scores captured were assessed during inpatient hospital stays, making the GAF score inclusion requirement essentially a proxy for inpatient hospitalization. Though this was unexpected when inclusion criteria were developed, imposing this criterion may have helped ensure similar acuity of illness and disease severity in OAA and PP patients. Patients with more severe disease are more likely to be hospitalized with schizophrenia and would be in greater need of interventions to improve symptoms. In addition, including this criterion was important to ensure all patients had a baseline functioning score that could be adjusted for by including the variable in the model used to construct IPTW. Thus, while the GAF score requirement may be a limitation, it also may have strengthened the analysis.

Also, almost all patients in the PP cohort used atypical oral and short-term injectable antipsychotics during the follow-up period. This may be due to the fact that OAAs are used to treat a number of mental health comorbidities that co-occur with schizophrenia, such as depression and bipolar disorder as well as insomnia, or it may be that these agents are adjunctive support for management of schizophrenia symptoms. In addition, this study does not consider whether patients switch treatment during the observation period. Rather, the analysis took an “intention-to-treat” approach that likely resulted in conservative estimates of association as many patients in the OAA cohort had LAT dispensings during the study period. Sixty percent of PP users and 74% of AP users had a treatment gap of at least 60 days, indicating that there may be partial or full overlap of medications when patients are being switched to a new antipsychotic, as evidenced by the 17% of PP and OAA patients with antipsychotic polypharmacy.

Findings from this study may be limited in their generalizability to the total US population as the study sample was specific to veterans obtaining health care through the VHA system, who may have very different characteristics and comorbidities compared to the general population. Specifically, less than 10% of our study sample consisted of women. Also, as with all retrospective observational studies, the results may be subject to selection bias and residual confounding by unmeasured confounders, though a large number of covariates were included when building the IPTW. While outcomes such as relapse and adverse events associated with PP or OAA treatment may be of interest and warranted in a future study, they were not assessed in the current study.

CONCLUSIONS

With its once monthly injection, PP was associated with improvements in adherence, reduced hospitalization rates, and improved socioeconomic standing among veterans with schizophrenia. Although more frequent MHICM visits among PP patients during the observation period may have contributed to differences observed relative to OAA patients, the greater pharmacy cost observed among PP patients was more than offset by reductions in inpatient costs resulting in average annual total health care (medical and pharmacy) cost savings of more than $8,000 per patient. Thus, PP appears to be a promising treatment option for schizophrenia with the potential to reduce hospitalizations as well as health care costs compared to OAA therapy.

Submitted: February 12, 2016; accepted June 10, 2016.

Objective: To examine the cross-sectional and longitudinal associations between sleep disturbance and posttraumatic stress disorder (PTSD) and depressive symptoms in a large cohort of adolescents exposed to the 2008 Wenchuan earthquake in China.

Methods: Participants were 1,573 adolescents (mean age at initial survey = 15.0 years, SD = 1.3 years; 46% male) in the Wenchuan Earthquake Adolescent Health Cohort (WEAHC) in Dujiangyan, China, 20 km away from the east epicenter. The Pittsburgh Sleep Quality Index, Post-Traumatic Stress Disorder Self-Rating Scale, and Depression Self-Rating Scale for Children were used to assess participants’ sleep, PTSD symptoms, and depressive symptoms, respectively, at 12 months (T12m) and 24 months (T24m) after the Wenchuan earthquake that occurred on May 12, 2008.

Results: At T12m and T24m, 38.3% and 37.5% of participants reported sleep disturbance, 22.5% and 14.0% reported PTSD symptoms, and 41.0% and 38.3% reported depressive symptoms, respectively. The prevalence rates of PTSD and depressive symptoms at T12m and T24m significantly increased with sleep disturbance and short sleep duration. After adjusting for demographics, earthquake exposure, and PTSD/depressive symptoms at T12m, sleep disturbance at T12m was significantly associated with increased risk for PTSD (odds ratio [OR] = 1.80; 95% CI, 1.17–2.75) and depressive symptoms (OR = 1.51; 95% CI, 1.14–2.02) at T24m. Furthermore, sleep disturbance predicted the persistence of PTSD (OR = 2.35; 95% CI, 1.43–3.85) and depressive symptoms (OR = 2.41; 95% CI, 1.80–3.24).

Conclusions: Sleep disturbance, PTSD, and depressive symptoms were prevalent and persistent in adolescents at 12 and 24 months after exposure to the Wenchuan earthquake. Sleep disturbance predicts the development and persistence of PTSD and depressive symptoms. Early assessment and treatment of sleep disturbance may be an important strategy for prevention and intervention of PTSD and depression in adolescent trauma survivors.

Because of similar symptoms of depression, bipolar disorder and borderline personality disorder may be misdiagnosed or confused with one another.

In a new study, researchers reveal the distinct differences between bipolar and borderline personality disorders in order to better treat both.

An individual with bipolar disorder has cyclical changes in mood, energy and activity levels that range from deep depression, to mania or hypomania. A person with borderline personality disorder has trouble regulating emotions and thoughts, and has impulsive and reckless behavior and unstable relationships with others.

The findings reveal that patients with borderline personality disorder are more likely to have additional disorders and also more likely to have experienced childhood trauma than those with bipolar disorder. They may also experience longer and more severe episodes of depression.

The study involved interviewing 268 participants between 1995 and 2012. Of these, 62 participants were diagnosed with bipolar II depression and 206 participants were diagnosed with major depressive disorder with co-occurring borderline personality disorder (MDD-BPD).

Depressive episodes are a considered a part of bipolar disorder, but depression is a separate disorder that can co-occur with borderline personality disorder.

All the participants were between the ages of 18 and 68, and could only have one of the two disorders — not both. They also had to meet the official criteria for experiencing a major depressive episode at the time of the interviews.

The findings showed that the average age of the patients in the MDD-BPD group was 33 years old, versus 37 years old in the bipolar group. The MDD-BPD patients were also less likely to be married. For both groups, the average age of onset was below 20 years old.

Between the two groups, there were no major differences in race, education level, gender, the average number of psychiatric hospitalizations or amount of time spent away from work during the previous five years.

Furthermore, 38 percent of the MDD-BPD group was diagnosed with three or more non-personality disorders (anxiety, mood and eating disorders) compared to 26 percent of the bipolar group.

Thirty percent of the MDD-BPD group was diagnosed with post-traumatic stress disorder compared to 10 percent of the bipolar group.

Patients in the MDD-BPD group also had longer depressive episodes, were more depressed overall, had a harder time doing day-to-day activities, and had significantly more childhood trauma events — especially physical neglect — than the bipolar group. This group was also more suicidal, with twice as many MDD-BPD participants as bipolar participants reporting three or more suicide attempts.

The only factor found to be more common in the bipolar group was having an immediate family member with a history of bipolar disorder.

The lead author of this study was Mark Zimmerman, M.D., from the Department of Psychiatry at Rhode Island Hospital and the Department of Psychiatry and Human Behavior at Brown Medical School.

Meditation affects a person’s brain function long after the act of meditation is over, according to new research.

“This is the first time meditation training has been shown to affect emotional processing in the brain outside of a meditative state,” said Gaelle Desbordes, Ph.D., a research fellow at the Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital and at the Boston University Center for Computational Neuroscience and Neural Technology.

“Overall, these results are consistent with the overarching hypothesis that meditation may result in enduring, beneficial changes in brain function, especially in the area of emotional processing.”

The researchers began the study with the hypothesis that meditation can help control emotional responses.

During meditation, a part of the brain called the amygdala (known for the processing of emotional stimuli) showed decreased activity. However, when the participants were shown images of other people that were either good, bad, or neutral for a practice known as “compassion meditation,” the amygdala was exceptionally responsive.

The subjects were able to focus their attention and greatly reduce their emotional reactions. And over an eight-week period, the participants retained this ability.

Even when they were not engaged in a meditative state, their emotional responses were subdued, and they experienced more compassion for others when faced with disturbing images.

Around the same time, another group at Harvard Medical School (HMS) began to study the effect of meditation on retaining information. Their hypothesis was that people who meditate have more control over alpha rhythm — a brain wave thought to screen out everyday distractions, allowing for more important information to be processed.

“Mindfulness meditation has been reported to enhance numerous mental abilities, including rapid memory recall,” said Catherine Kerr of the Martinos Center for Biomedical Imaging and the Osher Research Center, both at HMS.

“Our discovery that mindfulness meditators more quickly adjusted the brain wave that screens out distraction could explain their superior ability to rapidly remember and incorporate new facts.”

Both studies used participants that had no previous experience with meditation.

Over an eight-week period and a 12-week period, both groups showed a marked change in their daily normal brain function, while they were meditating and while they were involved in medial activities.

Some researchers believe that meditation might be the key to help ease off dependency on pharmaceutical drugs.

“The implications extend far beyond meditation,” said Kerr.

“They give us clues about possible ways to help people better regulate a brain rhythm that is deregulated in attention-deficit hyperactivity disorder and other conditions.”

Source:  Harvard University

A new study has found that people experiencing a depressive episode process information about themselves differently than people who are not depressed.

Using functional magnetic resonance imaging (fMRI), researchers at the University of Liverpool scanned the brains of people in major depressive episodes and those who weren’t. The task subjects were given while in the fMRI machine was to choose adjectives to describe themselves or the British Queen — a figure significantly removed from their daily lives that all but one of the participants were familiar with.

“We found that participants who were experiencing depressed mood chose significantly fewer positive words and more negative and neutral words to describe themselves, in comparison to participants who were not depressed,” said Professor Peter Kinderman, head of the university’s Institute of Psychology, Health and Society.

“That’s not too surprising, but the brain scans also revealed significantly greater blood oxygen levels in the medial superior frontal cortex — the area associated with processing self-related information — when the depressed participants were making judgments about themselves.”

The research leads the way for further studies into the psychological and neural processes that accompany depressed mood, he continued.

“Understanding more about how people evaluate themselves when they are depressed and how neural processes are involved could lead to improved understanding and care,” he said.

“This study explored ways to consolidate some of the differences between medical and psychological models ofdepression,” added Dr. May Sarsam, from the Mersey Care NHS Trust.

“It showed that brain activity only differed when depressed people thought about themselves, not when they thought about the Queen or when they made other types of judgments, which fits very well with the current psychological theory.”

“Thought and neurochemistry should be considered as equally important in our understanding of mental health difficulties such as depression,” she added.

The research, in collaboration with the Mersey Care NHS Trust and the Universities of Manchester, Edinburgh and Lancaster, was published in PLOS One.

Source: University of Liverpool

A few weeks ago someone raised in an interesting question in response to one of my posts: what are the differences between healthy and unhealthy ways of dealing with boredom in ADHD?

We often talk about things being “healthy” or “unhealthy” from a mental health point of view, but these terms can be tricky to define – even more so because something that’s “healthy” for someone in one situation might be “unhealthy” for someone in another situation.

One thing I’ve noticed is that people with ADHD seem to have a tendency to cope with boredom using addictions and “addictions.” By addictions without quotes I mean actual addictions to nicotine, drugs, etc. By “addictions” I mean addictions in the sense of people saying “I’m addicted to Netflix.”

For example, some research (here’s one study, but there are others) suggests that boredom is an important factor that leads people with ADHD to start smoking, along with things like stress and restlessness.

When it comes to no-quotes addictions, we’re talking about things that are unhealthy in the literal, physical sense. So that’s a pretty obvious example of an unhealthy way of coping with boredom.

For with-quotes “addictions,” it’s a little more complicated. To generalize, if it’s something that makes you feel good and doesn’t harm you physically or lower your quality of life, it’s probably a healthy way of coping with boredom.

So for example, TV fails that test because I usually don’t feel that great after if I binge-watch a TV show.

On the other hand, the two “addictions” that do the most for me in terms of fending off boredom are music and travel. For me, both these things get my brain into gear, so I organize my life to be able to get as much of each as possible. With music, that just means listening to as much as possible – things like concerts are my biggest non-essential expense. With travel, one of the biggest advantages of being self-employed is that I can travel and work at the same time.

Of course, one of the things about ADHD-related boredom is that it tends to strike when it’s least welcome – often, when we’re trying to do some sort of tedious task we have to focus on. When people with ADHD are faced with unstimulating tasks, our brains can just disengage and go looking for something more interesting to do, refusing to come back to the job at hand.

A common ADHDer tactic here is simply to avoid boredom-provoking tasks. Depending on the situation, this can be healthy or unhealthy.

If there are unnecessary activities that make you bored and exacerbate your concentration problems, it absolutely is healthy to cut these out of our life altogether. However, the problem is when you have necessary activities that you find boring and hard to pay attention to.

Here, avoiding these things isn’t a healthy approach because it’s obviously not sustainable – the boring tasks will just pile up and become overwhelming. Instead, the trick is to find something you can do alongside these activities that’ll make your brain happier. For me, listening to music while doing boring tasks is something that’s very helpful.

More generally, I think the key to dealing with ADHD-related boredom is to figure out what’s really interesting to you (this part can take a little exploring) and then structure your life to do those things as much as possible – including while you’re doing the things that are boring!

What are some other healthy or unhealthy ways of dealing with boredom? Please share your experiences!