Development of an algorithm to identify inpatient opioid-related overdoses and oversedation using electronic data.

PURPOSE: To facilitate surveillance and evaluate interventions addressing opioid-related overdoses, algorithms are needed for use in large health care databases to identify and differentiate community-occurring opioid-related overdoses from inpatient-occurring opioid-related overdose/oversedation. METHODS: Data were from Kaiser Permanente Northwest (KPNW), a large integrated health plan. We iteratively developed and evaluated an algorithm for electronically identifying inpatient overdose/oversedation in KPNW hospitals from 1 January 2008 to 31 December 2014. Chart audits assessed accuracy; data sources included administrative and clinical records. RESULTS: The best-performing algorithm used these rules: (1) Include events with opioids administered in an inpatient setting (including emergency department/urgent care) followed by naloxone administration within 275 hours of continuous inpatient stay; (2) exclude events with electroconvulsive therapy procedure codes; and (3) exclude events in which an opioid was administered prior to hospital discharge and followed by readmission with subsequent naloxone administration. Using this algorithm, we identified 870 suspect inpatient overdose/oversedation events and chart audited a random sample of 235. Of the random sample, 185 (78.7%) were deemed overdoses/oversedation, 37 (15.5%) were not, and 13 (5.5%) were possible cases. The number of hours between time of opioid and naloxone administration did not affect algorithm accuracy. When "possible" overdoses/oversedations were included with confirmed events, overall positive predictive value (PPV) was very good (PPV = 84.0%). Additionally, PPV was reasonable when evaluated specifically for hospital stays with emergency/urgent care admissions (PPV = 77.0%) and excellent for elective surgery admissions (PPV = 97.0%). CONCLUSIONS: Algorithm performance was reasonable for identifying inpatient overdose/oversedation with best performance among elective surgery patients.

Identifying and classifying opioid-related overdoses: A validation study.

PURPOSE: The study aims to develop and validate algorithms to identify and classify opioid overdoses using claims and other coded data, and clinical text extracted from electronic health records using natural language processing (NLP). METHODS: Primary data were derived from Kaiser Permanente Northwest (2008-2014), an integrated health care system (~n > 475 000 unique individuals per year). Data included International Classification of Diseases, Ninth Revision (ICD-9) codes for nonfatal diagnoses, International Classification of Diseases, Tenth Revision (ICD-10) codes for fatal events, clinical notes, and prescription medication records. We assessed sensitivity, specificity, positive predictive value, and negative predictive value for algorithms relative to medical chart review and conducted assessments of algorithm portability in Kaiser Permanente Washington, Tennessee State Medicaid, and Optum. RESULTS: Code-based algorithm performance was excellent for opioid-related overdoses (sensitivity = 97.2%, specificity = 84.6%) and classification of heroin-involved overdoses (sensitivity = 91.8%, specificity = 99.0%). Performance was acceptable for code-based suicide/suicide attempt classifications (sensitivity = 70.7%, specificity = 90.5%); sensitivity improved with NLP (sensitivity = 78.7%, specificity = 91.0%). Performance was acceptable for the code-based substance abuse-involved classification (sensitivity = 75.3%, specificity = 79.5%); sensitivity improved with the NLP-enhanced algorithm (sensitivity = 80.5%, specificity = 76.3%). The opioid-related overdose algorithm performed well across portability assessment sites, with sensitivity greater than 96% and specificity greater than 84%. Cross-site sensitivity for heroin-involved overdose was greater than 87%, specificity greater than or equal to 99%. CONCLUSIONS: Code-based algorithms developed to detect opioid-related overdoses and classify them according to heroin involvement perform well. Algorithms for classifying suicides/attempts and abuse-related opioid overdoses perform adequately for use for research, particularly given the complexity of classifying such overdoses. The NLP-enhanced algorithms for suicides/suicide attempts and abuse-related overdoses perform significantly better than code-based algorithms and are appropriate for use in settings that have data and capacity to use NLP.

Assessing the accuracy of opioid overdose and poisoning codes in diagnostic information from electronic health records, claims data, and death records.

PURPOSE: The purpose of this study is to assess positive predictive value (PPV), relative to medical chart review, of International Classification of Diseases (ICD)-9/10 diagnostic codes for identifying opioid overdoses and poisonings. METHODS: Data were obtained from Kaiser Permanente Northwest and Northern California. Diagnostic data from electronic health records, submitted claims, and state death records from Oregon, Washington, and California were linked. Individual opioid-related poisoning codes (e.g., 965.xx and X42), and adverse effects of opioids codes (e.g., E935.xx) combined with diagnoses possibly indicative of overdoses (e.g., respiratory depression), were evaluated by comparison with chart audits. RESULTS: Opioid adverse effects codes had low PPV to detect overdoses (13.4%) as assessed in 127 charts and were not pursued. Instead, opioid poisoning codes were assessed in 2100 individuals who had those codes present in electronic health records in the period between the years 2008 and 2012. Of these, 10/2100 had no available information and 241/2100 were excluded potentially as anesthesia-related. Among the 1849 remaining individuals with opioid poisoning codes, 1495 events were accurately identified as opioid overdoses; 69 were miscodes or misidentified, and 285 were opioid adverse effects, not overdoses. Thus, PPV was 81%. Opioid adverse effects or overdoses were accurately identified in 1780 of 1849 events (96.3%). CONCLUSIONS: Opioid poisoning codes have a predictive value of 81% to identify opioid overdoses, suggesting ICD opioid poisoning codes can be used to monitor overdose rates and evaluate interventions to reduce overdose. Further research to assess sensitivity, specificity, and negative predictive value are ongoing. Copyright © 2017 John Wiley & Sons, Ltd.

A qualitative analysis of family involvement in prescribed opioid medication monitoring among individuals who have experienced opioid overdoses.

BACKGROUND: Little is known about the role, extent, or effects of family member involvement in monitoring and managing opioid analgesics. Knowing when or how family members monitor prescribed opioid medication taking, whether it is acceptable to patients, or how family relationships may be affected by monitoring, are not well documented. METHODS: The study was conducted at Kaiser Permanente Northwest, an integrated health plan in Oregon and Washington. Semistructured in-depth interviews (N = 87) assessed circumstances surrounding overdose events among individuals who either experienced an opioid-related overdose or were family members of patients who died as a result of such an overdose. A subset of participants (n = 20) described family members' roles in monitoring opioid medications before or after overdoses. Interviews were transcribed verbatim and coded using Atlas.ti. We used a modified grounded theory approach to categorize emergent data and to identify common themes. RESULTS: When family members played roles in monitoring and managing opioid medications, clinicians were often unaware of their involvement. Patients and family members reported better outcomes when the patient, caregiver, and clinician developed a shared treatment plan. Negative outcomes included relationship stress, particularly when patients and caregivers had differing perspectives about what constituted effective pain management versus misuse and abuse. CONCLUSIONS: When families are concerned about opioid medications, coordination between clinicians, patients, and family carers appears to clarify roles and foster better outcomes. Increased stress and worse outcomes were reported when clinicians were not actively involved and when they did not attend to carers' concerns.

Dual recovery among people with serious mental illnesses and substance problems: a qualitative analysis.

OBJECTIVE: Individuals with serious mental illnesses are more likely to have substance-related problems than those without mental health problems. They also face more difficult recovery trajectories as they cope with dual disorders. Nevertheless, little is known about individuals' perspectives regarding their dual recovery experiences. METHODS: This qualitative analysis was conducted as part of an exploratory mixed-methods study of mental health recovery. Members of Kaiser Permanente Northwest (a group-model, not-for-profit, integrated health plan) who had serious mental illness diagnoses were interviewed four times over two years about factors affecting their mental health recovery. Interviews were recorded, transcribed, and coded with inductively derived codes. Themes were identified by reviewing text coded "alcohol or other drugs." RESULTS: Participants (N = 177) had diagnosed schizophrenia/schizoaffective disorder (n = 75, 42%), bipolar I/II disorder (n = 84, 48%), or affective psychosis (n = 18, 10%). At baseline, 63% (n = 112) spontaneously described addressing substance use as part of their mental health recovery. When asked at follow-up, 97% (n = 171) provided codeable answers about substances and mental health. We identified differing pathways to recovery, including through formal treatment, self-help groups or peer support, "natural" recovery (without the help of others), and continued but controlled use of alcohol. We found three overarching themes in participants' experiences of recovering from serious mental illnesses and substance-related problems: Learning about the effects of alcohol and drugs provided motivation and a foundation for sobriety; achieving sobriety helped people to initiate their mental health recovery processes; and achieving and maintaining sobriety built self-efficacy, self-confidence, improved functioning and a sense of personal growth. Non-judgmental support from clinicians adopting chronic disease approaches also facilitated recovery. CONCLUSIONS: Irrespective of how people achieved sobriety, quitting or severely limiting use of substances was important to initiating and continuing mental health recovery processes. Substance abuse treatment approaches that are flexible, reduce barriers to engagement, support learning about effects of substances on mental health and quality of life, and adopt a chronic disease model of addiction may increase engagement and success. Peer-based support like Alcoholics or Narcotics Anonymous can be helpful for people with serious mental illnesses, particularly when programs accept use of mental health medications.

A 12-week weight reduction intervention for overweight individuals taking antipsychotic medications.

People taking antipsychotic medications are at increased risk for obesity, diabetes, and early mortality. Few weight loss interventions have targeted this population. Thirty-six individuals were randomized to an evidence-based 12-week weight loss intervention (PREMIER with DASH diet, n = 18) or to usual care (n = 18) in this feasibility trial. Average attendance was 8.6 of 12 sessions. Intent-to-treat analyses of covariance, adjusted for baseline weight, showed significant changes in weight: Mean weight in intervention participants declined from 213.3 to 206.6 pounds, while control participants' weight was unchanged. It is possible to recruit, assess, intervene with, and retain participants taking antipsychotic medications in a dietary and exercise lifestyle change trial. Participants reported high levels of satisfaction with the intervention.

Reduced emergency department use among insured individuals receiving extended-release buprenorphine in a health system setting.

Introduction: Extended-release buprenorphine (XR-Bup) is associated with reduced opioid use and opioid negative urine drug screens. Little is known about its use in outpatient addiction care provided within health systems. Methods: Individuals prescribed XR-Bup were identified from electronic health records; chart abstraction was conducted. Primary outcome was all-cause emergency department (ED) use. Secondary outcomes included ED use or inpatient stays for mental health or substance use, ED use for any other cause, discontinuation reasons, and drug substitution. Statistical comparisons used nonparametric tests from related samples (McNemar's test and Wilcoxon matched pair tests) to test outcomes six months prior and 6 months following XR-Bup initiation. Results: 152 individuals had an XR-Bup order, 126 received >1 injection. Among those consistently insured 6 months prior to and following XR-Bup initiation (n=99), the mean number of injections following initiation was 3.95; one-third received 6 doses in the 6 months. The proportion of individuals using ED services for all causes declined (41% prior vs. 28% following XR-Bup initiation, p<.05); similar results were found for secondary ED use outcomes. The proportion of individuals requiring inpatient treatment for mental health or substance use also declined (46% vs. 16%, p<.01). Common reasons for discontinuing XR-Bup included losing insurance (21%) or cost (11%). The most common non-prescribed substances used during treatment were opioids (n=31) and THC (n=20). Conclusions: In this non-randomized retrospective observational study, use of XR-Bup was associated with reduced ED use 6 months following initiation. XR-Bup may help health systems reduce use of costly ED services.

Drinking Patterns, Gender and Health III: Avoiding vs. Seeking Healthcare.

BACKGROUND: Inability to predict most health services use and costs using demographics and health status suggests that other factors affect use, including attitudes and practices that influence health and willingness to seek care. Alcohol consumption has generated interest because heavy, chronic consumption causes adverse health consequences, acute consumption increases injury, and moderate drinking is linked to better health while hazardous drinking and alcohol-related problems are stigmatized and may affect willingness to seek care. METHODS: A stratified random sample of health-plan members completed a mail survey, yielding 7884 respondents (2995 male/4889 female). We linked survey data to 24 months of health-plan records to examine relationships between alcohol use, gender, health-related attitudes, practices, health, and service use. In-depth interviews with a stratified 150-respondent subsample explored individuals' reasons for seeking or avoiding care. RESULTS: Quantitative results suggest health-related practices and attitudes predict subsequent service use. Consistent predictors of care were having quit drinking, current at-risk consumption, cigarette smoking, higher BMI, disliking visiting doctors, and strong religious/spiritual beliefs. Qualitative analyses suggest embarrassment and shame are strong motivators for avoiding care. CONCLUSIONS: Although models included numerous health, functional status, attitudinal and behavioral predictors, variance explained was similar to previous reports, suggesting more complex relationships than expected. Qualitative analyses suggest several potential predictive factors not typically measured in service-use studies: embarrassment and shame, fear, faith that the body will heal, expectations about likelihood of becoming seriously ill, disliking the care process, the need to understand health problems, and the effects of self-assessments of health-related functional limitations.

Measuring problem prescription opioid use among patients receiving long-term opioid analgesic treatment: development and evaluation of an algorithm for use in EHR and claims data.

Objective: Opioid surveillance in response to the opioid epidemic will benefit from scalable, automated algorithms for identifying patients with clinically documented signs of problem prescription opioid use. Existing algorithms lack accuracy. We sought to develop a high-sensitivity, high-specificity classification algorithm based on widely available structured health data to identify patients receiving chronic extended-release/long-acting (ER/LA) therapy with evidence of problem use to support subsequent epidemiologic investigations. Methods: Outpatient medical records of a probability sample of 2,000 Kaiser Permanente Washington patients receiving ≥60 days' supply of ER/LA opioids in a 90-day period from 1 January 2006 to 30 June 2015 were manually reviewed to determine the presence of clinically documented signs of problem use and used as a reference standard for algorithm development. Using 1,400 patients as training data, we constructed candidate predictors from demographic, enrollment, encounter, diagnosis, procedure, and medication data extracted from medical claims records or the equivalent from electronic health record (EHR) systems, and we used adaptive least absolute shrinkage and selection operator (LASSO) regression to develop a model. We evaluated this model in a comparable 600-patient validation set. We compared this model to ICD-9 diagnostic codes for opioid abuse, dependence, and poisoning. This study was registered with ClinicalTrials.gov as study NCT02667262 on 28 January 2016. Results: We operationalized 1,126 potential predictors characterizing patient demographics, procedures, diagnoses, timing, dose, and location of medication dispensing. The final model incorporating 53 predictors had a sensitivity of 0.582 at positive predictive value (PPV) of 0.572. ICD-9 codes for opioid abuse, dependence, and poisoning had a sensitivity of 0.390 at PPV of 0.599 in the same cohort. Conclusions: Scalable methods using widely available structured EHR/claims data to accurately identify problem opioid use among patients receiving long-term ER/LA therapy were unsuccessful. This approach may be useful for identifying patients needing clinical evaluation.

Understanding how clinician-patient relationships and relational continuity of care affect recovery from serious mental illness: STARS study results.

OBJECTIVE: Recommendations for improving care include increased patient-clinician collaboration, patient empowerment, and greater relational continuity of care. All rely upon good clinician-patient relationships, yet little is known about how relational continuity and clinician-patient relationships interact, or their effects on recovery from mental illness. METHODS: Individuals (92 women, 85 men) with schizophrenia, schizoaffective disorder, affective psychosis, or bipolar disorder participated in this observational study. Participants completed in-depth interviews detailing personal and mental health histories. Questionnaires included quality of life and recovery assessments and were linked to records of services used. Qualitative analyses yielded a hypothesized model of the effects of relational continuity and clinician-patient relationships on recovery and quality of life, tested using covariance structure modeling. RESULTS: Qualitative data showed that positive, trusting relationships with clinicians, developed over time, aid recovery. When "fit" with clinicians was good, long-term relational continuity of care allowed development of close, collaborative relationships, fostered good illness and medication management, and supported patient-directed decisions. Most valued were competent, caring, trustworthy, and trusting clinicians who treated clinical encounters "like friendships," increasing willingness to seek help and continue care when treatments were not effective and supporting "normal" rather than "mentally ill" identities. Statistical models showed positive relationships between recovery-oriented patient-driven care and satisfaction with clinicians, medication satisfaction, and recovery. Relational continuity indirectly affected quality of life via satisfaction with clinicians; medication satisfaction was associated with fewer symptoms; fewer symptoms were associated with recovery and better quality of life. CONCLUSIONS: Strong clinician-patient relationships, relational continuity, and a caring, collaborative approach facilitate recovery from mental illness and improved quality of life.

"Not getting tanked": definitions of moderate drinking and their health implications.

BACKGROUND: People encounter large amounts of sometimes-inconsistent information about risks and benefits of alcohol consumption, and about what constitutes "low-risk" or "moderate" drinking. METHODS: We used 150 in-depth interviews linked to questionnaire data to learn how people define moderate drinking and to describe the relationships between definitions, attitudes, and beliefs about moderate drinking and individuals' drinking patterns. RESULTS: People adhere to definitions of moderate alcohol consumption that could put them, or others, at risk for short- or long-term negative consequences of drinking. Definitions that confused increased tolerance of alcohol with moderate drinking, and those that defined moderate drinking by the absence of short-term negative consequences or ability to maintain control over drinking, ignore long-term risks of heavy consumption. Individuals with risky attitudes were also more likely to report at-risk drinking practices. CONCLUSIONS: Americans have complex beliefs about benefits and risks of alcohol consumption, and public health officials have not succeeded in conveying strong or clear messages about what constitutes low-risk drinking or about dose-response effects. Different (but more consistent) approaches to public education may be needed to increase knowledge about drinking-related risks. The prevalence of diverse norm-based definitions suggests that alternative normative information could help people reassess their own consumption.

Getting by, getting back, and getting on: Matching mental health services to consumers' recovery goals.

OBJECTIVE: The goal of this study was to better understand mental health recovery from the point of view of mental health consumers to identify opportunities for practice improvements that closely align services with consumer goals and consumer-preferred outcomes. METHOD: As part of an exploratory study of recovery, semistructured interviews were conducted with 177 integrated health plan members diagnosed with schizophrenia, schizoaffective disorder, bipolar disorder, or affective psychosis. Transcripts of in-depth interviews were coded using Atlas.ti, and definitions of recovery were further subcoded. A qualitative analysis using a modified grounded theory approach and constant comparative method identified common themes and less common but potentially important recovery-related experiences and perspectives. RESULTS: Three primary and 2 cross-cutting themes emerged. "Getting by" meant coping and meeting basic needs. "Getting back" meant learning to live with mental illness. "Getting on" meant living a life where mental illness was no longer prominent. Regaining control and recouping losses were cross-cutting themes. CONCLUSIONS/IMPLICATIONS FOR PRACTICE: Mental health recovery is complex and dynamic; individuals' recovery goals can be expected to change over time. Person-centered care must accommodate changing consumer priorities, services must be flexible and responsive, and outcomes need to match consumers' objectives. Clinicians can assist in (a) identifying recovery goals, (b) monitoring progress toward and recognizing movement away from goals, (c) tailoring support to different phases/stages, and (d) supporting transitions between phases/stages. (PsycINFO Database Record

Improvement in Body Image, Perceived Health, and Health-Related Self-Efficacy Among People With Serious Mental Illness: The STRIDE Study.

OBJECTIVE: The authors examined secondary outcomes of STRIDE, a randomized controlled trial that tested a weight-loss and lifestyle intervention for individuals taking antipsychotic medications. METHODS: Hierarchical linear regression was used to explore the effects of the intervention and weight change at follow-up (six, 12, and 24 months) on body image, perceived health, and health-related self-efficacy. RESULTS: Participants were 200 adults who were overweight and taking antipsychotic agents. Weight change × study arm interaction was associated with significant improvement in body image from baseline to six months. From baseline to 12 months, body image scores of intervention participants improved by 1.7 points more compared with scores of control participants; greater weight loss was associated with more improvement. Between baseline and 24 months, greater weight loss was associated with improvements in body image, perceived health, and health-related self-efficacy. CONCLUSIONS: Participation in STRIDE improved body image, and losing weight improved perceived health and health-related self-efficacy.

Protocol: changes in rates of opioid overdose and poisoning events in an integrated health system following the introduction of a formulation of OxyContin® with abuse-deterrent properties.

BACKGROUND: Addiction, overdoses and deaths resulting from prescription opioids have increased dramatically over the last decade. In response, several manufacturers have developed formulations of opioids with abuse-deterrent properties. For many of these products, the Food and Drug Administration (FDA) recognized the formulation with labeling claims and mandated post-marketing studies to assess the abuse-deterrent effects. In response, we assess differences in rates of opioid-related overdoses and poisonings prior to and following the introduction of a formulation of OxyContin® with abuse-deterrent properties. METHODS/DESIGN: To assess effects of this formulation, electronic medical record (EMR) data from Kaiser Permanente Northwest (KPNW) and Kaiser Permanente Northern California (KPNC) are linked to state death data and compared to chart audits. Overdose and poisoning events will be categorized by intentionality and number of agents involved, including illicit drugs and alcohol. Using 6-month intervals over a 10-year period, trends will be compared in rates of opioid-related overdoses and poisoning events associated with OxyContin® to rates of events associated with other oxycodone and opioid formulations. Qualitative interviews with patients and relatives of deceased patients will be conducted to capture circumstances surrounding events. DISCUSSION: This study assesses and tracks changes in opioid-related overdoses and poisoning events prior to and following the introduction of OxyContin® with abuse-deterrent properties. Public health significance is high because these medications are designed to reduce abuse-related behaviors that lead to important adverse outcomes, including overdoses and deaths.

Understanding opioid overdose characteristics involving prescription and illicit opioids: A mixed methods analysis.

BACKGROUND: Opioid abuse and misuse are significant public health issues. The CDC estimated 72% of pharmaceutical-related overdose deaths in the US in 2012 involved opioids. While studies of opioid overdoses have identified sociodemographic characteristics, agents used, administration routes, and medication sources associated with overdoses, we know less about the context and life circumstances of the people who experience these events. METHODS: We analyzed interviews (n=87) with survivors of opioid overdoses or family members of decedents. Individuals experiencing overdoses were members of a large integrated health system. Using ICD codes for opioid overdoses and poisonings, we identified participants from five purposefully derived pools of health-plan members who had: 1) prescriptions for OxyContin(®) or single-ingredient sustained-release oxycodone, 2) oxycodone single-ingredient immediate release, 3) other long-acting opioids, 4) other short-acting opioids, or 5) no active opioid prescriptions. RESULTS: Individuals who experienced opioid overdoses abused and misused multiple medications/drugs; experienced dose-related miscommunications or medication-taking errors; had mental health and/or substance use conditions; reported chronic pain; or had unstable resources or family/social support. Many had combinations of these risks. Most events involved polysubstance use, often including benzodiazepines. Accidental overdoses were commonly the result of abuse or misuse, some in response to inadequately treated chronic pain or, less commonly, medication-related mistakes. Suicide attempts were frequently triggered by consecutive negative life events. CONCLUSIONS: To identify people at greater risk of opioid overdose, efforts should focus on screening for prescribed and illicit polysubstance use, impaired cognition, and changes in life circumstances, psychosocial risks/supports, and pain control.

Costs of implementing a behavioral weight-loss and lifestyle-change program for individuals with serious mental illnesses in community settings.

Little research has examined costs of adopting a successful lifestyle intervention for people with serious mental illnesses in community clinics. The study aims to calculate the real-world costs of implementing a group-based weight-loss and lifestyle intervention in community settings. We used empirically derived costs to estimate implementation costs and conducted sensitivity analyses to estimate costs: (1) when implementing the intervention in high/low resource-intensive environments and (2) assuming variability in participant enrollment. To implement the STRIDE program for 15 individuals with serious mental illnesses, we estimated costs for the 12-month (30-session) intervention, with materials available in the public domain, at $16,427 or $1095 per participant. The majority of costs, $12,767, were associated with direct labor costs. Replication costs are largely associated with labor. Community health centers offer an untapped resource for implementing behavioral-lifestyle interventions, particularly under the Affordable Care Act, though additional payment reforms or incentives may be needed.

The STRIDE weight loss and lifestyle intervention for individuals taking antipsychotic medications: a randomized trial.

OBJECTIVES: The STRIDE study assessed whether a lifestyle intervention, tailored for individuals with serious mental illnesses, reduced weight and diabetes risk. The authors hypothesized that the STRIDE intervention would be more effective than usual care in reducing weight and improving glucose metabolism. METHOD: The study design was a multisite, parallel two-arm randomized controlled trial in community settings and an integrated health plan. Participants who met inclusion criteria were ≥18 years old, were taking antipsychotic agents for ≥30 days, and had a body mass index ≥27. Exclusions were significant cognitive impairment, pregnancy/breastfeeding, recent psychiatric hospitalization, bariatric surgery, cancer, heart attack, or stroke. The intervention emphasized moderate caloric reduction, the DASH (Dietary Approaches to Stop Hypertension) diet, and physical activity. Blinded staff collected data at baseline, 6 months, and 12 months. RESULTS: Participants (men, N=56; women, N=144; mean age=47.2 years [SD=10.6]) were randomly assigned to usual care (N=96) or a 6-month weekly group intervention plus six monthly maintenance sessions (N=104). A total of 181 participants (90.5%) completed 6-month assessments, and 170 (85%) completed 12-month assessments, without differential attrition. Participants attended 14.5 of 24 sessions over 6 months. Intent-to-treat analyses revealed that intervention participants lost 4.4 kg more than control participants from baseline to 6 months (95% CI=-6.96 kg to -1.78 kg) and 2.6 kg more than control participants from baseline to 12 months (95% CI=-5.14 kg to -0.07 kg). At 12 months, fasting glucose levels in the control group had increased from 106.0 mg/dL to 109.5 mg/dL and decreased in the intervention group from 106.3 mg/dL to 100.4 mg/dL. No serious adverse events were study-related; medical hospitalizations were reduced in the intervention group (6.7%) compared with the control group (18.8%). CONCLUSIONS: Individuals taking antipsychotic medications can lose weight and improve fasting glucose levels. Increasing reach of the intervention is an important future step.

The recovery group project: development of an intervention led jointly by peer and professional counselors.

OBJECTIVE The objective of this study was to develop and evaluate a low-cost, strengths-based group intervention led jointly by peer counselors and professional counselors to foster recovery among adults with serious mental illnesses. METHODS Cohort 1 included development of materials and a feasibility pilot, with participants recruited from community mental health centers (CMHCs). Cohorts 2 and 3 included a small randomized controlled trial with participants recruited from members of a not-for-profit, integrated health plan. Cohorts 4 and 5 involved evaluation of the most appropriate length for the intervention with a pre-post design that allowed intervention length to vary between 12 and 18 sessions; participants and peer leaders were recruited from two CMHCs (N=82). RESULTS Participants were very satisfied with the recovery-focused group intervention, preferred a greater number of weekly sessions (17 or 18 sessions), and reported improved outcomes across multiple domains. CONCLUSIONS Using peer-developed materials and a combination of peer and professional counselors as group leaders is feasible to offer and valuable to participants. Outcomes measures suggest that the intervention has potential to facilitate recovery in multiple domains.

Recovery from serious mental illness: trajectories, characteristics, and the role of mental health care.

OBJECTIVE The objective was to identify trajectories of recovery from serious mental illnesses. METHODS A total of 177 members (92 women; 85 men) of a not-for-profit integrated health plan participated in a two-year mixed-methods study of recovery (STARS, the Study of Transitions and Recovery Strategies). Diagnoses included schizophrenia, schizoaffective disorder, bipolar disorder, and affective psychosis. Data sources included self-reported standardized measures, interviewer ratings, qualitative interviews, and health plan data. Recovery was conceptualized as a latent construct, and factor analyses and factor scores were used to calculate recovery trajectories. Individuals with similar trajectories were identified through cluster analyses. RESULTS Four trajectories were identified-two stable (high and low levels of recovery) and two fluctuating (higher and lower). Few demographic or diagnostic factors differentiated clusters at baseline. Discriminant analyses for trajectories found differences in psychiatric symptoms, physical health, satisfaction with mental health clinicians, resources and strains, satisfaction with medications, and mental health service use. Those with higher scores on recovery factors had fewer psychiatric symptoms, better physical health, greater satisfaction with mental health clinicians, fewer strains and greater resources, less service use, better quality of care, and greater satisfaction with medication. Consistent predictors of trajectories included psychiatric symptoms, physical health, resources and strains, and use of psychiatric medications. CONCLUSIONS Having access to good-quality mental health care-defined as including satisfying relationships with clinicians, responsiveness to needs, satisfaction with psychiatric medications, receipt of services at needed levels, support in managing deficits in resources and strains, and care for general medical conditions-may facilitate recovery. Providing such care may improve recovery trajectories.

Delivering a lifestyle and weight loss intervention to individuals in real-world mental health settings: Lessons and opportunities.

BACKGROUND: Most weight loss interventions for obesity-related risks exclude people with serious mental health conditions. PURPOSE: To adapt a successful lifestyle/weight loss intervention for this population, deliver it in an HMO and two public mental health clinics, and concurrently measure implementation factors. METHODS: Developmental and implementation-focused formative evaluations guided adaptations and identified barriers/facilitators to successful program deployment. RESULTS: Adaptations included content specific to the population's needs, consciousness-raising among clinicians and patients, additional case-management, and greater program flexibility. Barriers included instability in both settings from different sources. Facilitators included familiarity with groups, manual integrity, and appreciation of the program. It was delivered consistently across settings with maximum exposure and fairly good fidelity to the protocol (mean rating=1.7, 2.0=complete fidelity). CONCLUSIONS: This mixed-method implementation evaluation demonstrated that lifestyle/weight loss interventions in mental health settings are complex, but feasible, and valued by participants. Main program outcomes will be reported at the trial's conclusion.