Challenges of Population-based Measurement of Suicide Prevention Activities Across Multiple Health Systems

Suicide is a preventable public health problem. Zero Suicide (ZS) is a suicide prevention framework currently being evaluated by Mental Health Research Network investigators embedded in six Health Care Systems Research Network (HCSRN) member health systems implementing ZS. This paper describes ongoing collaboration to develop population-based process improvement metrics for use in, and comparison across, these and other health systems. Robust process improvement metrics are sorely needed by the hundreds of health systems across the country preparing to implement their own best practices in suicide care. Here we articulate three examples of challenges in using health system data to assess suicide prevention activities, each in ascending order of complexity: 1) Mapping and reconciling different versions of suicide risk assessment instruments across health systems; 2) Deciding what should count as adequate suicide prevention follow-up care and how to count it in different health systems with different care processes; and 3) Trying to determine whether a safety planning discussion took place between a clinician and a patient, and if so, what actually happened. To develop broadly applicable metrics, we have advocated for standardization of care processes and their documentation, encouraged standardized screening tools and urged they be recorded as discrete electronic health record (EHR) variables, and engaged with our clinical partners and health system data architects to identify all relevant care processes and the ways they are recorded in the EHR so we are not systematically missing important data. Serving as embedded research partners in our local ZS implementation teams has facilitated this work

Directions for Future Patient-Centered and Comparative Effectiveness Research for People With Serious Mental Illness in a Learning Mental Health Care System

This supplement, while ambitious in scope, presents its major concepts with elegance and clarity. In this critical appraisal of mental health services treatment and outcomes, the authors have extended the utility of research findings by systematically gathering data on the experiences and preferences of numerous stakeholders. Key among the report’s conclusions is the need for patient-centered, patient-developed measures that can be used at all levels of a learning system to assess service provision approaches, compare treatment interventions, and improve outcomes

The acute-to-chronic workload ratio:An inaccurate scaling index for an unnecessary normalisation process?

BACKGROUND: Problematic use of alcohol and other drugs (AOD) is highly prevalent among people living with the human immunodeficiency virus (PLWH), and untreated AOD use disorders have particularly detrimental effects on human immunodeficiency virus (HIV) outcomes. The Healthcare Effectiveness Data and Information Set (HEDIS) measures of treatment initiation and engagement are important benchmarks for access to AOD use disorder treatment. To inform improved patient care, we compared HEDIS measures of AOD use disorder treatment initiation and engagement and health care utilization among PLWH and patients without an HIV diagnosis. METHODS: Patients with a new AOD use disorder diagnosis documented between October 1, 2014, and August 15, 2015, were identified using electronic health records (EHR) and insurance claims data from 7 health care systems in the United States. Demographic characteristics, clinical diagnoses, and health care utilization data were also obtained. AOD use disorder treatment initiation and engagement rates were calculated using HEDIS measure criteria. Factors associated with treatment initiation and engagement were examined using multivariable logistic regression models. RESULTS: There were 469 PLWH (93% male) and 86,096 patients without an HIV diagnosis (60% male) in the study cohort. AOD use disorder treatment initiation was similar in PLWH and patients without an HIV diagnosis (10% vs. 11%, respectively). Among those who initiated treatment, few engaged in treatment in both groups (9% PLWH vs. 12% patients without an HIV diagnosis). In multivariable analysis, HIV status was not significantly associated with either AOD use disorder treatment initiation or engagement. CONCLUSIONS: AOD use disorder treatment initiation and engagement rates were low in both PLWH and patients without an HIV diagnosis. Future studies need to focus on developing strategies to efficiently integrate AOD use disorder treatment with medical care for HIV

Receipt of medications for opioid use disorder among youth engaged in primary care: data from 6 health systems

PURPOSE: Little is known about prevalence and treatment of OUD among youth engaged in primary care (PC). Medications are the recommended treatment of opioid use disorder (OUD) for adolescents and young adults (youth). This study describes the prevalence of OUD, the prevalence of medication treatment for OUD, and patient characteristics associated with OUD treatment among youth engaged in PC. METHODS: This cross-sectional study includes youth aged 16-25 years engaged in PC. Eligible patients had ≥ 1 PC visit during fiscal years (FY) 2014-2016 in one of 6 health systems across 6 states. Data from electronic health records and insurance claims were used to identify OUD diagnoses, office-based OUD medication treatment, and patient demographic and clinical characteristics in the FY of the first PC visit during the study period. Descriptive analyses were conducted in all youth, and stratified by age (16-17, 18-21, 22-25 years). RESULTS: Among 303,262 eligible youth, 2131 (0.7%) had a documented OUD diagnosis. The prevalence of OUD increased by ascending age groups. About half of youth with OUD had documented depression or anxiety and one third had co-occurring substance use disorders. Receipt of medication for OUD was lowest among youth 16-17 years old (14%) and highest among those aged 22-25 (39%). CONCLUSIONS: In this study of youth engaged in 6 health systems across 6 states, there was low receipt of medication treatment, and high prevalence of other substance use disorders and mental health disorders. These findings indicate an urgent need to increase medication treatment for OUD and to integrate treatment for other substance use and mental health disorders

PRimary Care Opioid Use Disorders treatment (PROUD) trial protocol: a pragmatic, cluster-randomized implementation trial in primary care for opioid use disorder treatment

BACKGROUND: Most people with opioid use disorder (OUD) never receive treatment. Medication treatment of OUD in primary care is recommended as an approach to increase access to care. The PRimary Care Opioid Use Disorders treatment (PROUD) trial tests whether implementation of a collaborative care model (Massachusetts Model) using a nurse care manager (NCM) to support medication treatment of OUD in primary care increases OUD treatment and improves outcomes. Specifically, it tests whether implementation of collaborative care, compared to usual primary care, increases the number of days of medication for OUD (implementation objective) and reduces acute health care utilization (effectiveness objective). The protocol for the PROUD trial is presented here. METHODS: PROUD is a hybrid type III cluster-randomized implementation trial in six health care systems. The intervention consists of three implementation strategies: salary for a full-time NCM, training and technical assistance for the NCM, and requiring that three primary care providers have DEA waivers to prescribe buprenorphine. Within each health system, two primary care clinics are randomized: one to the intervention and one to Usual Primary Care. The sample includes all patients age 16-90 who visited the randomized primary care clinics from 3 years before to 2 years after randomization (anticipated to be \u3e 170,000). Quantitative data are derived from existing health system administrative data, electronic medical records, and/or health insurance claims ( electronic health records, [EHRs]). Anonymous staff surveys, stakeholder debriefs, and observations from site visits, trainings and technical assistance provide qualitative data to assess barriers and facilitators to implementation. The outcome for the implementation objective (primary outcome) is a clinic-level measure of the number of patient days of medication treatment of OUD over the 2 years post-randomization. The patient-level outcome for the effectiveness objective (secondary outcome) is days of acute care utilization [e.g. urgent care, emergency department (ED) and/or hospitalizations] over 2 years post-randomization among patients with documented OUD prior to randomization. DISCUSSION: The PROUD trial provides information for clinical leaders and policy makers regarding potential benefits for patients and health systems of a collaborative care model for management of OUD in primary care, tested in real-world diverse primary care settings

Acupuncture and chiropractic care for chronic pain in an integrated health plan: a mixed methods study

<p>Abstract</p> <p>Background</p> <p>Substantial recent research examines the efficacy of many types of complementary and alternative (CAM) therapies. However, outcomes associated with the "real-world" use of CAM has been largely overlooked, despite calls for CAM therapies to be studied in the manner in which they are practiced. Americans seek CAM treatments far more often for chronic musculoskeletal pain (CMP) than for any other condition. Among CAM treatments for CMP, acupuncture and chiropractic (A/C) care are among those with the highest acceptance by physician groups and the best evidence to support their use. Further, recent alarming increases in delivery of opioid treatment and surgical interventions for chronic pain--despite their high costs, potential adverse effects, and modest efficacy--suggests the need to evaluate real world outcomes associated with promising non-pharmacological/non-surgical CAM treatments for CMP, which are often well accepted by patients and increasingly used in the community.</p> <p>Methods/Design</p> <p>This multi-phase, mixed methods study will: (1) conduct a retrospective study using information from electronic medical records (EMRs) of a large HMO to identify unique clusters of patients with CMP (e.g., those with differing demographics, histories of pain condition, use of allopathic and CAM health services, and comorbidity profiles) that may be associated with different propensities for A/C utilization and/or differential outcomes associated with such care; (2) use qualitative interviews to explore allopathic providers' recommendations for A/C and patients' decisions to pursue and retain CAM care; and (3) prospectively evaluate health services/costs and broader clinical and functional outcomes associated with the receipt of A/C relative to carefully matched comparison participants receiving traditional CMP services. Sensitivity analyses will compare methods relying solely on EMR-derived data versus analyses supplementing EMR data with conventionally collected patient and clinician data.</p> <p>Discussion</p> <p>Successful completion of these aggregate aims will provide an evaluation of outcomes associated with the real-world use of A/C services. The trio of retrospective, qualitative, and prospective study will also provide a clearer understanding of the decision-making processes behind the use of A/C for CMP and a transportable methodology that can be applied to other health care settings, CAM treatments, and clinical populations.</p> <p>Trial registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01345409">NCT01345409</a></p

Removing Barriers to Preventive Care for People With Serious Mental Illnesses: Preliminary Results From the PRIME Study

Background/Aims: People with serious mental illnesses (SMI) experience premature morbidity and mortality, largely due to preventable conditions, and may not receive guideline-concordant preventive care. Understanding modifiable factors that produce health disparities among this population will inform efforts to improve care delivery and reduce excess mortality. Methods: Interview and survey data was obtained from primary care providers (PCPs) practicing in a not-for-profit integrated health plan, Federally Qualified Health Centers and safety-net clinics, and patients with SMI. Formative interviews with both groups explored approaches, experiences, barriers and perceived effectiveness of preventive services for people with SMI. Web-based surveys with PCPs (n=249; response rate=51%) and interviews with patients diagnosed with schizophrenia-spectrum disorders, affective psychosis or mood disorders, followed formative interviews. Patient data collection is ongoing (projected n=150). Results: PCPs felt patients with SMI lacked future orientation and interest in prevention and perceived that these patients have too many needs and are seen too infrequently to affect their health. For providers, lack of time was the most common barrier to providing preventive care (89%). Providers felt office visits were too short, particularly when patients were experiencing psychiatric symptoms; 59% said psychiatric stability greatly/moderately affected ability to provide preventive services. Patients agreed visits were short but saw symptoms as a barrier only when they interfered with making/attending appointments or made providers uncomfortable. Provider-patient relationships were a barrier if providers were dismissive/rude. Patients mentioned appointment logistics (e.g. scheduling, transportation), costs, avoidance and forgetfulness as barriers. A lack of interest in prevention was not supported among patients. Both groups mentioned lack of time, lack of coordination with mental health providers, lack of insurance coverage and lack of understanding insurance as barriers. Discussion: To increase preventive service use among patients with SMI, patients need assistance overcoming logistical barriers that prevent them from getting into the office. Psychiatric symptoms can make it difficult to get in, but once patients are in front of the PCP they are amenable to prevention, particularly when recommendations come from a provider who engages them. Providers need more time, resources that support collaboration with mental health providers, and some may need additional training to increase their comfort with these patients and their confidence that their recommendations can be effective

Improving Lifestyle Interventions for People With Serious Mental Illnesses: Qualitative Results from the STRIDE Study

Background/Aims: Overweight and obesity are disproportionately prevalent among individuals with serious mental illnesses, in part due to psychiatric medications, poor dietary habits and sedentary lifestyles. Behavioral lifestyle-change interventions are effective yet require more than training participants on energy balance. Interventions must address factors relevant to the context within which people attempt to lose weight and improve health, such as lack of the following: nutrition education, access to and affordability of healthy foods, safe places to exercise and skills. Methods: As part of a randomized controlled trial (N=200) that was successful in producing significant weight loss at 12 months, we conducted 101 semistructured interviews with 84 participants to understand barriers and facilitators of weight loss and lifestyle changes associated with the intervention, or with efforts at losing weight and remaining physically active more generally. Interviews were coded by a team (with 79% agreement among coders) and were analyzed using Atals.ti. Results: Interviewees averaged 48 years old; 36% were men, 21% were nonwhite, and 24% were from the control group. Participants had diagnoses of schizophrenia or schizoaffective disorder (41%), bipolar disorder (20%), affective psychosis (37%) or posttraumatic stress disorder (2%). Thematic analyses revealed a number of key facilitators and barriers. Facilitators included: 1) current health concerns that precipitated the decision to engage in a lifestyle intervention; 2) group camaraderie facilitating participation and weight loss during the intervention; and 3) social support for exercise. Barriers included: 1) loss of structured support and subsequent difficulties continuing with lifestyle improvements postintervention; 2) bad weather as a deterrent to exercise; 3) the interaction of mental health symptoms (e.g. depression, anxiety) with disinhibited eating; and 4) all-or-nothing thinking that led to defeatist attitudes about weight loss. Discussion: Successful weight loss can be achieved among individuals with serious mental illnesses with the right intervention. We found a strong preference for consistent, group-based support to foster a sense of accountability, which motivated behavior changes. Lifestyle change interventions for this population should also help participants develop flexible cognitive restraint and the ability to iteratively cope and adapt to changes in mood and subsequent changes in motivation to eat healthfully and exercise regularly