Effects of primary care clinician beliefs and perceived organizational facilitators on the delivery of preventive care to individuals with mental illnesses.

BACKGROUND: Although many studies have documented patient-, clinician-, and organizational barriers/facilitators of primary care among people with mental illnesses, few have examined whether these factors predict actual rates of preventive service use. We assessed whether clinician behaviors, beliefs, characteristics, and clinician-reported organizational characteristics, predicted delivery of preventive services in this population. METHODS: Primary care clinicians (n = 247) at Kaiser Permanente Northwest (KPNW) or community health centers and safety-net clinics (CHCs), in six states, completed clinician surveys in 2014. Using electronic health record data, we calculated preventive care-gap rates for patients with mental illnesses empaneled to survey respondents (n = 37,251). Using separate multi-level regression models for each setting, we tested whether survey responses predicted preventive service care-gap rates. RESULTS: After controlling for patient-level characteristics, patients of clinicians who reported a greater likelihood of providing preventive care to psychiatrically asymptomatic patients experienced lower care-gap rates (KPNW γ= - .05, p = .041; CHCs γ= - .05, p = .033). In KPNW, patients of female clinicians had fewer care gaps than patients of male clinicians (γ= - .07, p = .011). In CHCs, patients of clinicians who had practiced longer had fewer care gaps (γ= - .004, p = .010), as did patients whose clinicians believed that organizational quality goals facilitate preventive service provision (γ= - .06, p = .006). Case manager availability in CHCs was associated with higher care-gap rates (γ=.06, p = .028). CONCLUSIONS: Clinicians who report they are likely to address preventive concerns when their mentally ill patients present without apparent psychiatric symptoms had patients with fewer care gaps. In CHCs, care quality goals may facilitate preventive care whereas case managers may not.

Balint work and the creation of medical knowledge.

Michael Balint's pioneering work in primary care was not simply the application of psychodynamic theory to the complex problems and relationships encountered by clinicians. Rather, Balint's work was part of a wider conversation in Western epistemology that had already begun to break down the enlightenment rationalist agenda. Since the time of Descartes, we sought to find certain truth through decontextualizing and abstracting problems, and through separation of the observer from the thing observed, with a focus on finding universal timeless laws that could be generalized. By the mid-1950s, it was clear that this agenda was insufficient to answer important questions about what it means to be human and to live a healthy and happy life. Balint's experiment was a return to a method of knowledge creation that is case based, narrative, local, timely, particular, and especially considers specific contexts for finding solutions to problems. For current healthcare reform efforts to be effective, we must include Balint's focus on the context of the doctor, patient, and their relationship, as well as development of practical wisdom (i.e. Aristotelian phronesis) that we know in medicine as professional judgment. The case study method of the Balint group is one of the few and best formal methods to teach and practice this way of knowing.

Personal characteristics associated with the effect of childhood trauma on health.

Objective This article will describe a pilot study to explore associations between adult attachment style, resilience, Adverse Childhood Experiences, and adult health. Method A self-report survey was mailed to 180 randomly selected primary care patients and linked to a retrospective chart review. The patients met the following criteria: (1) enrolled for at least the previous year at their primary care clinic, (2) 21 years of age or greater, (3) English as their primary language, and (4) were seen by their provider on selected dates of the study. The survey was made up of three instruments: (1) the Adverse Childhood Experiences Questionnaire which consists of 10 questions about the respondent's adverse experiences during their first 18 years of life; (2) the Relationship Scales Questionnaire which measures adult attachment style; and (3) the Connor-Davidson Resilience Scale, a self-report scale that measures individual's perceptions of their resilience. For each returned questionnaire, we calculated a measure of medical complexity using the Elixhauser Comorbidity Index. Results Of the 180 randomly selected patients from four clinic sites, 84 (46.6%) returned completed questionnaires. We found that Adverse Childhood Experience scores were significantly correlated with health and attachment style and trended toward association with resilience. Conclusion This pilot study revealed expected relationships of the complex associations between Adverse Childhood Experiences, attachment style, and resiliency. Further research with more subjects is warranted in order to continue to explore these relationships.

Cardiovascular care guideline implementation in community health centers in Oregon: a mixed-methods analysis of real-world barriers and challenges.

BACKGROUND: Spreading effective, guideline-based cardioprotective care quality improvement strategies between healthcare settings could yield great benefits, particularly in under-resourced contexts. Understanding the diverse factors facilitating or impeding such guideline implementation could improve cardiovascular care quality and outcomes for vulnerable patients. METHODS: We sought to identify multi-level factors affecting uptake of cardioprotective care guidelines in community health centers (CHCs), within a successful trial of cross-setting implementation of an effective intervention. Quantitative analyses used multivariable logistic regression to examine in-person patient encounters at 10 CHCs from June 2011-May 2014. At these encounters, a point-of-care alert flagged adults with diabetes who were clinically indicated for, but not currently prescribed, cardioprotective medications. The main outcome measure was the rate of relevant prescriptions issued within two days of encounters. Qualitative analyses focused on CHC providers and staff, and, guided by the constant comparative method, were used to enhance understanding of the factors that influenced this prescribing. RESULTS: Recommended prescribing occurred at 13-16% of encounters with patients who were indicated for such prescribing. The odds of this prescribing were higher when the patient was male, had HbA1c ≥7, was previously prescribed a similar medication, gave diabetes as the chief complaint, saw a mid-level practitioner, or saw their primary care provider. The odds were lower when the patient was insured, had ≥1 clinic visits in the past year, had kidney disease, or was prescribed certain other medications. Additional factors were associated with prescribing of each medication class. Qualitative results both supported and challenged the quantitative findings, illustrating important tensions involved in guideline-based prescribing. Clinic staff stressed the importance of the provider-patient relationship in guiding prescribing decisions in the face of competing priorities and care needs, and the impact of rapidly changing guidelines. CONCLUSIONS: Diverse factors associated with guideline-concordant prescribing illuminate the complexity of delivering evidence-based care in CHCs. We present possible strategies for addressing barriers to guideline-based prescribing. CLINICAL TRIALS REGISTRATION: This trial was registered retrospectively. Currently Controlled Trials NCT02299791 . Retrospectively registered 10 November 2014.

Medication-assisted treatment for substance use disorders within a national community health center research network.

BACKGROUND: The Affordable Care Act increases access to treatment services for people who suffer from substance use disorders (SUDs), including alcohol use disorders (AUDs) and opioid use disorders (OUDs). This increased access to treatment has broad implications for delivering health services and creates a dramatic need for transformation in clinical care, service lines, and collaborative care models. Medication-assisted treatments (MAT) are effective for helping SUD patients reach better outcomes. This article uses electronic health record (EHR) data to examine the prevalence of EHR-documented SUDs, patient characteristics, and patterns of MAT prescribing and screening for patients within the Community Health Applied Research Network (CHARN), a national network of 17 community health centers that facilitates patient-centered outcomes research among underserved populations. METHODS: Hierarchical generalized linear models examined patient characteristics, SUD occurrence rates, MAT prescription, and human immunodeficiency virus (HIV) and hepatitis virus C screening for patients with AUDs or OUDs. Results: Among 572,582 CHARN adult patients, 16,947 (3.0%) had a documented AUD diagnosis and 6,080 (1.1%) an OUD diagnosis. Alcohol MAT prescriptions were documented for 547 AUD patients (3.2%) and opioid MAT for 1,764 OUD patients (29.0%). Among OUD patients, opioid MAT was significantly associated with HIV screening (odds ratio [OR] = 1.31, P < .001) in OUD patients, as was alcohol MAT among AUD patients (OR = 1.30, P = .013). CONCLUSIONS: These findings suggest that effective opioid and alcohol MAT may be substantially underprescribed among safety-net patients identified as having OUDs or AUDs.

Alcohol Screening among Opioid Agonist Patients in a Primary Care Clinic and an Opioid Treatment Program.

Problem alcohol use is associated with adverse health and economic outcomes, especially among people in opioid agonist treatment. Screening, brief intervention, and referral to treatment (SBIRT) are effective in reducing alcohol use; however, issues involved in SBIRT implementation among opioid agonist patients are unknown. To assess identification and treatment of alcohol use disorders, we reviewed clinical records of opioid agonist patients screened for an alcohol use disorder in a primary care clinic (n = 208) and in an opioid treatment program (n = 204) over a two-year period. In the primary care clinic, 193 (93%) buprenorphine patients completed an annual alcohol screening and six (3%) had elevated AUDIT scores. In the opioid treatment program, an alcohol abuse or dependence diagnosis was recorded for 54 (27%) methadone patients. Practitioner focus groups were completed in the primary care (n = 4 physicians) and the opioid treatment program (n = 11 counselors) to assess experience with and attitudes towards screening opioid agonist patients for alcohol use disorders. Focus groups suggested that organizational, structural, provider, patient, and community variables hindered or fostered alcohol screening. Alcohol screening is feasible among opioid agonist patients. Effective implementation, however, requires physician training and systematic changes in workflow.

Analgesic methadone prescribing in community health centers among patients with chronic pain.

OBJECTIVE: To examine analgesic methadone prescriptions among community health center (CHC) patients with chronic pain. DESIGN: Observational; two cross-sectional periods. SETTING: Oregon and California CHCs. PATIENTS: Chronic pain patients with ≥1 visit in 2012-2013 or 2017-2018 (N = 158,239). OUTCOMES: Changes in adjusted relative rates (aRRs) of receiving no opioids, short-acting only, long-acting only other than methadone, and methadone; characteristics associated with ≥1 methadone prescription. RESULTS: Opioid prescribing declined over time, with the largest decrease in methadone (aRR = 0.19, 95 percent confidence interval: 0.14-0.27). Among patients receiving ≥1 long-acting opioid, variables associated with methadone prescribing included being aged <65 years, having nonprivate insurance, and an opioid use disorder (OUD) diagnosis. From 2012-2013 to 2017-2018, aRR increased among patients with OUD and decreased for those aged 18-30 (vs ≥65), uninsured and Medicaid-insured (vs private), and race/ethnicity other than non-Hispanic Black (vs non-Hispanic White). CONCLUSIONS: Methadone prescribing decreased in CHCs but remained elevated for several high-risk demographic groups.

Sedative-hypnotic Co-prescribing with Opioids in a Large Network of Community Health Centers.

OBJECTIVE: When prescribed with opioids, sedative-hypnotics substantially increase the risk of overdose. The objective of this paper was to describe characteristics and trends in opioid sedative-hypnotic co-prescribing in a network of safety-net clinics serving low-income, publicly insured, and uninsured individuals. METHODS: This retrospective longitudinal analysis of prescription orders examined opioid sedative-hypnotic co-prescribing rates between 2009 and 2018 in the OCHIN network of safety-net community health centers. Sedative-hypnotics included benzodiazepine and non-benzodiazepine sedatives (eg, zolpidem). Co-prescribing patterns were assessed overall and across patient demographic and co-morbidity characteristics. RESULTS: From 2009 to 2018, 240 587 patients had ≥1 opioid prescriptions. Most were White (65%), female (59%), and had Medicaid insurance (43%). One in 4 were chronic opioid users (25%). During this period, 55 332 (23%) were co-prescribed a sedative-hypnotic. The prevalence of co-prescribing was highest for females (26% vs 19% for males), non-Hispanic Whites (28% vs 13% for Hispanic to 20% for unknown), those over 44 years of age (25% vs 20% for <44 years), Medicare insurance (30% vs 21% for uninsured to 22% for other/unknown), and among those on chronic opioid therapy (40%). Co-prescribing peaked in 2010 (32%) and declined steadily through 2018 (20%). Trends were similar across demographic subgroups. Co-prescribed sedative-hypnotics remained elevated for those with chronic opioid use (27%), non-Hispanic Whites (24%), females (23%), and those with Medicare (23%) or commercial insurance (22%). CONCLUSIONS: Co-prescribed sedative-hypnotic use has declined steadily since 2010 across all demographic subgroups in the OCHIN population. Concurrent use remains elevated in several population subgroups.

Chronic overlapping pain conditions and long-term opioid treatment.

OBJECTIVES: One in 5 people in the United States lives with chronic pain. Many patients with chronic pain experience a subset of specific co-occurring pain conditions that may share a common pain mechanism and that have been designated as chronic overlapping pain conditions (COPCs). Little is known about chronic opioid prescribing patterns among patients with COPCs in primary care settings, especially among socioeconomically vulnerable patients. This study aims to evaluate opioid prescribing among patients with COPCs in US community health centers and to identify individual COPCs and their combinations that are associated with long-term opioid treatment (LOT). STUDY DESIGN: Retrospective cohort study. METHODS: We conducted analyses of more than 1 million patients 18 years and older based on electronic health record data from 449 US community health centers across 17 states between January 1, 2009, and December 31, 2018. Logistic regression models were used to assess the relationship between COPCs and LOT. RESULTS: Individuals with COPCs were prescribed LOT 4 times more often than individuals without a COPC (16.9% vs 4.0%). The presence of chronic low back pain, migraine headache, fibromyalgia, or irritable bowel syndrome combined with any of the other COPCs increased the odds of LOT prescribing compared with the presence of a single COPC. CONCLUSIONS: Although LOT prescribing has declined over time, it remains relatively high among patients with certain COPCs and for those with multiple COPCs. These study findings suggest target populations for future interventions to manage chronic pain among socioeconomically vulnerable patients.

Tilling the soil while sowing the seeds: combining resident education with medical home transformation.

In order to successfully integrate screening, brief intervention, and referral to treatment (SBIRT) into primary care, education of clinicians must be paired with sustainable transformation of the clinical settings in which they practice. The SBIRT Oregon project adopted this strategy in an effort to fully integrate SBIRT into 7 primary care residency clinics. Residents were trained to assess and intervene in their patients' unhealthy substance use, whereas clinic staff personnel were trained to carry out a multistep screening process. Electronic medical record tools were created to further integrate and track SBIRT processes. This article describes how a resident training curriculum complemented and was informed by the transformation of workflow processes within the residents' home clinics.

Reduction of Long-Term Opioid Prescribing for Back Pain in Community Health Centers After a Medicaid Policy Change.

INTRODUCTION: Beginning around 2011, innumerable policies have aimed to improve pain treatment while minimizing harms from excessive use of opioids. It is not known whether changing insurance coverage for specific conditions is an effective strategy. We describe and assess the effect of an innovative Oregon Medicaid back/neck pain coverage policy on opioid prescribing patterns. METHODS: This retrospective cohort study uses electronic health record data from a network of community health centers (CHCs) in Oregon to analyze prescription opioid dose changes among patients on long-term opioid treatment (LOT) affected by the policy. RESULTS: Of the 1,789 patients on LOT at baseline, 41.6% had an average daily dose of <20 morphine milligram equivalents (MME), 32.3% had ≥20 to <50 MME, 14.5% had ≥50 to <90 MME, and 11.6% ≥90 MME. Around half of each group discontinued opioids within the 18-month policy period. Those who discontinued did so gradually (average of 11 months) regardless of starting dosage. Predictors of discontinuation included: diagnosis of opioid use disorder, older, non-Hispanic white, and less medical complexity. CONCLUSIONS: Regardless of starting opioid dose, nearly half of patients affected by the 2016 Oregon Medicaid back/neck pain treatment policy no longer received opioid prescriptions by the end of the 18-month study period; another 30% decreased their dose. Gradual dose reduction was typical. These outcomes suggest that the policy impacted opioid prescribing. Understanding patient experiences resulting from such policies could help clinicians and policy makers navigate the complex balance between potential harms and benefits of LOT.

Characterizations of Opioid Prescribing in Community Health Centers in 2018.

OBJECTIVE: To identify the patient- and clinic-level correlates of any prescription opioid use, chronic use, and high-dose opioid use in a multi-state network of Community Health Centers (CHCs). METHODS: We used electronic health record data from 337 primary care clinics serving 610 983 patients across 15 states in 2018. The primary outcomes were prescription of any opioid, chronic opioid, and high-dose opioid. RESULTS: Overall, 6.5% of patients were prescribed an opioid; of these, 31% were chronic users and 5% were high-dose users. Males had 5% lower odds (Odds Ratio [OR] = 0.95; 95% Confidence Interval = 0.93-0.97) of being prescribed an opioid but 16% higher odds (OR = 1.16; 95% CI = 1.10-1.21) of being chronic users and 48% (OR = 1.48; 95% CI = 1.36-1.64) higher odds of being high-dose users than females. Rural clinics had higher rates of chronic opioid (rate ratio = 1.86; 95% CI = 1.20, 2.88) and high-dose users (rate ratio = 2.95; 95% CI = 1.81-4.81). CONCLUSIONS: Our study highlights variations in opioid prescribing with regard to patient-level and clinic-level factors. Targeted efforts and resources may be required to support rural CHCs who seek to reduce high-risk opioid prescribing.

Improving screening, treatment, and intervention for unhealthy alcohol use in primary care through clinic, practice-based research network, and health plan partnerships: Protocol of the ANTECEDENT study.

BACKGROUND: Unhealthy alcohol use (UAU) is a leading cause of morbidity and mortality in the United States, contributing to 95,000 deaths annually. When offered in primary care, screening, brief intervention, referral to treatment (SBIRT), and medication-assisted treatment for alcohol use disorder (MAUD) can effectively address UAU. However, these interventions are not yet routine in primary care clinics. Therefore, our study evaluates tailored implementation support to increase SBIRT and MAUD in primary care. METHODS: ANTECEDENT is a pragmatic implementation study designed to support 150 primary care clinics in Oregon adopting and optimizing SBIRT and MAUD workflows to address UAU. The study is a partnership between the Oregon Health Authority Transformation Center-state leaders in Medicaid health system transformation-SBIRT Oregon and the Oregon Rural Practice-based Research Network. We recruited clinics providing primary care in Oregon and prioritized reaching clinics that were small to medium in size (<10 providers). All participating clinics receive foundational support (i.e., a baseline assessment, exit assessment, and access to the online SBIRT Oregon materials) and may opt to receive tailored implementation support delivered by a practice facilitator over 12 months. Tailored implementation support is designed to address identified needs and may include health information technology support, peer-to-peer learning, workflow mapping, or expert consultation via academic detailing. The study aims are to 1) engage, recruit, and conduct needs assessments with 150 primary care clinics and their regional Medicaid health plans called Coordinated Care Organizations within the state of Oregon, 2) implement and evaluate the impact of foundational and supplemental implementation support on clinic change in SBIRT and MAUD, and 3) describe how practice facilitators tailor implementation support based on context and personal expertise. Our convergent parallel mixed-methods analysis uses RE-AIM (reach, effectiveness, adoption, implementation, maintenance). It is informed by a hybrid of the i-PARIHS (integrated Promoting Action on Research Implementation in Health Services) and the Dynamic Sustainability Framework. DISCUSSION: This study will explore how primary care clinics implement SBIRT and MAUD in routine practice and how practice facilitators vary implementation support across diverse clinic settings. Findings will inform how to effectively align implementation support to context, advance our understanding of practice facilitator skill development over time, and ultimately improve detection and treatment of UAU across diverse primary care clinics.

Adverse effects of antipsychotic medications.

The use of antipsychotic medications entails a difficult trade-off between the benefit of alleviating psychotic symptoms and the risk of troubling, sometimes life-shortening adverse effects. There is more variability among specific antipsychotic medications than there is between the first- and second-generation antipsychotic classes. The newer second-generation antipsychotics, especially clozapine and olanzapine, generally tend to cause more problems relating to metabolic syndrome, such as obesity and type 2 diabetes mellitus. Also, as a class, the older first-generation antipsychotics are more likely to be associated with movement disorders, but this is primarily true of medications that bind tightly to dopaminergic neuroreceptors, such as haloperidol, and less true of medications that bind weakly, such as chlorpromazine. Anticholinergic effects are especially prominent with weaker-binding first-generation antipsychotics, as well as with the second-generation antipsychotic clozapine. All antipsychotic medications are associated with an increased likelihood of sedation, sexual dysfunction, postural hypotension, cardiac arrhythmia, and sudden cardiac death. Primary care physicians should understand the individual adverse effect profiles of these medications. They should be vigilant for the occurrence of adverse effects, be willing to adjust or change medications as needed (or work with psychiatric colleagues to do so), and be prepared to treat any resulting medical sequelae.

Assessment of Opioid Prescribing Patterns in a Large Network of US Community Health Centers, 2009 to 2018.

Importance: Understanding opioid prescribing patterns in community health centers (CHCs) that disproportionately serve low-income patients may help to guide strategies to reduce opioid-related harms. Objective: To assess opioid prescribing patterns between January 1, 2009, and December 31, 2018, in a network of safety-net clinics serving high-risk patients. Design, Setting, and Participants: Cross-sectional study of 3 227 459 opioid prescriptions abstracted from the electronic health records of 2 129 097 unique primary care patients treated from 2009 through 2018 at a network of CHCs that included 449 clinic sites in 17 states. All age groups were included in the analysis. Main Outcomes and Measures: The following measures were described at the population level for each study year: (1) percentage of patients with at least 1 prescription for an opioid by age and sex, (2) number of opioid prescriptions per 100 patients, (3) number of long-acting opioid prescriptions per 100 patients, (4) mean annual morphine milligram equivalents (MMEs) per patient, (5) mean MME per prescription, (6) number of chronic opioid users, and (7) mean of high-dose opioid users. Results: The study population included 2 129 097 patients (1 158 413 women [54.4%]) with a mean (SD) age of 32.2 (21.1) years and a total of 3 227 459 opioid prescriptions. The percentage of patients receiving at least 1 opioid prescription in a calendar year declined 67.4% from 15.9% in 2009 to 5.2% in 2018. Over the 10-year study period, a greater percentage of women received a prescription (13.1%) compared with men (10.9%), and a greater percentage of non-Hispanic White patients (18.1%) received an opioid prescription compared with non-Hispanic Black patients (9.5%), non-Hispanic patients who self-identified as other races (8.0%), and Hispanic patients (6.9%). The number of opioid prescriptions for every 100 patients decreased 73.7% from 110.8 in 2009 to 29.1 in 2018. The number of long-acting opioids for every 100 patients decreased 85.5% during the same period, from 22.0 to 3.2. The MMEs per patient decreased from 1682.7 in 2009 to 243.1 in 2018, a decline of 85.6%. Conclusions and Relevance: In this cross-sectional study, the opioid prescribing rate in 2009 in the CHC network was higher than national population estimates but began to decline earlier and more precipitously. This finding likely reflects harm mitigation policies and efforts at federal, state, and clinic levels and strong clinical quality improvement strategies within the CHCs.

Developing a clinical decision support for opioid use disorders: a NIDA center for the clinical trials network working group report.

There is an urgent need for strategies to address the US epidemic of prescription opioid, heroin and fentanyl-related overdoses, misuse, addiction, and diversion. Evidence-based treatment such as medications for opioid use disorder (MOUD) are available but lack numbers of providers offering these services to meet the demands. Availability of electronic health record (EHR) systems has greatly increased and led to innovative quality improvement initiatives but this has not yet been optimized to address the opioid epidemic or to treat opioid use disorder (OUD). This report from a clinical decision support (CDS) working group convened by the NIDA Center for the Clinical Trials Network aims to converge electronic technology in the EHR with the urgent need to improve screening, identification, and treatment of OUD in primary care settings through the development of a CDS algorithm that could be implemented as a tool in the EHR. This aim is consistent with federal, state and local government and private sector efforts to improve access and quality of MOUD treatment for OUD, existing clinical quality and HEDIS measures for OUD or drug and alcohol use disorders, and with a recent draft grade B recommendation from the US Preventative Services Task Force (USPSTF) for screening for illicit drug use in adults when appropriate diagnosis, treatment and care services can be offered or referred. Through a face-to-face expert panel meeting and multiple follow-up conference calls, the working group drafted CDS algorithms for clinical care felt to be essential for screening, diagnosis, and management of OUD in primary care. The CDS algorithm was reviewed by addiction specialists and primary care providers and revised based on their input. A clinical decision support tool for OUD screening, assessment, and treatment within primary care systems may help improve healthcare delivery to help address the current epidemic of opioid misuse and overdose that has outpaced the capacity of specialized treatment settings. A semi-structured outline of clinical decision support for OUD was developed to facilitate implementation within the EHR. Further work for adaptation at specific sites and for testing is needed.

Changes in Buprenorphine Prescribing in Community Health Centers.

This cohort study characterizes changes in buprenorphine prescribing among community health center clinicians between 2016 and 2021.

Predictors of Medication-Assisted Treatment Initiation for Opioid Use Disorder in an Interdisciplinary Primary Care Model.

INTRODUCTION: Medication-assisted treatment (MAT) for opioid use disorder (OUD) is underused in primary care. Little is known about patient demographics associated with MAT initiation, particularly among models with an interdisciplinary approach, including behavioral health integration. We hypothesize few disparities in MAT initiation by patient characteristics after implementing this model for OUD. METHODS: Electronic health record data were used to identify adults with ≥1 primary care visit in 1 of 2 study clinics in a Pacific Northwest academic health system between September 1, 2015 and August 31, 2017 (n = 23,372). Rates of documented OUD diagnosis were calculated. Multivariate logistic regression estimated odds ratios of MAT initiation, defined as ≥1 electronic health record order for buprenorphine or naltrexone, by patient covariates. RESULTS: Seven percent of the study sample had an OUD diagnosis. Of those patients, 32% had ≥1 MAT order. Patients with documented psychiatric diagnoses or tobacco use had higher odds of initiating MAT (odds ratio [OR] = 1.62, P = .0003; OR = 2.46, P < .0001, respectively). Uninsured, Medicaid, and Medicare patients had lower odds than those commercially insured (OR = 0.53, 0.38, and 0.31, respectively; P < .0001). Patients who were older, of a race/ethnicity other than non-Hispanic white, had documented diabetes, and had documented asthma or chronic obstructive pulmonary disease showed lower odds of initiation. DISCUSSION: MAT initiation varied by patient characteristics, including disparities by insurance coverage and race/ethnicity. The addition of behavioral health did not eliminate disparities in care, but higher odds of initiation among those with a documented psychiatric diagnosis may suggest this model reaches some vulnerable populations. Additional research is needed to further examine these findings.

Development of an algorithm to link electronic health record prescriptions with pharmacy dispense claims.

Objective: Medication adherence is an important aspect of chronic disease management. Electronic health record (EHR) data are often not linked to dispensing data, limiting clinicians' understanding of which of their patients fill their medications, and how to tailor care appropriately. We aimed to develop an algorithm to link EHR prescribing to claims-based dispensing data and use the results to quantify how often patients with diabetes filled prescribed chronic disease medications. Materials and Methods: We developed an algorithm linking EHR prescribing data (RxNorm terminology) to claims-based dispensing data (NDC terminology), within sample of adult (19-64) community health center (CHC) patients with diabetes from a network of CHCs across 12 states. We demonstrate an application of the method by calculating dispense rates for a set of commonly prescribed diabetes and cardio-protective medications. To further inform clinical care, we computed adjusted odds ratios of dispense by patient-, encounter-, and clinic-level characteristics. Results: Seventy-six percent of cardio-protective medication prescriptions and 74% of diabetes medications were linked to a dispensing record. Age, income, ethnicity, insurance, assigned primary care provider, comorbidity, time on EHR, and clinic size were significantly associated with odds of dispensing. Discussion: EHR prescriptions and pharmacy dispense data can be linked at the record level across different terminologies. Dispensing rates in this low-income population with diabetes were similar to other populations. Conclusion: Record linkage resulted in the finding that CHC patients with diabetes largely had their chronic disease medications dispensed. Understanding factors associated with dispensing rates highlight barriers and opportunities for optimal disease management.

Preventive Service Use Among People With and Without Serious Mental Illnesses.

INTRODUCTION: People with serious mental illnesses experience excess morbidity and premature mortality resulting from preventable conditions. The goal was to examine disparities in preventive care that might account for poor health outcomes. METHODS: In this retrospective cohort study, adults (N=803,276) served by Kaiser Permanente Northwest and federally qualified health centers/safety-net community health clinics were categorized into five groups: schizophrenia spectrum disorders, bipolar disorders/affective psychoses, anxiety disorders, nonpsychotic unipolar depression, and reference groups with no evidence of these specific mental illnesses. The primary outcome was overall preventive care-gap rate, the proportion of incomplete preventive services for which each patient was eligible in 2012-2013. Secondary analyses examined Kaiser Permanente Northwest data from 2002 to 2013. Data were analyzed in 2015. RESULTS: Controlling for patient characteristics and health services use, Kaiser Permanente Northwest mean care-gap rates were significantly lower for bipolar disorders/affective psychoses (mean=18.6, p<0.001) and depression groups (mean=18.6, p<0.001) compared with the reference group. Schizophrenia (mean=19.4, p=0.236) and anxiety groups (mean=19.9, p=0.060) did not differ from the reference group (mean=20.3). In community health clinics, schizophrenia (mean=34.1, p<0.001), bipolar/affective psychosis (mean=35.7, p<0.001), anxiety (mean=38.5, p<0.001), and depression groups (mean=36.3, p<0.001) had significantly lower care-gap rates than those in the reference group (mean=40.0). Secondary analyses of diabetes and dyslipidemia screening trends in Kaiser Permanente Northwest showed diagnostic groups consistently had fewer care gaps than patients in the reference group. CONCLUSIONS: In vastly different settings, individuals with serious mental illnesses received preventive services at equal or better rates than the general population.