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.

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.

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.

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.

HIV and Hepatitis C Virus Screening Practices in a Geographically Diverse Sample of American Community Health Centers.

Because of the advent of highly effective treatments, routine screening for HIV and hepatitis C virus (HCV) has been recommended for many Americans. This study explored the perceived barriers surrounding routine HIV and HCV screening in a diverse sample of community health centers (CHCs). The Community Health Applied Research Network (CHARN) is a collaboration of CHCs, with a shared clinical database. In July, 2013, 195 CHARN providers working in 12 CHCs completed a survey of their attitudes and beliefs about HIV and HCV testing. Summary statistics were generated to describe the prevalence of HIV and HCV and associated demographics by CHCs. HIV and HCV prevalence ranged from 0.1% to 5.7% for HIV and from 0.1% to 3.7% for HCV in the different CHCs. About 15% of the providers cared for at least 50 individuals with HIV and the same was true for HCV. Two-thirds saw less than 10 patients with HIV and less than half saw less than 10 patients with HCV. Less than two-thirds followed USPHS guidelines to screen all patients for HIV between the ages of 13 and 64, and only 44.4% followed the guidance to screen all baby boomers for HCV. Providers with less HIV experience tended to be more concerned about routine screening practices. More experienced providers were more likely to perceive lack of time being an impediment to routine screening. Many US CHC providers do not routinely screen their patients for HIV and HCV. Although additional education about the rationale for routine screening may be indicated, incentives to compensate providers for the additional time they anticipate spending in counseling may also facilitate increased screening rates.

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.

"Not a kidney or a lung:" research challenges in a network of safety net clinics.

BACKGROUND AND OBJECTIVES: To gain a better understanding of the facilitators and barriers to creating a practice-based research network (PBRN) of safety net clinics, we conducted a qualitative study within our network of safety net health centers. METHODS: Utilizing snowball sampling, we conducted interviews with 19 of our founding stakeholders and analyzed these interviews to draw out common themes. RESULTS: The results showed four barriers to research in our network: lack of research generated from clinician questions, lack of appropriate funding, lack of clinician time, and lack of infrastructure. We discuss these results and suggest that inadequate funding for practice-based research, particularly in the health care safety net, is a unifying theme of these four barriers. CONCLUSIONS: Our results suggest that the national funding strategy for research relevant to underserved populations and all of primary care must undergo a fundamental shift. We discuss the features of possible models to meet this need.

[Primary care in the USA and the Peruvian experience in perspective]. / La atención primaria en los Estados Unidos y la experiencia peruana en perspectiva.

Due to a complex payment system, the health system of the United States is fragmented, expensive, and achieves the goal of improving the health of the entire population. Excessive health costs increase the budget deficit in the US. This situation makes to the government to have greater willingness to try new approaches in the delivery of health services. Is well know that the states that have a solid system of primary health care (PC), spent less money in diseases and have lower utilization of health services (reflected in fewer days of hospitalization). This is why the AP is spreading in the US making doctors, nurses and other providers to collaborate on new proposals for team-based care, coordinated and patient-oriented generating real benefits while controlling costs. The US experience with AP support evidence-based approach to propose, from a foreign perspective, strengthening the AP in Peru.

La atención primaria en los Estados Unidos y la experiencia peruana en perspectiva / Primary care in the USA and the peruvian experience in perspective

Debido a un complejo sistema de pagos, el sistema de salud de los Estados Unidos (EE. UU.) es fragmentado, costoso, y alcanza el objetivo de mejorar la salud de toda la población. Los costos excesivos de salud incrementan el déficit económico en los EE. UU., y esto hace que su gobierno tenga mayor disposición a probar nuevos enfoques en la prestación de servicios de salud. Llama la atención que los estados norteamericanos que cuentan con un sistema de atención primaria (AP) sólido, tienen menores gastos por enfermedad y menor utilización de servicios de salud (reflejado en menos días de hospitalización). Es por esto que la AP está extendiéndose en los EE. UU., haciendo que médicos, enfermeras y otros proveedores colaboren en nuevas propuestas de atención basadas en equipo, coordinadas y orientadas al paciente generando beneficios reales, al mismo tiempo que controlan los costos. Esta experiencia estadounidense con una AP con enfoque basado en evidencias ayuda a proponer, desde una perspectiva extranjera, el fortalecimiento de la AP en el Perú.

Due to a complex payment system, the health system of the United States is fragmented, expensive, and achieves the goal of improving the health of the entire population. Excessive health costs increase the budget deficit in the US. This situation makes to the government to have greater willingness to try new approaches in the delivery of health services. Is well know that the states that have a solid system of primary health care (PC), spent less money in diseases and have lower utilization of health services (reflected in fewer days of hospitalization). This is why the AP is spreading in the US making doctors, nurses and other providers to collaborate on new proposals for team-based care, coordinated and patient-oriented generating real benefits while controlling costs. The US experience with AP support evidence-based approach to propose, from a foreign perspective, strengthening the AP in Peru.

Collaborative development of a randomized study to adapt a diabetes quality improvement initiative for federally qualified health centers.

This case study describes how we are translating a diabetes care quality improvement initiative from an insured (HMO) setting into federally qualified health centers (FQHCs). We outline the innovative collaborative processes whereby researchers and FQHC providers adapted this initiative, which includes health information technology tools, to meet the FQHCs' needs.

Developing a network of community health centers with a common electronic health record: description of the Safety Net West Practice-based Research Network (SNW-PBRN).

In 2001, community health center (CHC) leaders in Oregon established an organization to facilitate the integration of health information technology, including a shared electronic health record (EHR), into safety net clinics. The Oregon Community Health Information Network (shortened to OCHIN as other states joined) became a CHC information technology hub, supporting a network-wide EHR with one master patient index, now linked across >40 safety net organizations serving >900,000 patients with nearly 800,000 distinct CHC visits. Recognizing the potential of OCHIN's multiclinic network and comprehensive EHR database for conducting safety net-based research, OCHIN leaders and local researchers formed the Safety Net West practice-based research network (PBRN). The Safety Net West "community- based laboratory," based at OCHIN, is positioned to become an important resource for many studies including: evaluation of the real-time impact of health care reform on uninsured populations; development of new models of primary care delivery; dissemination and translation of interventions from other EHR-based systems (e.g., Kaiser Permanente) into the community health setting; and analyses of factors influencing disparities in health and health care access. We describe the founding of Safety Net West, its infrastructure development, current projects, and the future goals of this community-based PBRN with a common EHR.