Variation in Nevada primary care clinicians' use of urine drug testing to mitigate opioid harm.

INTRODUCTION: The prescription opioid epidemic led to federal, state, and health system guidelines and policies aimed at mitigating opioid misuse, including presumptive urine drug testing (UDT). This study identifies whether a difference exists in UDT use among different primary care medical license types. METHODS: The study used January 2017-April 2018 Nevada Medicaid pharmacy and professional claims data to examine presumptive UDTs. We examined correlations between UDTs and clinician characteristics (medical license type, urban/rural status, care setting) along with clinician-level measures of patient mix characteristics (proportions of patients with behavioral health diagnoses, early refills). Adjusted odds ratios (AORs) and predicted probabilities (PPs) from a logistic regression with a binomial distribution are reported. The analysis included 677 primary care clinicians (medical doctors [MD], physician assistants [PA], nurse practitioners [NP]). RESULTS: Of those in the study, 85.1 % of clinicians did not order any presumptive UDTs. NPs had the highest proportion of UDT use (21.2 % of NPs), followed by PAs (20.0 % of PAs), and MDs (11.4 % of MDs). Adjusted analyses showed that being a PA or NP was associated with higher odds of UDT (PA: AOR: 3.6; 95 % CI: 3.1-4.1; NP: AOR: 2.5; 95 % CI: 2.2-2.8) compared to being an MD. PAs had the highest PP for ordering UDTs (2.1 %, 95 % CI: 0.5 %-8.4 %). Among clinicians who ordered UDTs, midlevel clinicians had higher mean and median UDT use (PA and NP mean: 24.3 % vs. MDs: 19.4 %; PA and NP median: 17.7 % vs. MDs: 12.5 %). CONCLUSION: In Nevada Medicaid, UDTs are concentrated among 15 % of primary care clinicians who are frequently non-MDs. More research should include PAs and NPs when examining clinician variation in mitigating opioid misuse.

Comparing risk prediction models aimed at predicting hospitalizations for adverse drug events in community dwelling older adults: a protocol paper.

Background: The objective of this paper is to describe the creation, validation, and comparison of two risk prediction modeling approaches for community-dwelling older adults to identify individuals at highest risk for adverse drug event-related hospitalizations. One approach will use traditional statistical methods, the second will use a machine learning approach. Methods: We will construct medication, clinical, health care utilization, and other variables known to be associated with adverse drug event-related hospitalizations. To create the cohort, we will include older adults (≥ 65 years of age) empaneled to a primary care physician within the Cedars-Sinai Health System primary care clinics with polypharmacy (≥ 5 medications) or at least 1 medication commonly implicated in ADEs (certain oral hypoglycemics, anti-coagulants, anti-platelets, and insulins). We will use a Fine-Gray Cox proportional hazards model for one risk modeling approach and DataRobot, a data science and analytics platform, to run and compare several widely used supervised machine learning algorithms, including Random Forest, Support Vector Machine, Extreme Gradient Boosting (XGBoost), Decision Tree, Naïve Bayes, and K-Nearest Neighbors. We will use a variety of metrics to compare model performance and to assess the risk of algorithmic bias. Discussion: In conclusion, we hope to develop a pragmatic model that can be implemented in the primary care setting to risk stratify older adults to further optimize medication management.

Systematic Review of Care Coordination Interventions Linking Health and Social Services for High-Utilizing Patient Populations.

Recognizing that social factors influence patient health outcomes and utilization, health systems have developed interventions to address patients' social needs. Care coordination across the health care and social service sectors is a distinct and important strategy to address social determinants of health, but limited information exists about how care coordination operates in this context. To address this gap, the authors conducted a systematic review of peer-reviewed publications that document the coordination of health care and social services in the United States. After a structured elimination process, 25 publications of 19 programs were synthesized to identify patterns in care coordination implementation. Results indicate that patient needs assessment, in-person patient contact, and standardized care coordination protocols are common across programs that bridge health care and social services. Publications discussing these programs often provide limited detail on other key elements of care coordination, especially the nature of referrals and care coordinator caseload. Additional research is needed to document critical elements of program implementation and to evaluate program impacts.

Reducing Medicaid Coverage Gaps for Youth During Reentry.

Although many justice-involved youth (JIY) rely on Medicaid, due to the federal "inmate exclusion" Medicaid is often suspended or terminated upon youth's intake to detention, which can lead to coverage gaps at release. We interviewed 28 experts on Medicaid and the justice system and conducted thematic analysis to identify solutions for reducing Medicaid coverage gaps during reentry. Participants viewed coverage gaps during reentry as a significant public health problem to which JIY are especially vulnerable. Recommended solutions for reducing coverage gaps for JIY included (a) leave Medicaid activated, (b) reactivate Medicaid before or during reentry, (c) enhance interagency collaboration, and (d) address societal context to ensure health care access for Medicaid-eligible JIY. Doing so may improve health outcomes and reduce cycles of youth incarceration.

The one-year impact of accountable care networks among Washington State employees.

OBJECTIVE: To estimate the impact of a new, two-sided risk model accountable care network (ACN) on Washington State employees and their families. DATA SOURCES/STUDY SETTING: Administrative data (January 2013-December 2016) on Washington State employees. STUDY DESIGN: We compared monthly health care utilization, health care intensity as measured through proxy pricing, and annual HEDIS quality metrics between the five intervention counties to 13 comparison counties, analyzed separately by age categories (ages 0-5, 6-18, 19-26, 18-64). DATA COLLECTION/EXTRACTION METHODS: We used difference-in-difference methods and generalized estimating equations to estimate the effects after 1 year of implementation for adults and children. PRINCIPAL FINDINGS: We estimate a 1-2 percentage point decrease in outpatient hospital visits due to the introduction of ACNs (adults: -1.8, P < .01; age 0-5: -1.2, P = .07; age 6-18: -1.2, P = .06; age 19-26; -1.2, P < .01). We find changes in primary and specialty care office visits; the direction of impact varies by age. Dependents age 19-26 were also responsive with inpatient admissions declines (-0.08 percentage points, P = .02). Despite changes in utilization, there was no evidence of changes in intensity of care and mixed results in the quality measures. CONCLUSIONS: Washington's state employee ACN introduction changed health care utilization patterns in the first year but was not as successful in improving quality.

Mixed-Methods Evaluation of the Washington State Practice Transformation Support Hub.

PURPOSE: Practice transformation initiatives have the potential to promote collaborations between public health, primary care, and behavioral health, but limited empirical evidence is available on how these programs affect participating clinical practices. OBJECTIVE: To report the findings from a mixed-methods program evaluation of the Washington Practice Transformation Support Hub (Hub), a publicly funded, multicomponent practice transformation initiative in Washington State. DESIGN: We used quantitative and qualitative methods to evaluate the impact of Hub activities on participating primary care and behavioral health practices. Pre- and posttest survey data were combined with administrative program data to understand the effect of program components. Qualitative interviews contextualized findings. SETTING: Urban and rural primary care and behavioral health practices in Washington State. PARTICIPANTS: One hundred seventy-five practices that were recruited to receive Hub coaching and facilitation from 8 coaches; of these, 13 practices and all coaches participated in key informant interviews. INTERVENTION: Practice coaching and facilitation supported by an online resource portal, from January 2017 through January 2019. MAIN OUTCOME MEASURES: Self-reported progress in specific activities in 3 practice-level domains: bidirectional integration of physical and behavioral health care (care integration); alignment with community-based services for whole-person care (clinical-community linkages); and value-based payment. RESULTS: Participation in Hub activities was associated with improvements in care integration and clinical-community linkages but not with progress toward value-based payment. Qualitative results indicated that practice progress was influenced by communication with practices, the culture of the practice, resource constraints (particularly in rural areas), and perceptions about sustainability. CONCLUSIONS: This statewide practice transformation initiative was successful in strengthening primary care and behavioral health integration and clinical-community linkages among participating practices but not value-based payment. Future practice transformation efforts may benefit from addressing barriers posed by communication, limited application of value-based payment, culture change, competing priorities, and resource limitations, particularly for rural communities.

Integrating Health And Human Services In California's Whole Person Care Medicaid 1115 Waiver Demonstration.

Policy makers are increasingly investing in programs focused on identifying and addressing the nonmedical needs of high-utilizing Medicaid beneficiaries, yet little is known about these programs' implementation. This study provides an overview of early progress in and strategies used to implement California's Whole Person Care (WPC) Pilot Program, a $3 billion Medicaid Section 1115(a) waiver demonstration project focused on improving the integrated delivery of health, behavioral health, and social services for Medicaid beneficiaries who use acute and costly services in multiple service sectors. WPC pilots reported significant progress in developing partnerships, data-sharing infrastructure, and services needed to coordinate care for identified patient populations. We also identified major barriers to WPC implementation, such as difficulty identifying and engaging eligible beneficiaries and the lack of affordable housing. Our findings offer insights to leaders and policy makers interested in testing new approaches for improving the health and well-being of medically and socially complex patients.

Eliminating Gaps in Medicaid Coverage During Reentry After Incarceration.

This commentary explores the health and social challenges associated with gaps in Medicaid health insurance coverage for adults and youths exiting the US criminal justice system, and highlights some potential solutions.Because a high proportion of recently incarcerated people come from low-income backgrounds and experience a high burden of disease, the Medicaid program plays an important role in ensuring access to care for this population. However, the Medicaid Inmate Exclusion Policy, or "inmate exclusion," leads to Medicaid being terminated or suspended upon incarceration, often resulting in gaps in Medicaid coverage at release. These coverage gaps interact with individual-level and population-level factors to influence key health and social outcomes associated with recidivism.Ensuring Medicaid coverage upon release is an important, feasible component of structural change to alleviate health inequities and reduce recidivism. High-yield opportunities to ensure continuous coverage exist at the time of Medicaid suspension or termination and during incarceration prior to release.

Accountable Care Program Implementation and Effects on Participating Health Care Systems in Washington State: A Conceptual Model.

This study is based on key informant interviews with health care executives representing 5 large health systems that had entered into contracts with the Washington State Health Care Authority to provide accountable care network services under the State Innovation Model initiative. The purpose of this study was to explain effects of accountable care program (ACP) implementation on participating health care systems. Between January 2017 and May 2018, we conducted 2 rounds of semistructured interviews (n = 20). Results indicate the need to present a modified conceptual model aligned with ACP implementation in the current context.