Literature Collection

BACKGROUND: Co-occurring substance use disorders (SUDs) among individuals with opioid use disorder (OUD) are associated with additional impairment, overdose, and death. This study examined characteristics of patients who have OUD with and without co-occurring SUDs in rural primary care clinics. METHODS: Secondary analysis used electronic health record (EHR) data from six rural primary care clinics, including demographics, diagnoses, encounters, and prescriptions of medication for OUD (MOUD), as well as EHR data from an external telemedicine vendor that provided MOUD to some clinic patients. The study population included all adult patients who had a visit to the participating clinics from October 2019 to January 2021. RESULTS: We identified 1164 patients with OUD; 72.6 % had OUD only, 11.5 % had OUD and stimulant use disorder (OUD + StUD), and 15.9 % had OUD and other non-stimulant substance use disorder (OUD + Other). The OUD + StUD group had the highest rates of hepatitis C virus (25.4 % for OUD + StUD, 17.8 % for OUD + Other, and 7.5 % for OUD Only; p < 0.001) and the highest rates of mental health disorders (78.4 %, 69.7 %, and 59.9 %, respectively; p < 0.001). Compared to the OUD Only group, patients in the OUD + StUD and OUD + Other groups were more likely to receive telehealth services provided by clinic staff, in-clinic behavioral health services, and in-clinic MOUD. The OUD + StUD group had the highest proportion of referrals to the external telemedicine vendor. CONCLUSIONS: More than 27 % of patients with OUD in rural primary care clinics had other co-occurring SUDs, and these patients received more healthcare services than those with OUD only. Future studies should examine variations in outcomes associated with these other services among patients with OUD and co-occurring SUDs.

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder resulting in negative long-term outcomes if untreated. Pathways to healthcare in the United Kingdom are complex, especially for those aged 16-25 transitioning between child and adult mental health services. We aimed to co-produce evidence-informed resources to improve accessibility of primary care for young people with ADHD. METHODS: We utilised co-production principles from the National Institute for Health and Care Research and findings from recent research to create evidence-informed resources which collate experiences of multiple stakeholders. Lived experience advisors (young people aged 16-25 with ADHD and their supporters) and healthcare professionals were recruited through previous research engagement and local collaborations. Research partners engaged in workshops or individual meetings to agree priorities, content, and language/visual appearance for outputs. RESULTS: Lived experience advisors (7), healthcare professionals (5), and researchers (3) co-produced a downloadable resource for young people and their supporters. The resource identifies key stages on ADHD healthcare pathways, common barriers, and top tips recommended by people with lived experience, and verified by healthcare professionals. Key messages for primary care professionals were co-produced. CONCLUSION: Co-produced resources can help address barriers to accessing ADHD treatment and support via stretched NHS services. Collaborative working also highlighted the need for national policy change to alleviate pressures faced by healthcare professionals and patients. PATIENT AND PUBLIC CONTRIBUTION: Two research advisory groups (RAGs) of healthcare professionals and lived experience advisors informed research methods and presentation of results. RAG members participated in co-production workshops, contributed to authorship, and disseminated outputs.

INTRODUCTION: Behavioral symptoms in hospitalized older adults with cognitive impairment often lead to physical and chemical restraint use, despite associated harms. Patient-centered care models show promise in reducing restraint use but are rarely implemented in routine practice. This project implemented CoCare-CI, a clinical innovation to address behavioral symptoms in hospitalized older adults with cognitive impairment. METHODS: CoCare-CI was implemented on a 24-bed ACE unit in a 128-bed community hospital from January 2023 to August 2024 by a multidisciplinary team led by a geriatric nurse practitioner (GNP). CoCare-CI emphasized (1) systematic screening and assessment of mentation, and (2) individualized management plans for delirium or dementia. Implementation followed a phased, cyclical approach with champions supporting process improvement. Baseline restraint data (January-August 2023) were compared to intervention data (September 2023-August 2024). Primary outcomes included physical and chemical restraint use; process measures included documentation rates of the Confusion Assessment Method (CAM), CAM-Severity (CAM-S), Six-Item Cognitive Impairment Test (6CIT), and 4Ms checklist. RESULTS: Among 949 patients (mean age 81.5 years, 59% female, 80.6% White), 34.1% had cognitive impairment at baseline, including 22.6% with dementia and 11.5% with a significant 6CIT score (≥ 8). Documentation rates improved for CAM (68%-86%), CAM-S (0%-79%), 6CIT (0%-89%), and 4Ms checklist (0%-96%). Physical restraint use decreased from 4.3% to 0.7%, and chemical restraint use dropped from 7.6% to 2.3%. Most restraint use (84.2%, 16/19) was deemed potentially avoidable, with root cause analysis revealing that 78.6% (11/14) of patients with restraint orders had moderate to severe dementia with behavioral symptoms. CONCLUSIONS: CoCare-CI is associated with reductions in reduced physical and chemical restraint use, demonstrating potential for dissemination within routine clinical practice. Future research should assess sustainability, broader applicability, and integration of additional 4Ms components.

BACKGROUND: Mental, emotional, and behavioral disorders are chronic pediatric conditions, and their prevalence has been on the rise over recent decades. Affected children have long-term health sequelae and a decline in health-related quality of life. Due to the lack of a validated database for pharmacoepidemiological research on selected mental, emotional, and behavioral disorders, there is uncertainty in their reported prevalence in the literature. OBJECTIVES: We aimed to evaluate the accuracy of coding related to pediatric mental, emotional, and behavioral disorders in a large integrated health care system's electronic health records (EHRs) and compare the coding quality before and after the implementation of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding as well as before and after the COVID-19 pandemic. METHODS: Medical records of 1200 member children aged 2-17 years with at least 1 clinical visit before the COVID-19 pandemic (January 1, 2012, to December 31, 2014, the ICD-9-CM coding period; and January 1, 2017, to December 31, 2019, the ICD-10-CM coding period) and after the COVID-19 pandemic (January 1, 2021, to December 31, 2022) were selected with stratified random sampling from EHRs for chart review. Two trained research associates reviewed the EHRs for all potential cases of autism spectrum disorder (ASD), attention-deficit hyperactivity disorder (ADHD), major depression disorder (MDD), anxiety disorder (AD), and disruptive behavior disorders (DBD) in children during the study period. Children were considered cases only if there was a mention of any one of the conditions (yes for diagnosis) in the electronic chart during the corresponding time period. The validity of diagnosis codes was evaluated by directly comparing them with the gold standard of chart abstraction using sensitivity, specificity, positive predictive value, negative predictive value, the summary statistics of the F-score, and Youden J statistic. κ statistic for interrater reliability among the 2 abstractors was calculated. RESULTS: The overall agreement between the identification of mental, behavioral, and emotional conditions using diagnosis codes compared to medical record abstraction was strong and similar across the ICD-9-CM and ICD-10-CM coding periods as well as during the prepandemic and pandemic time periods. The performance of AD coding, while strong, was relatively lower compared to the other conditions. The weighted sensitivity, specificity, positive predictive value, and negative predictive value for each of the 5 conditions were as follows: 100%, 100%, 99.2%, and 100%, respectively, for ASD; 100%, 99.9%, 99.2%, and 100%, respectively, for ADHD; 100%, 100%, 100%, and 100%, respectively for DBD; 87.7%, 100%, 100%, and 99.2%, respectively, for AD; and 100%, 100%, 99.2%, and 100%, respectively, for MDD. The F-score and Youden J statistic ranged between 87.7% and 100%. The overall agreement between abstractors was almost perfect (κ=95%). CONCLUSIONS: Diagnostic codes are quite reliable for identifying selected childhood mental, behavioral, and emotional conditions. The findings remained similar during the pandemic and after the implementation of the ICD-10-CM coding in the EHR system.