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Background: While insurance is integral for accessing healthcare in the US, coverage alone may not ensure access, especially for those publicly insured. Access barriers for Medicaid-insured patients are rooted in social drivers of health, insurance complexities in the setting of managed care plans, and federal- and state-level policies. Elucidating barriers at the health system level may reveal opportunities for sustainable solutions., Methods: To understand barriers to ambulatory care access for patients with Medi-Cal (California's Medicaid program) and identify improvement opportunities, we performed a qualitative study using semi-structured interviews of a referred sample of clinicians and administrative staff members experienced with clinical patient encounters and/or completion of referral processes for patients with Medi-Cal (n = 19) at a large academic medical center. The interview guide covered the four process steps to accessing care within the health system: (1) scheduling, (2) referral and authorization, (3) contracting, and (4) the clinical encounter. We transcribed and inductively coded the interviews, then organized themes across the four steps to identify perceptions of barriers to access and improvement opportunities for ambulatory care for patients with Medi-Cal., Results: Clinicians and administrative staff members at a large academic medical center revealed barriers to ambulatory care access for Medi-Cal insured patients, including lack of awareness of system-level policy, complexities surrounding insurance contracting, limited resources for social support, and poor dissemination of information to patients. Particularly, interviews revealed how managed Medi-Cal impacts academic health systems through additional time and effort by frontline staff to facilitate patient access compared to fee-for-service Medi-Cal. Interviewees reported that this resulted in patient care delays, suboptimal care coordination, and care fragmentation., Conclusions: Our findings highlight gaps in system-level policy, inconsistencies in pursuing insurance authorizations, limited resources for scheduling and social work support, and poor dissemination of information to and between providers and patients, which limit access to care at an academic medical center for Medi-Cal insured patients. Many interviewees additionally shared the moral injury that they experienced as they witnessed patient care delays in the absence of system-level structures to address these barriers. Reform at the state, insurance organization, and institutional levels is necessary to form solutions within Medi-Cal innovation efforts., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Objectives: We sought to identify the most common diagnostic categories linked to dispensed opioid prescriptions among children 1-36 months old and changes in patterns over the years 2000 to 2017., Methods: This study used South Carolina's Medicaid claims data of pediatric dispensed outpatient opioid prescriptions between 2000 and 2017. The major opioid-related diagnostic category (indication) for each prescription was identified using visit primary diagnoses and the Clinical Classification System (AHRQ-CCS) software. The variables of interest were the rate of opioid prescriptions per 1,000 visits for each diagnostic category and the relative percentage of opioid prescriptions assigned to each category compared to all categories., Results: Six major diagnostic categories were identified; Diseases of the respiratory system (RESP), Congenital anomalies (CONG), Injury (INJURY), Diseases of the nervous system and sense organs (NEURO), Diseases of the digestive system (GI), and Diseases of the genitourinary system (GU). The overall rate of dispensed opioid prescriptions per category declined significantly for four diagnostic categories throughout the study period, RESP by 15.13, INJURY by 8.49, NEURO by 7.33, and GI by 5.93. Two categories increased during the same time, CONG (by 9.47) and GU (by 6.98). RESP was the most prevalent category linked to a dispensed opioid prescription within 2010-2012 (almost 25%) but CONG was the most prevalent by 2014 (17.77%)., Conclusions for Practice: Among Medicaid children 1-36 months old, annual dispensed opioid prescription rates declined for most major diagnostic categories (RESP, INJURY, NEURO, and GI). Future studies should explore alternatives to current opioid dispensing practices for GU and CONG cases., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objective: To examine dispensed opioid prescription patterns for limb fractures across racial/ethnic groups in a pediatric population., Methods: We used South Carolina's Medicaid claims data 2000 to 2018 for pediatric limb fracture cases (under age 19) discharged from the emergency department. The key independent variable was the child's race/ethnicity. The outcomes were: 1) whether the patient had a dispensed opioid prescription; and 2) whether dispensed opioid supply was longer than 5 days among cases with any dispensed opioid prescriptions. Logistic regression models were used to test the association between race/ethnicity and the outcomes. Covariates included age-at-service, gender, service year, and having multiple fracture injuries., Results: Compared with non-Hispanic White cases (NHW), the odds of receiving dispensed opioid prescriptions were lower for cases of non-Hispanic Black (NHB) (OR = 0.73; 95% confidence interval [CI]: 0.71, 0.75), Asian (OR = 0.69; CI: 0.53, 0.90), Other/Unknown (OR = 0.86; CI: 0.80, 0.92), and Hispanic (OR = 0.84; CI: 0.79, 0.90) race/ethnicity. The odds of receiving >5 days of dispensed opioid prescription supply did not differ significantly among race/ethnic categories., Conclusions: Our study confirms previous findings that as compared to NHW, the NHB children were less likely to receive dispensed opioid prescriptions. Also, it reveals that the different minority race/ethnic groups are not homogenous in their likelihoods of receiving dispensed opioid prescriptions after a limb fracture compared to NHW, findings underreported in previous studies. Children in the Other/Unknown race/ethnicity category have prescribing patterns different from those of other minority race/ethnic groups and should be analyzed separately., (Copyright © 2022 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.)

Background: Past mobile health (mHealth) efforts to empower type 2 diabetes (T2D) self-management include portals, text messaging, collection of biometric data, electronic coaching, email, and collection of lifestyle information., Objective: The primary objective was to enhance patient activation and self-management of T2D using the US Department of Defense's Mobile Health Care Environment (MHCE) in a patient-centered medical home setting., Methods: A multisite study, including a user-centered design and a controlled trial, was conducted within the US Military Health System. Phase I assessed preferences regarding the enhancement of the enabling technology. Phase II was a single-blinded 12-month feasibility study that randomly assigned 240 patients to either the intervention (n=123, received mHealth technology and behavioral messages tailored to Patient Activation Measure [PAM] level at baseline) or the control group (n=117, received equipment but not messaging. The primary outcome measure was PAM scores. Secondary outcome measures included Summary of Diabetes Self-Care Activities (SDSCA) scores and cardiometabolic outcomes. We used generalized estimating equations to estimate changes in outcomes., Results: The final sample consisted of 229 patients. Participants were 61.6% (141/229) male, had a mean age of 62.9 years, mean glycated hemoglobin (HbA 1c ) of 7.5%, mean BMI of 32.7, and a mean duration of T2D diagnosis of 9.8 years. At month 12, the control group showed significantly greater improvements compared with the intervention group in PAM scores (control mean 7.49, intervention mean 1.77; P=.007), HbA 1c (control mean -0.53, intervention mean -0.11; P=.006), and low-density lipoprotein cholesterol (control mean -7.14, intervention mean 4.38; P=.01). Both groups showed significant improvement in SDSCA, BMI, waist size, and diastolic blood pressure; between-group differences were not statistically significant. Except for patients with the highest level of activation (PAM level 4), intervention group patients exhibited significant improvements in PAM scores. For patients with the lowest level of activation (PAM level 1), the intervention group showed significantly greater improvement compared with the control group in HbA 1c (control mean -0.09, intervention mean -0.52; P=.04), BMI (control mean 0.58, intervention mean -1.22; P=.01), and high-density lipoprotein cholesterol levels (control mean -4.86, intervention mean 3.56; P<.001). Significant improvements were seen in AM scores, SDSCA, and waist size for both groups and in diastolic and systolic blood pressure for the control group; the between-group differences were not statistically significant. The percentage of participants who were engaged with MHCE for ≥50% of days period was 60.7% (68/112; months 0-3), 57.4% (62/108; months 3-6), 49.5% (51/103; months 6-9), and 43% (42/98; months 9-12)., Conclusions: Our study produced mixed results with improvement in PAM scores and outcomes in both the intervention and control groups. Structural design issues may have hampered the influence of tailored behavioral messaging within the intervention group., Trial Registration: ClinicalTrials.gov NCT02949037; https://clinicaltrials.gov/ct2/show/NCT02949037., International Registered Report Identifier (irrid): RR2-10.2196/resprot.6993., (©Ronald W Gimbel, Lior M Rennert, Paul Crawford, Jeanette R Little, Khoa Truong, Joel E Williams, Sarah F Griffin, Lu Shi, Liwei Chen, LingLing Zhang, Jennie B Moss, Robert C Marshall, Karen W Edwards, Kristy J Crawford, Marie Hing, Amanda Schmeltz, Brandon Lumsden, Morgan Ashby, Elizabeth Haas, Kelly Palazzo. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 26.05.2020.)