The health and healthcare impact of providing insurance coverage to uninsured children: A prospective observational study.

BACKGROUND: Of the 4.8 million uninsured children in America, 62-72% are eligible for but not enrolled in Medicaid or CHIP. Not enough is known, however, about the impact of health insurance on outcomes and costs for previously uninsured children, which has never been examined prospectively. METHODS: This prospective observational study of uninsured Medicaid/CHIP-eligible minority children compared children obtaining coverage vs. those remaining uninsured. Subjects were recruited at 97 community sites, and 11 outcomes monitored monthly for 1 year. RESULTS: In this sample of 237 children, those obtaining coverage were significantly (P < .05) less likely than the uninsured to have suboptimal health (27% vs. 46%); no PCP (7% vs. 40%); experienced never/sometimes getting immediate care from the PCP (7% vs. 40%); no usual source of preventive (1% vs. 20%) or sick (3% vs. 12%) care; and unmet medical (13% vs. 48%), preventive (6% vs. 50%), and dental (18% vs. 62%) care needs. The uninsured had higher out-of-pocket doctor-visit costs (mean = $70 vs. $29), and proportions of parents not recommending the child's healthcare provider to friends (24% vs. 8%) and reporting the child's health caused family financial problems (29% vs. 5%), and lower well-child-care-visit quality ratings. In bivariate analyses, older age, birth outside of the US, and lacking health insurance for >6 months at baseline were associated with remaining uninsured for the entire year. In multivariable analysis, children who had been uninsured for >6 months at baseline (odds ratio [OR], 3.8; 95% confidence interval [CI], 1.4-10.3) and African-American children (OR, 2.8; 95% CI, 1.1-7.3) had significantly higher odds of remaining uninsured for the entire year. Insurance saved $2886/insured child/year, with mean healthcare costs = $5155/uninsured vs. $2269/insured child (P = .04). CONCLUSIONS: Providing health insurance to Medicaid/CHIP-eligible uninsured children improves health, healthcare access and quality, and parental satisfaction; reduces unmet needs and out-of-pocket costs; and saves $2886/insured child/year. African-American children and those who have been uninsured for >6 months are at greatest risk for remaining uninsured. Extrapolation of the savings realized by insuring uninsured, Medicaid/CHIP-eligible children suggests that America potentially could save $8.7-$10.1 billion annually by providing health insurance to all Medicaid/CHIP-eligible uninsured children.

New Caregiver Diagnoses of Severe Depression and Child Asthma Controller Medication Adherence.

BACKGROUND AND OBJECTIVES: Children with asthma who have depressed caregivers are known to be less adherent to medication regimes. However, it is less clear how adherence responds to a caregiver's new diagnosis of severe depression or whether there is a similar relationship with other serious caregiver diagnoses. The hypothesis is that adherence worsens both with new diagnoses of depression and possibly with new diagnoses of other serious conditions. METHODS: This study follows a cohort of 341,444 continuously insured children with asthma before and after a caregiver's new diagnosis of severe depression or another serious health condition. The effect of a new depression diagnosis on a child's medication adherence is compared to the effect of new diagnoses of other common caregiver chronic conditions including diabetes, cancer, congestive heart failure, coronary artery disease, and chronic obstructive pulmonary disease. RESULTS: Results show that children's medication adherence declines following a caregiver's new diagnosis of severe depression, but that it also declines following a caregiver's new diagnosis of diabetes. There is no association with new diagnoses of the other caregiver chronic conditions examined. CONCLUSIONS: Children whose caregivers have a new diagnosis of depression or diabetes may be at increased risk of deterioration in their medication adherence. These caregivers may benefit from additional support and follow-up. The relationship between caregivers' health and children's medication adherence is complex and deserves further study.

Prescribing of Opioid Analgesics and Buprenorphine for Opioid Use Disorder During the COVID-19 Pandemic.

Importance: The COVID-19 pandemic disrupted medical care, impacting prescribing of opioid analgesics and buprenorphine for opioid use disorder. Understanding these patterns can help address barriers to care. Objective: To evaluate how prescribing of opioid analgesics and buprenorphine for opioid use disorder changed throughout the COVID-19 pandemic among both new and existing patients. Design, Setting, and Participants: In this cross-sectional study, use of opioid analgesics and buprenorphine for opioid use disorder from March 18 to September 1, 2020, was projected using a national database of retail prescriptions from January 1, 2018, to March 3, 2020. Actual prescribing was compared with projected levels for all, existing, and new patients. Exposures: The data include prescriptions to patients independent of insurance status or type and cover 90% of retail prescriptions, 70% of mail-order prescriptions, and 70% of nursing home prescriptions. Main Outcomes and Measures: Prescriptions for opioid analgesics and buprenorphine for opioid use disorder. Outcomes included total number of prescriptions, total morphine milligram equivalents, mean morphine milligram equivalents per prescription, mean dispensed units per prescription, and number of patients filling prescriptions. Results: A total of 452 691 261 prescriptions for opioid analgesics and buprenorphine for opioid use disorder were analyzed for 90 420 353 patients (50 921 535 female patients [56%]; mean [SD] age, 49 [20] years). From March 18 to May 19, 2020, 1877 million total morphine milligram equivalents of opioid analgesics were prescribed weekly vs 1843 million projected, a ratio of 102% (95% prediction interval [PI], 94%-111%; P = .71). The weekly number of opioid-naive patients receiving opioids was 370 051 vs 564 929 projected, or 66% of projected (95% PI, 63%-68%; P < .001). Prescribing of buprenorphine was as projected for existing patients, while the number of new patients receiving buprenorphine weekly was 9865 vs 12 008 projected, or 82% (95% PI, 76%-88%; P < .001). From May 20 to September 1, 2020, opioid prescribing for new patients returned to 100% of projected (95% PI, 96%-104%; P = .95), while the number of new patients receiving buprenorphine weekly was 10 436 vs 11 613 projected, or 90% (95% PI, 83%-97%; P = .009). Conclusions and Relevance: In this cross-sectional study, existing patients receiving opioid analgesics and buprenorphine for opioid use disorder generally maintained access to these medications during the COVID-19 pandemic. Opioid prescriptions for opioid-naive patients decreased briefly and then rebounded, while initiation of buprenorphine remained at a low rate through August 2020. Reductions in treatment entry may be associated with increased overdose deaths.

UNDERSTANDING DOCTOR DECISION MAKING: THE CASE OF DEPRESSION TREATMENT.

Treatment for depression is complex, requiring decisions that may involve trade-offs between exploiting treatments with the highest expected value and experimenting with treatments with higher possible payoffs. Using patient claims data, we show that among skilled doctors, using a broader portfolio of drugs predicts better patient outcomes, except in cases where doctors' decisions violate loose professional guidelines. We introduce a behavioral model of decision making guided by our empirical observations. The model's novel feature is that the trade-off between exploitation and experimentation depends on the doctor's diagnostic skill. The model predicts that higher diagnostic skill leads to greater diversity in drug choice and better matching of drugs to patients even among doctors with the same initial beliefs regarding drug effectiveness. Consistent with the finding that guideline violations predict poorer patient outcomes, simulations of the model suggest that increasing the number of possible drug choices can lower performance.

E-cigarette minimum legal sale age laws and traditional cigarette use among rural pregnant teenagers.

Teenagers under 18 could legally purchase e-cigarettes until states passed minimum legal sale age laws. These laws may have curtailed teenagers' use of e-cigarettes for smoking cessation. We investigate the effect of e-cigarette minimum legal sale age laws on prenatal cigarette smoking and birth outcomes for underage rural teenagers using data on all births from 2010 to 2016 from 32 states. We find that the laws increased prenatal smoking by 0.6 percentage points (pp) overall. These effects were concentrated in prepregnancy smokers, with no effect on prepregnancy non-smokers. These results suggest that the laws reduced cigarette smoking cessation during pregnancy rather than causing new cigarette smoking initiation. Our results may indicate an unmet need for assistance with smoking cessation among pregnant teenagers.

INEQUALITY IN MORTALITY OVER THE LIFE COURSE: WHY THINGS ARE NOT AS BAD AS YOU THINK.

Recent research shows increasing inequality in mortality among middle-aged and older adults. But this is only part of the story. Inequality in mortality among young people has fallen dramatically in the U.S. converging to almost Canadian rates. Increases in public health insurance for U.S. children, beginning in the late 80s, are likely to have contributed.

Parent Mentors and Insuring Uninsured Children: A Randomized Controlled Trial.

BACKGROUND: Six million US children are uninsured, despite two-thirds being eligible for Medicaid/Children's Health Insurance Program (CHIP), and minority children are at especially high risk. The most effective way to insure uninsured children, however, is unclear. METHODS: We conducted a randomized trial of the effects of parent mentors (PMs) on insuring uninsured minority children. PMs were experienced parents with ≥1 Medicaid/CHIP-covered child who received 2 days of training, then assisted families for 1 year with insurance applications, retaining coverage, medical homes, and social needs; controls received traditional Medicaid/CHIP outreach. The primary outcome was obtaining insurance 1 year post-enrollment. RESULTS: We enrolled 237 participants (114 controls; 123 in PM group). PMs were more effective (P< .05 for all comparisons) than traditional methods in insuring children (95% vs 68%), and achieving faster coverage (median = 62 vs 140 days), high parental satisfaction (84% vs 62%), and coverage renewal (85% vs 60%). PM children were less likely to have no primary care provider (15% vs 39%), problems getting specialty care (11% vs 46%), unmet preventive (4% vs 22%) or dental (18% vs 31%) care needs, dissatisfaction with doctors (6% vs 16%), and needed additional income for medical expenses (6% vs 13%). Two years post-PM cessation, more PM children were insured (100% vs 76%). PMs cost $53.05 per child per month, but saved $6045.22 per child insured per year. CONCLUSIONS: PMs are more effective than traditional Medicaid/CHIP methods in insuring uninsured minority children, improving health care access, and achieving parental satisfaction, but are inexpensive and highly cost-effective.