Cancer Treatment Before and After Physician-Pharmacy Integration.

Importance: Integration of pharmacies with physician practices, also known as medically integrated dispensing, is increasing in oncology. However, little is known about how this integration affects drug use, expenditures, medication adherence, or time to treatment initiation. Objective: To examine the association of physician-pharmacy integration with oral oncology drug expenditures, use, and patient-centered measures. Design, Setting, and Participants: This cohort study used claims data from a large commercial insurer in the US to analyze changes in outcome measures among patients treated by pharmacy-integrating vs nonintegrating community oncologists in 14 states between January 1, 2011, and December 31, 2019. Commercially insured patients were aged 18 to 64 years with 1 of the following advanced-stage diagnoses: breast cancer, colorectal cancer, kidney cancer, lung cancer, melanoma, or prostate cancer. Data analysis was conducted from May 2023 to March 2024. Exposure: Treatment by a pharmacy-integrating oncologist, ascertained by the presence of an on-site pharmacy or nonpharmacy dispensing site. Main Outcomes and Measures: Oral, intravenous (IV), total, and out-of-pocket drug expenditures for a 6-month episode of care; share of patients prescribed oral drugs; days' supply of oral drugs; medication adherence measured by proportion of days covered; and time to treatment initiation. The association between an oncologist's pharmacy integration and each outcome of interest was estimated using the difference-in-differences estimator. Results: Between 2012 and 2019, 3159 oncologists (745 females [27.1%], 2002 males [72.9%]) treated 23 968 patients (66.4% female; 53.4% aged 55-64 years). Of the 3159 oncologists, 578 (18.3%) worked in practices that integrated with pharmacies (with a low rate in 2011 of 0% and a high rate in 2019 of 31.5%). In the full sample (including all cancer sites), after physician-pharmacy integration, no significant changes were found in oral drug expenditures, IV drug expenditures, or total drug expenditures. There was, however, an increase in days' supply of oral drugs (5.96 days; 95% CI, 0.64-11.28 days; P = .001). There were no significant changes in out-of-pocket expenditures, medication adherence, or time to treatment initiation of oral drugs. In the breast cancer sample, there was an increase in oral drug expenditures ($244; 95% CI, $41-$446; P = .02) and a decrease in IV drug expenditures (-$4187; 95% CI, -$8293 to -$80; P = .05). Conclusions and Relevance: Results of this cohort study indicated that the integration of oncology practices with pharmacies was not associated with significant changes in expenditures or clear patient-centered benefits.

Telehealth Initiation of Buprenorphine for Opioid Use Disorder: Patient Characteristics and Outcomes.

BACKGROUND: The COVID-19 pandemic exacerbated access barriers for patients with opioid use disorder. Telehealth presents an opportunity to improve access, treatment quality, and patient outcomes. OBJECTIVE: To determine patient characteristics associated with initiating buprenorphine treatment via telehealth and to examine how telehealth initiation is associated with access, treatment quality, and health outcomes. DESIGN AND PARTICIPANTS: This cross-sectional study used deidentified insurance claims to identify opioid use disorder adult patients initiating buprenorphine treatment between March 1, 2020, and November 30, 2021. Multivariable logistic regression assessed determinants of telehealth initiation. Propensity score matching addressed observed differences between in-person and telehealth initiators. MAIN MEASURES: Treatment quality outcomes included initiation within 14 days of diagnosis, engagement (at least 2 opioid use disorder-related visits), and any buprenorphine refill during the study period. Health outcomes included opioid overdose and opioid use disorder-related emergency department and inpatient visits. KEY RESULTS: We identified 23,565 adult buprenorphine initiators, including 3314 (14.1%) patients using telehealth. Younger patients (OR 0.91 to 0.77), females (OR 1.18), South (OR 1.63) and Midwest (OR 1.27) regions, rural area (OR 1.12), and higher-income (OR 1.16) neighborhood residents were more likely to use telehealth. Telehealth patients were more likely than in-person patients (54.5% vs. 48.4%; adjusted odds ratio (AOR), 1.29; 95% CI, 1.19-1.40) to stay engaged with opioid use disorder treatment, and more likely to refill buprenorphine during the study period (83.6% vs. 79.0%, AOR 1.37; 95% CI, 1.23-1.52). Telehealth initiation of buprenorphine was associated with 36% lower overdose rate than in-person initiation (adjusted incidence rate ratio 0.64; 95% CI, 0.45-0.94). The two groups evidenced no significant differences in opioid use disorder-related ED visit and hospitalization. CONCLUSIONS: Our findings suggest that telehealth-initiated buprenorphine treatment is associated with reduced opioid overdose rate and improved patient engagement. Our findings strengthen the case for extending telehealth exemptions and prescribing flexibilities for treatment.

Distribution of a Remote Medical Exam Device Associated with an Increase in Telehealth Use.

Background: The COVID-19 pandemic accelerated telehealth adoption, but its effects on care quality and costs remain unclear. This study evaluates a remote patient monitoring device's impact on utilization and spending. Methods: A large insurer launched a pilot program involving 2,880 households, representing 6,731 members in three states. Administrative claims data compared participant households to a matched group lacking necessary contact information for participation. Results: Participants had a 0.19 per member (p = 0.03) increase in telehealth visits and a 0.19 per member (p = 0.08) decrease in outpatient in-person visits relative to nonparticipants during the post 6-month period. No significant differences were observed in total outpatient and emergency department visits or total spending. Subgroup analyses revealed a significant reduction in telehealth visits followed by in-person outpatient visits in households with younger children (-9.1%; p < 0.05). Conclusion: This evaluation suggests that remote devices may boost telehealth utilization without increasing costs.

Health related social needs and whole person health: Relationship between unmet social needs, health outcomes, and healthcare spending among commercially insured adults.

Commercially-insured adults comprise a majority of health plan members but are least likely to be surveyed about their social needs. Little is known, consequently, about health-related social needs (HRSNs) in this population. The primary aim of this study was to assess the prevalence of HRSNs and health among commercially-insured adults and estimate their relationship with health outcomes and spending. This cross-sectional study used survey data from a representative sample of Elevance Health commercially insured members residing in Georgia and Indiana (U.S.) Adult members reported on HSRNs across nine different domains. Survey data were linked to medical claims data, and regression models were used to estimate the relationship between HRSNs and self-reported health, emergency department visits, three major health outcomes, and healthcare spending (medical and pharmaceutical). Of 1,160 commercially insured adults, 76 % indicated ≥ 1 HRSN, and 29 % reported > 3 HRSNs, (i.e., "high" HRSN). Each HRSN was associated with 2.2 (95 % CI, 1.84-2.55) additional unhealthy days per month, 3.0 percent (95 % CI 1.36 - 4.57) higher prevalence of anxiety/depression, 2.2 percent (95 % CI 0.88 - 3.50) higher prevalence of hypertension, 3.9 more ED visits per 1,000 member-months (95 % CI, 0.29-7.42), and $1,418 higher total healthcare spending (95 % CI, $614.67-$2,220.39) over a 12-month period. The widespread prevalence of HRSNs among commercially insured adults demonstrates the importance of screening all health plan members for HRSNs-not just Medicare and Medicaid members. Commercially insured members who experience high HRSN are at significantly higher risk for worse health, even after controlling for income and demographic characteristics.

Impact of COVID-19 on Behavioral Health Services Use Among Medicaid Enrollees with Chronic Behavioral Needs by Race and Ethnicity.

The COVID-19 pandemic may widen the disparities in access to behavioral health (BH) services among groups that have been historically marginalized. However, the rapid expansion of telehealth presents an opportunity to reduce these disparities. The objective was to assess the impact of COVID-19 on BH visits, including in-person and telehealth, and BH treatments by different race and ethnicity groups. This was a retrospective, observational study using administrative claim data. Two cohorts were created: a before-COVID-19 group and a during-COVID-19 group. A difference-in-differences analysis was conducted to assess the access to BH-related visits between the 2 groups by different race and ethnicity groups. The study sample included 90,268 patients aged 18 to 64 years with repeated BH diagnoses in baseline periods and continuous medical and pharmacy enrollment. During the pandemic, BH telehealth visits surged, whereas the overall utilization of BH services, mental health medication, and counseling declined among all racial groups as the BH telehealth increase did not fully compensate for the reduction of in-person visits. Latino patients had a higher likelihood of using BH telehealth visits than White patients. However, Black patients had a lower likelihood of using substance use disorder (SUD) treatment than their White counterparts. Our results also suggested that care continuation and pre-established care-seeking behaviors are associated with increasing BH visits and treatments. As policy makers and payers are expanding offerings of telehealth visits, it is imperative to do so through a health equity lens and center the needs of groups that have been economically and socially marginalized to advance equitable adoption of telehealth.

Social determinants of health and high-cost utilization among commercially insured population.

OBJECTIVES: To assess the impact of adding neighborhood social determinants of health (SDOH) data to demographic and clinical characteristics for predicting high-cost utilizers and to examine variations across age groups. STUDY DESIGN: Using US Census data and 2017-2018 commercial claims from a large national insurer, we estimated association between neighborhood-level SDOH and the probability of being a high-cost utilizer. METHODS: Observational study using administrative claims from a national insurer and US Census data. Data included a 50% random sample of commercially insured individuals who were younger than 89 years and had 1 year of continuous eligibility in 2017 and at least 30 days in 2018. Probit models assessed impact of SDOH and neighborhood conditions on predicting cost status. RESULTS: SDOH did not improve predictive power of evaluated models. However, disadvantaged neighborhood residence was still associated with being a high-cost utilizer. Adults 65 years and older in disadvantaged neighborhoods had increased likelihood of high-cost utilization. Children and younger adults in disadvantaged neighborhoods had lower risk of becoming high-cost utilizers. CONCLUSIONS: Policy makers and industry stakeholders should be aware of the mechanisms behind the relationship between neighborhood social conditions and health outcomes and how the relationship differs across age groups.

Observational Analysis of a Generalized, Health Plan-led Community Health Worker Intervention in Medicaid.

INTRODUCTION/OBJECTIVES: In 2018, a Medicaid managed care plan launched a new community health worker (CHW) initiative in several counties within a state, designed to improve the health and quality of life of members who could benefit from additional services. The CHW program involved telephonic and face-to-face visits from CHWs who provided support, empowerment, and education to members, while identifying and addressing health and social issues. The primary objective of this study was to evaluate the impact of a generalized (not disease-specific), health plan-led CHW program on overall healthcare use and spending. METHODS: This retrospective cohort study used data from adult members who received the CHW intervention (N = 538 participants) compared to those who were identified for participation but were unable to be reached (N = 435 nonparticipants). Outcomes measures included healthcare utilization, including scheduled and emergency inpatient admissions, emergency department (ED) visits, and outpatient visits; and healthcare spending. The follow-up period for all outcome measures was 6 months. Using generalized linear models, 6-month change scores were regressed on baseline characteristics to adjust for between-group differences (eg, age, sex, comorbidities) and an indicator for group. RESULTS: Program participants experienced a greater increase in outpatient evaluation and management visits (0.09 per member per month [PMPM]) than the comparison group during the first 6 months of the program. This greater increase was observed across in-person (0.07 PMPM), telehealth (0.03 PMPM), and primary care (0.06 PMPM) visits. There was no observed difference in inpatient admissions, ED utilization or allowed medical spending and pharmacy spending. CONCLUSIONS: A health plan-led CHW program successfully increased multiple forms of outpatient utilization in a historically disadvantaged population of patients. Health plans may be particularly well positioned to finance, sustain, and scale programs that address social drivers of health.

The Association Between Mammography Screening Frequency and Breast Cancer Treatment and Outcomes: A Retrospective Cohort Study.

OBJECTIVE: Guidelines for optimal frequency of screening mammography vary by professional society. Sparse evidence exists on the association between screening frequency and breast cancer treatment options. The main objective was to examine differences in cancer treatment rendered for U.S. women with different numbers of screenings prior to breast cancer diagnosis. Cancer stage at diagnosis and health care cost were assessed in secondary analyses. METHODS: This IRB-exempt retrospective study used administrative claims data to identify women aged 44 or older with various numbers of mammographic screenings ≥11 months apart, during the four years prior to incident breast cancer diagnosis from January 2010 to December 2018. Outcomes were assessed over the six months following diagnosis. Generalized linear regression models were used to compare women with differing numbers of mammograms, adjusting for patient characteristics. RESULTS: Claims data review identified 25 492 women who met inclusion criteria. There was a stepwise improvement in each of these screening categories such that women with four screenings, compared to women with only one screening, experienced higher rates of lumpectomy (70% vs 55%) and radiation therapy (48% vs 36%), lower rates of mastectomy (27% vs 34%) and chemotherapy (28% vs 36%), less stage 3 or 4 cancer at diagnosis (15% vs 29%), and lower health care costs within six months postdiagnosis (P < 0.001). Results were similar in a subgroup limited to women aged 44 to 49 at diagnosis. CONCLUSION: Potential benefits of more frequent screening include less aggressive treatment and lower health care costs among women who develop breast cancer.

Provider Charges And State Surprise Billing Laws: Evidence From New York And California.

Surprise billing laws that allow dispute arbitration relying on provider charges may incentivize out-of-network providers to increase their charges to increase upcoming or future out-of-network payments. Although the federal No Surprises Act forbids arbitrators from considering charges during payment disputes over surprise bills covered by the act, states with existing laws can continue to use the specified state laws, which may allow the consideration of charges. This analysis examined provider charges in two such states, using claims data to compare trends in billed charges for out-of-network care during surprise bill scenarios involving nonemergency inpatient hospitalizations. The analysis considered New York, where state law uses arbitration tied to charges; California, where state law uses a payment standard rather than charges; and a comparison group of states without a law regarding surprise billing. We estimated that provider out-of-network charges for the nonemergency out-of-network bills we studied increased by $1,157 (24 percent) in New York after the passage of New York's surprise billing law and decreased by $752 (25 percent) in California compared to states without surprise billing laws. Assistant surgeons and surgical assistants had a large increase in charges in New York from before to after the law's passage, which may have driven the overall increase in charges.

The Impact of the COVID-19 Pandemic on Health Care Utilization Among Insured Individuals With Common Chronic Conditions.

OBJECTIVE: The COVID pandemic has had a significant impact on the US health care system. Our primary objective was to understand the impact of the COVID pandemic on non-COVID-related health care utilization among insured individuals with chronic conditions. Our secondary objective was to examine the differential impact by individual characteristics. MAIN DATA SOURCE: Medical and pharmacy claims data for individuals enrolled in a large insurer across the United States. RESEARCH DESIGN: A retrospective and repeated cross-sectional study. Overall and condition-specific health care utilization and cost metrics in (1) March 1 to June 15 and (2) June 16 to September 30, 2020 were compared with the same months during 2016-2019. SUBJECTS: Members of all ages with a diagnosis of diabetes, cardiovascular disease, or chronic kidney disease with commercial or Medicare Advantage insurance. RESULTS: Most non-COVID-related health care utilization decreased drastically on March 1 to June 15, 2020 [odds ratio (OR) range across condition-specific tests: 0.55-0.69; incidence rate ratio (IRR) range for hospitalization/emergency department (ED) visit/outpatient visit: 0.65-0.77] but returned to closer to pre-COVID levels by June 16 to September 30, 2020 [OR range across condition-specific tests: 0.93-1.08; IRR range for hospitalization/ED visit/outpatient visit: 0.77-0.97]. Our study found an enormous increase in telehealth use on March 1 to June 15, 2020 (90-170 times prepandemic levels). A differential impact was observed by age, sex, region of residence, and insurance type. IMPLICATIONS: Further investigation is needed to assess the impact of these changes in health care utilization on long-term health outcomes.

Cost and Utilization Impacts of a Medicaid Managed Care Organization's Behavioral Health Wraparound Program.

Wraparound programs that provide comprehensive evidence-based outpatient treatment, transportation, social services, and housing supports have shown promise for improving clinical behavioral health-related outcomes to reduce the need for institutionalized care; however, the majority of evidence is based on wraparound programs for children. This study examined the impact of a wraparound program for adult Medicaid managed care organization members with serious mental health or substance use disorders on health care costs and utilization. This retrospective observational study used 2013-2018 claims data collected from a large Medicaid managed care organization operating in multiple states. We used an intention-to-treat difference-in-difference study design to examine the association of the wraparound with costs and utilization. Adult Medicaid members with an emergency department (ED) or inpatient visit for a behavioral health condition (index visit) were eligible for the study. Outcomes included all-cause and behavioral health-related costs and utilization during follow-up after the index visit's admission date. Outcomes were calculated overall, as well as separately by inpatient, ED, and outpatient/wraparound settings. We found that during the first post-admission month, the wraparound program was associated with 27.6 percentage points (PP) and 27.2 PP reductions in the number of behavioral health-related inpatient nights and costs, respectively. However, during subsequent months (median follow-up ranging from 7 to 10 months) there were no associations with per-member-per-month total all-cause or behavioral health-related costs. Nonetheless, the wraparound program was associated with 12.3 PP reduction in all-cause cost during the entire study period among a subset of members who were high cost at the baseline. Reduced hospital utilization and costs during the first month of wraparound services were fully counteracted by outpatient, housing, and other wraparound services costs during the following months. This indicates the importance of proper payment arrangements with value-based contracting or performance targets with wraparound services providers to align the objective of reducing inpatient use. Future wraparound programs may consider a more focused recruitment from high-cost members with complex care needs. However, our estimates were conservative given that it's from a single Medicaid managed care organization's perspective and some benefit from investing in addressing social needs may be realized in longer term (beyond our study period). States' Medicaid programs may consider the longer-term cost and broader, societal benefit of wraparound investment.

Neighborhood-level Social Determinants of Health Improve Prediction of Preventable Hospitalization and Emergency Department Visits Beyond Claims History.

This study was conducted to assess if neighborhood-level social determinants of health improve model performance of predicting preventable hospitalization. Using medical and pharmacy claims and neighborhood-level social determinants and the split sample method (67% training with balanced sample and 33% validation), the authors developed prospective modeling for preventable hospital use, defined as hospitalization for ambulatory care sensitive conditions (Agency for Healthcare Research and Quality Prevention Quality Indicators 90 and 92) and preventable emergency department (ED) use (based on Billing's algorithm). Performance of age-gender only or age-gender with administrative claims models were compared to models with the addition of social determinants. Adding social determinants to age-gender only models and claim history models improves model performance as measured by Brier score, C statistics, and area under the precision-recall curve for preventable ED use measures while it leads to similar performance for predicting preventable hospital use compared to models without social determinants. Adding neighborhood-level social determinants improved prediction for preventable ED use in the absence of individual-level social determinants, regardless of the availability of full administrative claims history.

Association of Utilization Management Policy With Uptake of Hypofractionated Radiotherapy Among Patients With Early-Stage Breast Cancer.

Importance: Breast cancer accounts for the largest portion of cancer-related spending in the United States. Although hypofractionated radiotherapy after breast-conserving surgery is a cost-effective and convenient treatment strategy for patients with early-stage breast cancer, less than 40% of eligible women received hypofractionated radiotherapy in 2013. Objective: To assess the association of a large commercial payer's utilization management policy with the use of hypofractionated radiotherapy among women with early-stage breast cancer and its associated cost. Design, Setting, and Participants: A retrospective, adjusted difference-in-differences economic analysis was conducted using administrative claims data from January 1, 2012, to June 1, 2018, of women 18 years or older with early-stage breast cancer who were eligible for hypofractionated radiotherapy according to 2011 guidelines from the American Society for Radiation Oncology and were continuously enrolled in 14 geographically diverse commercial health plans covering 6.9% of US adult women. Women who received mastectomy, brachytherapy, or less than 11 or more than 40 external beam fractions of radiotherapy were excluded. A utilization management policy was used to encourage the use of hypofractionated radiotherapy among women in fully insured and Medicare Advantage (fully insured) plans. Under the new policy, claims for extended-course radiotherapy were not reimbursed for fully insured women who were eligible for hypofractionated radiotherapy. This policy did not apply to women in self-insured or Medicare supplemental insurance (self-insured) plans, allowing these groups to serve as a comparison group. Main Outcomes and Measures: The primary outcome was use of hypofractionated radiotherapy, and the secondary outcome was the cost of this type of radiotherapy. Results: Of 10 540 eligible women, 3619 (34.3%) were in fully insured plans and thus subject to the policy. There were no meaningful differences between the fully insured and self-insured groups in mean (SD) age at the start of radiotherapy (63.8 [8.6] vs 65.0 [8.9] years), mean (SD) Charlson Comorbidity Index score (3.0 [1.5] vs 3.2 [1.6]), or practice setting (outpatient hospital setting, 2982 of 3619 [82.4%] vs 5600 of 6921 [80.9%]). The policy was associated with an increase in use of hypofractionated radiotherapy among fully insured patients subject to the policy (adjusted percentage point difference-in-difference, 4.2%; 95% CI, 0.0%-8.4%; P = .05) and a nonsignificant decrease in radiotherapy-associated expenditures (-$2275 relative to self-insured patients; P = .09). Spillover analyses revealed a significantly higher uptake of hypofractionated radiotherapy among self-insured patients who were indirectly exposed to the policy (adjusted percentage point difference-in-difference, 8.5%; 95% CI, 3.6%-13.5%; P < .001) compared with those who were not exposed. Conclusions and Relevance: This study suggests that a payer's utilization management policy was associated with direct and spillover increases in the use of hypofractionated radiotherapy, even after accounting for a long-term secular trend in the uptake of hypofractionated radiotherapy in the control groups. Utilization management may promote evidence-based cancer care.

Multimorbidity and Decision-Making Preferences Among Older Adults.

PURPOSE: Understanding individuals' preferences for participating in health care decisions is foundational to delivering person-centered care. We aimed to (1) explore preferences for health care decision making among older adults, and (2) identify multimorbidity profiles associated with preferring less active, ie, passive, participation among older US adults. METHOD: Ours was a cross-sectional, nationally representative study of 2,017 National Health and Aging Trends Study respondents. Passive decision-making preference was defined as preferring to leave decisions to physicians. Multimorbidity profiles, based on 13 prevalent chronic conditions, were examined as (1) presence of 2 or more conditions, (2) a simple conditions count, and (3) a condition clusters count. Multiple logistic regression was used with adjustment for age, sex, education, English proficiency, and mobility limitation. RESULTS: Most older adults preferred to participate actively in making health care decisions. Older adults with 4 or more conditions, however, and those with multiple condition clusters are relatively less likely to prefer active decision making. CONCLUSIONS: Primary care physicians should initiate a shared decision-making process with older adults with 4 or more conditions or multiple condition clusters. Physicians should anticipate variation in decision-making preferences among older adults and adapt a decision-making process that suits individuals' preferences for participation to ensure person-centered care delivery.

Comparing Population-based Risk-stratification Model Performance Using Demographic, Diagnosis and Medication Data Extracted From Outpatient Electronic Health Records Versus Administrative Claims.

BACKGROUND: There is an increasing demand for electronic health record (EHR)-based risk stratification and predictive modeling tools at the population level. This trend is partly due to increased value-based payment policies and the increasing availability of EHRs at the provider level. Risk stratification models, however, have been traditionally derived from claims or encounter systems. This study evaluates the challenges and opportunities of using EHR data instead of or in addition to administrative claims for risk stratification. METHODS: This study used the structured EHR records and administrative claims of 85,581 patients receiving outpatient care at a large integrated provider system. Common data elements for risk stratification (ie, age, sex, diagnosis, and medication) were extracted from outpatient EHR records and administrative claims. The performance of a validated risk-stratification model was assessed using data extracted from claims alone, EHR alone, and claims and EHR combined. RESULTS: EHR-derived metrics overlapped considerably with administrative claims (eg, number of chronic conditions). The accuracy of the model, when using EHR data alone, was acceptable with an area under the curve of ∼0.81 for hospitalization and ∼0.85 for identifying top 1% utilizers using the concurrent model. However, when using EHR data alone, the predictive model explained a lower amount of variation in utilization-based outcomes compared with administrative claims. DISCUSSION: The results show a promising performance of models predicting cost and hospitalization using outpatient EHR's diagnosis and medication data. More research is needed to evaluate the benefits of other EHR data types (eg, lab values and vital signs) for risk stratification.

Opioid use among adolescent patients treated for headache.

PURPOSE: To determine the pervasiveness of opioid prescribing for adolescents with headache and patient and provider characteristics associated with likelihood of opioid prescribing. METHODS: This observational cohort analysis used commercial medical and pharmacy claims between January 1, 2007 and December 31, 2008. Included were adolescents (13-17 years of age) with newly diagnosed headache, ≥2 distinct claims for headache, and ≥12 months health plan eligibility preindex and postindex. Adolescents with a trauma diagnosis at any point were excluded. The primary outcome was current practice patterns, measured by a number of opioid claims, a percentage of patients prescribed opioids, a number of opioid prescriptions per year, a length of opioid therapy, and a frequency of specific comorbidities. A secondary outcome characterized providers and practice settings, comparing patients who received opioids with those who did not. RESULTS AND CONCLUSIONS: Of 8,373 adolescents with headache, 46% (3,859 patients) received an opioid prescription. Nearly half (48%) received one opioid prescription during follow-up; 29% received ≥3 opioid prescriptions. Of those with opioid prescriptions, 25% (977 patients) had a migraine diagnosis at index date. Among adolescents who received opioids, 28% (1,076 adolescents) had an emergency department (ED) visit for headache during follow-up versus 14% (608 adolescents) who did not receive opioids (p < .01). ED visits with a headache diagnosis during follow-up were strongly correlated with opioid use after adjusting for other covariates (odds ratio, 2.02; 95% confidence interval, 1.79-2.29). Despite the treatment guidelines recommending against their use, a large proportion of adolescents with headache were prescribed opioids. ED visits were strongly correlated with opioid prescriptions.