Prescription drug coverage and effective coverage of three chronic conditions of high prevalence in Chile: Hypertension, diabetes and dyslipidemia.

BACKGROUND: Access to medicines is a serious problem globally and in Chile. Despite the creation of coverage policies, part of the population with chronic conditions of high prevalence, still does not have access to the medicines it requires and disease control continues to be low. The objective of the study was to estimate the medication use and effective coverage for diabetes, dyslipidemia and hypertension in Chile, analyzing them according to sociodemographic variables and social determinants of health. METHODS: Cross-sectional analytical study with information from the 2016-2017 National Health Survey (sample = 6,233 people aged 15 years or older, expanded = 14,518,969). Descriptive analyses of medication use and effective coverage for hypertension, diabetes and dyslipidemia were carried out, and multivariate logistic regression models were developed to analyze possible associations with variables of interest. RESULTS: 60% of people with hypertension or diabetes use medications and only 27.7% in dyslipidemia. While 54.2% of those with diabetes have their glycemia controlled, in hypertension and dyslipidemia the effective coverage drops to 33.3% and 6.6%, respectively. There are no differences in use by health system, but there are differences in the control of hypertension and diabetes, favoring beneficiaries of the private subsystem. Effective coverage of dyslipidemia and hypertension also increases in those using medications. The drugs coincide with the established protocols, although beneficiaries of the private sector report greater use of innovative drugs. CONCLUSION: A significant proportion of Chileans with hypertension, diabetes or dyslipidemia still do not use the required medications and do not control their conditions.

Trends in Out-of-Pocket Costs for and Characteristics of Pharmacy-Dispensed Naloxone by Payer Type.

This study examines mean yearly out-of-pocket cost for naloxone dispensed from retail pharmacies by payer between 2018 and 2022 and by prescription characteristics and payer in 2022.

Hospital Prices for Physician-Administered Drugs for Patients with Private Insurance.

BACKGROUND: Hospitals can leverage their position between the ultimate buyers and sellers of drugs to retain a substantial share of insurer pharmaceutical expenditures. METHODS: In this study, we used 2020-2021 national Blue Cross Blue Shield claims data regarding patients in the United States who had drug-infusion visits for oncologic conditions, inflammatory conditions, or blood-cell deficiency disorders. Markups of the reimbursement prices were measured in terms of amounts paid by Blue Cross Blue Shield plans to hospitals and physician practices relative to the amounts paid by these providers to drug manufacturers. Acquisition-price reductions in hospital payments to drug manufacturers were measured in terms of discounts under the federal 340B Drug Pricing Program. We estimated the percentage of Blue Cross Blue Shield drug spending that was received by drug manufacturers and the percentage retained by provider organizations. RESULTS: The study included 404,443 patients in the United States who had 4,727,189 drug-infusion visits. The median price markup (defined as the ratio of the reimbursement price to the acquisition price) for hospitals eligible for 340B discounts was 3.08 (interquartile range, 1.87 to 6.38). After adjustment for drug, patient, and geographic factors, price markups at hospitals eligible for 340B discounts were 6.59 times (95% confidence interval [CI], 6.02 to 7.16) as high as those in independent physician practices, and price markups at noneligible hospitals were 4.34 times (95% CI, 3.77 to 4.90) as high as those in physician practices. Hospitals eligible for 340B discounts retained 64.3% of insurer drug expenditures, whereas hospitals not eligible for 340B discounts retained 44.8% and independent physician practices retained 19.1%. CONCLUSIONS: This study showed that hospitals imposed large price markups and retained a substantial share of total insurer spending on physician-administered drugs for patients with private insurance. The effects were especially large for hospitals eligible for discounts under the federal 340B Drug Pricing Program on acquisition costs paid to manufacturers. (Funded by Arnold Ventures and the National Institute for Health Care Management.).

Association Between California's State Insurance Gender Nondiscrimination Act and Utilization of Gender-Affirming Surgery.

Importance: Gender-affirming surgery is often beneficial for gender-diverse or -dysphoric patients. Access to gender-affirming surgery is often limited through restrictive legislation and insurance policies. Objective: To investigate the association between California's 2013 implementation of the Insurance Gender Nondiscrimination Act, which prohibits insurers and health plans from limiting benefits based on a patient's sex, gender, gender identity, or gender expression, and utilization of gender-affirming surgery among California residents. Design, Setting, and Participants: Population epidemiology study of transgender and gender-diverse patients undergoing gender-affirming surgery (facial, chest, and genital surgery) between 2005 and 2019. Utilization of gender-affirming surgery in California before and after implementation of the Insurance Gender Nondiscrimination Act in July 2013 was compared with utilization in Washington and Arizona, control states chosen because of geographic similarity and because they expanded Medicaid on the same date as California-January 1, 2014. The date of last follow-up was December 31, 2019. Exposures: California's Insurance Gender Nondiscrimination Act, implemented on July 9, 2013. Main Outcomes and Measures: Receipt of gender-affirming surgery, defined as undergoing at least 1 facial, chest, or genital procedure. Results: A total of 25 252 patients (California: n = 17 934 [71%]; control: n = 7328 [29%]) had a diagnosis of gender dysphoria. Median ages were 34.0 years in California (with or without gender-affirming surgery), 39 years (IQR, 28-49 years) among those undergoing gender-affirming surgery in control states, and 36 years (IQR, 22-56 years) among those not undergoing gender-affirming surgery in control states. Patients underwent at least 1 gender-affirming surgery within the study period in 2918 (11.6%) admissions-2715 (15.1%) in California vs 203 (2.8%) in control states. There was a statistically significant increase in gender-affirming surgery in the third quarter of July 2013 in California vs control states, coinciding with the timing of the Insurance Gender Nondiscrimination Act (P < .001). Implementation of the policy was associated with an absolute 12.1% (95% CI, 10.3%-13.9%; P < .001) increase in the probability of undergoing gender-affirming surgery in California vs control states observed in the subset of insured patients (13.4% [95% CI, 11.5%-15.4%]; P < .001) but not self-pay patients (-22.6% [95% CI, -32.8% to -12.5%]; P < .001). Conclusions and Relevance: Implementation in California of its Insurance Gender Nondiscrimination Act was associated with a significant increase in utilization of gender-affirming surgery in California compared with the control states Washington and Arizona. These data might inform state legislative efforts to craft policies preventing discrimination in health coverage for state residents, including transgender and gender-diverse patients.

Examining US commercial health plans' use of The Institute for Clinical and Economic Review's reports in specialty drug coverage decisions.

BACKGROUND: The Institute for Clinical and Economic Review (ICER) has emerged in a visible role in US health care. However, it is unclear to what extent US commercial health plans use ICER value assessments in their specialty drug coverage decisions. OBJECTIVE: To evaluate the relationship between ICER's reported cost-effectiveness ratios (CERs) and coverage restrictiveness. Also, to examine the frequency with which plans have cited ICER in their coverage policies and to investigate how frequently health plans adjusted their drug coverage criteria in the 12 months after ICER's assessments. METHODS: We analyzed the Tufts Medical Center Specialty Drug Evidence and Coverage Database, which includes specialty drug coverage decisions issued by 17 large US commercial health plans. For ICER-assessed drugs, we recorded ICER's estimated CERs in the form of cost per quality-adjusted life-year (QALY) gained. First, we used multivariate logistic regression to examine the association between ICER's reported CERs and plan coverage restrictiveness, when controlling for other factors that were likely to affect decision-making. Next, we examined how often plans cited ICER's assessments in coverage decisions issued in years 2017-2020. Lastly, we examined whether plans added or removed coverage restrictions (eg, patient subgroup restrictions or step therapy protocols) in the 12 months following ICER's assessment. RESULTS: Plans tended to cover drugs with higher (less favorable) CERs more restrictively than drugs with CERs less than $100,000 per QALY: odds ratio (OR) = 4.48 if $100,000-$175,000 per QALY; OR = 2.00 if $175,000-$500,000 per QALY; and OR = 2.10 if $500,000 or more per QALY (all P < 0.01). Plans cited ICER in 0.8% (5/622) of coverage policies in 2017, 0.6% (5/833) in 2018, 1.7% (19/1,139) in 2019, and 2.4% (33/1,406) in 2020. For drugs with CERs less than $175,000 per QALY, plans adjusted coverage in 37% of cases: added restrictions in 20%, removed restrictions in 15%, and added one restriction but removed another in 2%. For drugs with CERs of $175,000 or more, plans changed coverage criteria in 29% of cases: added restrictions in 21%, removed restrictions in 5%, and added one restriction but removed another in 4%. CONCLUSIONS: We found that when controlling for other factors, health plans' specialty drug coverage decisions were associated with ICER's estimated CERs. Plans infrequently cited ICER value assessments. We did not observe a trend for plans more often narrowing coverage criteria for drugs with CERs $175,000 or more compared with drugs with CERs less than $175,000. DISCLOSURES: This research study was supported by a consortium of funders: Amgen, Genen-tech, Janssen Pharmaceuticals, Otsuka, and GSK.

Association of Family Income With Morbidity and Mortality Among US Lower-Income Children and Adolescents.

Importance: Family income is known to be associated with children's health; the association may be particularly pronounced among lower-income children in the US, who tend to have more limited access to health resources than their higher-income peers. Objective: To investigate the association of family income with claims-based measures of morbidity and mortality among children and adolescents in lower-income families in the US enrolled in Medicaid or the Children's Health Insurance Program. Design, Setting, and Participants: This cross-sectional analysis included 795 000 participants aged 5 to 17 years enrolled in Medicaid (Medicaid Analytic eXtract claims, 2011-2012) living in families with income below 200% of the federal poverty threshold (American Community Survey, 2008-2013). Follow-up ended in December 2021. Exposures: Family income relative to the federal poverty threshold. Main Outcomes and Measures: Record of International Classification of Diseases, Ninth Revision codes for an infection, mental health disorder, injury, asthma, anemia, or substance use disorder and death record within 10 years of observation (Social Security Administration death records through 2021). Results: Among 795 000 individuals in the sample (all statistics weighted: mean [SD] income-to-poverty ratio, 90% [53%]; mean [SD] age, 10.6 [3.9] years; 56% aged 10 to 17 years), 33% had a diagnosed infection, 13% had a mental health disorder, 6% had an injury, 5% had asthma, 2% had anemia, 1% had a substance use disorder, and 0.6% died between 2011 and 2021, with the mean (SD) age at death of 19.8 (4.2) years. For those aged 5 to 9 years, higher family income was associated with lower adjusted prevalence of all outcomes, except mortality: children in families with an additional 100% income relative to the federal poverty threshold had 2.3 (95% CI, 1.8-2.9) percentage points fewer infections, 1.9 (95% CI, 1.5-2.2) percentage points fewer mental health diagnoses, 0.7 (95% CI, 0.5-0.8) percentage points fewer injuries, 0.3 (95% CI, 0.09-0.5) percentage points less asthma, 0.2 (95% CI, 0.08-0.3) percentage points less anemia, and 0.06 (95% CI, 0.03-0.09) percentage points fewer substance use disorder diagnoses. Except for injury and anemia, the associations were more pronounced among those aged 10 to 17 years than those 5 to 9 years (P for interaction <.05). For those aged 10 to 17 years, an additional 100% income relative to the federal poverty threshold was associated with a lower 10-year mortality rate by 0.18 (95% CI, 0.12-0.25) percentage points. Conclusions and Relevance: Among children and adolescents in the US aged 5 to 17 years with family income under 200% of the federal poverty threshold who accessed health care through Medicaid or the Children's Health Insurance Program, higher family income was significantly associated with a lower prevalence of diagnosed infections, mental health disorders, injury, asthma, anemia, and substance use disorders and lower 10-year mortality. Further research is needed to understand whether these associations are causal.

Differences in the diagnosis and treatment of hematologic malignancies attributable to health insurance coverage.

ABSTRACT: Medical care should be equally provided to the public regardless of their financial capability. In the real world, expenditures directly out from the patient sector decide the medical journey, even in a country with national health insurance. The aim of this study was to investigate whether there are differences in the diagnostic and treatment processes in hematologic malignancies based on patient characteristics, such as health insurance status.Through the review of 5614 "CBCs with differential count" results with abnormal cells from 358 patients from January 2010 to June 2017, 238 patients without past medical histories of hematologic malignancies were enrolled. Excluding reactive cases, 206 patients with hematologic malignancy were classified into 8 disease categories: acute leukemia, myelodysplastic syndrome, myeloproliferative neoplasm (MPN), myelodysplastic syndrome/MPN, lymphoid neoplasm, plasma cell neoplasm, r/o hematologic malignancy, and cancer.The patients' age, sex, disease categories and follow-up durations showed associations with the clinical course. The "refusal of treatment" group was the oldest and had a relatively higher percentage of females, whereas those who decided to transfer to a tertiary hospital were younger. The age, clinical course, and follow-up durations were different across health insurance statuses. The medical aid group was the oldest, and the group whose status changed from a medical insurance subscriber to a medical aid beneficiary during treatment was the youngest. The majority of patients who refused treatment or wished to be transferred to a tertiary hospital were medical insurance subscribers. The percentage of patients who were treated in this secondary municipal hospital was higher in the medical-aid beneficiaries group than in the medical insurance group. Follow-up durations were longest in the status change group and shortest in the medical insurance group.Almost all medical aid beneficiaries with hematologic malignancies opted to continue treatment at this secondary/municipal hospitals, indicating that this category of medical institutions provides adequate levels and qualified healthcare services to those patients. The secondary municipal hospital provides qualified healthcare services for medical aid beneficiaries with hematologic malignancies.

Association Between Changes in Postoperative Opioid Utilization and Long-Term Health Care Spending Among Surgical Patients With Chronic Opioid Utilization.

BACKGROUND: There is growing interest in identifying and developing interventions aimed at reducing the risk of increased, long-term opioid use among surgical patients. While understanding how these interventions impact health care spending has important policy implications and may facilitate the widespread adoption of these interventions, the extent to which they may impact health care spending among surgical patients who utilize opioids chronically is unknown. METHODS: This study was a retrospective analysis of administrative health care claims data for privately insured patients. We identified 53,847 patients undergoing 1 of 10 procedures between January 1, 2004, and September 30, 2018 (total knee arthroplasty, total hip arthroplasty, laparoscopic cholecystectomy, open cholecystectomy, laparoscopic appendectomy, open appendectomy, cesarean delivery, functional endoscopic sinus surgery, transurethral resection of the prostate, or simple mastectomy) who had chronic opioid utilization (≥10 prescriptions or ≥120-day supply in the year before surgery). Patients were classified into 3 groups based on differences in opioid utilization, measured in average daily oral morphine milligram equivalents (MMEs), between the first postoperative year and the year before surgery: "stable" (<20% change), "increasing" (≥20% increase), or "decreasing" (≥20% decrease). We then examined the association between these 3 groups and health care spending during the first postoperative year, using a multivariable regression to adjust for observable confounders, such as patient demographics, medical comorbidities, and preoperative health care utilization. RESULTS: The average age of the sample was 62.0 (standard deviation [SD] 13.1) years, and there were 35,715 (66.3%) women. Based on the change in average daily MME between the first postoperative year and the year before surgery, 16,961 (31.5%) patients were classified as "stable," 15,463 (28.7%) were classified as "increasing," and 21,423 (39.8%) patients were classified as "decreasing." After adjusting for potential confounders, "increasing" patients had higher health care spending ($37,437) than "stable" patients ($31,061), a difference that was statistically significant ($6377; 95% confidence interval [CI], $5669-$7084; P < .001), while "decreasing" patients had lower health care spending ($29,990), a difference (-$1070) that was also statistically significant (95% CI, -$1679 to -$462; P = .001). These results were generally consistent across an array of subgroup and sensitivity analyses. CONCLUSIONS: Among patients with chronic opioid utilization before surgery, subsequent increases in opioid utilization during the first postoperative year were associated with increased health care spending during that timeframe, while subsequent decreases in opioid utilization were associated with decreased health care spending.