Safety vs price in the generic drug market: metformin.

OBJECTIVES: Generic medications represent 90% of prescriptions in the US market and provide a tremendous financial benefit for patients. Recently, multiple generic drugs have been recalled due to the presence of carcinogens, predominantly N-nitrosodimethylamine (NDMA), including an extensive recall of extended-release (ER) metformin products in 2020. STUDY DESIGN: Primary pharmaceutical quality testing and database analysis. METHODS: We tested marketed metformin immediate-release (IR) and ER tablets from a wide sample of generic manufacturers for the presence of carcinogenic impurities NDMA and N,N-dimethylformamide (DMF). We examined the association of level of impurity with drug price and the impact of the 2020 FDA recalls on unit price and prescription fill rate. RESULTS: Postrecall NDMA levels were significantly lower in metformin ER samples (standardized mean difference = -2.0; P = .01); however, we found continued presence of carcinogens above the FDA threshold in 2 of 30 IR samples (6.67%). Overall, the presence of contaminant levels was not significantly associated with price for either IR (NDMA: R2 = 0.142; P = .981; DMF: R2 = 0.382; P = .436) or ER (NDMA: R2 = 0.124; P = .142; DMF: R2 = 0.199; P = .073) samples. Despite recalls, metformin ER prescription fills increased by 8.9% while unit price decreased by 19.61% (P < .05). CONCLUSIONS: Recalls of metformin ER medications were effective in lowering NDMA levels below the FDA threshold; however, some samples of generic metformin still contained carcinogens even after FDA-announced recalls. The absence of any correlation with price indicates that potentially safer products are available on the market for the same price as poorer-quality products.

Place of Death Before and During the COVID-19 Pandemic.

This quality improvement study examines the national and ongoing impact of the COVID-19 pandemic with the place of death among individuals in the US.

AI Alone Will Not Reduce the Administrative Burden of Health Care.

This Viewpoint considers AI's limits in solving the medical billing quagmire and argues that standardizing health insurance claim forms and simplifying billing must occur before AI can shoulder the load.

Time From Authorization by the US Food and Drug Administration to Medicare Coverage for Novel Technologies.

Importance: A wide variety of novel medical diagnostics and devices are determined safe and effective by the US Food and Drug Administration (FDA) each year, but to our knowledge the literature lacks evidence documenting how long it takes to establish new Medicare coverage for these technologies. Objective: To measure time from FDA authorization to at least nominal Medicare coverage for technologies requiring a new reimbursement pathway. Design, Setting, and Participants: In this cross-sectional study, public databases were used to associate each technology to billing codes, determine the effective date of each code and Medicare coverage decisions, and stratify by the maturity of the Medicare coverage. At least nominal coverage was defined as achievement of explicit coverage milestones through a national coverage determination, local coverage determinations by Medicare administrative contractors, or by implicit coverage aligned to a new billing code. Characterization by product type (acute treatment, chronic or ongoing treatment, diagnostic assay, and diagnostic device), manufacturer size, and evidence level were assessed for association with coverage achievement. The study included new product applications authorized by the FDA through the premarket approval pathway, the de novo pathway, or with breakthrough designation in the 510(k) pathway from January 1, 2016, to December 31, 2019. Data analysis took place between May 1, 2022, and December 31, 2022. Main Outcome Measurement: Time from FDA authorization to the first coverage milestone. Results: Among 281 identified technologies in the total sample, 64 (23%) were deemed novel technologies based on the absence of coverage determinations and/or the use of temporary or miscellaneous billing codes. Twenty-eight of 64 technologies (44%) successfully achieved explicit or implicit coverage following FDA authorization. The median time to at least nominal coverage for the analysis cohort was 5.7 years (90% CI, 4.4-NA years). Analysis of time-to-coverage data highlighted company size (log-rank P<.001) and product type (log-rank P = .01) as significant covariates associated with coverage achievement. No association was observed for technologies with level 1 evidence at FDA authorization and subsequent coverage milestone achievement (log-rank P = .40). Conclusions and Relevance: In this cross-sectional study of 64 novel technologies, only 28 (44%) achieved coverage milestones over the study timeline. The several-year period observed to establish at least nominal coverage suggests existing coverage processes may affect timely reimbursement of new technologies.

Engaging Medicare Beneficiaries in Coverage Choices.

This Viewpoint discusses the recently announced monthly Medicare Part B premium hike and the limited role beneficiaries play in decisions about their coverage, and proposes ways to engage Medicare beneficiaries in program decisions.

Maintaining Health Care Innovations After the Pandemic.

This Viewpoint discusses evaluating and perhaps extending the record of successful innovation arising from the COVID-19 pandemic.

Randomized Clinical Trial to Evaluate an Atrial Fibrillation Stroke Prevention Shared Decision-Making Pathway.

Background Oral anticoagulation reduces stroke and disability in atrial fibrillation (AF) but is underused. We evaluated the effects of a novel patient-clinician shared decision-making (SDM) tool in reducing oral anticoagulation patient's decisional conflict as compared with usual care. Methods and Results We designed and evaluated a new digital decision aid in a multicenter, randomized, comparative effectiveness trial, ENHANCE-AF (Engaging Patients to Help Achieve Increased Patient Choice and Engagement for AF Stroke Prevention). The digital AF shared decision-making toolkit was developed using patient-centered design with clear health communication principles (eg, meaningful images, limited text). Available in English and Spanish, the toolkit included the following: (1) a brief animated video; (2) interactive questions with answers; (3) a quiz to check on understanding; (4) a worksheet to be used by the patient during the encounter; and (5) an online guide for clinicians. The study population included English or Spanish speakers with nonvalvular AF and a CHA2DS2-VASc stroke score ≥1 for men or ≥2 for women. Participants were randomized in a 1:1 ratio to either usual care or the shared decision-making toolkit. The primary end point was the validated 16-item Decision Conflict Scale at 1 month. Secondary outcomes included Decision Conflict Scale at 6 months and the 10-item Decision Regret Scale at 1 and 6 months as well as a weighted average of Mann-Whitney U-statistics for both the Decision Conflict Scale and the Decision Regret Scale. A total of 1001 participants were enrolled and followed at 5 different sites in the United States between December 18, 2019, and August 17, 2022. The mean patient age was 69±10 years (40% women, 16.9% Black, 4.5% Hispanic, 3.6% Asian), and 50% of participants had CHA2DS2-VASc scores ≥3 (men) or ≥4 (women). The primary end point at 1 month showed a clinically meaningful reduction in decisional conflict: a 7-point difference in median scores between the 2 arms (16.4 versus 9.4; Mann-Whitney U-statistics=0.550; P=0.007). For the secondary end point of 1-month Decision Regret Scale, the difference in median scores between arms was 5 points in the direction of less decisional regret (P=0.078). The treatment effects lessened over time: at 6 months the difference in medians was 4.7 points for Decision Conflict Scale (P=0.060) and 0 points for Decision Regret Scale (P=0.35). Conclusions Implementation of a novel shared decision-making toolkit (afibguide.com; afibguide.com/clinician) achieved significantly lower decisional conflict compared with usual care in patients with AF. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT04096781.

A data-driven quality-score system for rating drug products and its implications for the health care industry.

The quality of drug products in the United States has been a matter of growing concern. Buyers and payers of pharmaceuticals have limited insight into measures of drug-product quality. Therefore, a quality-score system driven by data collection is proposed to differentiate between the qualities of drug products produced by different manufacturers. The quality scores derived using this proposed system would be based upon public regulatory data and independently-derived chemical data. A workflow for integrating the system into procurement decisions within health care organizations is also suggested. The implementation of such a quality-score system would benefit health care organizations by including the consideration of the quality of products while also considering price as a part of the drug procurement process. Such a system would also benefit the U.S. health care industry by bringing accountability and transparency into the drug supply chain and incentivizing manufacturers to place an increased emphasis on the quality and safety of their drug products.

Are Patient Satisfaction Instruments Harming Both Patients and Physicians?

In this Viewpoint, Richman and Schulman argue that patient satisfaction surveys may not actually reflect clinical performance or assist efforts to improve patient experience and are not useful tools to measure physician performance.

Billing And Insurance-Related Administrative Costs: A Cross-National Analysis.

Billing and insurance-related costs are a significant source of wasteful health care spending in Organization for Economic Cooperation and Development nations, but these administrative burdens vary across national systems. We executed a microlevel accounting of these costs in different national settings at six provider locations in five nations (Australia, Canada, Germany, the Netherlands, and Singapore) that supplements our prior study measuring the costs in the US. We found that billing and insurance-related costs for inpatient bills range from a low of $6 in Canada to a high of $215 in the US for an inpatient surgical bill (purchasing power parity adjusted). We created a taxonomy of billing and insurance-related activities (eligibility, coding, submission, and rework) that was applied to data from the six sites and allows cross-national comparisons. Higher costs in the US and Australia are attributed to high coding costs. Much of the savings achieved in some nations is attributable to assigning tasks to people in lower-skill job categories, although most of the savings are due to more efficient billing and insurance-related processes. Some nations also reduce these costs by offering financial counseling to patients before treatment. Our microlevel approach can identify specific cost drivers and reveal national billing features that reduce coding costs. It illustrates a valuable pathway for future research in understanding and mitigating administrative costs in health care.

Trends and determinants of retail prescription drug costs.

OBJECTIVE: To characterize price trends and variation for US generic and branded drugs at the retail level as they relate to pharmacy acquisition costs and local market factors. DATA SOURCES: Drug pricing data consisting of US pharmacy claims from 2014 to 2019 collected and licensed by GoodRx, an online tool for comparing drug prices. STUDY DESIGN: Time trends of median drug prices and coefficients of variation were measured for generic and branded drugs, including subgroups based on clinical condition (i.e., diabetes and cancer). Pharmacy competition was measured using the Herfindahl-Hirschman Index (HHI) at the zip-code level. Multivariable linear regression analysis assessed the impact of local market-level factors on drug prices and variation. DATA COLLECTION: US drug pricing data consisting of claims filled through a mix of public and private insurance at 58,332 chain and independent pharmacies across 14,421 zip codes in all 50 states. PRINCIPAL FINDINGS: From 2014 to 2019, pharmacy retail markets trended towards greater competition: average HHI by zip code decreased by 15.0% (p < 0.001). Median cash price increased significantly for both generic (6.58%, p < 0.001) and branded (84.10%, p < 0.001) drugs. When normalized to acquisition costs, cash prices for generic drugs rose 22.03% (p < 0.001) while those of branded drugs decreased by 2.31% (p < 0.001). Diabetes drugs showed higher baseline overall markup of cash prices relative to acquisition costs (10.54, Interquartile range (IQR) 3.28-18.43) than cancer drugs (1.88, IQR 1.36-3.08). Neither local pharmacy competition nor median income significantly predicted drug price or variation. CONCLUSION: Measures of generic drug price and price variation are high despite decreased costs earlier in the pharmaceutical supply chain, defying expectations of what would happen in a competitive market. Efforts to bypass the pharmacy benefit model for generic drugs may offer consumers an opportunity for substantial savings.

Exploring Workplace Testing with Real-Time Polymerase Chain Reaction SARS-CoV-2 Testing.

BACKGROUND: Molecular tests (ie, real-time polymerase chain reaction [RT-PCR]) and antigen tests are used to detect SARS-CoV-2. RT-PCR tests are generally considered to be the standard for clinical diagnosis of SARS-CoV-2 due to accuracy and reliability but can take longer to return results than antigen tests. Our aim was to examine if point-of-care (POC) testing for SARS-CoV-2 infection would provide a flexible resource to help achieve workplace safety. We compared test results and time-to-test results between a POC RT-PCR test and a send-out PCR test in a program implemented in summer 2020. RESULTS: POC testing shortened the time to results to 110 minutes in the POC setting from the 754 minutes for send-out tests. The specificity of POC RT-PCR single POC testing was 98.7% compared with send-out RT-PCR testing and was confirmed at 99.8% in a validation analysis. The sensitivity of the POC testing was 100% compared with send-out RT-PCR, although in a validation analysis, sensitivity appeared as 0% because only the 12 positive or indeterminate samples on the first analysis were retested and the majority were false-positives that were correctly ruled out. CONCLUSIONS: POC testing for SARS-CoV-2 with RT-PCR technology is possible at reduced time compared with send-out PCR testing.