The extent and growth of prior authorization in Medicare Advantage.

OBJECTIVES: To assess trends in the use of prior authorization requirements among Medicare Advantage (MA) plans. STUDY DESIGN: Descriptive quantitative analysis. METHODS: Data were from the CMS MA benefit and enrollment files for 2009-2019, supplemented with area-level data on demographic and provider market characteristics. For each service category, we calculated the annual share of MA enrollees in plans requiring at least some prior authorization and plotted trends over time. We mapped the county-level share of MA enrollees exposed to prior authorization in 2009 vs 2019. We quantified the association between local share of MA enrollees exposed to prior authorization and characteristics of that county in the same year. Finally, we plotted the share of MA enrollees exposed to prior authorization requirements over time for the 6 largest MA carriers. RESULTS: From 2009 to 2019, the share of MA enrollees in plans requiring prior authorization for any service remained stable. By service category, the share of MA enrollees exposed to prior authorization ranged from 30.7% (physician specialist services) to 72.2% (durable medical equipment) in 2019, with most service categories requiring prior authorization more often over time. Several area-level demographic and provider market characteristics were associated with prior authorization requirements, but these associations weakened over time. The use of prior authorization varied widely across plans. CONCLUSIONS: In 2019, roughly 3 in 4 MA enrollees were in a plan requiring prior authorization. Service-level, area-level, and carrier-level patterns suggest a wide range of approaches to prior authorization requirements.

What happens to rural hospitals during a ransomware attack? Evidence from Medicare data.

PURPOSE: Hospitals are increasingly the target of cybersecurity threats, including ransomware attacks. Little is known about how ransomware attacks affect care at rural hospitals. METHODS: We used data on hospital ransomware attacks from the Tracking Healthcare Ransomware Events and Traits database, linked to American Hospital Association survey data and Medicare fee-for-service (FFS) claims data from 2016 to 2021. We measured Medicare FFS volume and revenue in the inpatient, outpatient, and emergency room setting-at the hospital-week level. We then conducted a stacked event study analysis, comparing hospital volume and revenue at ransomware-attacked and nonattacked hospitals before and after attacks. FINDINGS: Ransomware attacks severely disrupted hospital operations-with comparable effects observed at rural versus urban hospitals. During the first week of the attack, inpatient admissions volume fell by 14.7% at rural hospitals (P = .04) and 16.9% at urban hospitals (P = .01)-recovering to preattack levels within 2-3 weeks. Outpatient visits fell by 35.3% at rural hospitals (P<.01) and 22.0% at urban hospitals (P = .03) during the first week. Emergency room visits fell by 10.0% at rural hospitals (P = .04) and 19.3% at urban hospitals (P = .01). Travel time and distance to the closest nonattacked hospital was 4-7 times greater for rural ransomware-attacked hospitals than for urban ransomware-attacked hospitals. CONCLUSIONS: Ransomware attacks disrupted hospital operations in rural and urban areas. Disruptions of similar magnitudes may be more detrimental in rural areas, given the greater distances patients must travel to receive care and the outsized impact that lost revenue may have on rural hospital finances.

Clinical and healthcare use outcomes after cessation of long term opioid treatment due to prescriber workforce exit: quasi-experimental difference-in-differences study.

OBJECTIVE: To examine the association between prescriber workforce exit, long term opioid treatment discontinuation, and clinical outcomes. DESIGN: Quasi-experimental difference-in-differences study SETTING: 20% sample of US Medicare beneficiaries, 2011-18. PARTICIPANTS: People receiving long term opioid treatment whose prescriber stopped providing office based patient care or exited the workforce, as in the case of retirement or death (n=48 079), and people whose prescriber did not exit the workforce (n=48 079). MAIN OUTCOMES: Discontinuation from long term opioid treatment, drug overdose, mental health crises, admissions to hospital or emergency department visits, and death. Long term opioid treatment was defined as at least 60 days of opioids per quarter for four consecutive quarters, attributed to the plurality opioid prescriber. A difference-in-differences analysis was used to compare individuals who received long term opioid treatment and who had a prescriber leave the workforce to propensity-matched patients on long term opioid treatment who did not lose a prescriber, before and after prescriber exit. RESULTS: Discontinuation of long term opioid treatment increased from 132 to 229 per 10 000 patients who had prescriber exit from the quarter before to the quarter after exit, compared with 97 to 100 for patients who had a continuation of prescriber (adjusted difference 1.22 percentage points, 95% confidence interval 1.02 to 1.42). In the first quarter after provider exit, when discontinuation rates were highest, a transient but significant elevation was noted between the two groups of patients in suicide attempts (adjusted difference 0.05 percentage points (95% confidence interval 0.01 to 0.09)), opioid or alcohol withdrawal (0.14 (0.01 to 0.27)), and admissions to hospital or emergency department visits (0.04 visits (0.01 to 0.06)). These differences receded after one to two quarters. No significant change in rates of overdose was noted. Across all four quarters after prescriber exit, an increase was reported in the rate of mental health crises (0.39 percentage points (95% confidence interval 0.08 to 0.69)) and opioid or alcohol withdrawal (0.31 (0.014 to 0.58)), but no change was seen for drug overdose (-0.12 (-0.41 to 0.18)). CONCLUSIONS: The loss of a prescriber was associated with increased occurrences of discontinuation of long term opioid treatment and transient increases in adverse outcomes, such as suicide attempts, but not other outcomes, such as overdoses. Long term opioid treatment discontinuation may be associated with a temporary period of adverse health impacts after accounting for unobserved confounding.

Artificial intelligence in Medicare: utilization, spending, and access to AI-enabled clinical software.

OBJECTIVES: In 2018, CMS established reimbursement for the first Medicare-covered artificial intelligence (AI)-enabled clinical software: CT fractional flow reserve (FFRCT) to assist in the diagnosis of coronary artery disease. This study quantified Medicare utilization of and spending on FFRCT from 2018 through 2022 and characterized adopting hospitals, clinicians, and patients. STUDY DESIGN: Analysis, using 100% Medicare fee-for-service claims data, of the hospitals, clinicians, and patients who performed or received coronary CT angiography with or without FFRCT. METHODS: We measured annual trends in utilization of and spending on FFRCT among hospitals and clinicians from 2018 through 2022. Characteristics of FFRCT-adopting and nonadopting hospitals and clinicians were compared, as well as the characteristics of patients who received FFRCT vs those who did not. RESULTS: From 2018 to 2022, FFRCT billing volume in Medicare increased more than 11-fold (from 1083 to 12,363 claims). Compared with nonbilling hospitals, FFRCT-billing hospitals were more likely to be larger, part of a health system, nonprofit, and financially profitable. FFRCT-billing clinicians worked in larger group practices and were more likely to be cardiac specialists. FFRCT-receiving patients were more likely to be male and White and less likely to be dually enrolled in Medicaid or receiving disability benefits. CONCLUSIONS: In the initial 5 years of Medicare reimbursement for FFRCT, growth was concentrated among well-resourced hospitals and clinicians. As Medicare begins to reimburse clinicians for the use of AI-enabled clinical software such as FFRCT, it is crucial to monitor the diffusion of these services to ensure equal access.

Characteristics of short-term acute care hospitals that experienced a ransomware attack from 2016 to 2021.

As cybercrime increasingly targets the health care sector, hospitals face the growing threat of ransomware attacks. Ransomware is a type of malicious software that prevents users from accessing their electronic systems-demanding payment to restore access. In response, momentum is gathering to enact policy that will help hospitals strengthen their cybersecurity defenses. However, to design effective policy, it is crucial to understand the characteristics of hospitals associated with the risk of ransomware attack. In this paper, we compare the characteristics of ransomware-attacked and non-attacked short-term acute care hospitals in the United States. Using data from the American Hospital Association's Annual Survey and the Healthcare Cost Report Information System, we found that ransomware-attacked hospitals were larger, had higher net operating revenue, were more likely to be financially profitable, and more likely to provide trauma, emergency, and obstetric care than non-attacked hospitals. Measures of information technology sophistication did not vary between ransomware-attacked and non-attacked hospitals. These results can be used to tailor policy interventions in order to most effectively respond to and prevent cybercrime in health care.

How Should Medicare Pay for Artificial Intelligence?

This Viewpoint examines artificial intelligence­enabled clinical services, existing payment structures, and the economics of artificial intelligence pricing.