Radiologists' 2021 Quality Reporting and Performance in Medicare's Merit-Based Incentive Payment System: Analysis by Practice Type.

This study of national CMS data shows differences in quality reporting and performance of Merit-Based Incentive Payment System (MIPS)-participating radiologists by practice specialty mix. For certain practice types, radiologist-reported quality measures were commonly not radiology measures. The results support a need to expand radiology measures and to better align measure reporting with clinician specialty.

Prevalence of "One-Off Events" in Radiology: Implications for Radiology in Episode-Based Alternative Payment Models.

OBJECTIVE: As reimbursement mechanisms become more value-based, there are questions about the applicability of these mechanisms for nonepisodic care, particularly care provided by nonpatient-facing specialists, for example, radiologists. Accordingly, this study examined the prevalence of nonepisodic care-one-off events-in diagnostic radiology. METHODS: We conducted a multiyear (2015-2019) retrospective study of diagnostic imaging using a large commercial payer database including commercial insurance and Medicare Advantage. Using a 12-month evaluation period starting with the day of the initial imaging study/studies, we categorized imaging studies as one-off events if there were no additional studies (beyond the first day of the evaluation period) for the next 12 months in the same body region. We also evaluated an alternative, more stringent definition of a one-off event: the only imaging study during the 12-month evaluation period. We computed the percentage of one-off events overall and by body region. RESULTS: We found that one-off events comprised 33.2%-45.8% of imaging studies depending on whether one-off events are defined as the only study in the evaluation period or imaging only on the first day of the evaluation period, respectively. This share varied widely by body region: highest for cardiac (80.9%-87.7%) and lower for chest (26.8%-35.2%). By place-of-service, the proportion was lowest for the inpatient (12.9%-29.1%) and long-term care settings (18.6%-30%). DISCUSSION: Given the sizeable share of imaging studies categorized as one-off events, much of radiologists' workload falls outside of the framework of episodic measurement tools and value-based payment models.

Unlocking the Value: Quantifying the Return on Investment of Hospital Artificial Intelligence.

PURPOSE: A comprehensive return on investment (ROI) calculator was developed to evaluate the monetary and nonmonetary benefits of an artificial intelligence (AI)-powered radiology diagnostic imaging platform to inform decision makers interested in adopting AI. METHODS: A calculator was constructed to calculate comparative costs, estimated revenues, and quantify the clinical value of using an AI platform compared with no use of AI in radiology workflows of a US hospital over a 5-year time horizon. Parameters were determined on the basis of expert interviews and a literature review. Scenario and deterministic sensitivity analyses were conducted to evaluate calculator drivers. RESULTS: In the calculator, the introduction of an AI platform into the hospital radiology workflow resulted in labor time reductions and delivery of an ROI of 451% over a 5-year period. The ROI was increased to 791% when radiologist time savings were considered. Time savings for radiologists included more than 15 8-hour working days of waiting time, 78 days in triage time, 10 days in reading time, and 41 days in reporting time. Using the platform also provided revenue benefits for the hospital in bringing in patients for clinically beneficial follow-up scans, hospitalizations, and treatment procedures. Results were sensitive to the time horizon, health center setting, and number of scans performed. Among those, the most influential outcome was the number of additional necessary treatments performed because of AI identification of patients. CONCLUSIONS: The authors demonstrate a substantial 5-year ROI of implementing an AI platform in a stroke management-accredited hospital. The ROI calculator may be useful for decision makers evaluating AI-powered radiology platforms.

Six-minute walk test distance at time of hospital discharge is strongly and independently associated with all-cause mortality following cardiac surgery.

We investigated the impact of distance covered in the six-minute walk test (6mWT) before being discharged from the hospital after cardiac surgery on the risk of all-cause mortality. Our study included 1127 patients who underwent cardiac surgery and then took part in a standardised physiotherapist-supervised inpatient rehabilitation programme during 2007-2017. The percentage of the predicted 6mWT distance, and the lower limit of normal distance was calculated based on individual patients' age, sex, and body mass index. We used Cox regression with adjustment for confounders to determine multivariable-adjusted hazard ratios (HRs) for mortality. Over a median follow-up period of 6.4 (IQR: 3.5-9.2) years, 15% (n = 169) patients died. We observed a strong and independent inverse association between 6mWT distance and mortality, with every 10 m increase in distance associated to a 4% reduction in mortality (HR: 0.96, 95% CI 0.94-0.98, P < 0.001). Those in the top tertile for predicted 6mWT performance had a 49% reduced risk of mortality (HR: 0.51, 95% CI 0.33-0.79) compared to those in the bottom tertile. Patients who met or exceeded the minimum normal 6mWT distance had 36% lower mortality risk (HR: 0.64, 95% CI 0.45-0.92) compared to those who did not meet this benchmark. Subgroup analysis showed that combined CABG and valve surgery patients walked less in the 6mWT compared to those undergoing isolated CABG or valve surgeries, with a significant association between 6mWT and mortality observed in the isolated procedure groups only. In conclusion, the longer the distance covered in the 6mWT before leaving the hospital, the lower the risk of mortality.