What Physicians and Health Organizations Should Know About Mandated Imaging Appropriate Use Criteria.

The Appropriate Use Criteria Program, enacted by the Centers for Medicare & Medicaid Services in response to the Protecting Access to Medicare Act of 2014 (PAMA), aims to reduce inappropriate and unnecessary imaging by mandating use of clinical decision support (CDS) by all providers who order advanced imaging examinations (magnetic resonance imaging; computed tomography; and nuclear medicine studies, including positron emission tomography). Beginning 1 January 2020, documentation of an interaction with a certified CDS system using approved appropriate use criteria will be required on all Medicare claims for advanced imaging in all emergency department patients and outpatients as a prerequisite for payment. The Appropriate Use Criteria Program will initially cover 8 priority clinical areas, including several (such as headache and low back pain) commonly encountered by internal medicine providers. All providers and organizations that order and provide advanced imaging must understand program requirements and their options for compliance strategies. Substantial resources and planning will be needed to comply with PAMA regulations and avoid unintended negative consequences on workflow and payments. However, robust evidence supporting the desired outcome of reducing inappropriate use of advanced imaging is lacking.

Insurance payment for artificial intelligence technology: Methods used by a stroke artificial intelligence system and strategies to qualify for the new technology add-on payment.

The first ever insurance reimbursement for an artificial intelligence (AI) system, which expedites triage of acute stroke, occurred in 2020 when the Centers for Medicare and Medicaid Services (CMS) granted approval for a New Technology Add-on Payment (NTAP). Key aspects of the AI system that led to its approval by the CMS included its unique mechanism of action, use of robotic process automation, and clear linkage of the system's output to clinical outcomes. The specific strategies employed encompass a first-case scenario of proving reimbursable value for improved stroke outcomes using AI. Given the rapid change in utilization of AI technology in stroke care, we describe the economic drivers of stroke AI systems in healthcare, focusing on concepts of reimbursement for value added by AI to the stroke care system. This report reviews (1) the successful approach used by the first NTAP-approved AI system, (2) economic variables in insurance reimbursement for AI, and (3) resultant strategies that may be utilized to facilitate qualification for NTAP reimbursement, which may be adopted by other AI systems used in stroke care.

Impact of provider-led, technology-enabled radiology management program on imaging.

OBJECTIVE: The study objective was to assess the impact of a provider-led, technology-enabled radiology medical management program on high-cost imaging use. METHODS: This study was performed in the ambulatory setting of an integrated healthcare system. After negotiating a risk contract with a major commercial payer, we created a physician-led radiology medical management program to help address potentially inappropriate high-cost imaging use. The radiology medical management program was enabled by a computerized physician order entry system with integrated clinical decision support and accountability tools, including (1) mandatory peer-to-peer consultation with radiologists before order completion when test utility was uncertain on the basis of order requisition; (2) quarterly practice pattern variation reports to providers; and (3) academic detailing for targeted outliers. The primary outcome measure was intensity of high-cost imaging, defined as the number of outpatient computed tomography (CT), magnetic resonance imaging (MRI), and nuclear cardiology studies per 1000 patient-months in the payer's panel. Chi-square test was used to assess trends. RESULTS: In 1.8 million patient-months from January 2004 to December 2009, 50,336 eligible studies were performed (54.1% CT, 40.3% MRI, 5.6% nuclear cardiology). There was a 12.0% sustained reduction in high-cost imaging intensity over the 5-year period (P < .001). The number of CT studies performed decreased from 17.5 per 1000 patient-months to 14.5 (P < .01); nuclear cardiology examinations decreased from 2.4 to 1.4 (P < .01) per 1000 patient-months. The MRI rate remained unchanged at 11 studies per 1000 patient-months. CONCLUSION: A provider-led radiology medical management program enabled through health information technology and accountability tools may produce a significant reduction in high-cost imaging use.

Adoption and meaningful use of computerized physician order entry with an integrated clinical decision support system for radiology: ten-year analysis in an urban teaching hospital.

PURPOSE: The aim of this study was to assess whether an integrated imaging computerized physician order entry (CPOE) system with embedded decision support for imaging can be accepted clinically. METHODS: The study was performed in a health care delivery network with an affiliated academic hospital. After pilot testing and user feedback, a Web-enabled CPOE system with embedded imaging decision support was phased into clinical use between 2000 and 2010 across outpatient, emergency department, and inpatient settings. The primary outcome measure was meaningful use, defined as the proportion of imaging studies performed with orders electronically created (EC) or electronically signed by an authorized provider. The secondary outcome measure was adoption, defined as the proportion of imaging studies that were ordered electronically, irrespective of who entered the order in the CPOE system. Univariate and multivariate regression analyses were performed to estimate trends and the significance of practice settings, examination modality, and body part to outcome measures. Chi-square statistics were used to assess differences across specialties. RESULTS: A total of 4.1 million imaging studies were performed during the study period. From 2000 to 2010, significant increases in meaningful use (for EC studies, from 0.4% to 61.9%; for electronically signed studies, from 0.4% to 92.2%; P < .005) and the adoption of CPOE (from 0.5% to 94.6%, P < .005) were observed. The use of EC studies was greatest in the emergency department and inpatient settings. Meaningful use varied across specialties; surgical subspecialties had the lowest rates of EC studies. CONCLUSIONS: Imaging CPOE with embedded decision support integrated into the IT infrastructure of the health care enterprise and clinicians' workflow can be broadly accepted clinically.

"Hyperscrutiny" of academic-industrial relationships: potential for unintended consequences--a response.

In the current environment, academic-industrial relationships are coming under intense scrutiny from government and other regulatory bodies. Although there clearly have been incidents of abuse in these relationships, academic-industrial collaboration is an engine that drives innovation in the biomedical sciences in this country. The academic radiology community must ensure that the societal benefits of these relationships are not sacrificed via "overregulation."