Dispute Resolution Outcomes for Surprise Bills in Texas.
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ABSTRACT:
SUBMITTER: Duffy EL
PROVIDER: S-EPMC9214586 | biostudies-literature | 2022 Jun
REPOSITORIES: biostudies-literature
Publications
Dispute Resolution Outcomes for Surprise Bills in Texas.
Duffy Erin L EL Adler Loren L Chartock Benjamin L BL Trish Erin E
JAMA 20220601 23
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Project description: Not available
| S-EPMC7947118 | biostudies-literature
Project description:This cross-sectional study examines surprise bills that are received for childbirths and newborn hospitalizations.
| S-EPMC8796895 | biostudies-literature
Project description:The No Surprises Act banned surprise billing and established a final-offer arbitration system, independent dispute resolution (IDR), to resolve disagreements between health plans and providers. One factor that arbiters must consider in the IDR process is the qualifying payment amount (QPA), the median contracted rate for the same or similar service in the same market as computed by health plans. We analyzed public IDR data from 2023 for the most common disputed professional service: evaluation and management of a moderate to severe emergency medicine visit. Providers won 86% of cases, with mean decisions 2.7 times the QPA. Private equity-backed providers won more often and higher monetary awards than other providers. The mean QPA was 2.4 times Medicare payments. Disputes were dominated by a small group of health plans and providers, so payments may not reflect the overall market for emergency services.
| S-EPMC11523055 | biostudies-literature
Project description:ImportanceThe No Surprises Act (NSA) banned surprise patient balance bills and established a binding arbitration system to resolve payment disputes between insurers and health care providers (eg, clinicians, hospitals, air ambulance organizations) for certain services, including air ambulance transportation. Understanding use and results of this new independent dispute resolution (IDR) system can inform ongoing adjustments to its implementation.ObjectiveTo describe the involved parties and outcomes of air ambulance NSA IDR cases.Design, setting, and participantsThis cross-sectional study assessed cases arbitrated through NSA IDR in 2023 as reported by the Centers for Medicare & Medicaid Services. Participants included air ambulance organizations and commercial insurers. Data were analyzed between August 1 and September 1, 2024.ExposuresFixed-wing and rotary transport disputes arbitrated under the NSA IDR system.Main outcomes and measuresThe activation components of fixed-wing and rotary transport disputes were evaluated with data from 2 distinct public files: (1) disclosed parties and outcomes relative to qualifying payment amounts (QPAs), the insurers' median of contracted rates for similar services in the region among similar health plans; and (2) monetary measures but without parties. The first file describes the insurers and organizations involved, including their ownership status, as well as the prevailing party and the offers and decisions relative to QPA. The second file describes QPAs, offers, and decisions monetarily and these are compared with Medicare's urban allowed amount.ResultsThere were 5678 IDR cases in 2023, comprising disputes for 4935 rotary and 743 fixed-wing transports. Air ambulance organizations offered a mean (SD) of 3.18 (4.20) times QPA, and insurers offered 1.39 (3.89) times QPA. Organizations won 4905 cases (86.4%) at a mean (SD) of 2.95 (4.12) times the QPA. A total of 3478 cases (61.3%) involved organizations owned by private equity investors, and these cases had higher prevailing offers relative to the QPA. Due to data suppression, analysis of financial measures was possible for 2897 of 5983 activation cases (48.4%), among which the mean (SD) QPA offer was $15 561.08 ($9730.97) (3.74 [2.31] times Medicare), and the winning offer was $32 463.70 ($9987.17) (7.82 [2.39] times Medicare).Conclusions and relevanceIn this cross-sectional study of air ambulance payment disputes, air ambulance organizations won most cases, requiring insurers to pay more in these cases. Notably, the NSA does not require changes to patient cost-sharing based on IDR outcomes. Assessment of the financial metrics and outcomes of air ambulance cases was limited due to missing and masked information. Continued monitoring of air ambulance IDR cases is needed to assess the impacts of the NSA.
| S-EPMC11877184 | biostudies-literature
Project description:Mental health services are up to six times more likely than general medical services to be delivered by an out-of-network provider, in part because many psychiatrists do not accept commercial insurance. Provider directories help patients identify in-network providers, although directory information is often not accurate. We conducted a national survey of privately insured patients who received specialty mental health treatment. We found that 44 percent had used a mental health provider directory and that 53 percent of these patients had encountered directory inaccuracies. Those who encountered inaccuracies were more likely (40 percent versus 20 percent) to be treated by an out-of-network provider and four times more likely (16 percent versus 4 percent) to receive a surprise outpatient out-of-network bill (that is, they did not initially know that a provider was out of network). A federal standard for directory accuracy, stronger enforcement of existing laws with insurers liable for directory errors, and additional monitoring by regulators may be needed.
| S-EPMC7497897 | biostudies-literature
Project description: Not available
| S-EPMC11608355 | biostudies-literature
Project description:IntroductionThe resource burden of healthcare disputes and medico-legal claims has been rising. A dispute resolution system operating at the hospital level could ameliorate this disturbing trend.MethodsThis is a retrospective observational study on patient complaints and medico-legal cases received by the dispute resolution unit of an acute tertiary hospital from 2011 to 2015. We described the characteristics and analysed the resolution methodology and outcomes of all closed medico-legal cases.ResultsPatient complaints significantly increased at a compound annual growth rate (CAGR) of 4.2% (p<0.01), while medico-legal cases and ex-gratia payments for case settlements decreased at CAGRs of 4.8% (p<0.05) and 15.9% (p = 0.19), respectively. Out of 237 closed medico-legal cases, 88.6% were resolved without legal action, of which 78.1% were closed without any ex-gratia payments or waivers. Of the 11.4% of medico-legal cases that involved legal action, 66.7% were settled without ex-gratia payments or waivers. The primary resolution modes were the Patient Relations Service (PRS)'s engagement of the complainants and facilitation of written replies. No cases were brought to court. Cases were more likely resolved without legal action when there was engagement by the PRS (p = 0.009). These cases incurred a lower median settlement value than those with legal action.ConclusionOur hospital-based dispute resolution system which addressed patients' core dissatisfactions and providers' perspectives, through a process of early engagement, open disclosure, and fair negotiations, was able to promote claims resolution before legal action was taken. This early dispute resolution strategy contained costs and maintained provider-patient relationships and complements system-level mediation and arbitration to reduce medico-legal litigation.
| S-EPMC9565668 | biostudies-literature
Project description: Not available
| S-EPMC11608374 | biostudies-literature
Project description:The modular organization of brain networks has been widely investigated using graph theoretical approaches. Recently, it has been demonstrated that graph partitioning methods based on the maximization of global fitness functions, like Newman's Modularity, suffer from a resolution limit, as they fail to detect modules that are smaller than a scale determined by the size of the entire network. Here we explore the effects of this limitation on the study of brain connectivity networks. We demonstrate that the resolution limit prevents detection of important details of the brain modular structure, thus hampering the ability to appreciate differences between networks and to assess the topological roles of nodes. We show that Surprise, a recently proposed fitness function based on probability theory, does not suffer from these limitations. Surprise maximization in brain co-activation and functional connectivity resting state networks reveals the presence of a rich structure of heterogeneously distributed modules, and differences in networks' partitions that are undetectable by resolution-limited methods. Moreover, Surprise leads to a more accurate identification of the network's connector hubs, the elements that integrate the brain modules into a cohesive structure.
| S-EPMC4725862 | biostudies-literature