Payment Innovation in Emergency Care: A Case for Global Clinician Budgets.

The fee-for-service funding model for US emergency department (ED) clinician groups is increasingly fragile. Traditional fee-for-service payment systems offer no financial incentives to improve quality, address population health, or make value-based clinical decisions. Fee-for-service also does not support maintaining ED capacity to handle peak demand periods. In fee-for-service, clinicians rely heavily on cross-subsidization, where high reimbursement from commercial payors offsets low reimbursement from government payors and the uninsured. Although fee-for-service survived decades of steady cuts in government reimbursement rates, it is increasingly strained because of visit volatility and the effects of the No Surprises Act, which is driving down commercial reimbursement. Financial pressures on ED clinician groups and higher hospital boarding and clinical workloads are increasing workforce attrition. Here, we propose an alternative model to address some of these fundamental issues: an all-payer-funded, voluntary global budget for ED clinician services. If designed and implemented effectively, the model could support robust clinician staffing over the long term, ensure stability in clinical workload, and potentially improve equity in payments. The model could also be combined with population health programs (eg, pre-ED and post-ED telehealth, frequent ED use programs, and other innovations), offering significant payer returns and addressing quality and value. A linked program could also change hospital incentives that contribute to boarding. Strategies exist to test and refine ED clinician global budgets through existing government programs in Maryland and potentially through state-level legislation as a precursor to broader adoption.

How artificial intelligence could transform emergency care.

Artificial intelligence (AI) in healthcare is the ability of a computer to perform tasks typically associated with clinical care (e.g. medical decision-making and documentation). AI will soon be integrated into an increasing number of healthcare applications, including elements of emergency department (ED) care. Here, we describe the basics of AI, various categories of its functions (including machine learning and natural language processing) and review emerging and potential future use-cases for emergency care. For example, AI-assisted symptom checkers could help direct patients to the appropriate setting, models could assist in assigning triage levels, and ambient AI systems could document clinical encounters. AI could also help provide focused summaries of charts, summarize encounters for hand-offs, and create discharge instructions with an appropriate language and reading level. Additional use cases include medical decision making for decision rules, real-time models that predict clinical deterioration or sepsis, and efficient extraction of unstructured data for coding, billing, research, and quality initiatives. We discuss the potential transformative benefits of AI, as well as the concerns regarding its use (e.g. privacy, data accuracy, and the potential for changing the doctor-patient relationship).

Describing Variability of Inpatient Consultation Practices: Physician, Patient, and Admission Factors.

Appropriate use of consultation can improve patient outcomes, but inappropriate use may cause harm. Factors affecting the variability of inpatient consultation are poorly understood. We aimed to describe physician-, patient-, and admission-level factors influencing the variability of inpatient consultations on general medicine services. We conducted a retrospective study of patients hospitalized from 2011 to 2016 and enrolled in the University of Chicago Hospitalist Project, which included 6,153 admissions of 4,772 patients under 69 attendings. Consultation use varied widely; a 5.7-fold difference existed between the lowest (mean, 0.613) and highest (mean, 3.47) quartiles of use (P <.01). In mixed-effect Poisson regression, consultations decreased over time, with 45% fewer consultations for admissions in 2015 than in 2011 (P <.01). Patients on nonteaching hospitalist teams received 9% more consultations than did those on teaching services (P =.02). Significant variability exists in inpatient consultation use. Further understanding may help to identify groups at high-risk for underuse/overuse and aid in the development of interventions to improve high-value care.

The Consultation Observed Simulated Clinical Experience: Training, Assessment, and Feedback for Incoming Interns on Requesting Consultations.

PROBLEM: Formal education in requesting consultations is inconsistent in medical education. To address this gap, the authors developed the Consultation Observed Simulated Clinical Experience (COSCE), a simulation-based curriculum for interns using Kessler and colleagues' 5Cs of Consultation model to teach and assess consultation communication skills. APPROACH: In June 2016, 127 interns entering 12 University of Chicago Medicine residency programs participated in the COSCE pilot. The COSCE featured an online training module on the 5Cs and an in-person simulated consultation. Using specialty-specific patient cases, interns requested telephone consultations from faculty, who evaluated their performance using validated checklists. Interns were surveyed on their preparedness to request consultations before and after the module and after the simulation. Subspecialty fellows serving as consultants were surveyed regarding consultation quality before and after the COSCE. OUTCOMES: After completing the online module, 84% of interns (103/122) were prepared to request consultations compared with 52% (63/122) at baseline (P < .01). After the COSCE, 96% (122/127) were prepared to request consultations (P < .01). Neither preparedness nor simulation performance differed by prior experience or training. Over 90% (115/127) indicated they would recommend the COSCE for future interns. More consultants described residents as prepared to request consultations after the COSCE (54%; 21/39) than before (27%; 11/41, P = .01). NEXT STEPS: The COSCE was well received and effective for preparing entering interns with varying experience and training to request consultations. Future work will emphasize consultation communication specific to training environments and evaluate skills via direct observation of clinical performance.

Perforin-like protein PPLP2 permeabilizes the red blood cell membrane during egress of Plasmodium falciparum gametocytes.

Egress of malaria parasites from the host cell requires the concerted rupture of its enveloping membranes. Hence, we investigated the role of the plasmodial perforin-like protein PPLP2 in the egress of Plasmodium falciparum from erythrocytes. PPLP2 is expressed in blood stage schizonts and mature gametocytes. The protein localizes in vesicular structures, which in activated gametocytes discharge PPLP2 in a calcium-dependent manner. PPLP2 comprises a MACPF domain and recombinant PPLP2 has haemolytic activities towards erythrocytes. PPLP2-deficient [PPLP2(-)] merozoites show normal egress dynamics during the erythrocytic replication cycle, but activated PPLP2(-) gametocytes were unable to leave erythrocytes and stayed trapped within these cells. While the parasitophorous vacuole membrane ruptured normally, the activated PPLP2(-) gametocytes were unable to permeabilize the erythrocyte membrane and to release the erythrocyte cytoplasm. In consequence, transmission of PPLP2(-) parasites to the Anopheles vector was reduced. Pore-forming equinatoxin II rescued both PPLP2(-) gametocyte exflagellation and parasite transmission. The pore sealant Tetronic 90R4, on the other hand, caused trapping of activated wild-type gametocytes within the enveloping erythrocytes, thus mimicking the PPLP2(-) loss-of-function phenotype. We propose that the haemolytic activity of PPLP2 is essential for gametocyte egress due to permeabilization of the erythrocyte membrane and depletion of the erythrocyte cytoplasm.

The Igf2/H19 muscle enhancer is an active transcriptional complex.

In eukaryotic cells, gene expression is mediated by enhancer activation of RNA polymerase at distant promoters. Recently, distinctions between enhancers and promoters have been blurred by the discovery that enhancers are associated with RNA polymerase and are sites of RNA synthesis. Here, we present an analysis of the insulin-like growth factor 2/H19 muscle enhancer. This enhancer includes a short conserved core element that is organized into chromatin typical of mammalian enhancers, binds tissue-specific transcription factors and functions on its own in vitro to activate promoter transcription. However, in a chromosomal context, this element is not sufficient to activate distant promoters. Instead, enhancer function also requires transcription in cis of a long non-coding RNA, Nctc1. Thus, the insulin-like growth factor 2/H19 enhancer is an active transcriptional complex whose own transcription is essential to its function.