Collaborative artificial intelligence system for investigation of healthcare claims compliance.

Healthcare fraud, waste and abuse are costly problems that have huge impact on society. Traditional approaches to identify non-compliant claims rely on auditing strategies requiring trained professionals, or on machine learning methods requiring labelled data and possibly lacking interpretability. We present Clais, a collaborative artificial intelligence system for claims analysis. Clais automatically extracts human-interpretable rules from healthcare policy documents (0.72 F1-score), and it enables professionals to edit and validate the extracted rules through an intuitive user interface. Clais executes the rules on claim records to identify non-compliance: on this task Clais significantly outperforms two baseline machine learning models, and its median F1-score is 1.0 (IQR = 0.83 to 1.0) when executing the extracted rules, and 1.0 (IQR = 1.0 to 1.0) when executing the same rules after human curation. Professionals confirm through a user study the usefulness of Clais in making their workflow simpler and more effective.

The glycoimmune checkpoint receptor Siglec-7 interacts with T-cell ligands and regulates T-cell activation.

Siglec-7 (sialic acid-binding immunoglobulin-like lectin 7) is a glycan-binding immune receptor that is emerging as a significant target of interest for cancer immunotherapy. The physiological ligands that bind Siglec-7, however, remain incompletely defined. In this study, we characterized the expression of Siglec-7 ligands on peripheral immune cell subsets and assessed whether Siglec-7 functionally regulates interactions between immune cells. We found that disialyl core 1 O-glycans are the major immune ligands for Siglec-7 and that these ligands are particularly highly expressed on naïve T-cells. Densely glycosylated sialomucins are the primary carriers of these glycans, in particular a glycoform of the cell-surface marker CD43. Biosynthesis of Siglec-7-binding glycans is dynamically controlled on different immune cell subsets through a genetic circuit involving the glycosyltransferase GCNT1. Siglec-7 blockade was found to increase activation of both primary T-cells and antigen-presenting dendritic cells in vitro, indicating that Siglec-7 binds T-cell glycans to regulate intraimmune signaling. Finally, we present evidence that Siglec-7 directly activates signaling pathways in T-cells, suggesting a new biological function for this receptor. These studies conclusively demonstrate the existence of a novel Siglec-7-mediated signaling axis that physiologically regulates T-cell activity. Going forward, our findings have significant implications for the design and implementation of therapies targeting immunoregulatory Siglec receptors.

Comparative analysis of the myoglobin gene in whales and humans reveals evolutionary changes in regulatory elements and expression levels.

Cetacea and other diving mammals have undergone numerous adaptations to their aquatic environment, among them high levels of the oxygen-carrying intracellular hemoprotein myoglobin in skeletal muscles. Hypotheses regarding the mechanisms leading to these high myoglobin levels often invoke the induction of gene expression by exercise, hypoxia, and other physiological gene regulatory pathways. Here we explore an alternative hypothesis: that cetacean myoglobin genes have evolved high levels of transcription driven by the intrinsic developmental mechanisms that drive muscle cell differentiation. We have used luciferase assays in differentiated C2C12 cells to test this hypothesis. Contrary to our hypothesis, we find that the myoglobin gene from the minke whale, Balaenoptera acutorostrata, shows a low level of expression, only about 8% that of humans. This low expression level is broadly shared among cetaceans and artiodactylans. Previous work on regulation of the human gene has identified a core muscle-specific enhancer comprised of two regions, the "AT element" and a C-rich sequence 5' of the AT element termed the "CCAC-box". Analysis of the minke whale gene supports the importance of the AT element, but the minke whale CCAC-box ortholog has little effect. Instead, critical positive input has been identified in a G-rich region 3' of the AT element. Also, a conserved E-box in exon 1 positively affects expression, despite having been assigned a repressive role in the human gene. Last, a novel region 5' of the core enhancer has been identified, which we hypothesize may function as a boundary element. These results illustrate regulatory flexibility during evolution. We discuss the possibility that low transcription levels are actually beneficial, and that evolution of the myoglobin protein toward enhanced stability is a critical factor in the accumulation of high myoglobin levels in adult cetacean muscle tissue.

The consequences of face-threatening feedback on innovators' psychological safety, affect, and willingness to engage in future innovation projects.

While there is substantial research on how firms successfully end project initiatives deemed unsuitable for them very few studies focus on how leaders and managers communicate termination messages. Drawing from politeness theory and organizational support theory we explore the impact termination messages varying in face sensitivity have on innovators' feelings of psychological safety, affect, and their willingness to continue to innovate We find that face-threatening messages significantly and negatively affect innovators' psychological safety, affect, and willingness to further innovate. The negative effects are amplified when innovators feel high commitment to their projects.

Identifying Genetic Regulators of Protein-Glycan Interactions with Genome-Wide CRISPR Screening.

Glycans are carbohydrate molecules appended to proteins and lipids on the surface of all living cells. Glycans play key roles in a wide array of biological processes, and structural changes in cell-surface glycosylation patterns have been connected to pathogenesis of several diseases. In particular, cancer cells frequently upregulate expression of glycans that bind to inhibitory receptors (lectins) on immune cells. These glycosylated antigens systematically inhibit immune activity and protect cancer cells from immune surveillance. Understanding how cancer cells generate these glycan ligands can thus lead to identification of novel druggable targets for therapeutic intervention. However, glycan ligand biosynthesis is subject to extremely complex genetic regulation, making it difficult to identify the key genes involved in production of immune-regulatory glycan antigens. In a recent publication, we described a CRISPR/Cas9 screening approach to identify genes that drive synthesis of ligands for glycan-binding immune receptors. Here, we outline a detailed, step-by-step protocol for completing this type of genome-wide screen. Our protocol produces a genome-wide atlas of all genes whose expression is required for cell-surface binding of a recombinant immune lectin. This dataset can be used both to identify novel ligands for immune lectins and annotate regulatory genes that drive changes in cancer-associated glycosylation. Our protocol serves as a general resource for researchers interested in the detailed study of cancer glyco-immunology. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Generation of a genome-wide CRISPR library using lentiviral transduction Support Protocol: Generation of dCas9KRAB-expressing K-562 cells Basic Protocol 2: Staining of genome-wide CRISPR libraries with Siglec-Fc reagents and fluorescence-activated cell sorting Basic Protocol 3: Library amplification and sequencing Basic Protocol 4: Data analysis and hit identification.

Learning Insurance Benefit Rules from Policy Texts with Small Labeled Data.

To protect vital health program funds from being paid out on services that are wasteful and inconsistent with medical practices, government healthcare insurance programs need to validate the integrity of claims submitted by providers for reimbursement. However, due the complexity of healthcare billing policies and the lack of coded rules, maintaining "integrity" is a labor-intensive task, often narrow-scope and expensive. We propose an approach that combines deep learning and an ontology to support the extraction of actionable knowledge on benefit rules from regulatory healthcare policy text. We demonstrate its feasibility even in the presence of small ground truth labeled data provided by policy investigators. Leveraging deep learning and rich ontological information enables the system to learn from human corrections and capture better benefit rules from policy text, beyond just using a deterministic approach based on pre-defined textual and semantic pattterns.

Development of PARcific Approach: Participatory Action Research Methodology for Collectivist Health Research.

This article explores the evolution of a novel approach designed to advance qualitative methods in cross-cultural health research. This methodology was developed by synthesising several research methods and involved in-depth stakeholder consultation with participants of a Pacific-based nursing and midwifery health leadership program. Many of these participants played a crucial role in creating, exploring and evaluating several research methods and implementing and evaluating this co-designed research methodology. Starting with a Participatory Action Research framework, the research methodology evolved as it was informed by the local Pacific methodologies (in particular Talanoa and Kakala frameworks), where researchers, co-researchers and participants alike, working from within their own collectivist/individualist paradigms, negotiated cultural differences. Finally, a methodological framework of 'best practice' for future health research methods was developed for use with capacity building research. The new methodology could provide a foundation for future co-designed cross-cultural research in collectivist cultures.

Comprehensive compartmental model and calibration algorithm for the study of clinical implications of the population-level spread of COVID-19: a study protocol.

INTRODUCTION: The complex dynamics of the coronavirus disease 2019 (COVID-19) pandemic has made obtaining reliable long-term forecasts of the disease progression difficult. Simple mechanistic models with deterministic parameters are useful for short-term predictions but have ultimately been unsuccessful in extrapolating the trajectory of the pandemic because of unmodelled dynamics and the unrealistic level of certainty that is assumed in the predictions. METHODS AND ANALYSIS: We propose a 22-compartment epidemiological model that includes compartments not previously considered concurrently, to account for the effects of vaccination, asymptomatic individuals, inadequate access to hospital care, post-acute COVID-19 and recovery with long-term health complications. Additionally, new connections between compartments introduce new dynamics to the system and provide a framework to study the sensitivity of model outputs to several concurrent effects, including temporary immunity, vaccination rate and vaccine effectiveness. Subject to data availability for a given region, we discuss a means by which population demographics (age, comorbidity, socioeconomic status, sex and geographical location) and clinically relevant information (different variants, different vaccines) can be incorporated within the 22-compartment framework. Considering a probabilistic interpretation of the parameters allows the model's predictions to reflect the current state of uncertainty about the model parameters and model states. We propose the use of a sparse Bayesian learning algorithm for parameter calibration and model selection. This methodology considers a combination of prescribed parameter prior distributions for parameters that are known to be essential to the modelled dynamics and automatic relevance determination priors for parameters whose relevance is questionable. This is useful as it helps prevent overfitting the available epidemiological data when calibrating the parameters of the proposed model. Population-level administrative health data will serve as partial observations of the model states. ETHICS AND DISSEMINATION: Approved by Carleton University's Research Ethics Board-B (clearance ID: 114596). Results will be made available through future publication.

Targeting hypersialylation in multiple myeloma represents a novel approach to enhance NK cell-mediated tumor responses.

Abnormal glycosylation is a hallmark of cancer, and the hypersialylated tumor cell surface facilitates abnormal cell trafficking and drug resistance in several malignancies, including multiple myeloma (MM). Furthermore, hypersialylation has also been implicated in facilitating evasion of natural killer (NK) cell-mediated immunosurveillance but not in MM to date. In this study, we explore the role of hypersialylation in promoting escape from NK cells. We document strong expression of sialic acid-derived ligands for Siglec-7 (Siglec-7L) on primary MM cells and MM cell lines, highlighting the possibility of Siglec-7/Siglec-7L interactions in the tumor microenvironment. Interactomics experiments in MM cell lysates revealed PSGL-1 as the predominant Siglec-7L in MM. We show that desialylation, using both a sialidase and sialyltransferase inhibitor (SIA), strongly enhances NK cell-mediated cytotoxicity against MM cells. Furthermore, MM cell desialylation results in increased detection of CD38, a well-validated target in MM. Desialylation enhanced NK cell cytotoxicity against CD38+ MM cells after treatment with the anti-CD38 monoclonal antibody daratumumab. Additionally, we show that MM cells with low CD38 expression can be treated with all trans-retinoic acid (ATRA), SIA and daratumumab to elicit a potent NK cell cytotoxic response. Finally, we demonstrate that Siglec-7KO potentiates NK cell cytotoxicity against Siglec-7L+ MM cells. Taken together, our work shows that desialylation of MM cells is a promising novel approach to enhance NK cell efficacy against MM, which can be combined with frontline therapies to elicit a potent anti-MM response.

Antibiotic Prophylaxis Prescribing Practice in Head and Neck Tumor Resection and Free Flap Reconstruction.

BACKGROUND: Adherence to guidelines for antibiotic prophylaxis is often poor and is an important target for antimicrobial stewardship programs. Prescribing audits that suggested poor adherence to guidelines in a plastic surgery department led to a targeted education program to bring antibiotic prescriptions in line with hospital guidelines. We reviewed whether this intervention was associated with changed perioperative prescribing and altered surgical outcomes, including the rate of surgical site infections, specifically looking at clean-contaminated head and neck tumor resections with free flap reconstruction. METHODS: A retrospective cohort study was performed on 325 patients who underwent clean-contaminated head and neck tumor resection and free flap reconstruction from January 1, 2013, to February 19, 2019. Patients were divided into 2 groups, those before (pre-intervention) and after (postintervention) the education campaign. We analyzed patient demographic and disease characteristics, intraoperative and postoperative factors, and surgical outcomes. RESULTS: Patients pre-intervention were prescribed longer courses of prophylactic antibiotics (median [interquartile range], 9 [8] vs 1 [1]; P < .001), more topical chloramphenicol ointment (21.82% vs 0%; P < .001), and more oral nystatin (36.9% vs 12.2%; P < .001). Patients postintervention had higher rates of recipient infections (36.11% vs 17.06%; P < .001) and donor site infections (6.94% vs 1.19%; P = .006). CONCLUSIONS: Following the education campaign, patients were prescribed shorter courses of prophylactic antibiotics, more of the recommended cefazolin-metronidazole regimen, and fewer topical antibiotics. However, patients also had a higher rate of surgical site infections.

Risk factors for surgical site infection in free-flap reconstructive surgery for head and neck cancer: Retrospective Australian cohort study.

BACKGROUND: Surgical site infections (SSI) are common complications of free-flap reconstruction for head and neck cancer defects. This study aimed to identify risk factors for SSI following a significant change in local antibiotic prophylaxis practice. METHODS: A retrospective cohort study was conducted of 325 patients receiving free-flap reconstruction for head and neck cancer defects at a tertiary hospital in Melbourne, Australia between 2013 and 2019. Charts were queried for recipient SSI (primary outcome), donor SSI, other infections, antibiotic use, hospital length of stay, and mortality. RESULTS: Risk factors for SSI included female sex, T-classification, hardware insertion, clindamycin prophylaxis, and operative duration. There was a trend toward increased SSI with shorter ≤24 h prophylaxis (OR: 0.43). CONCLUSION: Antibiotic duration and type were associated with SSI. Complexity of surgery, T-classification, hardware use, and operative duration were also independently associated with SSI. A prospective trial is indicated to elicit optimal prophylactic antibiotic duration.

Does the false-negative rate for 1 or 2 negative sentinel nodes after neo-adjuvant chemotherapy translate into a high local recurrence rate?

Prospective trials demonstrate that sentinel node (SN) biopsy after neo-adjuvant chemotherapy (NACT) has a significant false-negative rate (FNR) when only 1 or 2 SNs are removed. It is unknown whether this increased FNR correlates with an elevated risk of recurrence. Tumor Registry data at an NCI-Designated Comprehensive Cancer Center were reviewed from 2004 to 2018 for patients having a negative SN biopsy after NACT. Among 190 patients with histologically negative nodes after NACT having 1 (n = 42), 2 (n = 46), and ≥3 (n = 102) SNs, axillary recurrences occurred in 7.14%, 0%, and 1.96% (p = 0.09), breast recurrences occurred in 2.38%, 6.52%, and 0.98% (p = 0.12), and distance recurrences occurred in 16.67%, 8.70%, and 7.84% (p = 0.27), respectively. Time to first recurrence did not differ by SN count (p = 0.41). After adjustment for age, race, clinical stage, and receptor status, there were no differences in the rates of axillary (p = 0.26), breast (p = 0.44), or distance recurrence (p = 0.24) by numbers of SNs harvested. Median follow-up was 46.8 months. Despite higher post-NACT FNRs reported in randomized trials for patients having <3 sentinel nodes, recurrence rates were not significantly different for 1 versus 2 versus ≥3 SNs. This suggests that patients having 1 or 2 post-NACT SNs identified may not necessitate axillary dissection.

Discovering New Social Determinants of Health Concepts from Unstructured Data: Framework and Evaluation.

Social determinants of health (SDoH) are the complex set of circumstances in which individuals are born, or with which they live, that impact their health. Integrating SDoH into practice requires that information systems are able to identify SDoH-related concepts from charts and case notes through vocabularies or terminologies. Despite significant standardisation efforts across healthcare domains, SDoH coverage remains sparse in existing terminologies due to the broad spectrum of this domain, ranging from family relations, risk factors, to social programs and benefits, which are not consistently captured across administrative and clinical settings. This paper presents a framework to mine, evaluate and recommend new multidisciplinary concepts that relate to or impact the health and well-being of individuals using a word embedding model trained from a large dynamic corpus of unstructured data. Five key SDoH domains were selected and evaluated by domain experts. The concepts resulting from the trained model were matched against well-established meta-thesaurus UMLS and terminology SNOMED-CT and, overall, a significant proportion of concepts from a set of 10,000 candidates were not found (31% and 28% respectively). The results confirm both the gaps in current terminologies and the feasibility and impact of the methods presented in this paper for the incremental discovery and validation of new SDoH concepts together with domain experts. This sustainable approach facilitates the development and refinement of new and existing terminologies and, in turn, it allows systems such as Natural Language Processing (NLP) annotators to leverage SDoH concepts across integrated care settings.

Ontology-Guided Policy Information Extraction for Healthcare Fraud Detection.

Financial losses in Medicaid, from Fraud, Waste and Abuse (FWA), in the United States are estimated to be in the tens of billions of dollars each year. This results in escalating costs as well as limiting the funding available to worthy recipients of healthcare. The Centers for Medicare & Medicaid Services mandate thorough auditing, in which policy investigators manually research and interpret the policy to validate the integrity of claims submitted by providers for reimbursement, a very time-consuming process. We propose a system that aims to interpret unstructured policy text to semi-automatically audit provider claims. Guided by a domain ontology, our system extracts entities and relations to build benefit rules that can be executed on top of claims to identify improper payments, and often in turn payment policy or claims adjudication system vulnerabilities. We validate the automatic knowledge extraction from policies based on ground truth created by domain experts. Lastly, we discuss how the system can co-reason with human investigators in order to increase thoroughness and consistency in the review of claims and policy, to identify providers that systematically violate policies and to help in prioritising investigations.

Perforating the GORE® CARDIOFORM septal occluder and atrial septal defect occluder to gain access to the left atrium.

OBJECTIVE: Perforate the expanded polytetrafluoroethylene membrane of the GORE® CARDIOFORM Septal Occluder (GSO) and GORE® CARDIOFORM ASD Occluder (GCA) after implantation. BACKGROUND: Percutaneous transseptal access to the left atrium is necessary for many structural and electrophysiological procedures. The potential need to access the left atrium may influence decision-making for patent foramen ovale or atrial septal defect closure. METHODS: Sixteen canines underwent implantation of equal number GSO or GCA devices. A transseptal crossing procedure was performed through the device 85 (±1) days postoccluder implantation. The crossing procedure was performed utilizing commercially available equipment: radiofrequency/SureFlex sheath and standard needle/Mullin's sheath. Progressive dilation of the perforation was performed to allow passage of a 12 French Mullin's sheath into the left atrium. RESULTS: Left atrial access was achieved in all cases. Postmortem analysis demonstrated passage through both occluder discs in all radiofrequency/SureFlex sheath cases (4 GSO, 4 GCA) and half of the standard needle/Mullin's sheath cases (3 GSO, 1 GCA). The remaining standard needle/Mullin's sheath cases demonstrated perforation through the right atrial disc but passage around the septal aspect of the left atrial disc, thus not perforating the left atrial disc. No acute embolic complications from the procedure were observed. CONCLUSIONS: Left atrial access may be achieved through the GSO or GCA devices after implantation and endothelialization. The combination of a radiofrequency needle and steerable sheath provides benefit over a standard needle and Mullin's sheath in accomplishing passage through both occluder discs.