Understanding a Care Management System's Role in Influencing a Transitional-Aged Youth Program's Practice: Mixed Methods Study

BACKGROUND

Extended foster care programs help prepare transitional-aged youth (TAY) to step into adulthood and live independent lives. Aspiranet, one of California's largest social service organizations, used a social care management solution (SCMS) to meet TAY's needs.

OBJECTIVE

We aimed to investigate the impact of an SCMS, IBM Watson Care Manager (WCM), in transforming foster program service delivery and improving TAY outcomes.

METHODS

We used a mixed methods study design by collecting primary data from stakeholders through semistructured interviews in 2021 and by pulling secondary data from annual reports, system use logs, and data repositories from 2014 to 2021. Thematic analysis based on grounded theory was used to analyze qualitative data using NVivo software. Descriptive analysis of aggregated outcome metrics in the quantitative data was performed and compared across 2 periods: pre-SCMS implementation (before October 31, 2016) and post-SCMS implementation (November 1, 2016, and March 31, 2021).

RESULTS

In total, 6 Aspiranet employees (4 leaders and 2 life coaches) were interviewed, with a median time of 56 (IQR 53-67) minutes. The majority (5/6, 83%) were female, over 30 years of age (median 37, IQR 32-39) with a median of 6 (IQR 5-10) years of experience at Aspiranet and overall field experience of 10 (IQR 7-14) years. Most (4/6, 67%) participants rated their technological skills as expert. Thematic analysis of participants' interview transcripts yielded 24 subthemes that were grouped into 6 superordinate themes: study context, the impact of the new tool, key strengths, commonly used features, expectations with WCM, and limitations and recommendations. The tool met users' initial expectations of streamlining tasks and adopting essential functionalities. Median satisfaction scores around pre- and post-WCM workflow processes remained constant between 2 life coaches (3.25, IQR 2.5-4); however, among leaders, post-WCM scores (median 4, IQR 4-5) were higher than pre-WCM scores (median 3, IQR 3-3). Across the 2 study phases, Aspiranet served 1641 TAY having consistent population demographics (median age of 18, IQR 18-19 years; female: 903/1641, 55.03%; race and ethnicity: Hispanic or Latino: 621/1641, 37.84%; Black: 470/1641, 28.64%; White: 397/1641, 24.19%; Other: 153/1641, 9.32%). Between the pre- and post-WCM period, there was an increase in full-time school enrollment (359/531, 67.6% to 833/1110, 75.04%) and a reduction in part-time school enrollment (61/531, 11.5% to 91/1110, 8.2%). The median number of days spent in the foster care program remained the same (247, IQR 125-468 years); however, the number of incidents reported monthly per hundred youth showed a steady decline, even with an exponentially increasing number of enrolled youth and incidents.

CONCLUSIONS

The SCMS for coordinating care and delivering tailored services to TAY streamlined Aspiranet's workflows and processes and positively impacted youth outcomes. Further enhancements are needed to better align with user and youth needs.

Clinical insights into hematologic malignancies and comparative analysis of molecular signatures of acute myeloid leukemia in different ethnicities using an artificial intelligence offering

Next generation sequencing generates copious amounts of genomics data, causing manual interpretation to be laborious and non-scalable while remaining subjective (even for highly trained specialists). We evaluated the performance of the artificial intelligence-based offering Watson for Genomics (WfG), a variant interpretation platform, in hematologic malignancies for the first time.Next generation sequencing was performed for patients treated for various hematological malignancies at Hallym University Sacred Heart Hospital, South Korea, between December 2017 and August 2020 using a 54-gene panel. Both WfG and expert manual curation were used to evaluate the performance of WfG. Acute myeloid leukemia (AML) molecular profiles were compared between Koreans and other ethnic groups using a publicly available dataset.Seventy-seven patients were analyzed (AML: 45, myeloproliferative neoplasms: 12, multiple myeloma: 7, myelodysplastic syndromes: 6, and others: 7). The concordance between the manual and WfG interpretations of 35 variants in 11 random patients was 94%. Among all patients, WfG identified 39 (51%) with at least 1 clinically actionable therapeutic alteration (i.e., a variant targeted by a United States Food and Drug Administration [US FDA]-approved drug, off-label drug, or clinical trial). Moreover, 46% of these patients (18/39) had genes that were targeted by a US FDA-approved therapy. WfG identified diagnostic or prognostic insights in 65% of the patients with no targetable alterations. In those with AML, FLT3-internal tandem duplications or tyrosine kinase domain mutations were less frequent among Koreans than among Caucasians (6.7% vs 30.2%, P < .001) or Hispanics (6.7% vs 28.3%, P = .005), suggesting ethnic differences.Variant interpretation using WfG correlated well with manually curated expert opinions. WfG provided therapeutic insights (including variant-specific drugs and clinical trials that cannot easily be provided by expert manual curation), as well as diagnostic and/or prognostic information.

Barriers to Prescribing Targeted Therapies for Patients With NSCLC With Highly Actionable Gene Variants in the Veterans Affairs National Precision Oncology Program

PURPOSE

Next-generation sequencing (NGS) gene panels are frequently completed for patients with advanced non-small-cell lung cancer (NSCLC). Patients with highly actionable gene variants have improved outcomes and reduced toxicities with the use of corresponding targeted agents. We sought to identify barriers to targeted agent use within the Veterans Health Affairs' National Precision Oncology Program (NPOP).

METHODS

A retrospective evaluation of patients with NSCLC who underwent NGS multigene panels through NPOP between July 2015 and February 2019 was conducted. Patients who were assigned level 1 or 2A evidence for oncogenic gene variants by an artificial intelligence offering (IBM Watson for Genomics [WfG]) and NPOP staff were selected. Antineoplastic drug prescriptions and provider notes were reviewed. Reasons for withholding targeted treatments were categorized.

RESULTS

Of 1,749 patients with NSCLC who successfully underwent NGS gene panel testing, 112 (6.4%) patients were assigned level 1 and/or 2A evidence for available targeted treatments by WfG and NPOP staff. All highly actionable gene variants were within ALK, BRAF, EGFR, ERBB2, MET, RET, and ROS1. Of these, 36 (32.1%) patients were not prescribed targeted agents. The three most common reasons were (1) patient did not carry a diagnosis of metastatic disease (33.3%), (2) treating provider did not comment on the NGS results (25.0%), and (3) provider felt that patient could not tolerate therapy (19.4%). No patients were denied access to level 1 or 2A targeted drugs because of rejection of a nonformulary drug request.

CONCLUSION

A substantial minority of patients with NSCLC bearing highly actionable gene variants are not prescribed targeted agents. Further provider- and pathologist-directed educational efforts and implementation of health informatics systems to provide real-time decision support for test ordering and interpretation are needed.

The Perceived Impact and Usability of a Care Management and Coordination System in Delivering Services to Vulnerable Populations: Mixed Methods Study

Background

People with complex needs, such as those experiencing homelessness, require concurrent, seamless support from multiple social service agencies. Sonoma County, California has one of the nation’s largest homeless populations among largely suburban communities. To support client-centered care, the county deployed a Care Management and Coordination System (CMCS). This system comprised the Watson Care Manager (WCM), a front-end system, and Connect 360, which is an integrated data hub that aggregates information from various systems into a single client record.

Objective

The aim of this study is to evaluate the perceived impact and usability of WCM in delivering services to the homeless population in Sonoma County.

Methods

A mixed methods study was conducted to identify ways in which WCM helps to coordinate care. Interviews, observations, and surveys were conducted, and transcripts and field notes were thematically analyzed and directed by a grounded theory approach. Responses to the Technology Acceptance Model survey were analyzed.

Results

A total of 16 participants were interviewed, including WCM users (n=8) and department leadership members (n=8). In total, 3 interdisciplinary team meetings were observed, and 8 WCM users were surveyed. WCM provided a central shared platform where client-related, up-to-date, comprehensive, and reliable information from participating agencies was consolidated. Factors that facilitated WCM use were users’ enthusiasm regarding the tool functionalities, scalability, and agency collaboration. Constraining factors included the suboptimal awareness of care delivery goals and functionality of the system among the community, sensitivities about data sharing and legal requirements, and constrained funding from government and nongovernment organizations. Overall, users found WCM to be a useful tool that was easy to use and helped to enhance performance.

Conclusions

WCM supports the delivery of care to individuals with complex needs. Integration of data and information in a CMCS can facilitate coordinated care. Future research should examine WCM and similar CMCSs in diverse populations and settings.

Empowering Caseworkers to Better Serve the Most Vulnerable with a Cloud-Based Care Management Solution

BACKGROUND

Care-management tools are typically utilized for chronic disease management. Sonoma County government agencies employed advanced health information technologies, artificial intelligence (AI), and interagency process improvements to help transform health and health care for socially disadvantaged groups and other displaced individuals.

OBJECTIVES

The objective of this case report is to describe how an integrated data hub and care-management solution streamlined care coordination of government services during a time of community-wide crisis.

METHODS

This innovative application of care-management tools created a bridge between social and clinical determinants of health and used a three-step approach-access, collaboration, and innovation. The program Accessing Coordinated Care to Empower Self Sufficiency Sonoma was established to identify and match the most vulnerable residents with services to improve their well-being. Sonoma County created an Interdepartmental Multidisciplinary Team to deploy coordinated cross-departmental services (e.g., health and human services, housing services, probation) to support individuals experiencing housing insecurity. Implementation of a data integration hub (DIH) and care management and coordination system (CMCS) enabled integration of siloed data and services into a unified view of citizen status, identification of clinical and social determinants of health from structured and unstructured sources, and algorithms to match clients across systems.

RESULTS

The integrated toolset helped 77 at-risk individuals in crisis through coordinated care plans and access to services in a time of need. Two case examples illustrate the specific care and services provided individuals with complex needs after the 2017 Sonoma County wildfires.

CONCLUSION

Unique application of a care-management solution transformed health and health care for individuals fleeing from their homes and socially disadvantaged groups displaced by the Sonoma County wildfires. Future directions include expanding the DIH and CMCS to neighboring counties to coordinate care regionally. Such solutions might enable innovative care-management solutions across a variety of public, private, and nonprofit services.

Abstract 6579: Clinical utility of comprehensive genomic testing with artificial-intelligence-based analysis to identify targetable sub-clonal events in relapsed acute myeloid leukemia (AML)

Next-generation sequencing (NGS) is increasingly used to inform diagnostic, therapeutic, and prognostic decisions in AML at the time of first presentation. We highlight the utility of NGS combined with Watson™ for Genomics (WfG), an artificial-intelligence-based decision-support system, in identifying new clinically actionable alterations as a result of clonal evolution in the relapsed disease setting. In less than 3 minutes, WfG identified an IDH1 R132H pathogenic mutation in the relapsed sample sequenced with the Illumina TruSight Tumor 170-gene panel leading to the compassionate use of ivosidenib. In addition, mutations in two genes resulting in increased sensitivity to PARP inhibitors and mutations in PTEN resulting in activation of the MTOR/PI3K signaling pathway were detected by WfG. In February 2018, a previously healthy 23-year old Caucasian female presented with AML consisting of 80% blasts with positive FLT3 mutation. She received induction cytarabine plus daunorubicin (7+3) followed by multikinase inhibitor therapy with midostaurin on days 8 to 21. A 28-day bone marrow biopsy showed persistent disease with 40% blasts. In March 2018, the patient underwent re-induction chemotherapy with mitoxantrone, etoposide, and cytarabine (MEC) followed by midostaurin on days 8 to 21. A bone marrow biopsy after completion of re-induction therapy showed complete remission with &lt; 5% blasts (CR1). In May 2018, a matched donor was not found on a bone marrow registry, and the patient underwent a post-remission dual unrelated umbilical cord blood (UCB) hematopoietic stem cell transplantation (HSCT). Engraftment was not achieved. In July 2018, the patient had disease relapse with the presence of circulating blasts and 7% of blasts in the bone marrow. While NGS is typically not performed on relapsed samples, WfG identified IDH1 R132H and PTEN C78T pathogenic mutations using the 170-gene panel. Based on these results, the patient initiated azacytidine plus the IDH1 inhibitor ivosidenib. In August 2018, a bone marrow biopsy showed less than 5% blasts positive for a FLT3-ITD mutation. In September 2018, the patient underwent reduced-intensity conditioning with fludarabine, cyclophosphamide, and total body irradiation followed by haploidentical allogeneic HSCT from her mother. Maintenance therapy with azacytidine plus ivosidenib was continued until the present time. Currently, the patient is in remission for over 15 months without evidence of AML minimal residual disease. She has developed mild skin chronic graft-versus-host disease that is controlled with standard treatment. She works on a full-time basis and has excellent functional status. The combination of CGP, artificial intelligence, and expert care has resulted in an excellent outcome in a patient with relapsed AML. In conclusion, our experience suggests that CGP testing should be considered at different time points, at least in the relapsed setting, to help treating physicians alter or help improve clinical outcome. CGP testing in a relapsed setting is precluded because it is not covered by payers. In support of optimal care, we have initiated a new program for compassionate use of genomic testing, where such testing is medically necessary, but not covered by insurance or payer supported.

Citation Format: Ravindra Kolhe, Ashis Mondal, Vamsi Kota, Nkhil Sahajpal, Meenakshi Ahluwalia, Allan Njau, Dilhan Weeraratne, Yull Arriaga, David Brotman, Gretchen Jackson, Jane Snowdon. Clinical utility of comprehensive genomic testing with artificial-intelligence-based analysis to identify targetable sub-clonal events in relapsed acute myeloid leukemia (AML) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6579.

Genomic analysis of myeloproliferative neoplasm (MPN) patients from a single institution in South Korea to reveal novel pathogenic mutations and perturbed pathways

e19533

Background: Therapeutic, prognostic, and diagnostic insights gained from next generation sequencing (NGS) are a key premise of genomics-informed cancer care in hematological diseases. Particularly in BCR-ABL negative myeloproliferative neoplasms (MPN), insights gained from NGS is integral for risk stratification and prognostication. In this study, MPN patients of South Korean descent were sequenced, interpreted, and compared with a published validation cohort to identify variations in mutational profiles specific to demographics. Methods: 31 South Korean MPN patients including 12 essential thrombocythemia, 6 polycythemia vera, 6 primary myelofibrosis, and 7 chronic myelogenous leukemia were sequenced in 2018 and 2019 using the 54 gene Illumina TruSight Myeloid Panel at Hallym University College of Medicine. Orthogonal testing for CALR mutations was done by Sanger sequencing. Watson for Genomics (WfG), an artificial intelligence offering was used for variant interpretation and annotation. A cohort of 151 MPN patients previously published in the New England Journal of Medicine (NEJM) was used for comparison (PMID:24325359). Results: The table shows identified actionable mutations. Conclusions: Two novel pathogenic mutations in CALR (c.1162delG and c.1100_1145del)) were identified in Korean MPN patients. NOTCH1 pathogenic mutations were exclusive while TP53 mutations were significantly enriched in the Korean cohort suggesting that these pathways may play a role in MPN. TP53 mutations in MPN are clinically significant as they have been associated with increased risk for leukemic transformation. Of note, MPL mutations were not detected in the Korean cohort. In conclusion, race and ethnicity may contribute to some mutational signatures in cancer. [Table: see text]

Clinical utility of comprehensive genomic pathway and integrated network analyses in personalized oncology

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Background: Adoption of next-generation sequencing (NGS) technology in routine clinical practice has enabled the detection of genetic aberrations such as single nucleotide variants, copy number alterations, and gene fusions. Pathway and network analyses (PNA) are key components for evaluation of NGS data in a clinical setting to explain findings involving thousands of altered genes and proteins with a smaller and more interpretable set of altered processes. Though PNA have been applied to identify driver genes and pathways in cohort-based analyses, its application in precision oncology remains unexplored. We investigate the potential utility of the Watson for Genomics (WfG) pathway analyses tool in interpreting complex and multiple genomic alterations in individual cancers. Methods: DNA and RNA isolated from 70 patient tumors across 30 different cancer types were processed with Illumina’s TST170 NGS platform. WfG’s feature of pathway analyses was used to identify gene variants, signaling pathways, networks, and the drugs targeting these alterations based on evidence in the clinical literature and FDA drug databases. Results: Analyses defined 5 different pathway/network models: 1) downstream therapeutic targets, 2) synthetic lethality, 3) combinatorial downstream targets + synthetic lethality, 4) two or more pathways converging to downstream targets, and 5) complex profile analyses. The five PNA models are illustrated by the following unique cases. 1) A thyroid cancer case with HRAS variant and activated RAF1 downstream pathway showed MAPK1/3 were suggestive of relevant targets. 2) An acute myeloid leukemia case with BRCA1, BRCA2 and PTEN variants, targeting a common synthetic lethal partner PARP1 was ideal for therapy. 3) A penile carcinoma case with BRAF, CDKN2A and TP53 variants, targeting the BRAF downstream pathway in combination with either CDKN2A or TP53 were the likely choice for therapy. 4) A glioma case with activated PI3K and MEK downstream pathway, targeting a common downstream marker would block both pathways. 5) A breast carcinoma case with a complex pathogenic variant profile provided relevant clinical information and levels of evidence for multiple drug targets. Conclusions: We discovered that the integrated WfG pathway analyses tool is ideal for visualization of the variants with levels of evidence from clinical literature and FDA drug databases that can help inform treatment options and provides a holistic understanding of a specific tumor profile allowing the treating clinician to select personalized targeted therapy.

Comprehensive analysis of advanced-stage solid tumors from TCGA reveal widespread variation of genomics evidence levels across cancer types

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Background: Improved scalability and affordability of next generation sequencing (NGS) has pivoted cancer care toward genomics-driven treatment decisions. Particularly in advanced-stage or refractory cancer, clinical insights gleaned from NGS have become an integral option as these patients have typically exhausted all lines of available therapy. As precision oncology evolves, NGS is expected to have a differential impact based on the cancer type. In this study, a comprehensive NGS panel was used to determine the strength of clinical evidence in various advanced stage tumor samples from The Cancer Genome Atlas (TCGA). Methods: A hybrid capture panel, Oncofoco, was developed to evaluate SNVs, INDELs, CNVs and TMB in 366 genes. The panel’s utility was validated by interrogating a broader cohort of 2847 TCGA samples (advanced tumors with T3 or T4; or N > = 1; or M > = 1). Watsonä for Genomics, an artificial intelligence offering, was used for variant interpretation and annotation of the 366 genes. A clinical evidence classification system that evaluated the strength of biomarker/drug response associations was used for annotation with level 1/R1 strongest and level 4 weakest from clinical literature, FDA drug labels and guidelines (PMID:28890946). Results: The highest level of evidence for the top nine frequently occurring advanced stage cancers in TCGA is shown in Table. Conclusions: Thyroid cancer and cutaneous melanoma have emerged as the cancer types with the most level 1 evidence (FDA approved drugs) owing to BRAF V600E mutations. Kidney and prostate cancers show no cases with level 1 evidence and also had the largest fraction of unactionable tumors. Over half of colorectal cancer cases had level R1 resistance evidence attributed to KRAS and NRAS mutations. The clinical utility of NGS in late-stage refractory cancer varies widely by tumor type. The presence of level 3 and level 4 evidence in all cancer types bodes well for the development of new targeted drugs. [Table: see text]

Barriers to prescribing targeted therapies for NSCLC patients with highly actionable gene variants in the VA National Precision Oncology Program

2005

Background: Next-Generation Sequencing (NGS) gene panels are often completed to guide therapeutic decisions for patients with advanced stage non-small cell lung cancer (NSCLC). Patients with highly-actionable gene variants may experience improved therapeutic treatments and reduced toxicities with use of targeted agents. Ensuring appropriate prescription of targeted therapies is therefore of high importance. We sought to identify barriers to targeted agent use within the Veterans Health Affairs’ (VHA) National Precision Oncology Program (NPOP). Methods: A retrospective evaluation examined the cohort of NSCLC patients who underwent NGS multi-gene panels through NPOP between July 2015 and February 2019. A level of evidence for drug actionability was assigned to each observed oncogenic gene variant using an artificial intelligence offering (IBM Watson for Genomics: WfG). WfG level 1 and 2A evidence was reviewed by NPOP staff to exclude gene variants that did not conform to NPOP level 1 and 2A definitions. Anti-neoplastic drug prescriptions and oncology provider notes were obtained for all included patients from the VHA Corporate Data Warehouse. Review of clinical notes of patients who did not receive targeted agents was performed to categorize the reason(s). Results: Of 1764 NSCLC patients who successfully underwent NGS gene panel testing, 156 (8.9%) received therapeutic level 1 (7.3%) or 2A (1.6%) options for targeted agents based on WfG evidence analysis. In total, 117 (6.6%) patients had NPOP level 1 and 2A gene variants, all within ALK, BRAF, EGFR, ERBB2, MET, and RET. Of these, 49 (41.2%) patients were not prescribed available targeted agents. The three most common reasons were: (1) treating provider did not comment on NGS results (30.7%), (2) patient did not carry a diagnosis of advanced stage disease (18.4%), and (3) patient had begun an alternative systemic therapy prior to completion of sequencing (16.3%). No patient was denied access to a level 1 or 2A targeted drug due to utilization-management review. Conclusions: A substantial minority of patients with advanced NSCLC bearing highly-actionable gene variants are not prescribed available targeted agents. Further provider- and pathologist-directed educational effort are needed, as well as implementation of health informatics systems to provide near real-time decision support for test ordering and interpretation.

Effect of through-plane motion on left ventricular rotation: a study using slice-following harmonic phase imaging

Noninvasive quantification of regional left ventricular rotation may improve understanding of cardiac function. Current methods used to quantify rotation typically acquire data on a set of prescribed short-axis slices, neglecting effects due to through-plane myocardial motion. We combine principles of slice-following tagged imaging with harmonic phase analysis methods to account for through-plane motion in regional rotation measurements. We compare rotation and torsion measurements obtained using our method to those obtained from imaging datasets acquired without slice-following. Our results in normal volunteers demonstrate differences in the general trends of average and regional rotation-time plots in midbasal slices and the rotation versus circumferential strain loops. We observe substantial errors in measured peak average rotation of the order of 58% for basal slices (due to change in the pattern of the curve), -6.6% for midventricular slices, and -8.5% for apical slices; and an average error in base-to-apex torsion of 19% when through-plane motion is not considered. This study concludes that due to an inherent base-to-apex gradient in rotation that exists in the left ventricular, accounting for through-plane motion is critical to the accuracy of left ventricular rotation quantification.