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An Outcome-Weighted Network Model for Characterizing Collaboration.

ABSTRACT: Shared patient encounters form the basis of collaborative relationships, which are crucial to the success of complex and interdisciplinary teamwork in healthcare. Quantifying the strength of these relationships using shared risk-adjusted patient outcomes provides insight into interactions that occur between healthcare providers. We developed the Shared Positive Outcome Ratio (SPOR), a novel parameter that quantifies the concentration of positive outcomes between a pair of healthcare providers over a set of shared patient encounters. We constructed a collaboration network using hospital emergency department patient data from electronic health records (EHRs) over a three-year period. Based on an outcome indicating patient satisfaction, we used this network to assess pairwise collaboration and evaluate the SPOR. By comparing this network of 574 providers and 5,615 relationships to a set of networks based on randomized outcomes, we identified 295 (5.2%) pairwise collaborations having significantly higher patient satisfaction rates. Our results show extreme high- and low-scoring relationships over a set of shared patient encounters and quantify high variability in collaboration between providers. We identified 29 top performers in terms of patient satisfaction. Providers in the high-scoring group had both a greater average number of associated encounters and a higher percentage of total encounters with positive outcomes than those in the low-scoring group, implying that more experienced individuals may be able to collaborate more successfully. Our study shows that a healthcare collaboration network can be structurally evaluated to characterize the collaborative interactions that occur between healthcare providers in a hospital setting.

SUBMITTER: Carson MB

PROVIDER: S-EPMC5051930 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Tumorigenesis is a multi-step process, involving the acquisition of multiple oncogenic mutations that transform cells, resulting in systemic dysregulation that enables proliferation, invasion, and other cancer hallmarks. The goal of precision medicine is to identify therapeutically-actionable mutations from large-scale omic datasets. However, the multiplicity of oncogenes required for transformation, known as oncogenic collaboration, makes assigning effective treatments difficult. Motivated by this observation, we propose a new type of oncogenic collaboration where mutations in genes that interact with an oncogene may contribute to the oncogene's deleterious potential, a new genomic feature that we term "surrogate oncogenes." Surrogate oncogenes are representatives of these mutated subnetworks that interact with oncogenes. By mapping mutations to a protein-protein interaction network, we determine the significance of the observed distribution using permutation-based methods. For a panel of 38 breast cancer cell lines, we identified a significant number of surrogate oncogenes in known oncogenes such as BRCA1 and ESR1, lending credence to this approach. In addition, using Random Forest Classifiers, we show that these significant surrogate oncogenes predict drug sensitivity for 74 drugs in the breast cancer cell lines with a mean error rate of 30.9%. Additionally, we show that surrogate oncogenes are predictive of survival in patients. The surrogate oncogene framework incorporates unique or rare mutations from a single sample, and therefore has the potential to integrate patient-unique mutations into drug sensitivity predictions, suggesting a new direction in precision medicine and drug development. Additionally, we show the prevalence of significant surrogate oncogenes in multiple cancers from The Cancer Genome Atlas, suggesting that surrogate oncogenes may be a useful genomic feature for guiding pancancer analyses and assigning therapies across many tissue types.

Project description:BackgroundIn 2017, the American College of Physicians (ACP) designated Mindfulness-Based Stress Reduction (MBSR), an eight-week group program, as first-line non-pharmacological treatment for chronic low back pain. However, interprofessional collaboration between mindfulness instructors and Primary Care Providers (PCP) remains largely unknown.ObjectiveWe developed a survey to assess communication between mindfulness instructors and PCPs, identify predictors of referral to MBSR, and determine areas where interventions could increase patient access to MBSR.MethodsThe 25-question survey was sent via email to PCPs at the Division of General Internal Medicine, University of Pittsburgh, PA, the Piedmont Health Services Family Medicine Section, Chapel Hill, NC, the Boston Medical Center General Internal Medicine and Family Medicine Sections, Boston, MA, and the UMass Memorial Medical Center Family Medicine Section, Worcester, MA. We used descriptive statistics and logistic regression to analyze the data.ResultsAmong 118 eligible respondents, 85 (72.0%) were female PCPs, mean age was approximately 41.5±10.1, and the majority (65.2%) had been in medical practice ≤10 years. Of these PCPs, 83 (70.1%) reported familiarity with MBSR (95% CI: 62.1, 78.5), and 49 (59.0%) of them referred patients at least yearly. Of those who referred, 8 (16.3%) reported collaboration with mindfulness instructors. PCPs who were quite a bit or very much familiar with MBSR had 5.10 (1.10, 22.50) times the odds (P=.03), and those who were 50 years or younger had 3.30 times the odds (P=.04) of referring patients to MBSR. Frequency of PCPs' personal practice of mindfulness was not significantly associated with referrals (P=.30).ConclusionThis is the first study to assess interprofessional collaboration between mindfulness instructors and PCPs. Suggestions for a potential integrative health care model are included; further studies on methods to augment communication and education are warranted to improve the referral process and ultimately increase accessibility and utilization of mindfulness-based programs.

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An Outcome-Weighted Network Model for Characterizing Collaboration.

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