scholarly journals 3560 Using Research Performance Progress Report data to Explore CTSI-Stakeholder Engagement through Network Analysis

2019 ◽  
Vol 3 (s1) ◽  
pp. 100-100
Author(s):  
Elizabeth Wayman ◽  
Eric P. Rubinstein ◽  
Camille Anne Martina ◽  
Ann Marie Dozier
Keyword(s):  
Medical Center ◽  
Research Performance ◽  
Progress Report ◽  
Clustering Coefficient ◽  
Network Nodes ◽  
Stakeholder Groups ◽  
Report Data ◽  
Using Data ◽  
Average Vertex ◽  
And Function

OBJECTIVES/SPECIFIC AIMS: To develop a social network model of collaborations within and external to the University of Rochester Medical Center (URMC) CTSI using data from the annual Research Performance Progress Report (RPPR) as well as other sources, to provide longitudinal evaluation of the CTSI’s engagement with key stakeholder groups. METHODS/STUDY POPULATION: The annually submitted RPPR follows a specific format with well-defined sections. The Highlights, Milestones and Challenges Report includes areas in which CTSI function leaders provide details about program integration and innovation, including collaborations with other functions or external groups. The Highlights, Milestones and Challenges Report was qualitatively coded to identify function-collaborator dyads. Each entity in the dyad became a node in the network. Nodes were connected by edges named by the dyads. The network included two types of nodes. The first were CTSI internal functions/programs, i.e. the entities that submitted RPPR sections and formed an interconnected sub-network. The second type of nodes were entities external to the CTSI (collaborators, internal or external to the CTSI site). These entities were named by functions submitting RPPR narratives. External nodes with similar meanings were consolidated. Duplicate edges were removed. CTSI-external nodes were grouped into five stakeholder categories: URMC, University of Rochester (UR), community, other CTSA institutions, CTSA consortium. Thus, these nodes were connected to the CTSI internal nodes, but not to each other. A second source of collaboration data was function-reported internal metrics. As part of the internal metric data collection, functions list partners who play a role in improving metric data or who are responsible for providing data. Partners identified in the internal metrics data, but not specified in the RPPR, were added to the network. RESULTS/ANTICIPATED RESULTS: Twenty-three internal CTSI functions submitted an RPPR and represent the CTSI internal nodes. Internal CTSI functions identified 235 collaborations (edges): 125 collaborations with other CTSI internal functions, 57 collaborations with URMC entities, 14 with UR entities, 15 with the external community, 15 with other institutions (CTSA hubs and other universities), and 9 with CTSA consortium entities. Thirty-eight of the collaborations were identified in the internal metrics partners section. In total, the network comprised 104 nodes. Graph density was.022 for full network and.21 for the CTSI internal sub-network. The global clustering coefficient, a measure of connectivity, for the CTSI internal sub-network was.252. DISCUSSION/SIGNIFICANCE OF IMPACT: The RPPR provides an underutilized source of data for annually repeated analyses of internal and external CTSI collaborations and is a way to enhance use of this routinely collected information. Analyses of the network yield metrics for measuring CTSI reach and impact on stakeholder groups over time. For example, measures such as number of nodes representing entities external to CTSI and average vertex degree of the CTSI Internal nodes track aspects of CTSI collaborations. Visualizations using different layouts or highlighting different sub-networks provide a representation of CTSI engagement with the communities of stakeholders as well as insights to relationships between functions, regions of collaboration, and areas of gaps. These data also provide an important new mechanism to engage the CTSI leadership and function leads in understanding how their work contributes to the overall network and synergies they have with each other.

Abstract 406: Are Providers Overconfident in Predicting Outcome After Cardiac Arrest?

Circulation ◽  
2019 ◽  
Vol 140 (Suppl_2) ◽  
Author(s):  
Alexis Steinberg ◽  
Clifton W Callaway ◽  
Cameron Dezfulian ◽  
Jonathan Elmer
Keyword(s):  
Cardiac Arrest ◽  
Medical Center ◽  
Academic Medical Center ◽  
Favourable Outcome ◽  
Academic Medical ◽  
Predicting Outcome ◽  
Using Data ◽  
And Function ◽  
Future Work ◽  
Attending Physicians

Objective: Prognostication after cardiac arrest is challenging. We tested if providers’ confidence in their neuroprognostic assessments correlates with accuracy. Methods: We presented physicians with clinical synopses using data from real-time, post-arrest patients being treated at a single academic medical center. We allowed providers to ask for any additional data available at the time the assessment was performed. We asked providers: (1) will the patient survive to hospital discharge?; (2) will the patient have favourable function at discharge?; and, (3) their confidence in each prediction (0-100%). We repeated assessments daily until death or post-arrest day 5. Results: We completed 414 assessments of 51 patients with 59 providers. Of patients, 79% died, 8% were discharged with unfavourable function and 12% had functionally favourable survival. Providers accurately predicted survival in 257/414 (62%) assessments. In most errors (136/141, 96%), providers predicted survival in a patient who died. Providers accurately predicted function in 282/414 (68%) assessments. In most errors (125/132, 95%), providers incorrectly predicted a favourable outcome. Providers were confident in their assessments (median confidence predicting survival 80 [IQR 60 - 90]; median confidence predicting function 80 [IQR 60 - 95]). Accuracy predicting survival and function were both positively correlated with confidence (both P<0.001), but confidence explained only 7% and 15% of observed variance in accuracy, respectively. When providers reported 100% confidence predicting survival, they were correct in 31/42 (74%) cases. Accuracy did not vary over time. Attending physicians were not more accurate than trainees predicting survival (65% vs 60% accurate) and were less accurate prediciting functional outcome (62% vs 84% accurate, P< 0.001). Confidence did not differ between attendings and trainees. Conclusions: Providers were overly optimistic predicting outcomes at discharge. Self-reported confidence explained only a small percentage of variance in accuracy. Even when extremely confident, providers were often wrong. Our future work will explore patient and provider factors that contribute to error.

scholarly journals Policies and procedures governing patient portal use at an Academic Medical Center

JAMIA Open ◽  
2019 ◽  
Vol 2 (4) ◽  
pp. 479-488
Author(s):  
Bryan D Steitz ◽  
Joseph Isaac S Wong ◽  
Jared G Cobb ◽  
Brian Carlson ◽  
Gaye Smith ◽  
...  
Keyword(s):  
Government Regulation ◽  
Medical Center ◽  
Academic Medical Center ◽  
Successful Implementation ◽  
Patient Portal ◽  
Patient Portals ◽  
Identity Verification ◽  
Policies And Procedures ◽  
Academic Medical ◽  
And Function

Abstract Background and Objective Patient portal use has increased over the last two decades in response to consumer demand and government regulation. Despite growing adoption, few guidelines exist to direct successful implementation and governance. We describe the policies and procedures that have governed over a decade of continuous My Health at Vanderbilt (MHAV) patient portal use. Methods We examined MHAV usage data between May 2007 and November 2017. We classified patient portal activity into eight functional categories: Appointment, Billing, Document Access, Genetics, Health Result, Immunization, Medication, and Messaging. We describe our operating policies and measure portal uptake, patient account activity, and function use over time. Results By the end of the study period, there were 375 517 registered accounts. Policies made MHAV available to competent adults and adolescents 13 and over. Patients signed up for a limited access account online, which could be upgraded to a full-access account after identity verification. Patients could assign proxy accounts to family and caregivers, which permitted nonpatient access to select MHAV functions. Laboratory and radiology results were accessible via MHAV. Results were classified into three groups based on sensitivity, which govern the length of delay before results appeared in MHAV. Discussion and Conclusion Patient portals offer significant opportunity to engage patients in their healthcare. However, there remains a need to understand how policies can promote uptake and use. We anticipate that other institutions can apply concepts from our policies to support meaningful patient portal engagement.

scholarly journals The Postencounter Form System: Viewpoint on Efficient Data Collection Within Electronic Health Records (Preprint)

2019 ◽  
Author(s):  
Philip Held ◽  
Randy A Boley ◽  
Walter G Faig ◽  
John A O'Toole ◽  
Imran Desai ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Medical Center ◽  
Health Records ◽  
Clinical Notes ◽  
The Road ◽  
Clinical Encounters ◽  
Efficient Data ◽  
Data Points ◽  
Electronic Health ◽  
Using Data

UNSTRUCTURED Electronic health records (EHRs) offer opportunities for research and improvements in patient care. However, challenges exist in using data from EHRs due to the volume of information existing within clinical notes, which can be labor intensive and costly to transform into usable data with existing strategies. This case report details the collaborative development and implementation of the postencounter form (PEF) system into the EHR at the Road Home Program at Rush University Medical Center in Chicago, IL to address these concerns with limited burden to clinical workflows. The PEF system proved to be an effective tool with over 98% of all clinical encounters including a completed PEF within 5 months of implementation. In addition, the system has generated over 325,188 unique, readily-accessible data points in under 4 years of use. The PEF system has since been deployed to other settings demonstrating that the system may have broader clinical utility.

scholarly journals Evaluation of computer network security using attack undirected geography

2019 ◽  
Vol 16 (3) ◽  
pp. 1508
Author(s):  
Chanintorn Jittawiriyanukoon
Keyword(s):  
Network Security ◽  
Computer Network ◽  
Threshold Value ◽  
Clustering Coefficient ◽  
Security Model ◽  
Security Threat ◽  
Network Nodes ◽  
Computer Network Security ◽  
Security Problem ◽  
Individual Attack

<span>To secure a wealth of data traversing the computer network at your fingertips is compulsory. But when attack arises at various parts of the network it is difficult to protect, especially when each incident is investigated separately. Geography is a necessary construct in computer networks. The analytics of geography algorithms and metrics to curate insight from a security problem are a critical method of analysis for computer systems. A geography based representation is employed to highlight aspects (on a local and global level) of a security problem which are Eigenvalue, eccentricity, clustering coefficient and cliques. Network security model based on attack undirected geography (AUG) is familiarized. First, analysis based upon association rules is presented then the attack threshold value is set from AUG. The probability of an individual attack edge and associated network nodes are computed in order to quantify the security threat. The simulation is exploited to validate that results are effective.</span>

scholarly journals Analyzing the Formation Mechanism of Cross-City Transportation Network Resilience

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Liang Wang ◽  
Xiaolong Xue ◽  
Weirui Xue ◽  
Beile Zhao
Keyword(s):  
Theoretical Model ◽  
Formation Mechanism ◽  
Transportation Network ◽  
Network Resilience ◽  
Railway Network ◽  
Network Nodes ◽  
General Meaning ◽  
Important Position ◽  
And Function ◽  
Constituent Elements

The formation mechanism of cross-city transportation network resilience occupies an important position in cross-city transportation network resilience management. This study analyzes the constituent elements of the cross-city transportation network and their interrelationships, and the connotation of cross-city transportation network resilience is defined from the general meaning of system resilience. Combining with the connotation of cross-city transportation network resilience, the specific formation process of cross-city transportation network resilience is analyzed and summarized from three stages, including resisting disturbance, absorbing disturbance, and function recovery. Taking cross-city transportation network nodes and systems as specific objects, the static and dynamic formation path of cross-city transportation network resilience is condensed. Based on the standard linear solid model, a theoretical model is constructed and solved for revealing the formation mechanism of cross-city transportation network resilience. Finally, the theoretical model of cross-city transportation network resilience proposed in this study is used for analyzing the China railway network resilience.

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