scholarly journals Characterizing communication patterns among members of the clinical care team to deliver breast cancer treatment

2019 ◽  
Vol 27 (2) ◽  
pp. 236-243 ◽  
Author(s):  
Bryan D Steitz ◽  
Kim M Unertl ◽  
Mia A Levy

Abstract Objective Research to date focused on quantifying team collaboration has relied on identifying shared patients but does not incorporate the major role of communication patterns. The goal of this study was to describe the patterns and volume of communication among care team members involved in treating breast cancer patients. Materials and Methods We analyzed 4 years of communications data from the electronic health record between care team members at Vanderbilt University Medical Center (VUMC). Our cohort of patients diagnosed with breast cancer was identified using the VUMC tumor registry. We classified each care team member participating in electronic messaging by their institutional role and classified physicians by specialty. To identify collaborative patterns, we modeled the data as a social network. Results Our cohort of 1181 patients was the subject of 322 424 messages sent in 104 210 unique communication threads by 5620 employees. On average, each patient was the subject of 88.2 message threads involving 106.4 employees. Each employee, on average, sent 72.9 messages and was connected to 24.6 collaborators. Nurses and physicians were involved in 98% and 44% of all message threads, respectively. Discussion and Conclusion Our results suggest that many providers in our study may experience a high volume of messaging work. By using data routinely generated through interaction with the electronic health record, we can begin to evaluate how to iteratively implement and assess initiatives to improve the efficiency of care coordination and reduce unnecessary messaging work across all care team roles.

2021 ◽  
Vol 12 (04) ◽  
pp. 877-887
Author(s):  
Bryan D. Steitz ◽  
Kim M. Unertl ◽  
Mia A. Levy

Abstract Objective Asynchronous messaging is an integral aspect of communication in clinical settings, but imposes additional work and potentially leads to inefficiency. The goal of this study was to describe the time spent using the electronic health record (EHR) to manage asynchronous communication to support breast cancer care coordination. Methods We analyzed 3 years of audit logs and secure messaging logs from the EHR for care team members involved in breast cancer care at Vanderbilt University Medical Center. To evaluate trends in EHR use, we combined log data into sequences of events that occurred within 15 minutes of any other event by the same employee about the same patient. Results Our cohort of 9,761 patients were the subject of 430,857 message threads by 7,194 employees over a 3-year period. Breast cancer care team members performed messaging actions in 37.5% of all EHR sessions, averaging 29.8 (standard deviation [SD] = 23.5) messaging sessions per day. Messaging sessions lasted an average of 1.1 (95% confidence interval: 0.99–1.24) minutes longer than nonmessaging sessions. On days when the cancer providers did not otherwise have clinical responsibilities, they still performed messaging actions in an average of 15 (SD = 11.9) sessions per day. Conclusion At our institution, clinical messaging occurred in 35% of all EHR sessions. Clinical messaging, sometimes viewed as a supporting task of clinical work, is important to delivering and coordinating care across roles. Measuring the electronic work of asynchronous communication among care team members affords the opportunity to systematically identify opportunities to improve employee workload.


2011 ◽  
Vol 02 (04) ◽  
pp. 460-471 ◽  
Author(s):  
A. Skinner ◽  
J. Windle ◽  
L. Grabenbauer

SummaryObjective: The slow adoption of electronic health record (EHR) systems has been linked to physician resistance to change and the expense of EHR adoption. This qualitative study was conducted to evaluate benefits, and clarify limitations of two mature, robust, comprehensive EHR Systems by tech-savvy physicians where resistance and expense are not at issue.Methods: Two EHR systems were examined – the paperless VistA / Computerized Patient Record System used at the Veterans‘ Administration, and the General Electric Centricity Enterprise system used at an academic medical center. A series of interviews was conducted with 20 EHR-savvy multi-institutional internal medicine (IM) faculty and house staff. Grounded theory was used to analyze the transcribed data and build themes. The relevance and importance of themes were constructed by examining their frequency, convergence, and intensity.Results: Despite eliminating resistance to both adoption and technology as drivers of acceptance, these two robust EHR’s are still viewed as having an adverse impact on two aspects of patient care, physician workflow and team communication. Both EHR’s had perceived strengths but also significant limitations and neither were able to satisfactorily address all of the physicians’ needs.Conclusion: Difficulties related to physician acceptance reflect real concerns about EHR impact on patient care. Physicians are optimistic about the future benefits of EHR systems, but are frustrated with the non-intuitive interfaces and cumbersome data searches of existing EHRs.


Author(s):  
Elease McLaurin ◽  
Ellen J. Bass ◽  
Kathryn H. Bowles ◽  
Paulina Sockolow

A study was conducted to investigate how well the design of an electronic health record (EHR) supported the shared understanding of medication-related information between home healthcare team members. EHR data from a home healthcare admission visit was obtained and reviewed for medication-related entries. Entries were characterized based on their location within the EHR interface. The analysis identified 50 different medication-related entries which were distributed across 18 EHR sections. The results highlight opportunities to improve the EHR design to better support a shared understanding between healthcare team members of medication-related information, and patient information more generally.


2019 ◽  
Vol 37 (27_suppl) ◽  
pp. 322-322
Author(s):  
Lauren E. Geisel ◽  
Helen M. Johnson ◽  
Andrew Weil ◽  
Mahvish Muzaffar ◽  
Nasreen A. Vohra ◽  
...  

322 Background: Clinical pathways are widely accepted tools for improving the quality of cancer care. We developed and implemented, within the electronic health record (EHR), a standardized multidisciplinary breast cancer conference template comprised of NCCN clinical pathway elements, with triggers to promote adherence and measure compliance. Methods: The records of breast cancer patients diagnosed from January 2016 to December 2017 were reviewed. Baseline data on (1) the documentation of clinical stage prior to prospective presentation at multidisciplinary conference, (2) documentation of family history, and (3) functional breast imaging utilization were recorded. EHR enhancements developed throughout 2018 were implemented in January 2019. Post-implementation data were obtained via an EHR query of records from January 2019 to the present. Results: At baseline, 56.5% of new patients (n = 435) had a clinical stage documented appropriately (goal 100%). After the EHR enhancements went live, this rate increased to 76.9% (n = 78 new diagnoses), ranging from 40% for patients with metastatic disease to 85.7% for non-metastatic. Compared with baseline data, EHR-derived data from 149 multidisciplinary conference notes demonstrated relatively stable rates of compliance with the family history and imaging metrics: 94.3% to 93.9% (goal 100%), and 12.8% to 13.4% (goal ≤20%), respectively. In 2019, there were 128 instances of an EHR trigger prompting physicians to review the multidisciplinary conference recommendations. While 89.1% of users responded that they reviewed the note, only 42.1% of these clicked on the link to view it. Conclusions: The EHR is a powerful tool for incorporating clinical pathways into oncology providers’ daily workflow. Quality improvement data can be extracted rapidly and efficiently, which facilitates continuous QI. We observed a notable improvement in documentation of clinical staging prior to multidisciplinary conference after the implementation of the clinical pathways in the EHR. Our first report identified several areas for improvement, which will be the focus of subsequent PDSA cycles.


2012 ◽  
Vol 30 (6) ◽  
pp. 300-311 ◽  
Author(s):  
PAULINA S. SOCKOLOW ◽  
KATHRYN H. BOWLES ◽  
HAROLD P. LEHMANN ◽  
PATRICIA A. ABBOTT ◽  
JONATHAN P. WEINER

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 45-46
Author(s):  
Mansour Gergi ◽  
Katherine Wilkinson ◽  
Insu Koh ◽  
Jordan Munger ◽  
Nicholas L Smith ◽  
...  

Introduction: Bleeding is an uncommon event but it is causes significant increase in morbidity and mortality. Identifying bleeding events using electronic health record data (both resulting from hospitalization and causing hospitalization) would allow the development of risk assessment models (RAM) to identify those at most risk. Traditional prospective cohorts for rare events are time consuming and expensive. We suggest a more efficient method using the electronic health record (EHR) data by developing and validating an algorithm to detect bleeding in hospitalized patients, ie, a "computable phenotype". Methods: We captured all admissions to the University of Vermont (UVM) Medical Center between 2010-19, a tertiary care medical center in northwest Vermont. Using International Classification of Disease (ICD) 9 and 10 discharge diagnoses, "present on admission" flags, problem lists, laboratory values, vital signs, current procedure terminology (CPT) codes, medication administration, and flowsheet data for transfusion support, we developed computable phenotypes for bleeding. Classification was based on the gold standard International Society of Thrombosis and Haemostasis definitions for clinically relevant non-major bleeding (CRNMB) and major bleeding (MB) and validated by medical record review. To improve sensitivity and specificity, algorithms were developed by bleeding site (intracerebral, intraspinal, pericardial, retroperitoneal, orbital, intramuscular, gastrointestinal, genitourinary, gynecologic, pulmonary, nasal, post-procedure, or miscellaneous). We preliminary validated the computable phenotype by randomly abstracting 10 medical records from each bleeding site. Results: Among 62,468 admissions, our computable phenotype for bleeding identified 10,202 bleeding events associated with hospitalization; 4,650 were CRNMB and 5,552 were MB. On chart abstraction, 135 of 153 hospitalizations had either a MB or CRNMB (88%, Figure). For MB, 95 of 119 (80%) of the computed MB phenytope events were validated. Of the 24 of 119 (20%) not validated, 14% (16) were CRNMB and 7% (8) the bleeding was present on coding but was not detected by chart review. Only 29%(10/34) of the CRNMB were validated. The most common error in the CRNMB computable phenotype was misclassification of 14 MB as CRNMB (41% of CRNMB. For individual bleeding sites, (figure), the algorithms performed well for most sites including intracerebral hemorrhage, gastrointestinal, and intramuscular bleeding, but performed less well for unusual and rarer bleeding sites (i.e. nasal). Conclusion: We developed a computable phenotype for bleeding which can be applied to our EHR system. The computable phenotype was specific for MB, but underestimated the severity of potential CRNMB. Importantly, we correctly classified specific important bleeding sites such as intracerebral, gastrointestinal, and retroperitoneal. This computable phenotype forms the basis for further refinement, and provides a road map for future studies on epidemiology of hospital-acquired bleeding and hospitalization for bleeding. Figure: Major and Clinically relevant non-major bleeding as detected by Electronic Health Record compared to the chart validation Figure 1 Disclosures No relevant conflicts of interest to declare.


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