Enhancing the electronic health record to promote and measure adherence to breast cancer clinical pathways.

2019 ◽  
Vol 37 (27_suppl) ◽  
pp. 322-322
Author(s):  
Lauren E. Geisel ◽  
Helen M. Johnson ◽  
Andrew Weil ◽  
Mahvish Muzaffar ◽  
Nasreen A. Vohra ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
Electronic Health Record ◽  
Clinical Pathways ◽  
Clinical Stage ◽  
Baseline Data ◽  
Clinical Staging ◽  
Health Record ◽  
Electronic Health ◽  
Multidisciplinary Conference

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.

Enhancing goals of care communication by oncologists using a pathway-based intervention.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 324-324
Author(s):  
Isaac S. Chua ◽  
Elise Tarbi ◽  
Jocelyn H. Siegel ◽  
Kate Sciacca ◽  
Anne Kwok ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Advanced Cancer ◽  
Language Processing ◽  
Clinical Pathways ◽  
Free Text ◽  
Health Record ◽  
Goals Of Care ◽  
Progress Notes ◽  
Electronic Health ◽  
Pilot Sample

324 Background: Delivering goal-concordant care to patients with advanced cancer requires identifying eligible patients who would benefit from goals of care (GOC) conversations; training clinicians how to have these conversations; conducting conversations in a timely manner; and documenting GOC conversations that can be readily accessed by care teams. We used an existing, locally developed electronic cancer care clinical pathways system to guide oncologists toward these conversations. Methods: To identify eligible patients, pathways directors from 12 oncology disease centers identified therapeutic decision nodes for each pathway that corresponded to a predicted life expectancy of ≤1 year. When oncologists selected one of these pre-identified pathways nodes, the decision was captured in a relational database. From these patients, we sought evidence of GOC documentation within the electronic health record by extracting coded data from the advance care planning (ACP) module—a designated area within the electronic health record for clinicians to document GOC conversations. We also used rule-based natural language processing (NLP) to capture free text GOC documentation within these same patients’ progress notes. A domain expert reviewed all progress notes identified by NLP to confirm the presence of GOC documentation. Results: In a pilot sample obtained between March 20 and September 25, 2020, we identified a total of 21 pathway nodes conveying a poor prognosis, which represented 91 unique patients with advanced cancer. Among these patients, the mean age was 62 (SD 13.8) years old; 55 (60.4%) patients were female, and 69 (75.8%) were non-Hispanic White. The cancers most represented were thoracic (32 [35.2%]), breast (31 [34.1%]), and head and neck (13 [14.3%]). Within the 3 months leading up to the pathways decision date, a total 62 (68.1%) patients had any GOC documentation. Twenty-one (23.1%) patients had documentation in both the ACP module and NLP-identified progress notes; 5 (5.5%) had documentation in the ACP module only; and 36 (39.6%) had documentation in progress notes only. Twenty-two unique clinicians utilized the ACP module, of which 1 (4.5%) was an oncologist and 21 (95.5%) were palliative care clinicians. Conclusions: Approximately two thirds of patients had any GOC documentation. A total of 26 (28.6%) patients had any GOC documentation in the ACP module, and only 1 oncologist documented using the ACP module, where care teams can most easily retrieve GOC information. These findings provide an important baseline for future quality improvement efforts (e.g., implementing serious illness communications training, increasing support around ACP module utilization, and incorporating behavioral nudges) to enhance oncologists’ ability to conduct and to document timely, high quality GOC conversations.

scholarly journals An immune memory and negative selection to visualizing clinical pathways from electronic health record data

2020 ◽  
Vol 19 (1) ◽  
pp. 336
Author(s):  
Mouna Berquedich ◽  
Oulaid Kamach ◽  
Malek Masmoudi ◽  
Laurent Deshayes
Keyword(s):  
Electronic Health Record ◽  
Clinical Pathways ◽  
Immune Memory ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Specific Analysis ◽  
Record Data ◽  
Electronic Health ◽  
Structuring Knowledge ◽  
Treatment Order

Clinical pathways indicate the applicable treatment order of interventions. In this paper we propose a data-driven methodology to extract common clinical pathways from patient-centric Electronic Health Record data (EHR). The analysis of  patient's, can lead to better regarding pathologies. The proposed algorithmic methodology consist to designing a system of control and analysis of patient records based on an analogy between the elements of the new EHRs and the biological immune systems. The detection of patient profiles ensured by biclustering Matrix. We rely on biological immunity to develop a set of models for structuring knowledge extracted from EHR and to make pathway analysis decisions. A specific analysis of the functional data leds to the detection of several types of patients who share the same EHR information. This methodology demonstrates its ability to simultaneously processing data, and is able to providing information for understanding and identifying the path of patients as well as predicting the path of future patients.

An Analysis of Electronic Health Record Work to Manage Asynchronous Clinical Messages among Breast Cancer Care Teams

2021 ◽  
Vol 12 (04) ◽  
pp. 877-887
Author(s):  
Bryan D. Steitz ◽  
Kim M. Unertl ◽  
Mia A. Levy
Keyword(s):  
Breast Cancer ◽  
Electronic Health Record ◽  
Cancer Care ◽  
Medical Center ◽  
Asynchronous Communication ◽  
Care Team ◽  
Health Record ◽  
Breast Cancer Care ◽  
Team Members ◽  
Electronic Health

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.

scholarly journals An Electronic Health Record–based Algorithm to Ascertain the Date of Second Breast Cancer Events

Medical Care ◽  
2017 ◽  
Vol 55 (12) ◽  
pp. e81-e87 ◽  
Author(s):  
Jessica Chubak ◽  
Tracy Onega ◽  
Weiwei Zhu ◽  
Diana S. M. Buist ◽  
Rebecca A. Hubbard
Keyword(s):  
Breast Cancer ◽  
Electronic Health Record ◽  
Health Record ◽  
Electronic Health ◽  
Second Breast Cancer

scholarly journals Improving Utilization of the Family History in the Electronic Health Record

2016 ◽  
Vol 49 (1) ◽  
pp. 80-86 ◽  
Author(s):  
Kathleen T. Hickey ◽  
Maria C. Katapodi ◽  
Bernice Coleman ◽  
Karin Reuter-Rice ◽  
Angela R. Starkweather
Keyword(s):  
Family History ◽  
Electronic Health Record ◽  
Health Record ◽  
The Family ◽  
Electronic Health

scholarly journals Electronic Health Record Phenotypes for Precision Medicine: Perspectives and Caveats From Treatment of Breast Cancer at a Single Institution

2018 ◽  
Vol 11 (1) ◽  
pp. 85-92 ◽  
Author(s):  
Matthew K. Breitenstein ◽  
Hongfang Liu ◽  
Kara N. Maxwell ◽  
Jyotishman Pathak ◽  
Rui Zhang
Keyword(s):  
Breast Cancer ◽  
Electronic Health Record ◽  
Precision Medicine ◽  
Health Record ◽  
Single Institution ◽  
Electronic Health
Sign in / Sign up

Export Citation Format

Share Document