scholarly journals Quality Improvement Initiative to Improve Tobacco Cessation Efforts in Radiation Oncology

2019 ◽  
Vol 15 (4) ◽  
pp. e382-e388 ◽  
Author(s):  
Lisa Singer ◽  
Keith Sharee ◽  
Lauren Boreta ◽  
William R. Silveira ◽  
Steve Braunstein ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Quality Improvement ◽  
Electronic Health Record ◽  
Radiation Oncology ◽  
Tobacco Cessation ◽  
Quality Improvement Initiative ◽  
Health Record ◽  
Electronic Health ◽  
Readiness To Quit ◽  
Current Tobacco

PURPOSE: Although continued tobacco use in patients who are treated with radiation therapy is associated with inferior outcomes and increased treatment-related toxicity, multiple studies have shown that current tobacco cessation efforts in oncology are insufficient. A quality improvement (QI) initiative was developed with the goal of improving tobacco cessation efforts in radiation oncology. METHODS: Using iterative plan-do-study-act cycles, barriers to tobacco cessation were identified and then addressed with a single-institutional QI initiative designed to improve physician assessment of patient readiness to quit tobacco by 50% or more. Residents assessed readiness to quit tobacco during new patient consultations and recorded this assessment in prespecified fields within the electronic health record. Feedback on assessment efforts was provided to our department via an automated search of the electronic health record. RESULTS: From December 2014 to February 2015, before the initiation of the QI initiative, 4% of patients were assessed for their readiness to quit tobacco. After implementing the initiative, 67% of patients were assessed for their readiness to quit. CONCLUSION: After instituting a QI initiative at our institution, significantly more patients were assessed for readiness to quit tobacco before treatment with radiation therapy. Ongoing efforts in our department are aimed at improving the efficacy of this intervention.

scholarly journals Practice Facilitator Strategies for Addressing Electronic Health Record Data Challenges for Quality Improvement: EvidenceNOW

2018 ◽  
Vol 31 (3) ◽  
pp. 398-409 ◽  
Author(s):  
Jennifer R. Hemler ◽  
Jennifer D. Hall ◽  
Raja A. Cholan ◽  
Benjamin F. Crabtree ◽  
Laura J. Damschroder ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Electronic Health Record ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Record Data ◽  
Electronic Health

scholarly journals Pilot Study of Meaningful Use of Electronic Health Records in Radiation Oncology

2012 ◽  
Vol 8 (4) ◽  
pp. 219-223 ◽  
Author(s):  
Xinglei Shen ◽  
Adam P. Dicker ◽  
Laura Doyle ◽  
Timothy N. Showalter ◽  
Amy S. Harrison ◽  
...  
Keyword(s):  
Pilot Study ◽  
Electronic Health Records ◽  
Electronic Health Record ◽  
Radiation Oncology ◽  
Meaningful Use ◽  
Health Record ◽  
Health Records ◽  
Widespread Adoption ◽  
Electronic Health

Most large academic radiation oncology practices have incorporated electronic health record systems into practice and plan to meet meaningful use requirements. Further work should focus on needs of smaller practices, and specific guidelines may improve widespread adoption.

scholarly journals Implementing a quality improvement initiative for the management of chronic obstructive pulmonary disease in rural Nepal

2019 ◽  
Vol 8 (1) ◽  
pp. e000408 ◽  
Author(s):  
Stephen Mehanni ◽  
Dhiraj Jha ◽  
Anirudh Kumar ◽  
Nandini Choudhury ◽  
Binod Dangal ◽  
...  
Keyword(s):  
Chronic Obstructive Pulmonary Disease ◽  
Quality Improvement ◽  
Disease Management ◽  
Electronic Health Record ◽  
Pulmonary Disease ◽  
Chronic Obstructive ◽  
Health Record ◽  
Obstructive Pulmonary Disease ◽  
Low Middle Income Countries ◽  
Electronic Health

BackgroundChronic obstructive pulmonary disease accounts for a significant portion of the world’s morbidity and mortality, and disproportionately affects low/middle-income countries. Chronic obstructive pulmonary disease management in low-resource settings is suboptimal with diagnostics, medications and high-quality, evidence-based care largely unavailable or unaffordable for most people. In early 2016, we aimed to improve the quality of chronic obstructive pulmonary disease management at Bayalpata Hospital in rural Achham, Nepal. Given that quality improvement infrastructure is limited in our setting, we also aimed to model the use of an electronic health record system for quality improvement, and to build local quality improvement capacity.DesignUsing international chronic obstructive pulmonary disease guidelines, the quality improvement team designed a locally adapted chronic obstructive pulmonary disease protocol which was subsequently converted into an electronic health record template. Over several Plan-Do-Study-Act cycles, the team rolled out a multifaceted intervention including educational sessions, reminders, as well as audits and feedback.ResultsThe rate of oral corticosteroid prescriptions for acute exacerbations of chronic obstructive pulmonary disease increased from 14% at baseline to >60% by month 7, with the mean monthly rate maintained above this level for the remainder of the initiative. The process measure of chronic obstructive pulmonary disease template completion rate increased from 44% at baseline to >60% by month 2 and remained between 50% and 70% for the remainder of the initiative.ConclusionThis case study demonstrates the feasibility of robust quality improvement programmes in rural settings and the essential role of capacity building in ensuring sustainability. It also highlights how individual quality improvement initiatives can catalyse systems-level improvements, which in turn create a stronger foundation for continuous quality improvement and healthcare system strengthening.

scholarly journals Implementation of the Electronic Health Record-Embedded Radiation Oncology Pathways in Two Institutions

2020 ◽  
Vol 108 (3) ◽  
pp. e778
Author(s):  
M. Werner-Wasik ◽  
N.A. DeGregorio ◽  
L. Babinsky ◽  
A. Taylor ◽  
M.D. Hurwitz ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Radiation Oncology ◽  
Health Record ◽  
Electronic Health

The Surgical Risk Preoperative Assessment System: Determining which predictor variables can be automatically obtained from the electronic health record

2019 ◽  
Vol 24 (6) ◽  
pp. 230-237 ◽  
Author(s):  
Robert A Meguid ◽  
Michael R Bronsert ◽  
Karl E Hammermeister ◽  
David P Kao ◽  
Anne Lambert-Kerzner ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Electronic Health Record ◽  
Preoperative Assessment ◽  
Assessment System ◽  
Predictor Variables ◽  
Health Record ◽  
Improvement Program ◽  
Surgical Quality ◽  
Surgical Risk ◽  
Electronic Health

Introduction The Surgical Risk Preoperative Assessment System is a parsimonious, universal surgical risk calculator integrated into our local electronic health record. We determined how many of its eight preoperative risk predictor variables could be automatically obtained from the electronic health record. This has implications for the usability and adoption of Surgical Risk Preoperative Assessment System, serving as an example of use of electronic health record data for populating clinical decision support tools. Methods We quantified the availability and accuracy in the electronic health record of the eight Surgical Risk Preoperative Assessment System predictor variables (patient age, American Society of Anesthesiology physical status classification, functional health status, sepsis, work Relative Value Unit, in-/outpatient operation, surgeon specialty, emergency status) at the patient’s preoperative encounter of 5205 patients entered into the American College of Surgeons National Surgical Quality Improvement Program. Accuracy was determined by comparing the electronic health record data to the same patient’s National Surgical Quality Improvement Program data, used as the “gold standard.” Acceptable accuracy was defined as a Kappa statistic or Pearson correlation coefficient ≥0.8 when comparing electronic health record and National Surgical Quality Improvement Program data. Acceptable availability was defined as presence of the variable in the electronic health record at the preoperative encounter ≥95% of the time. Results Of the eight predictor variables, six had acceptable accuracy. Only preoperative sepsis and functional health status had Kappa statistics <0.8. However, only patient age and surgeon specialty were ≥95% available in the electronic health record at the preoperative visit. Conclusions Processes need to be developed to populate more of the Surgical Risk Preoperative Assessment System preoperative predictor variables in the patient’s electronic health record prior to the preoperative visit to lessen the burden on the busy surgeon and encourage more widespread use of Surgical Risk Preoperative Assessment System.

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