bluuebunny/crossref_metadata_2025 huggingface dataset:
Implementation of a patient experience–focused review at the time of radiation therapy simulation.
Authors: Robertson John M. , Rutka Elizabeth , Ye Hong
Published: September 2018

211

Background: Anxiety impairs information retention and may lower patient satisfaction. Because anxiety is highest at the time of radiation therapy (RT) simulation, we added a personal patient experience (PX) review of the treatment process focusing on resolution of any outstanding concerns and measured for a benefit using patient satisfaction scores. Methods: A single PX trained Senior Radiation Therapist met patients at simulation and reviewed multiple factors from registration to any outstanding medical issues, with the goal of addressing and resolving all questions. A CMS-approved patient satisfaction tool was recorded during this time to assess for any benefit of this PX review. The tool asks 17 questions in 5 domains (Registration, Facility, Your Treatment, Personal Issues, and Overall Assessment) and calculates an Overall Facility Rating. Tools received between the date of simulation and the date of follow-up were considered an on-treatment evaluation and were used for assessment. Scores were compared with a Mann-Whitney U test. There were no other formal departmental patient satisfaction efforts during this time. Results: Between 2/16 and 6/18 a total of 1369 patients (median 65 yrs; 64% women; 38% breast cancer; 82% curative) were met at simulation by our Senior Therapist spending a median of 23 minutes per patient (range 0 – 117). We received 732 patient satisfaction surveys (median 67 yrs; 61% women; 40% breast cancer; 90% curative) including 98 on-treatment respondents, 69 of whom had the PX review and reported significantly better scores for 10 of the 17 questions and 4 of the 5 domains (Registration p = 0.04, Facility p = 0.03, Personal Issues p = 0.02, Overall Assessment p = 0.002). The PX review was significantly better for the calculated Overall Facility Rating (p = 0.04). Conclusions: The PX review at simulation was associated with significantly higher patient satisfaction scores in 4 of 5 domains, including areas not specifically addressed during the interview (e.g. cleanliness). Improvements of this amount are typically associated with very large improvements in percentile rankings. This intervention was extremely successful but durability of this benefit into the follow up period was not assessed.
Improving patient-centered oral chemotherapy at an academic cancer center.
Authors: Lim Charles Henry , Petronis Jennifer , Mellor Sabrina , Krzyzanowska Monika K.
Published: September 2018

212

Background: Despite established standards for prescribing and monitoring oral anti-cancer medications (OAC) and validated tools supporting OAC patient education, substantial quality gaps remain. Methods: To identify local gaps in care for patients receiving OAC, we used a patient survey in the GI and Endocrine medical oncology clinic. Providers were also interviewed. The survey consisted of 23 questions addressing three domains (treatment plan (T) education, self-management (S) education and health team communication (C) as well as a single question overall satisfaction score. A composite average score encompassing all 23 questions was generated. Questions were derived from ASCO chemotherapy standards and validated patient communication instruments and scored on a 5-point Likert scale. Subsequently, individualized drug-specific written care plans guiding patient education were developed and tested in iterative PDSA cycles. The aim was to improve the composite average patient survey score by 10%. The same patient survey was used to assess the impact of the change ideas. Results: We collected 32 patient surveys, 21 pre- and 11 post-intervention. Baseline surveys indicated lowest scores in the C domain. Providers reported variation in education content and communication techniques used. Care plans with standardized content for 8 OAC agents were tested in simulated and clinic settings in a stepwise fashion, with implementation beginning in Feb 2018. Providers received training on integrating the care plans into clinic workflow. The composite average score for all 23 items improved from 4.18 to 4.29. The single question overall satisfaction score improved from 4.17 to 4.45. Improvement was noted across all 3 domains (T: 4.31 → 4.41, S: 4.26 → 4.36, C: 4.00 → 4.15). For balancing measures, provider teaching time per patient initially rose following implementation before returning to baseline. Conclusions: The intervention led to improvement in the patient experience when starting OAC. Standardized content and a framework guiding provider communication were key elements of the change ideas. To meet the study aim, further PDSA cycles integrating teach back methodology and proactive phone follow up are ongoing.
Consumer demand and implementation of a scalp cooling program at a multi-site organization.
Authors: Featherstone Ashley , Hernandez Karen , Fischer-Cartlidge Erica , Ross Mikel , Haase Curt
Published: September 2018

214

Background: Alopecia is so feared that patients may opt to forgo treatment or elect for a less effective treatment to prevent it. Consumer demand for scalp cooling has been on the rise recently and has escalated since the Food and Drug Administration cleared the use of scalp cooling machines to minimize chemotherapy-induced alopecia. This organization required a clinical support model to implement this unique intervention and to establish its own benchmarks for safety and quality. Methods: With no precedent for implementation, nursing, administration, facilities, information technology, finance and legal collaboratively established a process for integrating scalp cooling into current practice. Policies, patient education, staff training programs, billing codes and electronic documentation were created; technological solutions for tracking and scheduling patients at multiple sites were established; infection control and biomedical machine management systems were put into place. Results: Initially, eight sites offered scalp cooling for female breast cancer patients receiving alopecia-inducing chemotherapy. After expanded approval for all solid tumor patients, the program grew to all sites (n = 13) providing chemotherapy using one standard process. All sites implemented scalp cooling utilizing existing treatment space and schedules. To date, more than 800 cooling treatments have occurred. Conclusions: Patient priorities must be clinician priorities. A multi-site organization must respond to new research and consumer demand. Successful integration into the patient experience depends on alignment between providers, nursing, and support departments and forward thinking for scalability.
A description of the free text word choices physicians use to describe prognosis in over 50,000 electronic treatment plans.
Authors: Wilfong Lalan S. , Ferencik Mark , Neubauer Marcus A.
Published: September 2018

219

Background: Fourteen practices within the US Oncology Network are participating in the Center for Medicare and Medicaid Innovation’s (CMMI) Oncology Care Model. To meet the requirement of documenting a care plan that contains the 13 components in the Institute of Medicine Care Management Plan, an electronic treatment plan was developed which incorporates core elements from our EMR, IKnowMed, supplemented by additional physician documentation. Physicians must document in their own words the prognosis section of the care plan. Methods: To better understand the word choices physicians use for prognosis, we evaluated the word choices used in over 50,000 treatment plans. Using an excel based word count macro, all contents of the free text entry “prognosis” field were sorted based on frequency of the same answer and were then ranked from most common use to least common. A word count method was applied to determine and rank the most commonly used words across all answers. The “current status of disease” field in the treatment plan was used to divide the prognosis answers into those that mentioned “Metastatic” and “Not Metastatic” so that prognosis wording trends could be compared using pivot tables and data filters. Results: 70% of prognosis word choices were single words: “excellent, good, fair, poor, or guarded” were the most common. 20% of phrases were multi-word that appeared repeatedly such as “will depend on the response to therapy.” Only 10% of answers were uniquely worded per treatment plan and felt to be personal to the patient’s situation. Additionally, the number of words did not differ between metastatic and non-metastatic disease. Conclusions: To our knowledge, this is the largest cohort of treatment plans where the word choices used by physicians are described to document prognosis to patients. The results indicate that single words or short phrases are commonly used to describe prognosis when the treatment plan is shared with patients. The data set has high potential for further study to better understand the role and impact of written treatment plans (including downstream events) to help physicians refine this documentation for better patient understanding of this important topic.
Development of a person-centered patient portal in oncology using stakeholder co-design.
Authors: Kildea John , Hijal Tarek , Hendren Laurie
Published: September 2018

221

Background: Patient portals are software products that provide care recipients (patients) with access to some or all of their personal health information (PHI) within a healthcare institution’s electronic medical record (EMR). Most patient portals are just that–windows into an EMR. However, in today’s connected world, a patient portal can offer much more than just access to PHI. By exploiting modern technology and by recognizing that care recipients are people with complex needs that extend beyond just the delivery of care, patient portals can be person-centered. Such person-centered needs include: the ability to plan ahead and know one’s position in a waiting list, to feel in control of one’s own care, to understand one’s treatment options, and to share in all decision-making about one’s care. Methods: We used stakeholder co-design, involving care recipients, care providers (clinicians) and technical experts at all levels, to design and develop a person-centered patient portal from within the healthcare system. Results: Our mobile-friendly patient portal, known as Opal (opalmedapps.com), contains the following: One-stop multi-speciality and multi-institutional operation; Appointment schedule with personalized appointment preparation guidelines; Appointment check-in and waiting room management tools; Monitoring of step-by-step radiotherapy treatment planning; Access to PHI contextualized with explanatory information; Access to personalized educational materials; Patient-reported outcomes questionnaires with response visualizations; An automated rules-based system to minimize clinician workload; Triggered notifications to alert patients and clinicians to actionable events. Conclusions: Opal is currently in beta release involving a small number of oncology patients at our centre who are providing feedback about its use and usefulness. Their initial feedback is very positive and enthusiastic. A full pilot study is starting by July 2018.
A process for improving patient survey scores in the oncology care model (OCM).
Authors: Perry Manuel , Rudy-Tomczak Katie , Hines Scott
Published: September 2018

222

Background: The Oncology Care Model is an alternative payment model created by The Center for Medicare and Medicaid Services. Our goal was to improve patient education and to improve the patient experience. We hired nurse practitioners to achieve this. Methods: Crystal Run Healthcare is a multi-specialty group practice with nine oncologists. A total of 4 nurse practitioners have been hired since implementation of the OCM Program in July 1, 2016. All oncology patients and their family who are scheduled to initiate a new treatment program or a change in an existing treatment are scheduled to meet with a nurse practitioner for 60-75 minutes in order to review details of their treatment including a 13-point treatment summary recommended by the Institute of Medicine. Results: CMS administered anonymous patient surveys at baseline and in rolling 6 month episodes reported every 3 months. Data is represented from January-September 2016 (baseline)and is compared to July 2016-March 2017. Since implementation of our nurse practitioner access program, patient survey scores improved dramatically. Average overall rating improved from the 11th-20th percentile to 71st-80th percentile. The most dramatic improvement occurred in shared decision making which improved from 11th-20th percentile to the 91st-99th percentile. Conclusions: The addition of nurse practitioners who are tasked with educating patients regarding their treatment offers an opportunity for patients to have a comprehensive visit to review treatment details. The most striking improvement was seen in shared decision making which likely reflects the benefits of a prolonged discussion between the nurse practitioner, the patient and their family.[Table: see text]
Increasing the percentage of advance directives in patient medical records.
Authors: Waynick Christopher A. , Conwill Jan , Gian Victor
Published: September 2018

226

Background: Advance care planning is often initiated too late, which leads to added stress and high resource utilization at the end of life which is contrary to many patients’ wishes. Ideally, discussing patient’s wishes should start early. An advance directive (AD) documents patient preferences for end-of-life care. Methods: In order to improve this process, the team used the DMAIC process: Define, Measure, Analyze, Improve, and Control. In the define phase, 79 new cancer diagnosis patients’ medical records were reviewed and completed. This revealed that 25.58% of these patients claim to have an AD, but only 5% have an AD documented in their record within 30 days of their first visit. Upon further discussion with staff, there was no standard process. The focus performance metric for the project was to have the AD in the chart within 30 days of their first visit. Goal was set at 20%. Analyzing the process was as follows: Process map, Fishbone diagram to determine potential improvements. Priority pay-off matrix. The most effective process change would be to add a notice in the new patient packet for the patient to bring their AD with them to their first visit. Results: The first iteration of the improve phase included the notice created in the analyze phase. After completion, 60% of patients had an AD in their chart within 30 days of their first visit. For the second iteration, the team worked with psychology staff to create a letter to the patient explaining the advantages of having an AD in the chart. Results were 100% of the performance improvement metric. Controlling this process change is simple, but continuing a 100% target is difficult. Some patients who do not have an AD in their chart feel uncomfortable with it or do not understand what it is. Future improvements include patient education processes and provider discussions with the patients to ensure an 80% target is maintained. Conclusions: The team learned developing and communicating a formal process is imperative to achieving the target. Also important is to communicate clearly with the patients, enabling them to understand what (and why) their provider needs from them.
Standardized approach to incident management across a radiation oncology network.
Authors: Frey Seth D , McAleer Mary Frances , Walker Gary , Natter Rachel Bissonnett , Edwards Timothy , Koong Albert , Herman Joseph M. , Minsky Bruce D. , Khan Mohamed K , Dragun Anthony E. , Olson Michael R , Gabel Molly , Bierman Robin , Turner Lehendrick , Llorente Manolo , de Carvalho Icaro Thiago , Selek Ugur , Hahn Stephen M. , Kuban Deborah A.
Published: September 2018

235

Background: Quality and safety reporting is one of the most important aspects of creating a culture of safety. As part of a multidisciplinary Cancer Network, the Radiation Oncology Division at the lead institution devised an electronic incident reporting system that was implemented at the Network partners to define, standardize, quantify, and trend incidents in the radiation oncology treatment and care process. The purpose of this study is to assess robustness of the system, initial trends seen, and potential to improve quality and safety of the Network practice. Methods: Beginning in January 2017, the incident reporting system at the lead institution was configured to provide inclusion of 13 partnering radiation oncology facilities. Over one year, the organizations were on-boarded and trained on the use of the application. Descriptive analyses of the data from the use of this new reporting system were used in this study. Results: From January 1, 2017 to April 30 2018, a total of 832 incident reports were submitted by 13 different facilities. The average number of days from event submission to resolution was reduced to 10.25 days, compared with up to 60 days before implementation of the new central reporting system. The change in reporting rate was variable across the partner sites following implementation of the new system. The most frequent event types reported included ineffective communication (13%), planning-related problems (5%), incomplete or missing simulation orders (5%), and scheduling error or conflict (4%). Conclusions: Implementation of a centralized reporting system across a network of partner sites has greatly improved the overall reporting process, with reduced event resolution time and increased capability of tracking and trending incidents. By standardizing incident reporting across institutions, there are multiple opportunities to augment a strong culture of safety.
Use of a chemotherapy toxicity prediction tool to decrease the risks for hospitalization in the elderly.
Authors: Mintchev Mintcho Elinov , Bersabe Adrian Reyes
Published: September 2018

256

Background: Oncologists commonly use performance status scores such as ECOG and Karnofsky when making treatment decisions. However, there is limited data on the utility of these measures in selecting therapy and predicting treatment-related complications in the elderly. In July 2016, medical oncologists at our institution made it standard practice to use the Cancer and Aging Research Group toxicity prediction score (CARG) to identify elderly patients who are “fit” for conventional therapy versus those who are “frail” and may experience increased complications. Methods: We retrospectively reviewed referrals to our outpatient medical oncology clinic for patients 75 years of age and older. Referrals leading to systemic therapy (i.e. chemotherapy, targeted therapy, and immunotherapy) or changes to conventional therapy based on CARG were included in our study. We evaluated CARG utilization during the 6 months before and the 6 months after its institution. We also assessed how changes to therapy due to CARG impacted admissions and emergency department (ED) visits. Results: Thirty-eight patients with mean age of 81.2 years, 52.6% male, met inclusion criteria. Their diagnoses included GI (36.8%), lung (21.1%), hematologic (18.4%), breast (10.5%), GU (2.6%), and other (10.5%) malignancies. During 2016, CARG was assessed in 14 patients, 9 of whom received systemic therapy. CARG was assessed in 12.5% and 41.2% of patients receiving systemic therapy in the 6-month periods before and after its incorporation, respectively. Patients whose therapy was decreased in intensity or withheld based on CARG had fewer mean admissions (0.7 versus 2.25), days of admission (4.3 versus 8), and ED visits (1.1 versus 2.5) compared to those who received conventional therapy. However, the study lacked power to establish statistical significance. Conclusions: A CARG assessment occurred in less than 50% of elderly cancer patients who received systemic therapy and further inquiry may help formulate interventions to increase its adoption. Therapy modifications based on CARG may lead to fewer hospitalizations, admission days, and ED visits, but more consistent use of the score and further investigation are necessary.
Use of pregabalin for preemptive analgesia in an enhanced recovery after surgery program.
Authors: Cain Katherine , Hoang Nhi , Iniesta Maria , Pitcher Brandelyn , Corzo Camila , Meyer Larissa , Lasala Javier , Ramirez Pedro T
Published: September 2018

265

Background: A key component of any Enhanced Recovery After Surgery (ERAS) program is standardized multimodal analgesia to minimize opioid use. Our program utilizes acetaminophen, nonsteroidal anti-inflammatory agents and gabapentanoids perioperatively. The primary aim of our study was to evaluate pregabalin use after surgery and impact on total morphine equivalent daily dose (MEDD). Methods: Data was collected retrospectively on consecutive ERAS patients who underwent open gynecologic surgery from 3/4/2016 through 2/22/2018. We excluded any patient identified as a chronic opioid user. Standard preoperative medications included 300 mg tramadol ER, 75 mg pregabalin, and 400 mg celecoxib per institutional guidelines. Standard postoperative pain regimen included scheduled oral acetaminophen, ibuprofen and pregabalin unless contraindicated with rescue oral oxycodone and IV hydromorphone as needed. Pregabalin was ordered 75 mg twice daily for 4 doses. Recommended exceptions to pregabalin included hypersensitivity or age greater than 65 years. Median and range were calculated to summarize continuous variables. Spearman’s rank was used to test the correlation between post-operative pregabalin dose and MEDD. Results: A total of 533 patients were included for analysis. Twelve patients were excluded for chronic opioid use. 38% of patients received all four post-operative pregabalin doses (207/533). 32.8% of patients received no pregabalin (175/533). The fourth dose was the most common missed dose (274/533, 51.4%). The top reasons dose 4 was missed included not being ordered (58.8%) and patient already discharged (12.4%). There were 202 patients older than 65 years, the majority of these patients received no post-operative pregabalin (123/202, 60.9%). There was no difference in the amount of MEDD between those who received all pregabalin doses compared to those who received none (90.75 mg [4-663.5 mg] vs 82.5 mg [4-634.5 mg]; p = 0.269). Conclusions: Pregabalin for preemptive analgesia in an ERAS program does not decrease MEDD.
Representativeness of oncology clinical trials in Alberta.
Authors: Karim Safiya , Xu Yuan , Kong Shiying , Cheung Winson Y.
Published: September 2018

27

Background: The Institute of Medicine encourages broad participation by patients in clinical trials to “efficiently provide practice-changing evidence”. Enrolment of a representative sample of the general oncology population in clinical trials is essential to ensure that outcomes are generalizable and to ensure equity and social justice. Our aims were to 1) determine the characteristics of all cancer patients compared to those enrolled on a clinical trial and 2) to determine factors and outcomes associated with clinical trial participation. Methods: We assembled a large cohort of patients diagnosed with all solid malignancies between 2004 and 2016 in a large Canadian province. We collected information on age, sex, tumor type, Charlson comorbidity index (CCI), year of diagnosis, treatment type (surgery, chemo, radiation, and immunotherapy). Logistic regression was used to identify factors associated with clinical trial participation. Cox regression models were constructed to determine overall survival (OS). Results: We identified 146,294 patients with a cancer diagnosis, of which 43% were men and the mean age at diagnosis was 61 years (SD 15.6). Approximately 3% (4,364/146,294) of all patients were enrolled in a clinical trial. Baseline characteristics showed that clinical trial patients were younger (mean age 58 years vs 61 years), had fewer comorbidities (CCI 0 = 83% vs. 73%) and more often male (45% vs 43%). Compared to all patients, clinical trial patients were more likely to be younger (OR 0.98, p < 0.001), male (OR 1.21, 95% CI 1.10-1.32 p < 0.001), and to have a diagnosis of brain (OR 3.8, 95% CI 2.86-5.05, p < 0.001), kidney (OR 2.61, 95% CI 1.93-3.52) or breast cancer (OR 2.38, 95% CI 1.84-3.08). Compared to all patients and those not treated on clinical trial, patients on clinical trial had improved OS (HR 0.81, 95% CI 0.77-0.85, p < 0.001). Conclusions: Only a small proportion of real world patients are treated within a clinical trial. Characteristics of clinical trials patients are significantly different from all patients with cancer. More representative clinical trials are needed in order to reflect the real world cancer population.
National trends in end of life care for veterans with advanced cancer.
Authors: Smith Claire Elizabeth Powers , Coke Pat , Kluger Monica , Kamal Arif , Kelley Michael J.
Published: September 2018

3

Background: It is imperative to provide quality end of life (EOL) care for cancer patients. This entails minimizing aggressive measures at the EOL. Although rates of hospice utilization within the Veteran’s Health Administration have improved, chemotherapy administration and intensive care unit (ICU) admission at the EOL, indicators of aggressive care, are not clearly declining over recent years. Methods: We identified 32,665 veterans diagnosed with stage IV lung, colorectal, or pancreatic cancer who died between 2009-2016 using VA cancer registry and Corporate Data Warehouse data through a novel EOL Dashboard Tool, which has been validated at multiple VA sites. This EOL tool reports three indicators; incidence of chemotherapy use in the last 14 days of life, ICU admission in the last 30 days of life and hospice admission or consult. Change over time, 2009-2016, was assessed using a repeated measures one-way ANOVA with post hoc test for linear trend of time for individual cancers and two-way ANOVA for all cancers combined. Results: Chemotherapy use in the last 14 days of life declined from 6.8% in 2009 to 4.4% in 2016 (p < 0.05). ICU admission in the last 30 days did not change significantly, from 13.3% in 2009 to 14.7% in 2016. The exception was stage IV lung cancer patients in whom ICU admissions increased from 12.9% to 16.2% (p = 0.01). Patients utilizing hospice services increased from 32.4% to 52.6% (p < 0.01). When combined for all years in an unadjusted analysis by VA regional network (VISN), chemotherapy use ranged geographically from 4.2% to 8.1% and for ICU admission from 8.4% to 18.0%. Conclusions: While chemotherapy administration at the EOL is declining for veterans with stage IV cancer, ICU admissions are unchanged and becoming more common in stage IV lung cancer despite increasing hospice utilization. Compared to prior Medicare reports, veterans have similar rates of EOL chemotherapy use and fewer EOL ICU admissions, adding to a growing body of literature showing that despite veterans having poorer health and utilizing more medical resources, the VA performs at or above non-veteran health care institutions on end of life cancer care. There is notable geographic variation in aggressive EOL care.
Analyzing pathways data to reduce unwarranted variation, understand practice patterns, and update pathways.
Authors: Hall Julia Cooper , Hamilton Joanna M. , Jackman David Michael , Tremonti Carole Kathleen , Greenberg Teresa L. , Hayne Victoria , Stein Leah A. , Jacobson Joseph O.
Published: September 2018

300

Background: A clinical pathways program requires regular updates to pathways content, real-time decision support, and data collection and analysis of decisions made. A goal of Dana-Farber Pathways (DFP) is to analyze data to reduce unwarranted variation and inform granular, warranted variation. Methods: Each of our 31 medical oncology pathways is created and updated by DF experts (clinicians and scientists). DFP is implemented through a web-based portal that provides real-time decision support. DFP captures on- and off- pathway treatment decisions and reasons for off-pathway decisions; this is shared with each disease group monthly. For each interval review meeting we assess on-pathway rates and decisions for each node in the pathway. Low on-pathway rates prompt discussion about possible action, including provider education or pathway modification. Results: In 2017, 7,460 total treatment decisions were collected through DFP; 78% were on-pathway. We have clinical reasoning for 90% of the off-pathway decisions. Off-pathway analysis has been used in several important ways: 1. Catalyzing change: we detected early adoption of immunotherapy in small cell lung cancer and discussed the relevant data. The pathway was updated to adopt this class of treatment. 2. Understanding unexpected events: we identified a recent etoposide shortage and discussed alternate recommendations. They were added to the pathway in case of future shortages. 3. Provider education: we detected a consistently low on-pathway rate in one location, mostly driven by a specific provider. This provided a mechanism to discuss practice patterns and provide targeted education. Conclusions: Off-pathway analysis provides insight into user variation, fosters and supports peer coaching, and supports the creation of dynamic, up-to-date pathways.[Table: see text]
Creating an end-of-life dashboard with administrative data.
Authors: Wong Tracy , Mezheritsky Irina , Jagels Barbara , Loggers Elizabeth Trice
Published: September 2018

304

Background: The care given at the End of Life (EoL) is a topic of great interest for cancer patients, oncologists and insurers. This focus has been guided by a desire to achieve the highest quality of life (QoL) near the end of life while simultaneously decreasing costs of what is deemed by many as futile life-sustaining efforts. While EoL measures are reported by hospitals and clinics to external quality programs, the ability for a single center to sustainably measure these data proves burdensome, thus limiting the ability to assess and monitor for the purposes of improvement. Seattle Cancer Care Alliance (SCCA), a single comprehensive cancer center, set out to create regular, accessible and actionable EoL reporting. Methods: This project was broken into 5 phases: (1) Determining rationale for reporting and defining the audience(s). (2) Defining the patient population and measures of interest. (3) Identifying data sources and ensuring data quality. (4) Developing the report and building a data visualization. (5) Sharing report with stakeholders to seek input on definitions visual display. Results: An EoL Metrics Dashboard was created and made available to all SCCA clinicians and staff. The dashboard provides rates for 10 EoL metrics: chemotherapy at 7/14/30 days before death, radiation treatment at 7/14/30 days before death, emergency department (ED) visit within 30 days of death (DoD), ED plus inpatient admission within 30 DoD, intensive care unit (ICU) stay within 30 (DoD), and death in the ICU. The denominator is defined as decedents with ≤3 visits at SCCA within 12 months of death. Data is displayed monthly, rolling 16-month with trendlines for EoL events. Data is viewable by EoL event, cancer type, sex, race, age at death and payor. There is also a permission-based view containing patient-level data. Conclusions: With clear data definitions and dedicated analytic resources it is feasible to create an automated EoL report using administrative data. The largest limitation is that the data available to a hospital or clinic is only inclusive of care within their facility. Also, while this report is useful to detect trends, additional analysis is required at the patient level to determine whether an event was avoidable or did not align with the patient’s wishes.
Harnessing the electronic health record to optimize oral anticancer therapy monitoring and follow-up.
Authors: Jeffers Kate , Walde Amy
Published: September 2018

305

Background: UCHealth pursued and became certified as a Quality Oncology Program from the Quality Oncology Practice Initiative (QOPI) through the American Society of Clinical Oncology (ASCO) in 2015. During our gap analysis to prepare for certification, we identified a deficit in our education, monitoring, and follow up relating to oral anti-cancer therapies. Although we used QOPI as a benchmark, we sought to improve patient care and safety in the realm of oral anti-cancer therapies. Methods: UCHealth has implemented policies surrounding oral chemotherapy to include patient education, consent, use of the EHR for ordering, and patient monitoring of adherence and toxicity through development of a flowsheet. This includes the use of Best Practice Alerts (BPA) to trigger staff to evaluate adherence and compliance, smart texts to pull data into progress notes, silent BPAs to remind staff to call patients within 10 days of starting oral chemotherapy, and weekly reporting of staff compliance with assessing patient adherence. Results: EHR changes were implemented in May, 2015 with reporting of staff compliance beginning in September. At that time, UCHealth was only monitoring adherence and toxicity in 24% of patients on an oral anti-cancer therapy. Through continued quality improvement projects, staff education, and optimization of clinical decision support tools, UCHealth consistently monitors adherence and toxicity in over 85% of patients on an oral anti-cancer therapy. Results have been monitored for over two years with continued improvements seen. Conclusions: Using the reporting data, we are able to identify quality improvement projects to include discrete data such as individual staff member compliance. Continuous refinements of the BPA and report have occurred as a result of discrete data analysis by a multi-disciplinary committee.
Improving efficiency of exam room use at a comprehensive cancer center.
Authors: Yakowec Jing Jing Wang , Regan Emily , Wagner Andrew J. , Herold Christina Isabella
Published: September 2018

307

Background: Efficient use of exam rooms is crucial to be able to accommodate increasing patient volumes. One workflow approach that takes patients into an exam room only when the provider is ready can free up space for other patient-provider pairs (co-rooming), in contrast to rooming the patient before knowing the provider’s readiness status (sequential-rooming). We conducted a pilot to implement co-rooming on the breast cancer patient floor at Dana-Farber Cancer Institute (DFCI) and to assess whether patient time alone in exam rooms is reduced. Methods: As part of the planning for the co-rooming pilot, root cause analysis, current state sequential-rooming workflow mapping, and proposed future state co-rooming workflow mapping were performed. In the pilot group, clinic assistants roomed a patient only if the provider verbally expressed readiness within 10 minutes. The real-time locating system (RTLS) database was leveraged to generate baseline and pilot data. For 5 providers, patient time alone in an exam room on 5 and 3 consecutive baseline (2/17/17 – 3/17/17) and pilot (3/24/17 – 4/7/17) Friday mornings, respectively, were analyzed using the XbarS statistical process control chart method. Results: At baseline, the mean patient time alone in an exam room was 14 minutes (range 0-86). During pilot mornings, the mean patient time alone was reduced to 4 minutes (range 0-20), which was statistically significantly lower than the baseline mornings. The table below provides the XbarS chart data for the mean time alone +/- 3-sigma. Conclusions: In our pilot, patient time alone in an exam room was significantly decreased by changing from a sequential-rooming process to a co-rooming process, with minimal disruption to workflow. Co-rooming can reduce inefficient exam room use. [Table: see text]
Using electronic medical record system to improve compliance with national guidelines for comprehensive distress screening in cancer patients.
Authors: Pandya Chintan , Sabatka Sandra , Kettinger Michelle , Alongi Alexander , Hamel Lauren M. , Guancial Elizabeth A. , Dougherty David W.
Published: September 2018

309

Background: Psychosocial distress screening (DS) and management is associated with improved quality of life and outcomes in cancer patients and is required for accreditation by the American College of Surgeons Commission on Cancer. Comprehensive distress screening (CDS) consists of routine distress screening, evaluation, referral to appropriate psychosocial services, and follow-up to ensure adequate care. Electronic medical record (EMR) systems can be leveraged to facilitate and document CDS as part of clinical care and to evaluate the CDS process as a quality standard. The aim of this study is to develop and implement an EMR-based tool to document and evaluate the CDS process as part of routine oncology care. Methods: An EMR-based tool with structured data fields is developed for social workers to document risk factors for distress, assessment, management plan including psychosocial service referrals, and time spent delivering care following DS using the NCCN distress thermometer (DT). Evaluation of CDS process is done in cancer patients who have documented psychosocial care in the EMR-system from 1/2017-5/2018. Results: During the study period, 1327 cancer patients underwent 2480 distress screening evaluations. The average distress score was 3.2 (median = 2) on the DT scale of 0-10, with 855 (64%), 326 (25%), and 146 (11%) patients reporting on average mild (0-3), moderate (4-6), and severe (7-10) distress respectively. 400/1327 (30%) patients accounted for 1177 documented social work contact/visits, of which financial (40%) and emotional (15%) were the most common concerns. 89% (1047) of the visits had follow-up plans and 77% of encounters resulted in referrals, of which financial support (26%) and pharmacy assistance (22%) were the most common referral services. The average time spent on each psychosocial care visit was reported to be 21 minutes. Conclusions: EMR-based forms with structured data fields can be used to document and promote improved adherence to national guidelines for CDS as part of routine oncology care by facilitating data collection. Such tools can be leveraged to capture relevant data on impact of CDS on social work resource utilization.
The Washington State Community Cancer Care Report: A multi-stakeholder effort to characterize quality of care and costs for Washington State oncology practices.
Authors: Ramsey Scott David , Kreizenbeck Karma L. , Panattoni Laura Elizabeth , Fedorenko Catherine R. , Li Li , Sun Qin , Barger Sarah , Lyman Gary H.
Published: September 2018

31

Background: Although many quality measures exist in oncology, there have been few efforts to prioritize, measure, and report quality and costs for an entire region. Here, we report the results of a multi-year, multi-stakeholder effort aimed at public reporting of nationally recognized quality metrics for oncology practices in Washington State. Methods: Quality metrics were selected from nationally-recognized measures through a structured process involving oncology providers, health insurance leaders, patient advocates, and policy experts. Cancer registry records from 2014 to 2016 were linked with claims data from two commercial insurers and Medicare, representing approximately 70% of cancer patients in the state. Patients were assigned to oncology clinics using claims data; 27 clinics were large enough for inclusion in at least one measure in the report. Thirteen metrics were combined to produce one clinic-level quality score per measure. Each quality score was mapped to total episode cost per patient. Results were adjusted to account for clinic size, cancer characteristics (e.g. stage), demographics, and comorbidity where appropriate. Results: Conclusions: The Community Cancer Care in Washington State: Quality and Cost Report 2018 is the first publicly accessible report showing clinic-level quality measures linked to cost in oncology. Its ultimate goal is to improve care and lower costs by spurring collaboration, research and innovation.[Table: see text]
Improving quality care through IT/analytics for team-based care interventions.
Authors: Rodgers Georgina T. , Lindberg Jacob
Published: September 2018

316

Background: Team based care is essential to achieve coordinated, high-quality care. We recognized a responsibility to identify new treatment patients to provided targeted, team based interventions. Previous attempts at identifying new patients were difficult, manual, and delayed. Our aim was to provide personnel with the appropriate means to identify new patients for services such as patient education, financial navigation, social work assessments and outreach calls for care coordination. As a result of multiple barriers and challenges, only 51% of our new patients were being identified. This project fit well in the larger context of the transformation of health care delivery through our participation in the Oncology Care Model, which places an emphasis on team based care. Methods: We used the Plan-Do-Study-Act continuous improvement model to develop an automated data set to identify new treatment patients across the oncology service line and leveraged our Information Technology (IT) Analytics team. A report was established based utilizing logic to identify the first appointment scheduled within the department and a secondary tab to look back at new patients within a three week time frame. Information is housed within a business intelligence software system that is easy for end users to see and understand. The initial report was validated for accuracy at an identification rate of 93% and the 3 week “look back” report gives the ability to identify the remaining patients. Results: We have seen marked improvements metrics as a result of the utilization of this report. Our Financial Navigators have been able to improve out of pocket estimate calls to 98% in April of 2018. Social Work initial patient assessments have improved by 40%, post chemotherapy outreach calls from RN Care Coordinators have improved 12%, and we have seen a 20% increase in the number of documented oncology patient education encounters. Conclusions: This project demonstrates the value of using IT/Data Analytics for continuous quality improvement projects related to patient centered team based care. The cross collaboration of stakeholders in data analysis should be explored as a mechanism to transform care through key services and interventions.
Leveraging the electronic medical record (EMR) to improve sepsis care in cancer outpatients.
Authors: Dunson William A. , Erickson Emily , Freckleton Chad , Saseendran Mahima , Kissell Betsy , Graves Kencee , Horton Devin , Rohm Terrell , Milligan Donald , Ose Dominik
Published: September 2018

319

Background: Sepsis is a life-threatening organ dysfunction caused by a dysregulated response to infection and a major healthcare problem in cancer patients. Patients with cancer are at increased risk of morbidity and mortality from sepsis. Approaches like the modified Early Warning Score (mEWS) could offer an opportunity to identify patients at risk for sepsis earlier and to prompt a timely evaluation. However, available evidence for cancer outpatient settings remains scarce. The aim of this presentation is to describe first results of the mEWS implementation at Huntsman Cancer Hospital (HCC) outpatient clinics. The question, whether patients with sepsis can be detected using this approach will be answered. Methods: In 2015, the University of Utah Healthcare implemented mEWS as prediction tool for sepsis. The automated calculation of mEWS is based on real-time data from the EMR. For this analysis, we extracted a cancer outpatient population from a 15-month time frame (from December 2016 to February 2018) within the EHR. We selected patients with a mEWS > 4, grouped these patients according to the process of care after mEWS scoring (e.g., admitted to ICU) and analyzed subgroup based upon mEWS score, discharge disposition and sepsis diagnosis. Results: Within the analyzed time frame 502 cancer outpatients had a mEWS score of 4 or higher. 88 of these patients (17.5%) were diagnosed with sepsis after mEWS screening. Out of the patients with sepsis, 22 were admitted to ICU, 63 were admitted to a medical floor and 3 were treated at the Huntsman Acute Care Clinic. Out of the 414 without a diagnosis of sepsis, 13 patients were admitted to ICU, 72 patients were admitted to a medical floor (in each case for other reasons then sepsis) and 329 patients were sent to home. Conclusions: Sepsis is a serious problem in cancer outpatient care. In our analysis, one in six patients with a mEWS score of 4 and higher were diagnosed with sepsis. This analysis has shown that the implementation of a real-time, EMR based scoring system like mEWS can support the early detection and treatment of sepsis in this population.
Annual colorectal cancer screening in rural community clinics using the fecal immunochemical test (FIT): Second and third year screening.
Authors: Arnold Connie , Davis Terry C , Morris James , Mills Glenn Morris
Published: September 2018

35

Background: Colorectal cancer (CRC), the second leading cause of cancer death in the US, can be significantly reduced if it is detected early. Although overall CRC screening rates have increased significantly, disparities persist among low income individuals, adults with low literacy and those living in rural areas. Methods: Randomized controlled trial to assess the effectiveness of 2 health literacy informed phone follow-up strategies to improve annual screening with Fecal Immunochemical Test (FIT) in 4 rural community clinics. Eligible patients, age 50-75, were recruited. After consenting, a research assistant (RA) recommended screening and gave literacy and culturally appropriate education using a pamphlet, the FIT kit, simplified instructions and a demonstration of how to use it, At 4 weeks patients who had not returned their kit receive either 1) a personal follow-up call (PC) from a central RA using motivational interviewing skills and reminding them to complete FIT kits; or 2) an automated follow-up call (AC) using plain language and motivational messages encourages patients to complete the FIT. During years 2 and 3, FIT kits were mailed to patients. Follow-up call procedures previously used were followed. Results: 620 patients not up-to-date were enrolled: 308/AC & 306/PC; 66% were African American, 55% women; 40% had limited literacy. During Year 1, 69% completed screening in AC arm versus 67% in PC arm. During Year 2, percentage screened decreased: 40% screened in AC arm and 37% in PC arm. Number of patients that needed at least one follow-up called increased: 74% in both arms needed at least 1 reminder call. Among those called, 19% in the AC arm completed their kit versus 15% in the PC arm. To date in Year 3, 32% screened in AC and 34% in PC. Conclusions: Simplified instructions accompanied by a face-to-face demonstration of FIT, use of “teach back” to confirm understanding with a follow-up call if needed, facilitated completion rates of all patients, particularly those with limited literacy. The less costly and time consuming automated call was equally effective as a personal call. Screening rates in years 2 and 3 declined. CRC screening with FIT is only effective when completed annually. Clinical trial information: RSG-13-021-01 - CPPB.