Patient-reported Outcomes 2.0

How to optimize the oncology work force to respond to PRO’s

by Bobby Daly, MD, MBA and Abigail Baldwin-Medsker, MSN, RN, OCN

In my blog at the start of this year, I had highlighted five innovations to look for in 2019 in oncology care delivery that hold the promise of positively disrupting the way we practice. One such innovation is the adoption and integration of patient-reported outcomes into oncology clinical care. Basch et al.’s seminal study in 2017 demonstrated that patient reported outcomes achieved improved quality of life, fewer emergency room visits, and a five month gain in overall survival. In discussing the study at the ASCO plenary that year, Dr. Krzyzanowska advocated that active symptom monitoring during chemotherapy should be the new standard of care, but she cautioned that oncology practices must be cognizant of implementation issues in taking up this challenge. A key implementation issue is the workforce redesign that is needed to integrate PRO’s into practice. In writing this blog, we reached out to Dr. Kathi Mooney of the University of Utah, an accomplished researcher in this area to provide insight. 

Dr. Mooney’s work: A Pioneer Pivots in the Provider Responding to PRO’s

Dr. Mooney’s research in this area has explored different models for monitoring patient’s symptoms during ambulatory chemotherapy. In her first study, published in 2014 in the journal Supportive Care in Cancer , medical oncology patients used a touch tone telephone to report 10 common symptoms during chemotherapy. In the intervention group, symptoms exceeding thresholds for moderate-to-severe intensity levels generated emailed alert reports to both the patient’s oncologist and oncology nurse. In the control group patients reported their symptoms daily but understood that the data they submitted were for research purposes only and were not available for clinical action. The overall daily call adherence was 65.0% of expected days and on average 9 moderate-to-severe intensity alerts were generated per patient over the 45 study days. Mooney et al., however, found no significant difference in change of symptom severity between the two groups, and that providers rarely contacted patients after receiving alerts. The authors concluded: “Despite patients’ use of a daily symptom monitoring system and providers’ receipt of unrelieved symptoms of moderate-to-severe intensity, oncology physicians and nurses did not contact patients to intensify symptom treatment nor did symptoms improve.” This led to a pivot in research for a second study published in Cancer Medicine in 2017. In this study, the control group remained the same but in the intervention arm the alerts now went to a dedicated nurse practitioner (NP) for follow-up of poorly controlled symptoms. The NP used a guideline-based decision support system to respond. In contrast to the prior study, this NP-based model (called SymptomCare@Home or SCH) dramatically improved symptom outcomes. With a very rapid treatment benefit, SCH participants had a significant reduction in severe (67% fewer) and moderate (39% fewer) symptom days compared to usual care. We followed up with Dr. Mooney about the lessons learned from these two studies.


Work Force Models for PRO Monitoring and Management: Research Directions

In summarizing her 2017 study, Dr. Mooney wrote: “We conclude that the efficacy of automated symptom monitoring is dependent on timely oncology provider response to problematic symptoms. Despite the ease and feasibility of remote monitoring, our research suggests that without timely and proper clinical follow-up, telehealth approaches may not improve patient outcomes.” In discussing this finding with us, Dr. Mooney attributed it to provider inertia: providers had competing demands on time and expressed uncertainty about the value of following up on alerts. By creating a dedicated NP team, the SCH model was able to overcome that inertia. She notes though that it is possible to create a model where the primary oncology team manages PRO’s (this was the model Basch et al. employed in a clinical trial setting) but it would require a structure that incentivizes the primary team to respond to alerts and to monitor them as they do other important clinical data, such as labs. Implementing a dedicated team comes with its own challenges, such as fragmentation of care resulting in the oncology team being unaware of the symptom management care being provided. She found that a dedicated team works best when there is a culture of team care for patients. In addition, the NP’s tried to close the communication loop through electronic health record notes and emails to providers. Dr. Mooney also made note that the majority of the interventions implemented by the NP’s were education-based – correcting or reinforcing how patients used supportive medications – and, hence, a dedicated oncology RN model could also potentially support a successful PRO implementation. However, an RN would need ready access to a licensed prescriber for prescriptive issues such as medications or diagnostic tests. She also discovered that the NP’s found a lot of value in the decision support tool as it allowed them to operate autonomously, employ best practices in symptom care, and organize their time to provide more efficient care. Her ongoing clinical trial looks to better delineate the most essential and cost effective elements of the SymptomCare@Home program, including the NP workforce model and the decision support system, so that other institutions will be able to replicate its success.  

ASCO 2019 highlighted many programs that were trying to adapt Basch’s and Mooney’s prior work to their unique clinical environment. Determining the most efficient strategy that best serves our patients, will be of incredible value as we seek to achieve the promise of ASCO 2017 of incorporating PRO’s into the standard of care for oncology patients.