Creating computable algorithms for symptom management in an outpatient thoracic oncology setting

A qualitative analysis of algorithm-based decision support usability testing for symptom management across the trajectory of cancer care: one size does not fit all

BACKGROUND

Adults with cancer experience symptoms that change across the disease trajectory. Due to the distress and cost associated with uncontrolled symptoms, improving symptom management is an important component of quality cancer care. Clinical decision support (CDS) is a promising strategy to integrate clinical practice guideline (CPG)-based symptom management recommendations at the point of care.

METHODS

The objectives of this project were to develop and evaluate the usability of two symptom management algorithms (constipation and fatigue) across the trajectory of cancer care in patients with active disease treated in comprehensive or community cancer care settings to surveillance of cancer survivors in primary care practices. A modified ADAPTE process was used to develop algorithms based on national CPGs. Usability testing involved semi-structured interviews with clinicians from varied care settings, including comprehensive and community cancer centers, and primary care. The transcripts were analyzed with MAXQDA using Braun and Clarke's thematic analysis method. A cross tabs analysis was also performed to assess the prevalence of themes and subthemes by cancer care setting.

RESULTS

A total of 17 clinicians (physicians, nurse practitioners, and physician assistants) were interviewed for usability testing. Three main themes emerged: (1) Algorithms as useful, (2) Symptom management differences, and (3) Different target end-users. The cross-tabs analysis demonstrated differences among care trajectories and settings that originated in the Symptom management differences theme. The sub-themes of "Differences between diseases" and "Differences between care trajectories" originated from participants working in a comprehensive cancer center, which tends to be disease-specific locations for patients on active treatment. Meanwhile, participants from primary care identified the sub-theme of "Differences in settings," indicating that symptom management strategies are care setting specific.

CONCLUSIONS

While CDS can help promote evidence-based symptom management, systems providing care recommendations need to be specifically developed to fit patient characteristics and clinical context. Findings suggest that one set of algorithms will not be applicable throughout the entire cancer trajectory. Unique CDS for symptom management will be needed for patients who are cancer survivors being followed in primary care settings.

Care at Your Fingertips: Codesign, Development, and Evaluation of the Oncology Hub App for Remote Symptom Management in Pediatric Oncology

PURPOSE

To codesign, develop, and evaluate a smartphone app that includes patient-reported measures of symptoms and real-time advice in children's cancer.

METHODS

The Oncology Hub is a comprehensive approach to symptom management that includes a suite of codesigned tools and resources including clinical algorithms to determine the level of concern, symptom management advice, and resources for families of children with cancer. The evaluation involved Think Aloud interviews with parent and adolescent patients to complete tasks in the app as well as a User Experience questionnaire (score range, 0-120) and qualitative feedback. The accuracy of algorithms was determined by repeated testing of inputs and outputs over 4 weeks.

RESULTS

Design and wireframes were iteratively refined through consultation with parents and adolescents confirming the final design. Beta testing evaluation was then completed by 25 participants including two adolescents. Across all participants, 84% of tasks were easy to navigate, and the Oncology Hub demonstrated high usability, usefulness, and acceptability with participants' scores ranging between 90 and 120 (mean = 112.2, standard deviation = 9.43). Qualitative feedback was positive. Testing of algorithms identified inconsistencies in understanding between clinical research and coding teams; refinements were made until the expected response notifications were returned with 100% accuracy.

CONCLUSION

Technology offers new ways to think about how clinicians and families communicate and share information to harness the best of community and hospital services. Understanding how information is exchanged using health apps, and how this affects clinical workflow is critical to successful implementation, and optimizing symptom assessment and management in children with cancer.

Clinical Decision Support for Symptom Management in Lung Cancer Patients: A Group RCT

CONTEXT

Clinical guidelines are available to enhance symptom management during cancer treatment but often are not used in the practice setting. Clinical decision support can facilitate the implementation and adherence to clinical guidelines. and improve the quality of cancer care.

OBJECTIVES

Clinical decision support offers an innovative approach to integrate guideline-based symptom management into oncology care. This study evaluated the effect of clinical decision support-based recommendations on clinical management of symptoms and health-related quality of life (HR-QOL) among outpatients with lung cancer.

METHODS

Twenty providers and 179 patients were allotted in group randomization to attention control (AC) or Symptom Assessment and Management Intervention (SAMI) arms. SAMI entailed patient-report of symptoms and delivery of recommendations to manage pain, fatigue, dyspnea, depression, and anxiety; AC entailed symptom reporting prior to the visit. Outcomes were collected at baseline, two, four and six-months. Adherence to recommendations was assessed through masked chart review. HR-QOL was measured by the Functional Assessment of Cancer Therapy-Lung questionnaire. Descriptive statistics with linear and logistic regression accounting for the clustering structure of the design and a modified chi-square test were used for analyses.

RESULTS

Median age of patients was 63 years, 58% female, 88% white, and 32% ≤high school education. Significant differences in clinical management were evident in SAMI vs. AC for all target symptoms that passed threshold. Patients in SAMI were more likely to receive sustained-release opioids for constant pain, adjuvant medications for neuropathic pain, opioids for dyspnea, stimulants for fatigue and mental health referrals for anxiety. However, there were no statistically significant differences in HR-QOL at any time point.

CONCLUSION

SAMI improved clinical management for all target symptoms but did not improve patient outcomes. A larger study is warranted to evaluate effectiveness.

Palliative Care Skills and New Resources for Oncology Practices: Meeting the Palliative Care Needs of Patients With Cancer and Their Families

In its 2017 guideline, ASCO challenged members to integrate palliative care into their standard oncology practices for all patients, throughout their cancer trajectory. However, partnering with palliative care experts alone will not be enough to achieve that goal; there are too few experts now, and there will not be enough in the future to meet the needs of patients with cancer and their families. Other strategies are required. Oncologists can develop new communication skills that were not included in their fellowship curricula, skills that integrate into their visits the subjects that palliative care clinicians discuss routinely with patients referred to them. In this review, Dr. Back offers three questions matched to communication skills that can help oncologists explore key areas: (1) What is happening? (2) How do you (and I) feel? and (3) What is important? and discusses the "REMAP" strategy for making urgent medical decisions. Dr. Friedman reviews the impact of community-based palliative care resources and telehealth on care quality, patient centeredness, and reducing costs. Community-based palliative care services and telehealth are available to patients and families at home, during active treatment. Dr. Abrahm reviews how patient-reported outcomes (PROs) completed at home can enhance patients' symptom control, quality of life, and toleration of treatment and decrease unplanned emergency visits by alerting clinicians to patients' severe symptoms, making appropriate referrals, or suggesting patients contact their oncology team. She also provides an update on using PROs and natural language processing with clinical decision support to create sophisticated palliative care assessments and treatment options in the electronic health record during patients' office visits.

Design Process and Utilization of a Novel Clinical Decision Support System for Neuropathic Pain in Primary Care: Mixed Methods Observational Study

Background

Computerized clinical decision support systems (CDSSs) have emerged as an approach to improve compliance of clinicians with clinical practice guidelines (CPGs). Research utilizing CDSS has primarily been conducted in clinical contexts with clear diagnostic criteria such as diabetes and cardiovascular diseases. In contrast, research on CDSS for pain management and more specifically neuropathic pain has been limited. A CDSS for neuropathic pain has the potential to enhance patient care as the challenge of diagnosing and treating neuropathic pain often leads to tension in clinician-patient relationships.

Objective

The aim of this study was to design and evaluate a CDSS aimed at improving the adherence of interprofessional primary care clinicians to CPG for managing neuropathic pain.

Methods

Recommendations from the Canadian CPGs informed the decision pathways. The development of the CDSS format and function involved participation of multiple stakeholders and end users in needs assessment and usability testing. Clinicians, including family medicine physicians, residents, and nurse practitioners, in three academic teaching clinics were trained in the use of the CDSS. Evaluation over one year included the measurement of utilization of the CDSS; change in reported awareness, agreement, and adoption of CPG recommendations; and change in the observed adherence to CPG recommendations.

Results

The usability testing of the CDSS was highly successful in the prototype environment. Deployment in the clinical setting was partially complete by the time of the study, with some limitations in the planned functionality. The study population had a high level of awareness, agreement, and adoption of guideline recommendations before implementation of CDSS. Nevertheless, there was a small and statistically significant improvement in the mean awareness and adoption scores over the year of observation (P=.01 for mean awareness scores at 6 and 12 months compared with baseline, for mean adoption scores at 6 months compared with baseline, and for mean adoption scores at 12 months). Documenting significant findings related to diagnosis of neuropathic pain increased significantly. Clinicians accessed CPG information more frequently than they utilized data entry functions. Nurse practitioners and first year family medicine trainees had higher utilization than physicians.

Conclusions

We observed a small increase in the adherence to CPG recommendations for managing neuropathic pain. Clinicians utilized the CDSS more as a source of knowledge and as a training tool than as an ongoing dynamic decision support.

Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing

BACKGROUND

It is essential that cancer patients understand anticipated symptoms, how to self-manage these symptoms, and when to call their clinicians. However, patients are often ill-prepared to manage symptoms at home. Clinical decision support (CDS) is a potentially innovative way to provide information to patients where and when they need it. The purpose of this project was to design and evaluate a simulated model of an algorithm-based CDS program for self-management of cancer symptoms.

METHODS

This study consisted of three phases; development of computable algorithms for self-management of cancer symptoms using a modified ADAPTE process, evaluation of a simulated model of the CDS program, and identification of design objectives and lessons learned from the evaluation of patient-centered CDS. In phase 1, algorithms for pain, constipation and nausea/vomiting were developed by an expert panel. In phase 2, we conducted usability testing of a simulated symptom assessment and management intervention for self-care (SAMI-Self-Care) CDS program involving focus groups, interviews and surveys with cancer patients, their caregivers and clinicians. The Acceptability E-scale measured acceptability of the program. In phase 3, we developed design objectives and identified barriers to uptake of patient-centered CDS based on the data gathered from stakeholders.

RESULTS

In phase 1, algorithms were reviewed and approved through a consensus meeting and majority vote. In phase 2, 24 patients & caregivers and 13 clinicians participated in the formative evaluation. Iterative changes were made in a simulated SAMI-Self-Care CDS program. Acceptability scores were high among patients, caregivers and clinicians. In phase 3, we formulated CDS design objectives, which included: 1) ensure patient safety, 2) communicate clinical concepts effectively, 3) promote communication with clinicians, 4) support patient activation, and 5) facilitate navigation and use. We identified patient barriers and clinician concerns to using CDS for symptom self-management, which were consistent with the chronic care model, a theoretical framework used to enhance patient-clinician communication and patient self-management.

CONCLUSION

Patient safety and tool navigation were critical features of CDS for patient self-management. Insights gleaned from this study may be used to inform the development of CDS resources for symptom self-management in patients with other chronic conditions.

Pilot Testing a Web-Based System for the Assessment and Management of Chemotherapy-Induced Peripheral Neuropathy

Because numerous barriers hinder the assessment and management of chemotherapy-induced peripheral neuropathy in clinical practice, the Carevive Care Planning System, a novel Web-based platform, was developed to address these barriers. It provides patients an opportunity to report their symptoms before their clinic visit and generates customizable care plans composed of evidence-based management strategies. The purpose of this study was to evaluate patient and provider perspectives of feasibility, usability, acceptability, and satisfaction with the Carevive platform. We used a single-arm, pretest/posttest, prospective design and recruited 25 women with breast cancer who were receiving neurotoxic chemotherapy and six advanced practice providers from an academic hospital. At three consecutive clinical visits, patients reported their neuropathy symptoms on a tablet via the Carevive system. The Diffusion of Innovations Theory served as an overarching evaluation framework. The Carevive platform was feasible to use. However, patients had higher ratings of usability, acceptability, and satisfaction with the platform than did the providers, who disliked the amount of time required to use the platform and had difficulty logging into Carevive. If issues regarding provider dissatisfaction can be addressed, the Carevive platform may aid in the screening of neuropathy symptoms and facilitate the use of evidence-based management strategies.

Development of an evidence-based decision pathway for vestibular schwannoma treatment options

OBJECTIVE

To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS).

METHODS

This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS.

RESULTS

Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model.

DISCUSSION

The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives.

CONCLUSIONS

Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways.

Increasing Complexity in Rule-Based Clinical Decision Support: The Symptom Assessment and Management Intervention

BACKGROUND

Management of uncontrolled symptoms is an important component of quality cancer care. Clinical guidelines are available for optimal symptom management, but are not often integrated into the front lines of care. The use of clinical decision support (CDS) at the point-of-care is an innovative way to incorporate guideline-based symptom management into routine cancer care.

OBJECTIVE

The objective of this study was to develop and evaluate a rule-based CDS system to enable management of multiple symptoms in lung cancer patients at the point-of-care.

METHODS

This study was conducted in three phases involving a formative evaluation, a system evaluation, and a contextual evaluation of clinical use. In Phase 1, we conducted iterative usability testing of user interface prototypes with patients and health care providers (HCPs) in two thoracic oncology clinics. In Phase 2, we programmed complex algorithms derived from clinical practice guidelines into a rules engine that used Web services to communicate with the end-user application. Unit testing of algorithms was conducted using a stack-traversal tree-spanning methodology to identify all possible permutations of pathways through each algorithm, to validate accuracy. In Phase 3, we evaluated clinical use of the system among patients and HCPs in the two clinics via observations, structured interviews, and questionnaires.

RESULTS

In Phase 1, 13 patients and 5 HCPs engaged in two rounds of formative testing, and suggested improvements leading to revisions until overall usability scores met a priori benchmarks. In Phase 2, symptom management algorithms contained between 29 and 1425 decision nodes, resulting in 19 to 3194 unique pathways per algorithm. Unit testing required 240 person-hours, and integration testing required 40 person-hours. In Phase 3, both patients and HCPs found the system usable and acceptable, and offered suggestions for improvements.

CONCLUSIONS

A rule-based CDS system for complex symptom management was systematically developed and tested. The complexity of the algorithms required extensive development and innovative testing. The Web service-based approach allowed remote access to CDS knowledge, and could enable scaling and sharing of this knowledge to accelerate availability, and reduce duplication of effort. Patients and HCPs found the system to be usable and useful.

Assessment of Multiple Co-Occurring Cancer Symptoms in the Clinical Setting

OBJECTIVES

To discuss multiple co-occurring cancer symptoms, review symptom assessment instruments, identify innovative methods to integrate symptom assessment and management in the clinical setting, and examine barriers and facilitators for implementation of symptom assessment and use of clinical practice guidelines.

DATA SOURCES

Peer-reviewed articles, guidelines, systematic reviews, and web-based resources.

CONCLUSION

Despite the availability of brief, reliable, and valid instruments, symptom assessment has not been integrated as a routine aspect of clinical care. New technologies and changes in health policy provide an optimal environment to integrate electronic symptom assessment and management into cancer care.

IMPLICATIONS FOR NURSING PRACTICE

Oncology nurses play a key role in early identification and management of distressing symptoms.

Feasibility of using algorithm-based clinical decision support for symptom assessment and management in lung cancer

CONTEXT

Distressing symptoms interfere with the quality of life in patients with lung cancer. Algorithm-based clinical decision support (CDS) to improve evidence-based management of isolated symptoms seems promising, but no reports yet address multiple symptoms.

OBJECTIVES

This study examined the feasibility of CDS for a Symptom Assessment and Management Intervention targeting common symptoms in patients with lung cancer (SAMI-L) in ambulatory oncology. The study objectives were to evaluate completion and delivery rates of the SAMI-L report and clinician adherence to the algorithm-based recommendations.

METHODS

Patients completed a web-based symptom assessment and SAMI-L created tailored recommendations for symptom management. Completion of assessments and delivery of reports were recorded. Medical record review assessed clinician adherence to recommendations. Feasibility was defined as 75% or higher report completion and delivery rates and 80% or higher clinician adherence to recommendations. Descriptive statistics and generalized estimating equations were used for data analyses.

RESULTS

Symptom assessment completion was 84% (95% CI=81-87%). Delivery of completed reports was 90% (95% CI=86-93%). Depression (36%), pain (30%), and fatigue (18%) occurred most frequently, followed by anxiety (11%) and dyspnea (6%). On average, overall recommendation adherence was 57% (95% CI=52-62%) and was not dependent on the number of recommendations (P=0.45). Adherence was higher for anxiety (66%; 95% CI=55-77%), depression (64%; 95% CI=56-71%), pain (62%; 95% CI=52-72%), and dyspnea (51%; 95% CI=38-64%) than for fatigue (38%; 95% CI=28-47%).

CONCLUSION

The CDS systems, such as SAMI-L, have the potential to fill a gap in promoting evidence-based care.

Worsening renal function in heart failure: the need for a consensus definition

Acute decompensated heart failure is a common cause of hospitalisation. This is a period of vulnerability both in altered pathophysiology and also the potential for iatrogenesis due to therapeutic interventions. Renal dysfunction is often associated with heart failure and portends adverse outcomes. Identifying heart failure patients at risk of renal dysfunction is important in preventing progression to chronic kidney disease or worsening renal function, informing adjustment to medication management and potentially preventing adverse events. However, there is no working or consensus definition in international heart failure management guidelines for worsening renal function. In addition, there appears to be no concordance or adaptation of chronic kidney disease guidelines by heart failure guideline development groups for the monitoring of chronic kidney disease in heart failure. Our aim is to encourage the debate for an agreed definition given the prognostic impact of worsening renal function in heart failure. We present the case for the uptake of the Acute Kidney Injury Network criteria for acute kidney injury with some minor alterations. This has the potential to inform study design and meta-analysis thereby building the knowledgebase for guideline development. Definition consensus supports data element, clinical registry and electronic algorithm innovation as instruments for quality improvement and clinical research for better patient outcomes. In addition, we recommend all community managed heart failure patients have their baseline renal function classified and routinely monitored in accordance with established renal guidelines to help identify those at increased risk for worsening renal function or progression to chronic kidney disease.

A smartphone-based pain management app for adolescents with cancer: establishing system requirements and a pain care algorithm based on literature review, interviews, and consensus

BACKGROUND

Pain that occurs both within and outside of the hospital setting is a common and distressing problem for adolescents with cancer. The use of smartphone technology may facilitate rapid, in-the-moment pain support for this population. To ensure the best possible pain management advice is given, evidence-based and expert-vetted care algorithms and system design features, which are designed using user-centered methods, are required.

OBJECTIVE

To develop the decision algorithm and system requirements that will inform the pain management advice provided by a real-time smartphone-based pain management app for adolescents with cancer.

METHODS

A systematic approach to algorithm development and system design was utilized. Initially, a comprehensive literature review was undertaken to understand the current body of knowledge pertaining to pediatric cancer pain management. A user-centered approach to development was used as the results of the review were disseminated to 15 international experts (clinicians, scientists, and a consumer) in pediatric pain, pediatric oncology and mHealth design, who participated in a 2-day consensus conference. This conference used nominal group technique to develop consensus on important pain inputs, pain management advice, and system design requirements. Using data generated at the conference, a prototype algorithm was developed. Iterative qualitative testing was conducted with adolescents with cancer, as well as pediatric oncology and pain health care providers to vet and refine the developed algorithm and system requirements for the real-time smartphone app.

RESULTS

The systematic literature review established the current state of research related to nonpharmacological pediatric cancer pain management. The 2-day consensus conference established which clinically important pain inputs by adolescents would require action (pain management advice) from the app, the appropriate advice the app should provide to adolescents in pain, and the functional requirements of the app. These results were used to build a detailed prototype algorithm capable of providing adolescents with pain management support based on their individual pain. Analysis of qualitative interviews with 9 multidisciplinary health care professionals and 10 adolescents resulted in 4 themes that helped to adapt the algorithm and requirements to the needs of adolescents. Specifically, themes were overall endorsement of the system, the need for a clinical expert, the need to individualize the system, and changes to the algorithm to improve potential clinical effectiveness.

CONCLUSIONS

This study used a phased and user-centered approach to develop a pain management algorithm for adolescents with cancer and the system requirements of an associated app. The smartphone software is currently being created and subsequent work will focus on the usability, feasibility, and effectiveness testing of the app for adolescents with cancer pain.