Nudging best practice: the HITECH act and behavioral medicine

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.

Emerging digital technologies in cancer treatment, prevention, and control

The very first issue of the journal of Translational Behavioral Medicine (TBM) was dedicated, in part, to the theme of Health Information Technology as a platform for evidence implementation. The topic was timely: legislation in the USA was passed with the intent of stimulating the adoption of electronic health records; mobile smartphones, tablets, and other devices were gaining traction in the consumer market, while members within the Society of Behavioral Medicine were gaining scientific understanding on how to use these tools to effect healthy behavior change. For the anniversary issue of TBM, we evaluated the progress and problems associated with deploying digital health technologies to support cancer treatment, prevention, and control over the last decade. We conducted a narrative review of published literature to identify the role that emerging digital technologies may take in achieving national and international objectives in the decade to come. We tracked our evaluation of the literature across three phases in the cancer control continuum: (a) prevention, (b) early detection/screening, and (c) treatment/survivorship. From our targeted review and analyses, we noted that significant progress had been made in the adoption of digital health technologies in the cancer space over the past decade but that significant work remains to be done to integrate these technologies effectively into the cancer control systems needed to improve outcomes equitably across populations. The challenge for the next 10 years is inherently translational.

Prescribing Technology to Increase Uptake of Depression Treatment in Primary Care: A Pre-implementation Focus Group Study of SOVA (Supporting Our Valued Adolescents)

Supporting Our Valued Adolescents (SOVA) is a web-based technology intervention designed to increase depression and anxiety treatment uptake by adolescents in the context of an anonymous peer community with an accompanying website for parents. With a goal of informing the design of a hybrid effectiveness-implementation randomized controlled trial, we conducted a pre-implementation study in two primary care practices to guide implementation strategy development. We conducted focus groups with primary care providers (PCPs) at three different timepoints with PCPs (14 total) from two community practices. A baseline survey was administered using Evidence-Based Practice Attitude Scale (EBPAS) and Physician Belief Scale (PBS). Subsequently, during each focus group, PCPs listened to a relevant presentation after which a facilitated discussion was audio recorded and transcribed. After timepoint 1, a codebook based on Consolidated Framework for Intervention Research (CFIR) and qualitative description were used to summarize findings and inform implementation strategies that were then adapted based on PCP feedback from timepoint 2. PCPs were provided with resources to implement SOVA over 5 months and then a third focus group was conducted to gather their feedback. Based on EBPAS and PBS, PCPs are willing to try new evidence-based practices and have positive feelings about taking care of psychosocial problems with some concerns about increased burden. During focus groups, PCPs expressed SOVA has a relative advantage and intuitive appeal, especially due to its potential to overcome stigma and reach adolescents and parents who may not want to talk about mental health concerns with their PCP. PCPs informed various implementation strategies (e.g., advertising to reach a wider audience than the target population; physical patient reminders). During timepoint 3, however, they shared they had a difficult time utilizing these despite their intention. PCPs requested use of champions and others to nudge them and priming of families with advertising, so that the PCP would not be required to initiate recommendation of the intervention, but only offer their strong endorsement when prompted. The process of conducting a pre-implementation study in primary care settings may assist with piloting potential implementation strategies and understanding barriers to their use.Trial registration NCT03318666.

Patient and caregiver perspectives on decision support for symptom and quality of life management during cancer treatment: Implications for eHealth

OBJECTIVES

Adequate symptom and quality-of-life (SQL) management is a priority during cancer treatment. eHealth is a timely way to enhance patient-engagement, facilitate communication, and improve health outcomes. The objectives of this study were to describe patient and caregivers' perspectives for providing, processing, and managing SQL data to enhance communication and identify desired components for decision support.

METHODS

Data were collected from 64 participants through questionnaires and focus groups. Analysis was conducted using NVivo. Open and axial coding was completed, grouping commonalities and large constructs into nodes to identify and synthesize themes.

RESULTS

Face-to-face meetings with clinicians were the prime time to communicate, and patients strove to understand treatment options and the effect on SQL by bringing caregivers to their visits, taking notes, tracking symptoms, and creating portable health records. Patients/caregivers struggled to self-manage their symptoms and were uncertain when to contact clinicians when experiencing uncontrolled symptoms. Most participants identified eHealth solutions for decision support. However, 38% of participants (n = 24) rarely used computers and identified non-eHealth options for decision support. Core components for both eHealth and non-eHealth systems were access to (1) cancer information, (2) medical records, (3) peer support, and (4) improved support and understanding on when to contact clinicians.

CONCLUSIONS

Patients were faced with an overwhelming amount of information and relied on their caregivers to help navigate the complexities of cancer care and self-manage SQL. Health technologies can provide informational support; however, decision support needs to span multiple venues to avoid increasing disparities caused by a digital divide.

Skin self-examinations and visual identification of atypical nevi: comparing individual and crowdsourcing approaches

PURPOSE

Skin self-examination (SSE) is one method for identifying atypical nevi among members of the general public. Unfortunately, past research has shown that SSE has low sensitivity in detecting atypical nevi. The current study investigates whether crowdsourcing (collective effort) can improve SSE identification accuracy. Collective effort is potentially useful for improving people's visual identification of atypical nevi during SSE because, even when a single person has low reliability at a task, the pattern of the group can overcome the limitations of each individual.

METHODS

Adults (N=500) were recruited from a shopping mall in the Midwest. Participants viewed educational pamphlets about SSE and then completed a mole identification task. For the task, participants were asked to circle mole images that appeared atypical. Forty nevi images were provided; nine of the images were of nevi that were later diagnosed as melanoma.

RESULTS

Consistent with past research, individual effort exhibited modest sensitivity (.58) for identifying atypical nevi in the mole identification task. As predicted, collective effort overcame the limitations of individual effort. Specifically, a 19% collective effort identification threshold exhibited superior sensitivity (.90).

CONCLUSIONS

The results of the current study suggest that limitations of SSE can be countered by collective effort, a finding that supports the pursuit of interventions promoting early melanoma detection that contain crowdsourced visual identification components.

Why are Tailored Messages More Effective? A Multiple Mediation Analysis of a Breast Cancer Screening Intervention

Past research has found that tailoring increases the persuasive effectiveness of a message. However, the observed effect has been small and the explanatory mechanism remains unknown. To address these shortcomings, a tailoring software program was created that personalized breast cancer screening pamphlets according to risk, health belief model constructs, and visual preference. Women aged 40 and older (N = 119) participated in a 2 (tailored vs. stock message) × 2 (charts/graphs vs. illustrated visuals) × 3 (nested replications of the visuals) experiment. Participants provided with tailored illustrated pamphlets expressed greater breast cancer screening intentions than those provided with other pamphlets. In a test of 10 different mediators, perceived message relevance was found to fully mediate the tailoring × visual interaction.

Informatics-enabled behavioral medicine in oncology

For the practicing physician, the behavioral implications of preventing, diagnosing, and treating cancer are many and varied. Fortunately, an enhanced capacity in informatics may help create a redesigned ecosystem in which applying evidence-based principles from behavioral medicine will become a routine part of care. Innovation to support this evolution will be spurred by the "meaningful use" criteria stipulated by the Health Information Technology for Economic and Clinical Health Act of 2009 and by focused research and development efforts within the broader health information ecosystem. The implications for how to better integrate evidence-based principles in behavioral medicine into oncology care through both spheres of development are discussed within the framework of the cancer control continuum. The promise of using the data collected through these tools to accelerate discovery in psycho-oncology is also discussed. If nurtured appropriately, these developments should help accelerate successes against cancer by altering the behavioral milieu.

Grid-enabled measures: using Science 2.0 to standardize measures and share data

Scientists are taking advantage of the Internet and collaborative web technology to accelerate discovery in a massively connected, participative environment--a phenomenon referred to by some as Science 2.0. As a new way of doing science, this phenomenon has the potential to push science forward in a more efficient manner than was previously possible. The Grid-Enabled Measures (GEM) database has been conceptualized as an instantiation of Science 2.0 principles by the National Cancer Institute (NCI) with two overarching goals: (1) promote the use of standardized measures, which are tied to theoretically based constructs; and (2) facilitate the ability to share harmonized data resulting from the use of standardized measures. The first is accomplished by creating an online venue where a virtual community of researchers can collaborate together and come to consensus on measures by rating, commenting on, and viewing meta-data about the measures and associated constructs. The second is accomplished by connecting the constructs and measures to an ontological framework with data standards and common data elements such as the NCI Enterprise Vocabulary System (EVS) and the cancer Data Standards Repository (caDSR). This paper will describe the web 2.0 principles on which the GEM database is based, describe its functionality, and discuss some of the important issues involved with creating the GEM database such as the role of mutually agreed-on ontologies (i.e., knowledge categories and the relationships among these categories--for data sharing).

Supporting implementation of evidence-based behavioral interventions: the role of data liquidity in facilitating translational behavioral medicine

The advancement of translational behavioral medicine will require that we discover new methods of managing large volumes of data from disparate sources such as disease surveillance systems, public health systems, and health information systems containing patient-centered data informed by behavioral and social sciences. The term "liquidity," when applied to data, refers to its availability and free flow throughout human/computer interactions. In seeking to achieve liquidity, the focus is not on creating a single, comprehensive database or set of coordinated datasets, nor is it solely on developing the electronic health record as the "one-stop shopping" source of health-related data. Rather, attention is on ensuring the availability of secure data through the various methods of collecting and storing data currently existent or under development-so that these components of the health information infrastructure together support a liquid data system. The value of accessible, interoperable, high-volume, reliable, secure, and contextually appropriate data is becoming apparent in many areas of the healthcare system, and health information liquidity is currently viewed as an important component of a patient-centered healthcare system. The translation from research interventions to behavioral and psychosocial indicators challenges the designers of healthcare systems to include this new set of data in the correct context. With the intention of advancing translational behavioral medicine at the local level, "on the ground" in the clinical office and research institution, this commentary discusses data liquidity from the patient's and clinician's perspective, requirements for a liquid healthcare data system, and the ways in which data liquidity can support translational behavioral medicine.