OBJECTIVES:Contextualization of care has been well documented as an important process for optimizing health care outcomes. Yet there has been little research on attention to patient life context in care planning in the setting of life-threatening disease. We sought to explore how care is contextualized during medical visits in advanced lung cancer treatment in Norway. METHODS:We conducted an exploratory observational study using data from physician-patient dialogues about treatment decisions. The material consisted of consultations with patients receiving treatment for advanced lung cancer from several hospitals in Western Norway. Transcripts and audio recordings were analyzed using the Content Coding for Contextualization of Care (4 C) system. Physician attention to patient context was defined by whether clinicians (a) probed contextual red flags to elicit contextual factors and (b) incorporated contextual factors into care plans. Contextual factors were categorized into their twelve domains. RESULTS:Across 17 medical encounters, clinicians probed 19 of 30 contextual red flags (63%) and formulated contextualized care plans for 21 of 29 contextual factors, a contextualizing care rate of 72%. The most common contextual domains were Skills, Abilities and Knowledge (10 contextual domain assignments), followed by Access to Care (4) and Social Support (4). One contextual factor was assigned to two domains, yielding 30 contextual domain assignments across 29 contextual factors. CONCLUSION:This exploratory observational study suggests that inattention to contextual factors may hinder effective care for patients with advanced lung cancer. PRACTICE IMPLICATIONS:The findings support greater emphasis on contextualization of care in clinical training, assessment, and care planning.

Objective Contextualizing care results in better outcomes for patients. Several different prompts to clinicians to increase contextualization have been studied: audit & feedback (A&F), clinical decision support (CDS), or making recording of visits openly accessible to patients (OA). We measured the effects of prompting interventions on probing of contextual red flags and incorporation of contextual factors into care plans. Methods Individual participant data meta-analysis of data from three controlled studies of prompts. The first (A&F, 4160 visits to 667 physicians at 6 sites) employed reports to provider teams of missed and successful contextualization opportunities. The second (CDS, 450 visits to 39 physicians at 2 sites) employed a real-time CDS tool. The third (OA, 317 visits to 30 physicians at 2 sites) cued providers that visits were recorded and would be available to patients. In each, the audios were coded using the 4 C system to identify contextual red flags, clinician probes of red flags, contextual factors, and contextualization of care plans. Results Prompting interventions increased the odds of probing by 71 % (95 % CI 54 % - 79 %) on average, with the largest impact in the A&F study but the highest probing rate in the CDS study. Overall, they increased the odds of contextualizing care plans by 33 % (95 % CI 13 %-58 %), an effect partially mediated by probing of red flags, which increased the odds of contextualization by 337 % (95 % CI 287 % - 396 %). Contextual factors in the domains of Access to Care, Financial Situation, Emotional State, and Skills, Abilities, and Knowledge were most likely to be incorporated into plans and those in Competing Responsibilities least so. Conclusion Multiple strategies prompt clinicians to consider patient life context in care planning, with varying effectiveness according to the patient context. Practical implications Future efforts should consider combining prompting interventions and provide clinicians with additional domain-specific resources.

BACKGROUND:Physicians-in-training receive feedback based on assessment of their observed clinical skills in both the clinical setting and in simulations. These serve as proxy measures for clinician performance - that is, the application of those skills in routine clinical practice when "no one is watching." In research employing covert audio recording of internal medicine residents to directly assess clinical performance of one competency, contextualizing care, there is a "skills-to-performance gap," defined as the difference between what clinicians do when overtly observed compared to when covertly observed. Feedback collected based on covert observation has been shown to improve physician performance in adult medicine practice. This feasibility study tests whether covert assessment with feedback can be operationalized in a pediatric residency program employing a modified protocol adapted for the pediatric setting. METHODS:Parents of patients cared for by consented residents were recruited in a waiting room to carry a concealed audio recorder into their child's appointment. Following the encounter, the audio recording was coded using the Content Coding for Contextualization of Care (4C) supplemented by expert opinion to identify additional learning opportunities. Findings were shared with participating residents followed by a second round of data collection. RESULTS:Among 50 contextual red flags identified across 38 pre-feedback and 13 post feedback audio recorded visits, residents probed just six of them. Of these, patients revealed four contextual factors. They also revealed four contextual factors without a physician probe. In response to only two of these eight contextual factors, the resident attempt to formulate a contextualized care plan. Feedback opportunities unrelated to contextualization of care were also noted. There was no significant change in resident performance with feedback, although sample size was small. CONCLUSIONS:Concealed audio recording is a feasible strategy for assessing clinician performance and providing feedback in a pediatric residency program.

Monetary incentives are commonly used to help recruit trial participants. Some studies have found greater recruitment with larger incentives, while others have found smaller incentives more cost-effective in terms of cost per participant. As part of an implementation study, we compared the impact of four approaches to recruitment, three of which involved phone recruitment with varying financial incentives. Adding modest financial incentives reliably increased the recruitment ratio, and greater incentives increased recruitment more than smaller incentives. However, recruiters required less time to obtain agreement to participate when the greater incentive was offered, and these time savings made the greater incentive cost-saving relative to the smaller incentive and cost-effective relative to no incentive. Our results suggest the possibility of a “sweet spot” for financial incentives, and that trial designers should consider pilot-testing incentive levels in the context of their other recruitment costs to determine whether paying participants more may be cost-saving for trial sponsors.

Abstract The introduction to the second edition is designed to provide the reader who is not familiar with research on contextual error with an overview of the fundamental concepts and terms, followed by a brief description of each chapter, laying out a rationale for the body of work and placing it in a historical context. For instance, studies on contextualization of care build on the work of George Engel’s biopsychosocial model by introducing an empirical framework and set of tools for characterizing and measuring a dimension of quality that has previously been sidelined with non-specific terms like “art of medicine” and “humanistic care.” The authors argue that contextualizing care to prevent contextual error is a clinician competency that should be systematically taught, assessed, and then reinforced in clinical practice.

Abstract Chapter 7, “Is Lasting Change Possible?,” describes three different interventions designed to reduce contextual error rates, improving contextualization of care. In the first, termed “audit and feedback,” physicians and other health-care professionals receive ongoing data on their performance at contextualizing care, based on analysis of audio recordings of encounters with their patients. In the second, the feedback is based on data collected by unannounced standardized patients. These interventions are like “holding a mirror up” to the clinician so that they can see what their care looks like, both the good (contextualized care) and the bad (contextual errors), and adapt accordingly. In the third intervention, clinical decision support tools in the electronic medical record guide physicians to contextualize care, drawing on data provided by patients before the visits and from their medical record.

Abstract Chapter 4, “What We Hear That Physicians Don’t,” is a technical breakdown of how to analyze contextualization of care using data collected from audio-recorded encounters and the medical record. In particular, it describes in detail the “4C” content coding system introduced in the previous chapter. Coding content, in contrast to coding of process, requires following the thread and logic of a conversation. 4C identifies contextual red flags (clues that there may be relevant context), contextual probes (attempts to explore the clues), contextual factors (discovered by probes or revealed by the patient), and contextualized care plans (responsive to patient context). This chapter also explains the need for 4C, which is that other approaches to assessing communication in doctor–patient communication research do not capture information on whether clinicians are actually paying attention to and addressing key information that comes up during the medical encounter.

Abstract Chapter 6, “Better Teaching, Better Doctors,” describes the development and testing of a curriculum to improve physician performance at contextualizing care. The chapter begins with an overview of American medical training, illustrating how it fosters an “efficient task completer” mindset, with a narrow biomedical focus that is often inattentive to contextual factors in patients’ lives that are essential to planning their care. A brief intensive curriculum designed to build skills at addressing contextual factors in care planning is then described. The last section provides an overview of two randomized trials of the curriculum, one comparing the performance of fourth-year medical students and another of residents to their respective control group. In the latter, subjects are also assessed in a “real-world” setting utilizing audio recordings of their clinical encounters. The findings illustrate how such a curriculum can improve skills but is not sufficient to change actual performance in practice.

Abstract Listening for What Matters: Avoiding Contextual Errors in Health Care, 2nd edition (LFWM2) provides a comprehensive overview of research and quality improvement efforts to address the problem of inattention to patient life context during clinical encounters that undermine effective care. Such “contextual errors” occur when patient care plans that are otherwise consistent with research evidence for managing a particular clinical condition are, nevertheless, inappropriate for a particular individual based on their life situation, or patient context. Prescribing a medication a patient can’t afford and proposing a treatment plan they don’t have the skills or resources to follow when alternative options are available are examples of contextual error. Identifying contextual errors requires listening in on visits, by employing either unannounced standardized patients (undercover actors) or real patients who volunteer to audio-record encounters. LFWM2 synthesizes nearly two decades of published research employing these unconventional methods to demonstrate how they yield critical and otherwise inaccessible information about physician performance at contextualizing care, including its implication for patients’ health-care outcomes and unnecessary care. The authors also describe studies testing clinical decision support tools in the electronic medical record, medical student and resident trainee educational interventions, and an audio recording–based quality improvement program within the Department of Veterans Affairs to prevent contextual errors. They argue that, ultimately, a greater recognition among payers and the general public of the implications of contextual errors on quality of care and costs is essential to the widespread adoption of methods for identifying and preventing contextual errors.

Abstract Chapter 5, “High versus Low Performers,” asks and answers the question “What makes a clinician good at this?” From an analysis of high, medium, and low performers, the authors have identified six attributes that lead a physician either to overlook context or to recognize and incorporate it. The archetype of a clinician who exemplifies all of the skills for attending to the complexity of context in decision-making is an individual who is flexible rather than rigid in conversation, does not let checklists get in the way of building and testing theories about what might be going on, avoids drawing conclusions prematurely in the face of conflicting evidence, looks for opportunities in every visit to provide some level of care to the patient right now, manages rather than is managed by electronic medical record technology, and is capable of seeing the linkages between patients’ life situations and their clinical care.

Abstract Chapter 3, “The Problem Is Everywhere,” describes the next phase of work, in which hundreds of actual patients, carrying concealed audio recorders, recorded their visits with their physicians. This approach captures how often context matters in actual practice and how often effective care really hinges on a personalized approach in which individual life circumstances are a key factor in planning. The chapter describes the development of a coding system, termed “Content Coding for Contextualization of Care” or “4C,” designed to study actual patient interactions and their outcomes. It also delves into the complex process of conducting the research itself, including the legal and ethical implications of covert audio recording as well as the potential concerns of participants, clinicians, and patients alike.

Abstract Chapter 8, “What We Can’t Measure That Matters,” addresses the limitations of the measures described in this book for capturing what they are designed to measure. In an effort not to overreach and to retain high levels of inter-rater agreement and strong evidence for validity of the construct of contextual error, the coding methodology “4C” applies the term only to the most straightforward instances during clinical encounters where it applies. The benefit of the approach is that the system is highly specific in identifying contextual errors but not particularly sensitive. The concepts of engagement and boundary clarity are introduced to describe ideal clinician behaviors that result in highly contextualized care, beyond the bounds of what is currently measurable.

Abstract Chapter 9, “Bringing Context Back into Care,” reviews the core findings of research on contextualizing of care—that contextual errors are measurable, pervasive, diminish health-care outcomes, increase costs, and are preventable. Addressing the problem will require a broader appreciation of its significance and a commitment to change. Stakeholders, particularly payers and regulators, must hold physicians and all providers accountable for improved attention to patient context in care planning. Doing so will likely require widespread audit and feedback methods, including the use of unannounced standardized patients and real patients who are comfortable audio-recording their care. Medical schools and medical educators must also address a deficit in contextual reasoning skills by revising curricula to include attention to patient context in all clinical case-based instruction.

Abstract Chapter 2, “Measuring the Problem,” transitions from anecdotes and hypotheses to systematic inquiry. Contextual error is characterized as a subtype of medical error that has been overlooked because it is not detectable utilizing conventional methods for detecting error. The authors describe observing physician decision-making directly by sending unannounced standardized patients (USPs) into doctors’ practices to portray cases that challenge physicians to think contextually. Doing so is methodologically challenging as it entails training actors to adopt the personae of real patients while adhering to a script, creating fake medical records, and gaining the trust of physicians who consent not to know when a USP is recording them. The work demonstrates that when patients drop hints that there are life factors interfering with their care, doctors often miss them, instead sending them out with plans that look appropriate on paper but, in fact, are not if one takes into account the context.

Abstract Chapter 1, “Observing the Problem,” illustrates, through a series of case examples, what happens when clinicians overlook patient context and how care planning changes when they finally take it into account. The chapter also proposes hypotheses about why contextual errors in care planning occur—because of a tendency either to make unsupported assumptions about patients’ life circumstances and state of mind or not to consider them at all. Finally, the chapter considers how contextualizing care entails knowing what questions to ask patients and how to ask them. The authors describe how a contextualized care plan emerges out of an engaged interaction between two individuals working together to solve problems, one in the healing role and the other seeking health through health care. Interpersonal “engagement” is characterized as a particular kind of interaction between individuals, essential to contextualizing care in the clinical setting.

INTRODUCTION:Social risks (e.g., food/transportation insecurity) can hamper type 2 diabetes mellitus (T2DM) self-management, leading to poor outcomes. To determine the extent to which high-quality care can overcome social risks' health impacts, this study assessed the associations between reported social risks, receipt of guideline-based T2DM care, and T2DM outcomes when care is up to date among community health center patients.METHODS:A cross-sectional study of adults aged ≥18 years (N=73,484) seen at 186 community health centers, with T2DM and ≥1 year of observation between July 2016 and February 2020. Measures of T2DM care included up-to-date HbA1c, microalbuminuria, low-density lipoprotein screening, and foot examination, and active statin prescription when indicated. Measures of T2DM outcomes among patients with up-to-date care included blood pressure, HbA1c, and low-density lipoprotein control on or within 6‒12 months of an index encounter. Analyses were conducted in 2021.RESULTS:Individuals reporting transportation or housing insecurity were less likely to have up-to-date low-density lipoprotein screening; no other associations were seen between social risks and clinical care quality. Among individuals with up-to-date care, food insecurity was associated with lower adjusted rates of controlled HbA1c (79% vs 75%, p<0.001), and transportation insecurity was associated with lower rates of controlled HbA1c (79% vs 74%, p=0.005), blood pressure (74% vs 72%, p=0.025), and low-density lipoprotein (61% vs 57%, p=0.009) than among those with no reported need.CONCLUSIONS:Community health center patients received similar care regardless of the presence of social risks. However, even among those up to date on care, social risks were associated with worse T2DM control. Future research should identify strategies for improving HbA1c control for individuals with social risks.TRIAL REGISTRATION:This study is registered at www.CLINICALTRIALS:gov NCT03607617.

Background: Evidence-based treatment is provided infrequently and inconsistently to patients with opioid use disorder (OUD). Treatment guidelines call for high-quality, patient-centered care that meets individual preferences and needs, but it is unclear whether current quality measures address individualized aspects of care and whether measures of patient-centered OUD care are supported by evidence. Methods: We conducted an environmental scan of OUD care quality to (1) evaluate patient-centeredness in current OUD quality measures endorsed by national agencies and in national OUD treatment guidelines; and (2) review literature evidence for patient-centered care in OUD diagnosis and management, including gaps in current guidelines, performance data, and quality measures. We then synthesized these findings to develop a new quality measurement taxonomy that incorporates patient-centered aspects of care and identifies priority areas for future research and quality measure development. Results: Across 31 endorsed OUD quality measures, only two measures of patient experience incorporated patient preferences and needs, while national guidelines emphasized providing patient-centered care. Among 689 articles reviewed, evidence varied for practices of patient-centered care. Many practices were supported by guidelines and substantial evidence, while others lacked evidence despite guideline support. Our synthesis of findings resulted in EQuIITable Care, a taxonomy comprised of six classifications: (1) patient Experience and engagement, (2) Quality of life; (3) Identification of patient risks; (4) Interventions to mitigate patient risks; (5) Treatment; and (6) Care coordination and navigation. Conclusions: Current quality measurement for OUD lacks patient-centeredness. EQuIITable Care for OUD provides a roadmap to develop measures of patient-centered care for OUD.

Background: Opioid use disorder (OUD) in pregnancy disproportionately impacts rural and American Indian (AI) communities. With limited data available about access to care for these populations, this study's objective was to assess clinic knowledge and new patient access for OUD treatment in three rural U.S. counties.Material and methods: The research team used unannounced standardized patients (USPs) to request new patient appointments by phone for white and AI pregnant individuals with OUD at primary care and OB/GYN clinics that provide prenatal care in three rural Utah counties. We assessed a) clinic familiarity with buprenorphine for OUD; b) appointment availability for buprenorphine treatment; c) appointment wait times; d) referral provision when care was unavailable; and e) availability of OUD care at referral locations. We compared outcomes for AI and white USP profiles using descriptive statistics.Results: The USPs made 34 calls to 17 clinics, including 4 with publicly listed buprenorphine prescribers on the Substance Abuse and Mental Health Services Administration website. Among clinical staff answering calls, 16 (47%) were unfamiliar with buprenorphine. OUD treatment was offered when requested in 6 calls (17.6%), with a median appointment wait time of 2.5 days (IQR 1-5). Among clinics with a listed buprenorphine prescriber, 2 of 4 (50%) offered OUD treatment. Most clinics (n = 24/28, 85.7%) not offering OUD treatment provided a referral; however, a buprenorphine provider was unavailable/unreachable 67% of the time. The study observed no differences in appointment availability between AI and white individuals.Conclusions: Rural-dwelling AI and white pregnant individuals with OUD experience significant barriers to accessing care. Improving OUD knowledge and referral practices among rural clinics may increase access to care for this high-risk population.

After more than two decades of national attention to quality improvement in US healthcare, significant gaps in quality remain. A fundamental problem is that current approaches to measure quality are indirect and therefore imprecise, focusing on clinical documentation of care rather than the actual delivery of care. The National Academy of Medicine (NAM) has identified six domains of quality that are essential to address to improve quality: patient-centeredness, equity, timeliness, efficiency, effectiveness, and safety. In this perspective, we describe how directly observed care-a recorded audit of clinical care delivery-may address problems with current quality measurement, providing a more holistic assessment of healthcare delivery. We further show how directly observed care has the potential to improve each NAM domain of quality.

Contextualizing care is the process of adapting research evidence to patient life context. The failure to do so, when it results in a care plan that is not likely to achieve its intended aim, is a contextual error. There is substantial evidence that contextual errors are common, adversely affect patient outcomes and health care costs, and are preventable. This evidence comes from over 5000 mostly incognito recordings of physician-patient encounters over a range of practice settings that have been analyzed along with the medical records of each encounter utilizing a specialized coding algorithm. Educational and practice improvement interventions have been tested at the medical student, resident, and attending level, each with evidence of benefits and limitations. The author argues that contextualizing care is an essential clinician competency and proposes an evidence-informed strategy for building and reinforcing the requisite skills across the continuum of medical education and professional development.