Virtual Communication Across Differences: Development of a Workshop on Managing Patient Bias.

PROBLEM: Despite the prevalence and detrimental effects of racial discrimination in American society and its health care systems, few medical schools have designed and implemented curricula to prepare medical students to respond to patient bias and racism. APPROACH: During the summer of 2020, a virtual communication class was designed that focused on training medical students in how to respond to patient bias and racism. Following brief didactics at the start of the session, students practiced scenarios with actors in small groups and received direct feedback from faculty. For each scenario, students were instructed to briefly gather a patient's history and schedule an appointment with the attending whose name triggered the patient to request an "American" provider. In one scenario, the patient's request was motivated by untreated hearing loss and difficulty understanding accents. In another, it was motivated by racist views toward foreign physicians. Students were to use motivational interviewing (MI) to uncover the reasoning behind the request and respond appropriately. Students assessed their presession and postsession confidence on 5 learning objectives that reflect successful communication modeled after MI techniques. OUTCOMES: Following the session, student skills confidence increased in exploring intentions and beliefs ( P = .026), navigating a conversation with a patient exhibiting bias ( P = .019) and using nonverbal skills to demonstrate empathy ( P = .031). Several students noted that this was their first exposure to the topic in a medical school course and first opportunity to practice these skills under supervision. NEXT STEPS: The experience designing and implementing this module preparing students in responding to patient bias and racism suggests that such an effort is feasible, affordable, and effective. With the clear need for such a program and positive impact on student confidence navigating these discussions, including such training in medical school programs appears feasible and is strongly encouraged.

Validation of the What Matters Index: A brief, patient-reported index that guides care for chronic conditions and can substitute for computer-generated risk models.

INTRODUCTION: Current health care delivery relies on complex, computer-generated risk models constructed from insurance claims and medical record data. However, these models produce inaccurate predictions of risk levels for individual patients, do not explicitly guide care, and undermine health management investments in many patients at lesser risk. Therefore, this study prospectively validates a concise patient-reported risk assessment that addresses these inadequacies of computer-generated risk models. METHODS: Five measures with well-documented impacts on the use of health services are summed to create a "What Matters Index." These measures are: 1) insufficient confidence to self-manage health problems, 2) pain, 3) bothersome emotions, 4) polypharmacy, and 5) adverse medication effects. We compare the sensitivity and predictive values of this index with two representative risk models in a population of 8619 Medicaid recipients. RESULTS: The patient-reported "What Matters Index" and the conventional risk models are found to exhibit similar sensitivities and predictive values for subsequent hospital or emergency room use. The "What Matters Index" is also reliable: akin to its performance during development, for patients with index scores of 1, 2, and ≥3, the odds ratios (with 95% confidence intervals) for subsequent hospitalization within 1 year, relative to patients with a score of 0, are 1.3 (1.1-1.6), 2.0 (1.6-2.4), and 3.4 (2.9-4.0), respectively; for emergency room use, the corresponding odds ratios are 1.3 (1.1-1.4), 1.9 (1.6-2.1), and 2.9 (2.6-3.3). Similar findings were replicated among smaller populations of 1061 mostly older patients from nine private practices and 4428 Medicaid patients without chronic conditions. SUMMARY: In contrast to complex computer-generated risk models, the brief patient-reported "What Matters Index" immediately and unambiguously identifies fundamental, remediable needs for each patient and more sensibly directs the delivery of services to patient categories based on their risk for subsequent costly care.

Development of a care guidance index based on what matters to patients.

INTRODUCTION: Targeting resources for a designated higher-risk subgroup is a strategy for chronic care management. However, risk-designation has several limitations: it is inaccurate, seldom helpful for care guidance, and potentially misallocates care away from many patients. METHODS: To address limitations of risk designation, we tested a "what matters index" (WMI) in 19,593 adult patients with chronic conditions. The WMI contains five binary measures: insufficient confidence to manage health problems, level of pain, emotional problems, polypharmacy, and adverse medication effects. We examined its sum for association with patient-reported quality of life and prior emergency or hospital use. We compared its accuracy to a prototypic risk-designation model. RESULTS: The WMI was a good indicator for quality of life and in three diverse test populations it was strongly associated with the use of hospital and emergency services. For example, a sum of WMI ≥2 was associated with twice as many average uses as none; for ≥3, uses were three times higher. However, since relatively few patients use costly care, both the WMI and a prototypic risk-designation model had comparably low-positive predictive values. The WMI uses the patient voice to identify needs strongly associated with quality of life. Akin to risk designation models, the WMI can be used to place patients into groups associated with levels of costly services, but neither is likely to forecast costly service use for individuals. However, unlike risk-designation models, the WMI is based on measures that will immediately guide care for every patient.

Total cost of care: a discipline that leads to better care.

The health care system is undergoing dramatic change. Different approaches are underway to achieve the triple aim of improving care and population health, strengthening quality, and lowering costs. Integral to meeting the triple aim is aligning incentives for a population-based system, where the emphasis is on effectively managing and improving the care of patients and populations, thus lowering costs. Focusing on total cost of care, a composite of all cost and utilization for a person or population, enables health care payers and providers to make an impact through a patient-centered system that results in better care and reduced costs.

Patients use the internet to enter the medical home.

There is a large gap between the promise of patient-centered medical home (PCMH) and our current capacity to define and measure it. The purpose of this article is to describe the findings of "real-time" patient-reported data about constructs of the PCMH and to demonstrate how an Internet-based method can be useful for obtaining patient report about the PCMH. We find that patients' Internet ratings seem stable and demonstrate relationships that fit constructs and models for the PCMH. We also find that current PCMH performance across this sample of 69 clinical settings is highly variable and still leaves a great deal of room for improvement.

Clinical microsystems, part 2. Learning from micro practices about providing patients the care they want and need.

BACKGROUND: Usual medical care in the United States is frequently not a satisfying experience for either patients or primary care physicians. Whether primary care can be saved and its quality improved is a subject of national concern. An increasing number of physicians are using microsystem principles to radically redesign their practices. Small, independent practices-micro practices-are often able to incorporate into a few people the frontline attributes of successful microsystems such as clear leadership, patient focus, process improvement, performance patterns, and information technology. PATIENT FOCUS, PROCESS IMPROVEMENT, AND PERFORMANCE PATTERNS: An exemplary microsystem will (1) have as its primary purpose a focus on the patient-a commitment to meet all patient needs; (2) make fundamental to its work the study, measurement, and improvement ofcare-a commitment to process improvement; and (3) routinely measure its patterns of performance, "feed back" the data, and make changes based on the data. LESSONS FROM MICRO PRACTICES: The literature and experience with micro practices suggest that they (1) constitute an important group in which to demonstrate the value of microsystem thinking; (2) can become very effective clinical microsystems; (3) can reduce their overhead costs to half that of larger freestanding practices, enabling them to spend more time working with their patients; (4) can develop new tools and approaches without going through layers of clearance; and (5) need not reinvent the wheel. CONCLUSIONS: Patient-reported data demonstrate how micro practices are using patient focus, process improvement, performance patterns, and information technology to improve performance. Pati ents should be able to report that they receive "exactly the care they want and need exactly when and how they want and need it."

Clinical microsystems, part 1. The building blocks of health systems.

BACKGROUND: Wherever, however, and whenever health care is delivered-no matter the setting or population of patients-the body of knowledge on clinical microsystems can guide and support innovation and peak performance. Many health care leaders and staff at all levels of their organizations in many countries have adapted microsystem knowledge to their local settings. CLINICAL MICROSYSTEMS: A PANORAMIC VIEW: HOW DO CLINICAL MICROSYSTEMS FIT TOGETHER? As the patient's journey of care seeking and care delivery takes place over time, he or she will move into and out of an assortment of clinical microsystems, such as a family practitioner's office, an emergency department, and an intensive care unit. This assortment of clinical microsystems-combined with the patient's own actions to improve or maintain health--can be viewed as the patient's unique health system. This patient-centric view of a health system is the foundation of second-generation development for clinical microsystems. LESSONS FROM THE FIELD: These lessons, which are not comprehensive, can be organized under the familiar commands that are used to start a race: On Your Mark, Get Set, Go! ... with a fourth category added-Reflect: Reviewing the Race. These insights are intended as guidance to organizations ready to strategically transform themselves. CONCLUSION: Beginning to master and make use of microsystem principles and methods to attain macrosystem peak performance can help us knit together care in a fragmented health system, eschew archipelago building in favor of nation-building strategies, achieve safe and efficient care with reliable handoffs, and provide the best possible care and attain the best possible health outcomes.

An introduction to technology for patient-centered, collaborative care.

"Patient-centered, collaborative care" is healthcare jargon. But underlying the jargon is the principle that a patient who receives such care strongly agrees that "I receive exactly the healthcare I want and need exactly when and how I want and need it." Currently only about 1 in 4 Americans who have adequate financial resources can make this claim. Think of a pyramid. At the apex is the highest level of "patient-centered, collaborative care." At the base are measures about "what's the matter" (from the clinical perspective) and "what matters" (from the patient perspective). As patients and clinicians act collaboratively on these measures, they climb closer to the apex of the pyramid. Given the realities of healthcare in the Unites States, should busy professionals take time to think about ways to climb pyramids? In this "Introduction" we describe why the answer to this rhetorical question ought to be "yes." In the articles that comprise this issue, readers will learn how technology that supports patient-centered, collaborative care can help bridge the gap between desirable goals and limited time. All the authors understand technology (such as hardware and software), and the way humans use the technology (called techne) will not overcome the many obstacles to the attainment of patient-centered, collaborative care. Nevertheless, we are hopeful that the examples described in these articles suggest ways that significant progress toward patient-centered, collaborative care can be made. The articles are practical. The results are persuasive. It is worth the climb!

The emergence of Ideal Micro Practices for patient-centered, collaborative care.

Ideal Micro Practices are capable of delivering patient-centered collaborative care. With respect to comparable adult patients in "usual" care settings, twice as many patients who use Ideal Micro Practices report they receive care that is "exactly what they want and need exactly when and how they want and need it" (68% vs 35%). Compared to usual care, these very small, low-overhead practices are more likely to have patients report very high levels of continuity (98% vs 88%), efficiency (95% vs 73%), and access (72% vs 53%). Patient ratings of very good information (83% vs 67%) and clinician awareness of pain or emotional problem are also higher (87% vs 69%). However, only a slim majority of patients using Ideal Micro Practices report that they are confident in their ability to manage and control their health problems or concerns. Ideal Micro Practices are sharing new tools and approaches to better understand their patients' needs and increase patients' confidence in their ability to manage conditions. In addition, these practices are working collaboratively to standardize their approaches and make the essential elements of Ideal Micro Practice replicable.