No abstract

The phrase "patient-centered care" is in vogue, but its meaning is poorly understood. This article describes patient-centered care, why it matters, and how policy makers can advance it in practice. Ultimately, patient-centered care is determined by the quality of interactions between patients and clinicians. The evidence shows that patient-centered care improves disease outcomes and quality of life, and that it is critical to addressing racial, ethnic, and socioeconomic disparities in health care and health outcomes. Policy makers need to look beyond such areas as health information technology to shape a coordinated and focused national policy in support of patient-centered care. This policy should help health professionals acquire and maintain skills related to patient-centered care, and it should encourage organizations to cultivate a culture of patient-centeredness.

Among insured nonelderly adults, there are appreciable disparities in health-care use by race and Hispanic ethnicity. Ethnic disparities in care are largely explained by differences in English fluency, but racial disparities in care are not explained by commonly used access factors.

Cancer-related fatigue (CRF) is one of the most prevalent symptoms patients with cancer experience, both during and after treatment. CRF is pervasive and affects patients' quality of life considerably. It is important, therefore, to understand the underlying pathophysiology of CRF in order to develop useful strategies for prevention and treatment. At present, the etiology of CRF is poorly understood and the relative contributions of the neoplastic disease, various forms of cancer therapy, and comorbid conditions (e.g., anemia, cachexia, sleep disorders, depression) remain unclear. In any individual, the etiology of CRF probably involves the dysregulation of several physiological and biochemical systems. Mechanisms proposed as underlying CRF include 5-HT neurotransmitter dysregulation, vagal afferent activation, alterations in muscle and ATP metabolism, hypothalamic-pituitary-adrenal axis dysfunction, circadian rhythm disruption, and cytokine dysregulation. Currently, these hypotheses are largely based on evidence from other conditions in which fatigue is a characteristic, in particular chronic fatigue syndrome and exercise-induced fatigue. The mechanisms that lead to fatigue in these conditions provide a theoretical basis for future research into the complex etiology of this distressing and debilitating symptom. An understanding of relevant mechanisms may offer potential routes for its prevention and treatment in patients with cancer.

IMPORTANCE Observational studies demonstrate links between patient-centered communication, quality of life (QOL), and aggressive treatments in advanced cancer, yet few randomized clinical trials (RCTs) of communication interventions have been reported. OBJECTIVE To determine whether a combined intervention involving oncologists, patients with advanced cancer, and caregivers would promote patient-centered communication, and to estimate intervention effects on shared understanding, patient-physician relationships, QOL, and aggressive treatments in the last 30 days of life. DESIGN, SETTING, AND PARTICIPANTS Cluster RCT at community- and hospital-based cancer clinics in Western New York and Northern California; 38 medical oncologists (mean age 44.6 years; 11 (29%) female) and 265 community-dwelling adult patients with advanced nonhematologic cancer participated (mean age, 64.4 years, 146 [55.0%] female, 235 [89%] white; enrolled August 2012 to June 2014; followed for 3 years); 194 patients had participating caregivers. INTERVENTIONS Oncologists received individualized communication training using standardized patient instructors while patients received question prompt lists and individualized communication coaching to identify issues to address during an upcoming oncologist visit. Both interventions focused on engaging patients in consultations, responding to emotions, informing patients about prognosis and treatment choices, and balanced framing of information. Control participants received no training. MAIN OUTCOMES AND MEASURES The prespecified primary outcome was a composite measure of patient-centered communication coded from audio recordings of the first oncologist visit following patient coaching (intervention group) or enrollment (control). Secondary outcomes included the patient-physician relationship, shared understanding of prognosis, QOL, and aggressive treatments and hospice use in the last 30 days of life. RESULTS Data from 38 oncologists (19 randomized to intervention) and 265 patients (130 intervention) were analyzed. In fully adjusted models, the intervention resulted in clinically and statistically significant improvements in the primary physician-patient communication end point (adjusted intervention effect, 0.34; 95% CI, 0.06–0.62; P = .02). Differences in secondary outcomes were not statistically significant. CONCLUSIONS AND RELEVANCE A combined intervention that included oncologist communication training and coaching for patients with advanced cancer was effective in improving patient-centered communication but did not affect secondary outcomes. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01485627

BACKGROUND. Patient, provider, and systems barriers contribute to delays in cancer care, a lower quality of care, and poorer outcomes in vulnerable populations, including low‐income, underinsured, and racial/ethnic minority populations. Patient navigation is emerging as an intervention to address this problem, but navigation requires a clear definition and a rigorous testing of its effectiveness. Pilot programs have provided some evidence of benefit, but have been limited by evaluation of single‐site interventions and varying definitions of navigation. To overcome these limitations, a 9‐site National Cancer Institute Patient Navigation Research Program (PNRP) was initiated. METHODS. The PNRP is charged with designing, implementing, and evaluating a generalizable patient navigation program targeting vulnerable populations. Through a formal committee structure, the PNRP has developed a definition of patient navigation and metrics to assess the process and outcomes of patient navigation in diverse settings, compared with concurrent continuous control groups. RESULTS. The PNRP defines patient navigation as support and guidance offered to vulnerable persons with abnormal cancer screening or a cancer diagnosis, with the goal of overcoming barriers to timely, quality care. Primary outcomes of the PNRP are 1) time to diagnostic resolution; 2) time to initiation of cancer treatment; 3) patient satisfaction with care; and 4) cost effectiveness, for breast, cervical, colon/rectum, and/or prostate cancer. CONCLUSIONS. The metrics to assess the processes and outcomes of patient navigation have been developed for the NCI‐sponsored PNRP. If the metrics are found to be valid and reliable, they may prove useful to other investigators. Cancer 2008. © 2008 American Cancer Society.

No abstract

BackgroundMobile phone use and the adoption of healthy lifestyle software apps (“health apps”) are rapidly proliferating. There is limited information on the users of health apps in terms of their social demographic and health characteristics, intentions to change, and actual health behaviors.ObjectiveThe objectives of our study were to (1) to describe the sociodemographic characteristics associated with health app use in a recent US nationally representative sample; (2) to assess the attitudinal and behavioral predictors of the use of health apps for health promotion; and (3) to examine the association between the use of health-related apps and meeting the recommended guidelines for fruit and vegetable intake and physical activity.MethodsData on users of mobile devices and health apps were analyzed from the National Cancer Institute’s 2015 Health Information National Trends Survey (HINTS), which was designed to provide nationally representative estimates for health information in the United States and is publicly available on the Internet. We used multivariable logistic regression models to assess sociodemographic predictors of mobile device and health app use and examine the associations between app use, intentions to change behavior, and actual behavioral change for fruit and vegetable consumption, physical activity, and weight loss.ResultsFrom the 3677 total HINTS respondents, older individuals (45-64 years, odds ratio, OR 0.56, 95% CI 0.47-68; 65+ years, OR 0.19, 95% CI 0.14-0.24), males (OR 0.80, 95% CI 0.66-0.94), and having degree (OR 2.83, 95% CI 2.18-3.70) or less than high school education (OR 0.43, 95% CI 0.24-0.72) were all significantly associated with a reduced likelihood of having adopted health apps. Similarly, both age and education were significant variables for predicting whether a person had adopted a mobile device, especially if that person was a college graduate (OR 3.30). Individuals with apps were significantly more likely to report intentions to improve fruit (63.8% with apps vs 58.5% without apps, P=.01) and vegetable (74.9% vs 64.3%, P<.01) consumption, physical activity (83.0% vs 65.4%, P<.01), and weight loss (83.4% vs 71.8%, P<.01). Individuals with apps were also more likely to meet recommendations for physical activity compared with those without a device or health apps (56.2% with apps vs 47.8% without apps, P<.01).ConclusionsThe main users of health apps were individuals who were younger, had more education, reported excellent health, and had a higher income. Although differences persist for gender, age, and educational attainment, many individual sociodemographic factors are becoming less potent in influencing engagement with mobile devices and health app use. App use was associated with intentions to change diet and physical activity and meeting physical activity recommendations.