Explore the vast range of titles available.

Health services have failed to respond to the pressures of multimorbidity. Improved measures of multimorbidity are needed for conducting research, planning services and allocating resources. We modelled the association between 37 morbidities and 3 key outcomes (primary care consultations, unplanned hospital admission, death) at 1 and 5 years. We extracted development (n = 300 000) and validation (n = 150 000) samples from the UK Clinical Practice Research Datalink. We constructed a general-outcome multimorbidity score by averaging the standardized weights of the separate outcome scores. We compared performance with the Charlson Comorbidity Index. Models that included all 37 conditions were acceptable predictors of general practitioner consultations (C-index 0.732, 95% confidence interval [CI] 0.731–0.734), unplanned hospital admission (C-index 0.742, 95% CI 0.737–0.747) and death at 1 year (C-index 0.912, 95% CI 0.905–0.918). Models reduced to the 20 conditions with the greatest combined prevalence/weight showed similar predictive ability (C-indices 0.727, 95% CI 0.725–0.728; 0.738, 95% CI 0.732–0.743; and 0.910, 95% CI 0.904–0.917, respectively). They also predicted 5-year outcomes similarly for consultations and death (C-indices 0.735, 95% CI 0.734–0.736, and 0.889, 95% CI 0.885–0.892, respectively) but performed less well for admissions (C-index 0.708, 95% CI 0.705–0.712). The performance of the general-outcome score was similar to that of the outcome-specific models. These models performed significantly better than those based on the Charlson Comorbidity Index for consultations (C-index 0.691, 95% CI 0.690–0.693) and admissions (C-index 0.703, 95% CI 0.697–0.709) and similarly for mortality (C-index 0.907, 95% CI 0.900–0.914). The Cambridge Multimorbidity Score is robust and can be either tailored or not tailored to specific health outcomes. It will be valuable to those planning clinical services, policymakers allocating resources and researchers seeking to account for the effect of multimorbidity.

In primary, acute-care visits, patients frequently present with more than 1 concern. Various visit factors prevent additional concerns from being articulated and addressed. To test an intervention to reduce patients' unmet concerns. Cross-sectional comparison of 2 experimental questions, with videotaping of office visits and pre and postvisit surveys. Twenty outpatient offices of community-based physicians equally divided between Los Angeles County and a midsized town in Pennsylvania. A volunteer sample of 20 family physicians (participation rate = 80%) and 224 patients approached consecutively within physicians (participation rate = 73%; approximately 11 participating for each enrolled physician) seeking care for an acute condition. After seeing 4 nonintervention patients, physicians were randomly assigned to solicit additional concerns by asking 1 of the following 2 questions after patients presented their chief concern: \"Is there anything else you want to address in the visit today?\" (ANY condition) and \"Is there something else you want to address in the visit today?\" (SOME condition). Patients' unmet concerns: concerns listed on previsit surveys but not addressed during visits, visit time, unanticipated concerns: concerns that were addressed during the visit but not listed on previsit surveys. Relative to nonintervention cases, the implemented SOME intervention eliminated 78% of unmet concerns (odds ratio (OR) = .154, p = .001). The ANY intervention could not be significantly distinguished from the control condition (p = .122). Neither intervention affected visit length, or patients'; expression of unanticipated concerns not listed in previsit surveys. Patients' unmet concerns can be dramatically reduced by a simple inquiry framed in the SOME form. Both the learning and implementation of the intervention require very little time.

Background Most emergency department (ED) patients arrive by their own transport and, for various reasons, may not choose the nearest ED. How far patients travel for ED treatment may reflect both patients’ access to care and severity of illness. In this study, we aimed to examine the travel distance and travel time between a patient’s home and ED they visited and investigate how these distances/times vary by patient and hospital characteristics. Methods We randomly sampled and collected data from 14,812 patients discharged to the community (DTC) between January and March 2016 from 50 hospital-based EDs nationwide. We geocoded and calculated the distance and travel time between patient and hospital-based ED addresses, examined the travel distances/ times between patients’ home and the ED they visited, and used mixed-effects regression models to investigate how these distances/times vary by patient and hospital characteristics. Results Patients travelled an average of 8.0 (SD = 10.9) miles and 17.3 (SD = 18.0) driving minutes to the ED. Patients travelled significantly farther to avoid EDs in lower performing hospitals ( p  < 0.01) and in the West ( p  < 0.05) and Midwest ( p  < 0.05). Patients travelled farther when visiting EDs in rural areas. Younger patients travelled farther than older patients. Conclusions Understanding how far patients are willing to travel is indicative of whether patient populations have adequate access to ED services. By showing that patients travel farther to avoid a low-performing hospital, we provide evidence that DTC patients likely do exercise some choice among EDs, indicating some market incentives for higher-quality care, even for some ED admissions. Understanding these issues will help policymakers better define access to ED care and assist in directing quality improvement efforts. To our knowledge, our study is the most comprehensive nationwide characterization of patient travel for ED treatment to date.

Background Physical function is an important indicator of physical health and predicts mortality. This study identified characteristics associated with limitations in Medicare recipients' activities of daily living. Methods 2019 Consumer Assessment of Healthcare Providers and Systems Fee-for-Service Medicare Survey data: 79,725 respondents (34% response rate) who were 65 and older and 53% female; 7% Black, 5% Hispanic, 4% Asian American, Native Hawaiian, or other Pacific Islander, 2% Multiracial, 1% American Indian/Alaskan Native; 35% with high school education or less. Walking, getting in and out of chairs, bathing, dressing, toileting, and eating (scored as having no difficulty versus being able to do with difficulty or unable to do) and a scale of these items were regressed on patient characteristics. Results After adjustment for all characteristics, function limitations were found for those who smoked (effect sizes of significant associations range .04-.13), had chronic health conditions (.02-.33), were 85 years or older (.09-.46), needed assistance completing the survey (.32–1.29), were female (.05-.07), and had low income and assets (.15-.47). Conclusions These nationally representative U.S. estimates of physical function characteristics are useful for interventions for vulnerable population subgroups.

After the September 11 terrorist attacks, Americans experienced symptoms of psychological stress. This survey of U.S. adults performed just five days after the attacks quantifies the extent of the stress reactions. The terrorist attacks against the United States on September 11, 2001, shook the nation. Television coverage was immediate, graphic, and pervasive. 1 – 3 Newscasts included remarkable video footage showing two airplanes crashing into the World Trade Center and the aftermath of four airplane crashes. 2 , 3 People who are present at a traumatic event often have symptoms of stress, but there is evidence that adults and children need not be present to have stress symptoms, 4 – 6 especially if they consider themselves similar to the victims. 4 The events on September 11 were widely described as attacks on America, and most or all Americans . . .

BackgroundPrevious work has demonstrated racial/ethnic differences in emergency department (ED) utilization, but less is known about racial/ethnic differences in the experience of care received during an ED visit.ObjectiveTo examine differences in self-reported healthcare utilization and experiences with ED care by patients’ race/ethnicity.DesignAdult ED patients discharged to community (DTC) were surveyed (response rate: 20.25%) using the Emergency Department Patient Experience of Care (EDPEC) DTC Survey. Linear regression was used to estimate case-mix-adjusted differences in patient experience between racial/ethnic groups.Participants3122 survey respondents who were discharged from the EDs of 50 hospitals nationwide January–March 2016.Main MeasuresSix measures: getting timely care, doctor and nurse communication, communication about medications, receipt of sufficient information about test results, whether hospital staff discussed the patient’s ability to receive follow-up care, and willingness to recommend the ED.Key ResultsBlack and Hispanic patients were significantly more likely than White patients to report visiting the ED for an ongoing health condition (40% Black, 30% Hispanic, 28% White, p<0.001), report having visited an ED 3+ times in the last 6 months (26% Black, 25% Hispanic, 19% White, p<0.001), and report not having a usual source of care (19% Black, 19% Hispanic, 8% White, p<0.001). Compared with White patients, Hispanic patients more often reported that hospital staff talked with them about their ability to receive needed follow-up care (+7.2 percentile points, p=0.038) and recommended the ED (+7.2 points, p=0.037); Hispanic and Black patients reported better doctor and nurse communication (+6.4 points, p=0.008; +4 points, p=0.036, respectively).ConclusionsHispanic and Black ED patients reported higher ED utilization, lacked a usual source of care, and reported better experience with ED care than White patients. Results may reflect differences in care delivery by staff and/or different expectations of ED care among Hispanic and Black patients.

Patient experience is a key aspect of care quality. Since the 2007 release of the Consumer Assessment of Healthcare Providers and Systems Clinician and Group (CG-CAHPS) survey, no systematic review of factors associated with CG-CAHPS scores has been reported. We reviewed 52 peer-reviewed English language articles published in the United States using CG-CAHPS data. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines and used the Checklist for Analytical Cross-Sectional Studies. We identified several interventions (eg, adding a care coordinator focused on chronic care management) associated with improved overall provider rating and 2 interventions (eg, peer shadow coaching) that improved provider communication scores. Studies evaluating the implementation of patient-centered medical homes or patient-reported outcomes found mixed results. We identified site-level factors (eg, better team communication) and provider-level factors (eg, physician empathy) associated with better patient experience. In contrast, patient-level factors (eg, medication adherence) found mixed associations with patient experience. Policymakers, clinicians, and healthcare leaders can leverage this evidence for quality improvement efforts and interventions supporting patient-centered care.

When the degree of variation between healthcare organisations or geographical regions is quantified, there is often a failure to account for the role of chance, which can lead to an overestimation of the true variation. Mixed-effects models account for the role of chance and estimate the true/underlying variation between organisations or regions. In this paper, we explore how a random intercept model can be applied to rate or proportion indicators and how to interpret the estimated variance parameter.

Background The English Cancer Patient Experience Survey (CPES) is a regularly conducted survey measuring the experience of cancer patients. We studied the survey's underlying structure using factor analysis to identify potential for improvements in reporting or questionnaire design. Methods Cancer Patient Experience Survey 2015 respondents (n = 71,186, response rate 66%) were split into two random subgroups. Using exploratory factor analysis (EFA) on the first subgroup, we identified the survey's latent structure. EFA was then applied to 12 sets of items. A first (“core”) set was formed by questions that applied to all participants. The subsequent sets contained the “core set” plus questions corresponding to specific care pathways/patient groups. We used confirmatory factor analysis (CFA) on the second data subgroup for cross‐validation. Results The EFA suggested that five latent factors underlie the survey's core questions. Analysis on the remaining 11 care pathway/patient group items also indicated the same five latent factors, although additional factors were present for questions applicable to patients with an overnight stay or those accessing specialist nursing. The five factors models had an excellent fit (comparative fit index = 0.95, root mean square error of approximation = 0.045 for core set of questions). Items loading on each factor generally corresponded to a specific section or subsection of the questionnaire. CFA findings were concordant with the EFA patterns. Conclusion The findings suggest five coherent underlying sub‐constructs relating to different aspects of cancer health care. The findings support the construction of evidence‐based composite indicators for different domains of experience and provide options for survey re‐design. The underlying structure of the Cancer Patient experience Survey comprises five major factors. These include shared decisions; care coordination; diagnostic care; timely tests; and aftercare. Our results support the current survey structure, but provide options to guide survey redesign.

In theories of the journalism-state relationship, the watchdog model of journalism competes with other models emphasizing either subservient or oppositional relations. Since actual journalistic practice is circumstantially variable, this study isolates the social conditions associated with aggressive journalism. Data are drawn from presidential news conferences from 1953 to 2000, and the focus is on the aggressiveness of the questions asked therein. Through multivariate models, four sets of explanatory conditions are explored: (1) the administration life cycle, (2) presidential popularity, (3) the state of the economy, and (4) foreign affairs. Results show (1) no evidence of a first-term honeymoon period, but significantly more aggressive questions during second terms, (2) the president's Gallup job approval rating is not a significant independent predictor of aggressiveness, (3) both the unemployment rate and the prime interest rate are positively associated with aggressiveness, and (4) questions about foreign affairs are significantly less aggressive than questions about domestic affairs, and this differential has been stable for at least a half-century. We conclude by discussing the theoretical implications of these findings, which show that journalists modulate their conduct in complex ways that do not readily map onto any single model.