More effective models of care delivery are needed, but their successful implementation depends on effective care teams and good management of local operations (clinical microsystems). Clinicians influence both, and local clinician leaders will have several key tasks.
Research on asthma frequently recruits patients from clinics because the ready pool of patients leads to easy access to patients in office waiting areas, emergency departments, or hospital wards. Patients with other chronic conditions, and with mobility problems, face exposures at home that are not easily identified at the clinic. In this paper we describe the perspective of the community health workers and challenges they encountered when making home visits while implementing a research intervention in a cohort of low-income, minority patients. From their observations, poor housing, often the result of poverty and lack of social resources, is the real elephant in the chronic asthma room. To achieve a goal of reduced asthma morbidity and mortality will require a first-hand understanding of the real-world social and economic barriers to optimal asthma management and the solutions to those barriers.
Big data in medicine-massive quantities of health care data accumulating from patients and populations and the advanced analytics that can give those data meaning-hold the prospect of becoming an engine for the knowledge generation that is necessary to address the extensive unmet information needs of patients, clinicians, administrators, researchers, and health policy makers. This article explores the ways in which big data can be harnessed to advance prediction, performance, discovery, and comparative effectiveness research to address the complexity of patients, populations, and organizations. Incorporating big data and next-generation analytics into clinical and population health research and practice will require not only new data sources but also new thinking, training, and tools. Adequately utilized, these reservoirs of data can be a practically inexhaustible source of knowledge to fuel a learning health care system.
We investigated whether an expert’s consultation provided via telemedicine could improve the quality of care for patients with dysphagia. A trained clinician completed videofluoroscopic swallowing studies (VFSS) of 17 consecutive patients in a Greek hospital. The videofluoroscopic images were then stored on a website for independent review by an expert Speech and Language Pathologist in the US. An extra Rater evaluated 20% of all data for additional reliability testing. Eight diagnostic indicators of swallowing impairment and an overall subjective severity index were recorded for each study. Clinicians were also asked to choose from ten common treatment options for patients with dysphagia. There was good inter-rater agreement for most of the diagnostic indicators examined (ranging from 78% to 90%; kappa = 0.52-0.71) between all three Raters. Agreement on overall severity ratings was exact for more than half of the patients and within one-point on the 4-point scale for all other patients except one. However, the quality of care would have been substandard for more than half of the patients if teleconsultation had not been employed. In settings where a swallowing expert is not available and real-time telemedicine is not feasible, the use of asynchronous teleconsultation can produce better quality of care for patients with dysphagia.
Our objective was to determine whether components of fixed orthodontic appliances as received from the manufacturers and after exposure to the clinical environment are free from microbial contamination before clinical use. A pilot molecular microbiologic laboratory study was undertaken at a dental hospital in the United Kingdom.
- JAMA : the journal of the American Medical Association
- Published over 6 years ago
In older patients, acute medical illness that requires hospitalization is a sentinel event that often precipitates disability. This results in the subsequent inability to live independently and complete basic activities of daily living (ADLs). This hospitalization-associated disability occurs in approximately one-third of patients older than 70 years of age and may be triggered even when the illness that necessitated the hospitalization is successfully treated. In this article, we describe risk factors and risk stratification tools that identify older adults at highest risk of hospitalization-associated disability. We describe hospital processes that may promote hospitalization-associated disability and models of care that have been developed to prevent it. Since recognition of functional status problems is an essential prerequisite to preventing and managing disability, we also describe a pragmatic approach toward functional status assessment in the hospital focused on evaluation of ADLs, mobility, and cognition. Based on studies of acute geriatric units, we describe interventions hospitals and clinicians can consider to prevent hospitalization-associated disability in patients. Finally, we describe approaches clinicians can implement to improve the quality of life of older adults who develop hospitalization-associated disability and that of their caregivers.
- The Australian & New Zealand journal of obstetrics & gynaecology
- Published over 3 years ago
Anecdotally, severe dysmenorrhoea can pre-date the development of chronic pelvic pain (CPP). This study describes the timeline for the transition from dysmenorrhoea to CPP in a cohort of new patients attending a private gynaecology clinic. In 16.4% of cases, transition occurred within one year, and within 12 years in over 50%. Our study suggests clinicians need to observe women with severe dysmenorrhoea for signs of chronic pain. Further research is needed into the transition from dysmenorrhoea to CPP, and effective early interventions.
There is a lack of evidence on the best treatment option for umbilical granuloma. The primary aim of this study was to compare three treatments for umbilical granuloma: standard treatment with topical silver nitrate, clobetasol propionate cream (0.05%) and ethanol wipes. The secondary aim was to evaluate whether the treatment could be successfully administered by a parent at home, rather than in the outpatient clinic.
Practice-based research networks bring together academic researchers and primary care clinicians to conduct research that improves health outcomes in real-world settings. The Washington, Wyoming, Alaska, Montana, and Idaho region Practice and Research Network implemented a health data-sharing infrastructure across 9 clinics in 3 primary care organizations. Following implementation, we identified challenges and solutions. Challenges included working with diverse primary care organizations, adoption of health information data-sharing technology in a rapidly changing local and national landscape, and limited resources for implementation. Overarching solutions included working with a multidisciplinary academic implementation team, maintaining flexibility, and starting with an established network for primary care organizations. Approaches outlined may generalize to similar initiatives and facilitate adoption of health data sharing in other practice-based research networks.
Can we exploit our burgeoning understanding of molecular evolution to slow the progress of drug resistance? One role of an infection clinician is exactly that: to foresee trajectories to resistance during antibiotic treatment and to hinder that evolutionary course. But can this be done at a hospital-wide scale? Clinicians and theoreticians tried to when they proposed two conicting behavioural strategies that are expected to curb resistance evolution in the clinic, these are known as ‘antibiotic cycling’ and ‘antibiotic mixing’. However, the accumulated data from clinical trials, now approaching 4 million patient days of treatment, is too variable for cycling or mixing to be deemed successful. The former implements the restriction and prioritisation of di_erent antibiotics at di_erent times in hospitals in a manner said to ‘cycle’ between them. In antibiotic mixing, appropriate antibiotics are allocated to patients but randomly.Mixing results in no correlation, in time or across patients, in the drugs used for treatment which is why theorists saw this as an optimal behavioural strategy. So while cycling and mixing were proposed as ways of controlling evolution, we show there is good reason why clinical datasets cannot choose between them: by re-examining the theoretical literature we show prior support for the theoretical optimality of mixing was misplaced. Our analysis is consistent with a pattern emerging in data: neither cycling or mixing is a priori better than the other at mitigating selection for antibiotic resistance in the clinic.