Email for clinical communication between healthcare professionals

Email is one of the most widely used methods of communication, but its use in healthcare is still uncommon. Where email communication has been utilised in health care, its purposes have included clinical communication between healthcare professionals, but the effects of using email in this way are not well known. We updated a 2012 review of the use of email for two-way clinical communication between healthcare professionals

Summarisation and visualisation of e-Health data repositories

At the centre of the Clinical e-Science Framework (CLEF) project is a repository of well organised, detailed clinical histories, encoded as data that will be available for use in clinical care and in-silico medical experiments. We describe a system that we have developed as part of the CLEF project, to perform the task of generating a diverse range of textual and graphical summaries of a patient’s clinical history from a data-encoded model, a chronicle, representing the record of the patient’s medical history. Although the focus of our current work is on cancer patients, the approach we describe is generalisable to a wide range of medical areas

Email for clinical communication between healthcare professionals

Background Email is a popular and commonly-used method of communication, but its use in healthcare is not routine. Where email communication has been utilised in health care, its purposes have included use for clinical communication between healthcare professionals, but the effects of using email in this way are not known. This review assesses the use of email for two-way clinical communication between healthcare professionals. Objectives To assess the effects of healthcare professionals using email to communicate clinical information, on healthcare professional outcomes, patient outcomes, health service performance, and service efficiency and acceptability, when compared to other forms of communicating clinical information. Search methods We searched: the Cochrane Consumers and Communication Review Group Specialised Register, Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, Issue 1 2010), MEDLINE (OvidSP) (1950 to January 2010), EMBASE (OvidSP) (1980 to January 2010), PsycINFO (1967 to January 2010), CINAHL (EbscoHOST) (1982 to February 2010), and ERIC (CSA) (1965 to January 2010). We searched grey literature: theses/dissertation repositories, trials registers and Google Scholar (searched July 2010). We used additional search methods: examining reference lists, contacting authors. Selection criteria Randomised controlled trials, quasi-randomised trials, controlled before and after studies and interrupted time series studies examining interventions in which healthcare professionals used email for communicating clinical information, and that took the form of 1) unsecured email 2) secure email or 3) web messaging. All healthcare professionals, patients and caregivers in all settings were considered. Data collection and analysis Two authors independently assessed studies for inclusion, assessed the included studies' risk of bias, and extracted data. We contacted study authors for additional information. We report all measures as per the study report. Main results We included one randomised controlled trial involving 327 patients and 159 healthcare providers at baseline. It compared an email to physicians containing patient-specific osteoporosis risk information and guidelines for evaluation and treatment with usual care (no email). This study was at high risk of bias for the allocation concealment and blinding domains. The email reminder changed health professional actions significantly, with professionals more likely to provide guideline-recommended osteoporosis treatment (bone density measurement and/or osteoporosis medication) when compared with usual care. The evidence for its impact on patient behaviours/actions was inconclusive. One measure found that the electronic medical reminder message impacted patient behaviour positively: patients had a higher calcium intake, and two found no difference between the two groups. The study did not assess primary health service outcomes or harms. Authors' conclusions As only one study was identified for inclusion, the results are inadequate to inform clinical practice in regard to the use of email for clinical communication between healthcare professionals. Future research needs to use high-quality study designs that take advantage of the most recent developments in information technology, with consideration of the complexity of email as an intervention, and costs

Email for communicating results of diagnostic medical investigations to patients

<p>Background: As medical care becomes more complex and the ability to test for conditions grows, pressure on healthcare providers to convey increasing volumes of test results to patients is driving investigation of alternative technological solutions for their delivery. This review addresses the use of email for communicating results of diagnostic medical investigations to patients.</p> <p>Objectives: To assess the effects of using email for communicating results of diagnostic medical investigations to patients, compared to SMS/ text messaging, telephone communication or usual care, on outcomes, including harms, for health professionals, patients and caregivers, and health services.</p> <p>Search methods: We searched: the Cochrane Consumers and Communication Review Group Specialised Register, Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, Issue 1 2010), MEDLINE (OvidSP) (1950 to January 2010), EMBASE (OvidSP) (1980 to January 2010), PsycINFO (OvidSP) (1967 to January 2010), CINAHL (EbscoHOST) (1982 to February 2010), and ERIC (CSA) (1965 to January 2010). We searched grey literature: theses/dissertation repositories, trials registers and Google Scholar (searched July 2010). We used additional search methods: examining reference lists and contacting authors.</p> <p>Selection criteria: Randomised controlled trials, quasi-randomised trials, controlled before and after studies and interrupted time series studies of interventions using email for communicating results of any diagnostic medical investigations to patients, and taking the form of 1) unsecured email 2) secure email or 3) web messaging. All healthcare professionals, patients and caregivers in all settings were considered.</p> <p>Data collection and analysis: Two review authors independently assessed the titles and abstracts of retrieved citations. No studies were identified for inclusion. Consequently, no data collection or analysis was possible.</p> <p>Main results: No studies met the inclusion criteria, therefore there are no results to report on the use of email for communicating results of diagnostic medical investigations to patients.</p> <p>Authors' conclusions: In the absence of included studies, we can draw no conclusions on the effects of using email for communicating results of diagnostic medical investigations to patients, and thus no recommendations for practice can be stipulated. Further well-designed research should be conducted to inform practice and policy for communicating patient results via email, as this is a developing area.</p&gt

Structural variation in generated health reports

We present a natural language generator that produces a range of medical reports on the clinical histories of cancer patients, and discuss the problem of conceptual restatement in generating various textual views of the same conceptual content. We focus on two features of our system: the demand for 'loose paraphrases' between the various reports on a given patient, with a high degree of semantic overlap but some necessary amount of distinctive content; and the requirement for paraphrasing at primarily the discourse level

Training interventions for improving telephone consultation skills in clinicians

The objectives are as follows: To assess the effectiveness of training interventions on clinician telephone skills

What constitutes evidence in human rights-based approaches to health? Learning from lived experiences of maternal and sexual reproductive health

The impact of human rights interventions on health outcomes is complex, multiple, and difficult to ascertain in the conventional sense of cause and effect. Existing approaches based on probable (experimental and statistical) conclusions from evidence are limited in their ability to capture the impact of rights-based transformations in health. This paper argues that a focus on plausible conclusions from evidence enables policy makers and researchers to take into account the effects of a co-occurrence of multiple factors connected with human rights, including the significant role of “context” and power. Drawing on a subject-near and interpretive (in other words, with regard to meaning) perspective that focuses on the lived experiences of human rights-based interventions, the paper suggests that policy makers and researchers are best served by evidence arrived at through plausible, observational modes of ascertaining impact. Through an examination of what human rights-based interventions mean, based on the experience of their operationalization on the ground in culturally specific maternal and reproductive health care contexts, this paper contributes to an emerging scholarship that seeks to pluralize the concept of evidence and to address the methodological challenges posed by heterogeneous forms of evidence in the context of human rights as applied to health

Behaviors That Eliminate Health Disparities for Racial and Ethnic Minorities: A Narrative Systematic Review

Within the health care provider-health care recipient relationship the communication must be culturally competent to eliminate barriers to equitable health care for all Americans. This assertion has conceptual grounding in Public Law 106-129 (the Health Care Research and Quality Act of 1999) and Public Law 106-525 (the Minority Health and Health Disparities Research and Education Act of 2000). This narrative systematic review examines this assertion by using selection and exclusion criteria to gather interventions, assessments, and testimonies conducted from 2000-2007. Reports that were not eliminated via these criteria were analyzed to determine the effect of specific practices that were undertaken in interventions, assessments, and testimonies. Which practices does research propose as indispensable to efforts to eliminate health disparities for racial and ethnic minority health care recipients? Findings indicate that culturally competent behaviors by providers and recipients promote effective intercultural communication that eliminates health care disparities, and removes obstacles to care

DeepCare: A Deep Dynamic Memory Model for Predictive Medicine

Personalized predictive medicine necessitates the modeling of patient illness and care processes, which inherently have long-term temporal dependencies. Healthcare observations, recorded in electronic medical records, are episodic and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes. At the data level, DeepCare represents care episodes as vectors in space, models patient health state trajectories through explicit memory of historical records. Built on Long Short-Term Memory (LSTM), DeepCare introduces time parameterizations to handle irregular timed events by moderating the forgetting and consolidation of memory cells. DeepCare also incorporates medical interventions that change the course of illness and shape future medical risk. Moving up to the health state level, historical and present health states are then aggregated through multiscale temporal pooling, before passing through a neural network that estimates future outcomes. We demonstrate the efficacy of DeepCare for disease progression modeling, intervention recommendation, and future risk prediction. On two important cohorts with heavy social and economic burden -- diabetes and mental health -- the results show improved modeling and risk prediction accuracy.Comment: Accepted at JBI under the new name: "Predicting healthcare trajectories from medical records: A deep learning approach