Dataset Information

Patient attitudes regarding consent for emergency department computed tomographies.

ABSTRACT:

Introduction

Little is known about patient attitudes towards informed consent for computed tomography (CT) in the emergency department (ED). We set out to determine ED patient attitudes about providing informed consent for CTs.

Methods

In this cross-sectional questionnaire-based survey study, we evaluated a convenience sample of patients' attitudes about providing informed consent for having a CT at 2 institutional sites. Historically, at our institutional network, patients received a CT at approximately 25% of their ED visits. The survey consisted of 17 "yes/no" or multiple-choice questions. The primary outcome question was "which type of informed consent do you feel is appropriate for a CT in the Emergency Department?"

Results

We analyzed 300 survey responses, which represented a 90% return rate of surveys distributed. Seventy-seven percent thought they should give their consent prior to receiving a CT, and 95% were either comfortable or very comfortable with their physician making the decision regarding whether they needed a CT. Forty percent of the patients felt that a general consent was appropriate before receiving a CT in the ED, while 34% thought a verbal consent was appropriate and 15% percent thought a written consent was appropriate. Seventy-two percent of the ED patients didn't expect to receive a CT during their ED visit and 30% of the ED patients had previously provided consent prior to receiving a CT.

Conclusion

Most patients feel comfortable letting the doctor make the decision regarding the need for a CT. Most ED patients feel informed consent should occur before receiving a CT but only a minority feel the consent should be written and specific to the test.

SUBMITTER: Weigner MB

PROVIDER: S-EPMC3935784 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature

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Publications

Patient attitudes regarding consent for emergency department computed tomographies.

Weigner Michael B MB Basham Hilary F HF Dewar Kate M KM Rupp Valerie A VA Cornelius Llewellyn L Greenberg Marna Rayl MR

The western journal of emergency medicine 20140201 1

<h4>Introduction</h4>Little is known about patient attitudes towards informed consent for computed tomography (CT) in the emergency department (ED). We set out to determine ED patient attitudes about providing informed consent for CTs.<h4>Methods</h4>In this cross-sectional questionnaire-based survey study, we evaluated a convenience sample of patients' attitudes about providing informed consent for having a CT at 2 institutional sites. Historically, at our institutional network, patients receiv ...[more]

PMID: 24578764

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Project description:ObjectivesAlthough computerized decision support for imaging is often recommended for optimizing computed tomography (CT) use, no studies have evaluated emergency physicians' (EPs') preferences regarding computerized decision support in the emergency department (ED). In this needs assessment, the authors sought to determine if EPs view overutilization as a problem, if they want decision support, and if so, the kinds of support they prefer.MethodsA 42-item, Web-based survey of EPs was developed and used to measure EPs' attitudes, preferences, and knowledge. Key contacts at local EDs sent letters describing the study to their physicians. Exploratory principal components analysis (PCA) was used to determine the underlying factor structure of multi-item scales, Cronbach's alpha was used to measure internal consistency of items on a scale, Spearman correlations were used to describe bivariate associations, and multivariable linear regression analysis was used to identify variables independently associated with physician interest in decision support.ResultsOf 235 surveys sent, 155 (66%) EPs responded. Five factors emerged from the PCA. EPs felt that: 1) CT overutilization is a problem in the ED (α = 0.75); 2) a patient's cumulative CT study count affects decisions of whether and what type of imaging study to order only some of the time (α = 0.75); 3) knowledge that a patient has had prior CT imaging for the same indication makes EPs less likely to order a CT (α = 0.42); 4) concerns about malpractice, patient satisfaction, or insistence on CTs affect CT ordering decisions (α = 0.62); and 5) EPs want decision support before ordering CTs (α = 0.85). Performance on knowledge questions was poor, with only 18% to 39% correctly responding to each of the three multiple-choice items about effective radiation doses of chest radiograph and single-pass abdominopelvic CT, as well as estimated increased risk of cancer from a 10-mSv exposure. Although EPs wanted information on patients' cumulative exposures, they feel inadequately familiar with this information to make use of it clinically. If provided with patients' cumulative radiation exposures from CT, 87% of EPs said that they would use this information to discuss imaging options with their patients. In the multiple regression model, which included all variables associated with interest in decision support at p < 0.10 in bivariate tests, items independently associated with EPs' greater interest in all types of decision support proposed included lower total knowledge scores, greater frequency that cumulative CT study count affects EP's decision to order CTs, and greater agreement that overutilization of CT is a problem and that awareness of multiple prior CTs for a given indication affects CT ordering decisions.ConclusionsEmergency physicians view overutilization of CT scans as a problem with potential for improvement in the ED and would like to have more information to discuss risks with their patients. EPs are interested in all types of imaging decision support proposed to help optimize imaging ordering in the ED and to reduce radiation to their patients. Findings reveal several opportunities that could potentially affect CT utilization.

Project description:OBJECTIVES:As shared decision making (SDM) has received increased attention as a method to improve the patient-centeredness of emergency department (ED) care, we sought to determine patients' desired level of involvement in medical decisions and their perceptions of potential barriers and facilitators to SDM in the ED. METHODS:We surveyed a cross-sectional sample of adult ED patients at three academic medical centers across the United States. The survey included 32 items regarding patient involvement in medical decisions including a modified Control Preference Scale and questions about barriers and facilitators to SDM in the ED. Items were developed and refined based on prior literature and qualitative interviews with ED patients. Research assistants administered the survey in person. RESULTS:Of 797 patients approached, 661 (83%) agreed to participate. Participants were 52% female, 45% white, and 30% Hispanic. The majority of respondents (85%-92%, depending on decision type) expressed a desire for some degree of involvement in decision making in the ED, while 8% to 15% preferred to leave decision making to their physician alone. Ninety-eight percent wanted to be involved with decisions when "something serious is going on." The majority of patients (94%) indicated that self-efficacy was not a barrier to SDM in the ED. However, most patients (55%) reported a tendency to defer to the physician's decision making during an ED visit, with about half reporting they would wait for a physician to ask them to be involved. CONCLUSION:We found that the majority of ED patients in our large, diverse sample wanted to be involved in medical decisions, especially in the case of a "serious" medical problem, and felt that they had the ability to do so. Nevertheless, many patients were unlikely to actively seek involvement and defaulted to allowing the physician to make decisions during the ED visit. After fully explaining the consequences of a decision, clinicians should make an effort to explicitly ascertain patients' desired level of involvement in decision making.

Project description:ObjectivesEmergency department (ED) crowding is an increasing problem associated with adverse patient outcomes. ED expansion is one method advocated to reduce ED crowding. The objective of this analysis was to determine the effect of ED expansion on measures of ED crowding.MethodsThis was a retrospective study using administrative data from two 11-month periods before and after the expansion of an ED from 33 to 53 adult beds in an academic medical center. ED volume, staffing, and hospital admission and occupancy data were obtained either from the electronic health record (EHR) or from administrative records. The primary outcome was the rate of patients who left without being treated (LWBT), and the secondary outcome was total ED boarding time for admitted patients. A multivariable robust linear regression model was used to determine whether ED expansion was associated with the outcome measures.ResultsThe mean (±SD) daily adult volume was 128 (±14) patients before expansion and 145 (±17) patients after. The percentage of patients who LWBT was unchanged: 9.0% before expansion versus 8.3% after expansion (difference = 0.6%, 95% confidence interval [CI] = -0.16% to 1.4%). Total ED boarding time increased from 160 to 180 hours/day (difference = 20 hours, 95% CI = 8 to 32 hours). After daily ED volume, low-acuity area volume, daily wait time, daily boarding hours, and nurse staffing were adjusted for, the percentage of patients who LWBT was not independently associated with ED expansion (p = 0.053). After ED admissions, ED intensive care unit (ICU) admissions, elective surgical admissions, hospital occupancy rate, ICU occupancy rate, and number of operational ICU beds were adjusted for, the increase in ED boarding hours was independently associated with the ED expansion (p = 0.005).ConclusionsAn increase in ED bed capacity was associated with no significant change in the percentage of patients who LWBT, but had an unintended consequence of an increase in ED boarding hours. ED expansion alone does not appear to be an adequate solution to ED crowding.

Project description:BackgroundHealth care provider usage of mobile devices is increasing globally; however, there is little understanding of patient perceptions on this behavior in a health care setting.ObjectiveThe aim of this study was to assess patients' attitudes toward mobile device usage by health care providers in the emergency department and to identify predictors of these attitudes.MethodsThe study was carried out at the emergency department of a large academic tertiary care medical center in Lebanon. A cross-sectional survey design was adopted by administering a questionnaire to medically stable adult patients who presented to the emergency department with an emergency severity index of 3, 4, or 5 between January 2017 and March 2018. The questionnaire collected relevant patient demographic information and included questions related to their mobile device usage along with those evaluating attitudes for the use of mobile devices by health care providers with respect to six major domains: role in health care, distraction potential, impact on communication, empathy, privacy, and professionalism. The attitude toward mobile device usage by health care providers in the emergency department was the main outcome variable. A stepwise logistic regression model was used to assess the association between the outcome variable and the demographic and attitude-related independent variables.ResultsAmong the 438 eligible patients, 338 patients responded to the questionnaire for a response rate of 70.0%. Overall, 313/338 (92.6%) respondents agreed that mobile devices improve health care delivery, whereas 132/338 (39.1%) respondents were opposed to their usage by health care providers in the emergency department (95% CI: 34.0-44.4). The majority (240/338, 71.0%) of patients agreed that mobile devices are a source of distraction to health care providers in the workplace. Females (odds ratio [OR]=1.67, 95% CI: 1.00-2.78) as well as all patients (OR=2.54, 95% CI 1.36-4.76) who believed that mobile devices were a source of distraction, reflecting a lack of professionalism (OR=2.77, 95% CI 1.59-4.82) and impacting the provider's ability to relate to the patient (OR=2.93, 95% CI 1.72-4.99), were more likely to agree that mobile devices should not be used in the emergency department.ConclusionsPatients' negative attitude toward mobile device use in the emergency department is largely driven by patient gender (females), patient perception of the distraction potential of the devices, and their negative impact on the health care provider's empathy and professionalism. The findings of this study shed light on the importance of encouraging stakeholders to impose a digital professionalism code of conduct for providers working in acute health care settings.

Project description:IntroductionLaw enforcement officers (LEO) interact with patients and clinicians in the emergency department (ED) for many reasons. There is no current consensus on what should comprise, or how to best enact, guidelines that ideally balance LEO activities in the service of public safety with patient health, autonomy, and privacy. The purpose of this study was to explore how a national sample of emergency physicians (EP) perceives activities of LEOs during the delivery of emergency medical care.MethodsMembers of the Emergency Medicine Practice Research Network (EMPRN) were recruited via an email-delivered, anonymous survey that elicited experiences, perceptions, and knowledge of policies that guide interactions with LEOs in the ED. The survey included multiple-choice items, which we analyzed descriptively, and open-ended questions, which we analyzed using qualitative content analysis.ResultsOf 765 EPs in the EMPRN, 141 (18.4%) completed the survey. Respondents represented diverse locations and years in practice. A total of 113 (82%) respondents were White, and 114 (81%) were male. Over a third reported LEO presence in the ED on a daily basis. A majority (62%) perceived LEO presence as helpful for clinicians and clinical practice. When asked about the factors deemed highly important in allowing LEOs to access patients during care, 75% reported patients' potential as a threat to public safety. A small minority of respondents (12%) considered the patients' consent or preference to interact with LEOs. While 86% of EPs felt that information-gathering by LEO was appropriate in the ED setting, only 13% were aware of policy to guide these decisions. Perceived barriers to implementation of policy in this area included: issues of enforcement; leadership; education; operational challenges; and potential negative consequences.ConclusionFuture research is warranted to explore how policies and practices that guide intersections between emergency medical care and law enforcement impact patients, clinicians, and the communities that health systems serve.

Project description:BACKGROUND:Reliably abstracting outcomes from free-text electronic health records remains a challenge. While automated classification of free text has been a popular medical informatics topic, performance validation using real-world clinical data has been limited. The two main approaches are linguistic (natural language processing [NLP]) and statistical (machine learning). The authors have developed a hybrid system for abstracting computed tomography (CT) reports for specified outcomes. OBJECTIVES:The objective was to measure performance of a hybrid NLP and machine learning system for automated outcome classification of emergency department (ED) CT imaging reports. The hypothesis was that such a system is comparable to medical personnel doing the data abstraction. METHODS:A secondary analysis was performed on a prior diagnostic imaging study on 3,710 blunt facial trauma victims. Staff radiologists dictated CT reports as free text, which were then deidentified. A trained data abstractor manually coded the reference standard outcome of acute orbital fracture, with a random subset double-coded for reliability. The data set was randomly split evenly into training and testing sets. Training patient reports were used as input to the Medical Language Extraction and Encoding (MedLEE) NLP tool to create structured output containing standardized medical terms and modifiers for certainty and temporal status. Findings were filtered for low certainty and past/future modifiers and then combined with the manual reference standard to generate decision tree classifiers using data mining tools Waikato Environment for Knowledge Analysis (WEKA) 3.7.5 and Salford Predictive Miner 6.6. Performance of decision tree classifiers was evaluated on the testing set with or without NLP processing. RESULTS:The performance of machine learning alone was comparable to prior NLP studies (sensitivity = 0.92, specificity = 0.93, precision = 0.95, recall = 0.93, f-score = 0.94), and the combined use of NLP and machine learning showed further improvement (sensitivity = 0.93, specificity = 0.97, precision = 0.97, recall = 0.96, f-score = 0.97). This performance is similar to, or better than, that of medical personnel in previous studies. CONCLUSIONS:A hybrid NLP and machine learning automated classification system shows promise in coding free-text electronic clinical data.

Dataset Information

Patient attitudes regarding consent for emergency department computed tomographies.

Introduction

Methods

Results

Conclusion

Publications

Patient attitudes regarding consent for emergency department computed tomographies.

Similar Datasets

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