Out-of-hospital decision making and factors influencing the regional distribution of injured patients in a trauma system.

BACKGROUND: The decision-making processes used for out-of-hospital trauma triage and hospital selection in regionalized trauma systems remain poorly understood. The objective of this study was to assess the process of field triage decision making in an established trauma system. METHODS: We used a mixed methods approach, including emergency medical services (EMS) records to quantify triage decisions and reasons for hospital selection in a population-based, injury cohort (2006-2008), plus a focused ethnography to understand EMS cognitive reasoning in making triage decisions. The study included 10 EMS agencies providing service to a four-county regional trauma system with three trauma centers and 13 nontrauma hospitals. For qualitative analyses, we conducted field observation and interviews with 35 EMS field providers and a round table discussion with 40 EMS management personnel to generate an empirical model of out-of-hospital decision making in trauma triage. RESULTS: A total of 64,190 injured patients were evaluated by EMS, of whom 56,444 (88.0%) were transported to acute care hospitals and 9,637 (17.1% of transports) were field trauma activations. For nontrauma activations, patient/family preference and proximity accounted for 78% of destination decisions. EMS provider judgment was cited in 36% of field trauma activations and was the sole criterion in 23% of trauma patients. The empirical model demonstrated that trauma triage is driven primarily by EMS provider "gut feeling" (judgment) and relies heavily on provider experience, mechanism of injury, and early visual cues at the scene. CONCLUSIONS: Provider cognitive reasoning for field trauma triage is more heuristic than algorithmic and driven primarily by provider judgment, rather than specific triage criteria.

Local media influence on opting out from an exception from informed consent trial.

STUDY OBJECTIVE: News media are used for community education and notification in exception from informed consent clinical trials, yet their effectiveness as an added safeguard in such research remains unknown. We assessed the number of callers requesting opt-out bracelets after each local media report and described the errors and content within each media report. METHODS: We undertook a descriptive analysis of local media trial coverage (newspaper, television, radio, and Web log) and opt-out requests during a 41-month period at a single site participating in an exception from informed consent out-of-hospital trial. Two nontrial investigators independently assessed 41 content-based media variables (including background, trial information, graphics, errors, publication information, and assessment) with a standardized, semiqualitative data collection tool. Major errors were considered serious misrepresentation of the trial purpose or protocol, whereas minor errors included misinformation unlikely to mislead the lay reader about the trial. We plotted the temporal relationship between opt-out bracelet requests and media reports. Descriptive information about the news sources and the trial coverage are presented. RESULTS: We collected 39 trial-related media reports (33 newspaper, 1 television, 1 radio, and 4 blogs). There were 13 errors in 9 (23%) publications, 7 of which were major and 6 minor. Of 384 requests for 710 bracelets, 310 requests (80%) occurred within 4 days after trial media coverage. Graphic timeline representation of the data suggested a close association between media reports about the trial and requests for opt-out bracelets. CONCLUSION: According to results from a single site, local media coverage for an exception from informed consent clinical trial had a substantial portion of errors and appeared closely associated with opt-out requests.

A geospatial analysis of persons opting out of an exception from informed consent out-of-hospital clinical trial.

STUDY OBJECTIVE: For trials involving exception from informed consent, some IRBs require that community members be allowed to "opt out" prior to enrollment. We tested for geospatial clustering of opt-out requests and the associated census tract characteristics in one study region. METHODS: This was a retrospective study at a single site of a multicenter exception from informed consent resuscitation trial. We collected and geocoded mailing addresses for persons requesting opt-out bracelets over 16 months, then tested for geospatial clustering using geographic information systems (GIS) analysis. Characteristics for tracts with and without bracelet clustering were compared using univariate tests, multivariable regression, and classification and regression tree (CART) analysis. RESULTS: We received 395 phone calls requesting 718 bracelets, of which 673 were analyzable. Of 397 census tracts in the region, 208 (52%) had at least one request and 38 (10%) demonstrated clustering. In multivariable models, an increasing proportion of family households (OR .90, 95%CI .85-.93), veterans (OR .91, 95%CI .81-1.02), and renters (OR .96, 95%CI .92-.99) were associated with lower odds of requesting an opt-out bracelet, while census tracts with higher income had higher odds of opting-out (OR 1.07, 95%CI 1.02-1.11). Using CART, the proportion of family households and graduate education identified the majority of opt-out requests by census tracts (cross-validation sensitivity 92%, specificity 56%). CONCLUSIONS: Opt-out requests for an exception from informed consent trial at one study site were geographically clustered and associated with certain population demographics. These findings may help identify key target groups for community consultation in future trials.

Why persons choose to opt out of an exception from informed consent cardiac arrest trial.

BACKGROUND: We sought to characterize persons who requested to opt out of an exception from informed consent (EFIC) cardiac arrest trial and their reasons for opting out. METHODS: At one site of a multi-site, out-of-hospital, cardiac arrest EFIC trial (September 2007 - June 2009), persons who did not want to participate in the study could request an opt-out "NO STUDY" bracelet to prevent trial enrollment. We surveyed all persons who requested a bracelet by phone interview, web or mail. Opt-out bracelets were advertised in all public communication about the study, including community consultation and public disclosure efforts. Survey questions included demographics, Likert scale items about attitudes toward the trial and research in general, plus open-ended questions. We used descriptive statistics for standardized questions and qualitative analysis to identify common themes from open-ended questions. RESULTS: Sixty bracelets were requested by 50 individuals. Surveys were completed by 46 persons (92% response rate). Seventy percent of respondents agreed emergency research is important, but 87% objected to any research without consent. In the qualitative analysis, 5 overlapping themes emerged: questioning the ethics of EFIC research; concerns about how the study would impact end-of-life preferences; subjective emotions including sarcasm, anger, and allusions to past unethical research; negative reference to unrelated public health controversies; and objections to the study protocol based on misinformation. CONCLUSIONS: A primary reason for opting out from this EFIC trial was opposition to all research without informed consent, despite stated support for emergency research. Understanding the demographics and beliefs of persons opting out may aid researchers planning EFIC studies and help provide clarity in future EFIC-related community education efforts.