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Refusals of Medical Aid in the Prehospital Setting

Refusals of Medical Aid in the Prehospital Setting

Rachel Waldron, M.D., Cherie Finalle, M.D., Deborah Mogelof, M.D.

Background:  When an Emergency Medical Technician (EMT) responds to a call, the patient may choose to refuse medical attention (RMA).   In order to decrease RMA’s, we must first understand more about them.

Objective:  Our research examined the characteristics of both patients and EMTs who are involved in RMA’s.   As well, we studied the timing of RMA’s both by shift and within an individual shift.

Methods:  This was a retrospective chart review of all patient charts in which the patient RMA’d for the time period 8/1/05 through 7/31/06, a one-year period.  These patients were then compared to a control set of patients that was created by reviewing every chart in a 24- hour period for ten randomly selected days within the same one-year period.  The data was obtained from the patient care reports (PCR’s) which are scanned by NYHQ EMT’s into HealthEMS database.  Data analysis was performed using SAS 9.1 for Windows. 

Results:  The RMA data set had a total of 238 patients, 58% female and 42% male, with a mean age of 56. The control data set had a total of 303 patients, 53% female and 47% male, with a mean age of 53. There was no difference in the sex distribution between the RMA and control groups (Pr <= 0.2965.)  There was also no difference in average age of the RMA and control patients on the day and evening shifts (Pr 0.1764 & 0.0711).  However, on the night shift the patients in the RMA group were significantly younger – mean age of 47 in the research group versus 55 in the control group (Pr 0.0160).
The EMT teams in the RMA set were 0.42% female/female,7.14% mixed, and 92.44% male/male.  The EMT teams in the control set were 4.62% female/female, 34.65% mixed, and 60.73% male/male.  The higher percentage of males EMT’s in the RMA set achieved statistical significance (P < 0.0001).  The sex of the EMT team versus the sex of the patient had no effect on increasing RMA’s.  (P 0.9936)

The patient’s chief complaint was significantly different in the RMA versus control groups.  The RMA group had more neurological, psychiatric, and social chief complaints. (P< 0.0001)  This difference holds true for both day and evening shifts (Chi-Square 0.0003, 0.0001), however on nights is not significant (Chi-Square 0.0812).
In the RMA group, the shifts were 35.71% day, 41.6% evening, and 22.69% night.  In the control group, the shifts were 51% day, 30.03 % evening, and 18.48% night.  RMA’s were more common on the evening and night shifts (Chi-Square 0.0011).  The calls were also broken down as to whether occurring in the first two hours of the shift, the middle four, or the last two hours.  There was no difference in the frequency of RMA’s based on the timing within the shift. (P 0.5488)

Conclusions:  The call most likely to generate an RMA contains the following set of characteristics:  a younger patient with a chief complaint falling out of the usual medical categories like trauma or cardiac, two male EMT’s on the team, and an evening or night shift.  The commonly held perception that RMA’s are more common at the end of a shift (to avoid working overtime) was proven to be untrue.


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