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1.
Prehosp Emerg Care ; 11(1): 80-4, 2007.
Article in English | MEDLINE | ID: mdl-17169883

ABSTRACT

BACKGROUND: Continuing quality improvement (CQI) reviews reflect that medication administration errors occur in the prehospital setting. These include errors involving dose, medication, route, concentration, and treatment. METHODS: A survey was given to paramedics in San Diego County. The survey tool was established on the basis of previous literature reviews and questions developed with previous CQI data. RESULTS: A total of 352 surveys were returned, with the paramedics reporting a mean of 8.5 years of field experience. They work an average of 11.0 shifts/month with an average of 25.4 hours and 6.7 calls/shift. Thirty-two (9.1%) responding paramedics reported committing a medication error in the last 12 months. Types of errors included dose-related errors (63%), protocol errors (33%), wrong route errors (21%), and wrong medication errors (4%). Issues identified in contributing to the errors include failure to triple check, infrequent use of the medication, dosage calculation error, and incorrect dosage given. Fatigue, training, and equipment setup of the drug box were not listed as any of the contributing factors. The majority of these errors were self-reported to their CQI representative (79.1%), with 8.3% being reported by the base hospital radio nurse, 8.3% found upon chart review, and 4.2% noted by paramedic during call but never reported. CONCLUSIONS: Nine percent of paramedics responding to an anonymous survey report medication errors in the last 12 months, with 4% of these errors never having been reported in the CQI process. Additional safeguards must continue to be implemented to decrease the incidence of medication errors.


Subject(s)
Emergency Medical Technicians , Medication Errors , Truth Disclosure , California , Humans
2.
Prehosp Emerg Care ; 10(4): 457-62, 2006.
Article in English | MEDLINE | ID: mdl-16997774

ABSTRACT

BACKGROUND: Continuing quality improvement (CQI) reviews reflect that medication administration errors occur in the prehospital setting. These include errors involving dose, medication, route, concentration, and treatment. METHODS: A survey was given to paramedics in San Diego County. The survey tool was established based on previous literature reviews and questions developed based on previous CQI data. RESULTS: A total of 352 surveys were returned, with the paramedics reporting a mean of 8.5 years of field experience. They work an average of 11.0 shifts/month with an average shift length of 25.4 hours and 6.7 calls/shift. Thirty-two responding paramedics (9.1%) reported committing a medication error in the past 12 months. Types of errors included dose-related errors (63%), protocol errors (33%), wrong route errors (21%), and wrong medication errors (4%). Issues identified in contributing to the errors include failure to triple check, infrequent use of the medication, dosage calculation error, and incorrect dosage given. Fatigue, training, and equipment setup of the drug box were not listed as any of the contributing factors. The majority of these errors were self-reported to their CQI representative (79.1%), with 8.3% reported by the base hospital radio nurse, 8.3% found on chart review, and 4.2% noted by the paramedic during the call but never reported. CONCLUSIONS: Nine percent of paramedics responding to an anonymous survey reported medication errors in the past 12 months, with 4% of these errors never having been reported in the CQI process. Additional safeguards must continue to be implemented to decrease the incidence of medication errors.


Subject(s)
Allied Health Personnel/statistics & numerical data , Medication Errors/statistics & numerical data , Adult , California , Child , Humans , Medication Errors/prevention & control , Surveys and Questionnaires
3.
Ann Emerg Med ; 44(4): 295-303, 2004 Oct.
Article in English | MEDLINE | ID: mdl-15459611

ABSTRACT

STUDY OBJECTIVE: Emergency department (ED) ambulance diversion is a major issue in many communities. When patients do not reach requested facilities, challenges in care are compounded by lack of available medical records and delays in transferring admitted patients back to the originally requested facility. We seek to evaluate a community intervention to reduce ambulance diversion. METHODS: This was a community intervention in a county of 2.8 million individuals. Ambulance diversion guidelines were revised for all ambulance agencies and EDs. Participation by EDs was voluntary, and main outcome measures, which included ambulance transports, ambulance diversions, and bypass hours, were compared for the pretrial, trial, and posttrial periods. RESULTS: A total of 235,766 patients were transported to an ED by advanced life support ambulance during the 2-year study period. There was a significant decrease in the number of patients who did not reach the requested facility because of ambulance diversion for the trial period (n=322) and posttrial period (n=449) compared with the pretrial period (n=1,320; -998 diverted patients per month [95% confidence interval (CI) -1,162 to -833 patients] and -871 diverted patients per month [95% CI -963 to -780 patients], respectively). There was also a significant decrease in average monthly hours on diversion for the trial period (n=1,079) and posttrial period (n=1,774) compared with the pretrial period (n=4,007; -2,928 hours on bypass [95% CI -3,936 to -1,919 hours on bypass] and -2,232 hours on bypass [95% CI -3,620 to -2,235 hours on bypass], respectively). CONCLUSION: A voluntary community-wide approach to reducing hospital ED diversion and getting more ambulance patients to requested facilities was effective.


Subject(s)
Ambulances , Community Health Services/organization & administration , Emergency Medical Services/organization & administration , Emergency Service, Hospital/organization & administration , Patient Transfer/organization & administration , Regional Health Planning , Adolescent , Adult , California , Community Networks , Female , Humans , Male , Middle Aged , Patient Transfer/statistics & numerical data , Time Factors
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