RESEARCH

ANALYSIS OF EMERGENCY MEDICAL SERVICES TRIAGE AND DISPATCH ERRORS BY REGISTERED NURSES IN ITALY Authors: Elisabetta Palma, PhD, MSN, RN, Daniele Antonaci, MSN, RN, Antonio Colì, MSN, RN, and Giancarlo Cicolini, PhD, MSN, RN, Chieti and Lecce, Italy Introduction: The major elements of an effective emergency

medical services (EMS) system include a single telephone access number, accurate assessment of the urgency of the health problem, and timely dispatch of appropriate personnel and equipment. In Italy, EMS calls are managed by emergency operations centers by registered nurses who have received specialized education in this function. The nurses determine the criticality of the situations and assign an EMS response priority level identified by a color code, ranging from red (very critical) to green (not critical). At times, the severity of a situation may be underestimated, resulting in assignment of a lower EMS response priority and the potential for patient death (code black). The purpose of this study was to analyze factors associated with registered nurse under-triage of EMS calls subsequently found to be associated with deaths, termed “green-black code” cases. Methods: We carried out a retrospective qualitative analysis of EMS telephone conversations using Fele’s conversation analysis method. The characteristics of green-black code calls

Elisabetta Palma is Lecturer, Department of Nursing Sciences, Center of Excellence on Aging, Clinical Research Center, University of “G. d’Annunzio” Foundation, Chieti, Italy. Daniele Antonaci is Chief Nurse, Province of Lecce Emergency Department, Lecce, Italy. Antonio Colì is Chief Nurse, Province of Lecce Emergency Department, Lecce, Italy. Giancarlo Cicolini is Nurse Director, Second Level Degree Nursing Sciences, Faculty of Medicine, University of Chieti–Pescara, Chieti, Italy. For correspondence, write: Elisabetta Palma, PhD, MSN, RN, Center of Excellence on Aging, Clinical Research Center, University of “G. d’Annunzio” Foundation, Via dei Vestini 31, I-66013 Chieti, Scalo, Italy; E-mail: [email protected]. J Emerg Nurs ■. 0099-1767/$36.00 Copyright © 2014 Emergency Nurses Association. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jen.2014.02.009



were compared with the characteristics of the population of all EMS calls during the study period. Results: The study patients were older, with a mean age of 81.6

years. The callers were individuals calling on behalf of the patients, rather than the patients themselves. The callers reported symptoms that were not life-threatening. Nurse operators did not always inquire about the patients’ vital signs as required by the Medical Priority Dispatch System protocol. The phone conversations were shorter than normal (54.26 seconds vs 65 seconds). Discussion: Although the importance of dispatch system

protocols is well known, it is also important that nurse triage operators have proper training to ensure that major parameters such as vital signs and symptomatology are obtained and to reduce caller stress level. Key words: Ambulances/utilization; Emergency medical services organization and administration; Health priorities; Quality of health care; Triage

fforts to improve health care outcomes while fostering cost containment through appropriate use of resources have resulted in a proliferation in the provision of telephone assessment and consultation services by registered nurses (RNs) in a variety of settings. Handling a telephone call that may involve a request for emergency care requires substantial expertise. The operator is expected to quickly recognize the severity of the medical condition, identify the possible etiology, and determine the resources required while reducing the caller’s anxiety or aggressiveness to obtain the caller’s collaboration. 1 The operator should use time efficiently, collecting only the necessary information without prolonging the phone call. Operators require proficiency in effective communication skills to collect all the relevant data. The subsequent decision-making process should lead to the best response— the right emergency care mobile resource and the right staff at the right time.

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TABLE 1

Correspondence between color and numeric codes Color code

Numeric code

Description

White

0

Green

1

Yellow

2

Red

3

Black

4

The situation is not an emergency and an ambulance is not needed. The patient is safe or does not have a relevant pathology. The patient’s condition is not life threatening. The situation is not an emergency; the patient has an acute but stable pathology. The patient’s vital signs are normal. The situation is a medical emergency. Intervention cannot be delayed; the patient’s vital signs are stable at the moment but should be strictly monitored to prevent possible worsening. The situation is an absolute emergency. The patient’s vital signs have deteriorated or indicate an immediate threat to the patient’s life. The vital signs must be stabilized and supported during the intervention and transportation. The patient is dead.

In Italy, RNs are responsible for both the triage of patients arriving at the emergency department and the telephone emergency medical services (EMS) dispatch system. Italian law specifies at least 6 months’ seniority in emergency nursing to perform medical triage. In addition, emergency operations center (EOC) RN operators are emergency nurses with at least 2 years’ seniority in the emergency department and expertise in prehospital care. At the time of the study, Italy did not have a codified system to standardize the collection and analysis of prehospital data, although processes were in place for selected conditions, such as trauma and cardiac arrest. 2,3 A recent survey by the Italian Ministry of Health showed that EOC operators use a dual-mode (color and alphanumeric) code system to classify both the criticality and the severity of an emergency call 4 (Table 1). The code assigned to the prevailing pathology is the second most important information for emergency dispatchers. When a patient has comorbidities, the operator assigns a code that refers to the most relevant symptoms (Table 2). Finally, the location code indicates where the event took place (Table 2). Determining Appropriate Response Resources

Emergency dispatching is a dynamic decision-making process, 5 as well as the most important activity performed by EOCs. It consists of 4 phases: taking incoming calls, instructing callers, dispatching the appropriate EMS resources, and instructing the ambulance crew. Appropriate conversation techniques enable the operator to obtain collaboration from the caller. In addition, the use of a standardized interview

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protocol allows for the collection of all relevant details while avoiding conflicts with the caller. 6,7 Collaboration depends on 3 caller variables: emotional status, knowledge of the situation, and general behavior when reporting an emergency. Theoretically, the emotional status of the caller does not really affect collaboration because a well-trained operator can guide a scared or angry caller using specific interrogation techniques, as well as a calm voice. An Italian study confirmed that only 4% of callers were annoyed or irritated. 8 The caller may be the patient himself or herself (first-party caller), a person in the patient’s direct vicinity (second-party caller), or a person who is not with the patient but is reporting from some distance (third-party caller). About 55% of EMS phone calls in Italy are made by first- or second-party callers 9 who, if correctly interviewed, may provide all the relevant information. That is why the use of a standardized interview protocol, together with appropriate training on how to lead a succinct telephone conversation, is so important. When an emergency occurs, the caller has a distorted time perception. For this reason, it is important that an emergency medical call be answered by at least the third ring, although such a response time—about 12 seconds—would still prove rather lengthy for an emergency call. 10 In the case of life-threatening situations, such as cardiac arrest, electrocution, drowning, and suffocation, 11 the telephone conversation should last less than 1 minute. The mobilization time (from call end to EMS vehicle dispatch) generally varies from 75 to 90 seconds. This time interval is considered part of the standard ambulance response time set by the law in Italy,

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TABLE 2

Dispatch codes Prevalent pathology

Location

C01: trauma C02: cardiocirculatory

S: street (public or private) P: public place (business location, office) Y: sport facility K: home L: workplace Q: school Z: other location

C03: C04: C05: C06: C07: C08: C09: C10: C11: C12: C13: C14: C15: C19: C20:

respiratory neurologic psychiatric neoplastic toxicologic metabolic gastroenterologic urologic ophthalmologic otorhinolaryngologic dermatologic obstetric-gynecologic infective other pathology unidentified pathology

Review of Literature

which is 8 minutes for urban areas and for life-threatening emergencies and 20 minutes for rural areas.

Characteristics of Effective Telephone Encounter

What are the main features of satisfactory communication when taking an emergency medical call? Although research has increased in recent years, literature concerning the qualitative aspects of telephone dispatching is still rather poor. Several studies appear to lack methodologic rigor, 12 with the 5-level priority system used in France, Canada, the United States, the United Kingdom, and Australia being more consensus based than evidence based. 13 Several studies have focused on the efficacy of a single telephone number for all the emergency services, such as 911 in the United States or 112, introduced in the European community in 2001. With the exception of the province of Varese (Northern Italy), where a single emergency telephone number has been available since 2010, Italy has a different emergency number for each of the various emergency services (fire, medical, and police emergency). Data from Italy show that EOC operators are able to screen about half of all calls, which ensures that emergency services (police, fire department, EMS) are activated only



when needed. 14 One Italian study showed that EOC operators tend to overestimate the criticality and severity codes as compared with the assessment performed by the emergency medical team on the scene. 15 Several scene responder–identified green codes appeared to be overestimated as yellow, whereas red codes were not always properly identified. With regard to telephone conversation content analysis, qualitative research is oriented toward defining the local organizational structure 1 whereas sociolinguistic research is more oriented toward analyzing telephone conversations between people serving a formal organization/institution. 16 A study analyzing “special conversations” showed that intervention in emergency situations consists of 5 steps: dispatchers take the incoming call and identify themselves, the caller asks for help, a brief conversation takes place, the caller’s request is responded to, and the process is completed. 17

A systematic review of the literature concerning telephone triage performed by EMS system operators identified 326 studies. 18 The overall quality of these studies was modest, with only a few studies seeming to consistently support the use of specific criteria to identify medical priorities to improve patient outcomes. Sometimes calls are not appropriate, for example, patients who do not meet the specific criteria for an immediate ambulance response. It appears that the accuracy of emergency response procedures improves when operators assign a priority code using the Medical Priority Dispatch System (MPDS) protocol. Statistically, an assessment using the MPDS protocol is more concordant with the criticality code assigned by the on-scene emergency medical team. 18,19 The use of the MPDS protocol also seems to reduce emergency medical technicians’ response time in the most critical cases. 20–22 Despite the use of standard protocols, EMS dispatch assessment errors (under-triage) still occur, especially in complex situations involving patients with multiple or chronic diseases. Underestimating an emergency situation may be significant, such as when an emergency medical team, arriving on the scene of what they were told was a green code (not particularly critical), finds that the patient has died in the meantime. Such occurrences, dubbed “green-black code” cases by Italian emergency health workers, are considered sentinel events (Figure). This study aims to detect, through a retrospective qualitative analysis of telephone conversations, the factors associated with under-triage.

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green-black codes

35 30 25 20 15 10 5 0

2005

2006

2007

2008

2009

2010

2011

FIGURE Sentinel events (ie, green-black code cases) for the years 2005 through 2011.

Methods

well as vehicle response time. In Italy, volunteer-staffed vehicles provide basic life support (BLS) and early defibrillation whereas vehicles staffed with a physician and RN provide advanced life support (ALS). The patient data section permitted analysis of the concordance between the emergency code initially assigned by the dispatchers and the medical team’s assessment on their arrival on scene. Using Fele’s model, we analyzed the 15 green-black telephone conversations, focusing on 4 crucial aspects: incoming call receipt (operators identify the service), problem description (operators collect all relevant data from the caller), problem identification (operators assign a criticality code), and call ending (operators reassure the caller and revise the information collected from the caller). STATISTICAL ANALYSIS

The characteristics of 2 different call groups were analyzed. We carried out a retrospective study of a sample of 839 EMS calls that occurred during 2011 at the EOC of Lecce, Italy. Permission to access the database was obtained from the General Administrative Management of the EOC. The sample was randomly extracted by use of a table of random numbers from a population of 62,392 EMS calls (α b 5%, 99% confidence interval [CI]). We compared the characteristics of the sample telephone conversations with the characteristics of the 15 green-black calls occurring in 2011. The phone calls were analyzed with the aim of collecting information on conversational features. The following variables were considered: details of the event, telephone conversation, EMS care resources, and patient data. Specific data were analyzed for each section. The section on details of the event comprised the time interval from call receipt until the appropriate mobile care resource was physically en route to the emergency, the dispatcher, the final criticality/priority assessment, and other data. With regard to the telephone conversation section, the criticality code assigned while the caller is interrogated is the product of a decision-making process that can be based on dispatcher experience or on application of the MPDS protocol. This code is communicated to the ambulance crew immediately after the call. Conversations were analyzed using the qualitative and phenomenological techniques implemented by Fele 23 in his conceptual model. Fele is an Italian sociologist who has conducted several investigations in the field of the emergency services (police, fire department, EMS). His “conversational analysis method” is specifically applied to study institution-centered interactions, such as those occurring in EOCs. The section on EMS care resources comprised information regarding the type of resource dispatched, as

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Data were exported to a Microsoft Access database (version 10.00; Microsoft, Redmond, WA) and analyzed by use of SPSS software for Windows, version 17.0 (SPSS, Chicago, IL). We performed a factorial analysis considering all the variables of a dispatch. In addition, the qualitative variables of the green-black code were examined. Results

The EOC is equipped with an Ericsson MD-110 PBX system (Ericsson Enterprise, Stockholm, Sweden) that routes emergency calls to operators (there are generally 6 dispatchers per shift). During 2011, operators received 62,392 emergency calls, from which we randomly extracted a sample of 839 calls. The number of incoming emergency calls per operator while dispatchers were already handling phone calls varied from 2 to 47 (mean, 23.41; SD, 11.12). Although the proficiency of operators when creating a dispatch depends on several variables, a regression analysis showed that the variable “operator” was not strictly related to the whole green-black code phenomenon. Linear regression analysis (R 2 test) showed that the variable “operator” accounted for only 14% of the entire process. DISPATCH CREATION TIME

The overall time to generate a dispatch was calculated by use of a linear model. The mean time was about 65 seconds (99% CI, 61-69 seconds). The mean duration of telephone conversations was about the same in both the sample (range, 43.8-64.8 seconds) and the green-black code subgroup (range, 61.5-69.4 seconds). The mean time necessary to send the appropriate mobile care resource and complete the

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TABLE 3

Data comparison between sample and green-black code subgroup Patient age (y) Dispatch creation time (s) Ambulance response time (min) Urban areas Rural areas

Sample

Green-black code subgroup

61.8 (99% CI, 57-67) 65.47 (99% CI, 61.4-69.4)

81.6 (95% CI, 77-86) 54.26 (95% CI, 44.7-65.7)

11.5 (99% CI, 5.2-17.8) 19.4 (99% CI, 4.9-33.9)

17.7 (95% CI, 6.2-29.2) 17.9 (95% CI, 9.6-26.1)

dispatch was 95 seconds (99% CI, 84-106 seconds). Phone calls generally lasted less than 120 seconds (82.5%) and, in some cases, less than 60 seconds (43.3%). COMPLETENESS OF DATA COLLECTION

Operators failed to record all the details required for computer-assisted dispatching for 85.7% of the calls. This missing information could enable a better post hoc analysis. Some data seemed to be less neglected than others, as in the case of cardiovascular patients, for whom additional information was almost always present. EVENT LOCATION

Most phone calls were about medical emergencies occurring at home (76.9%) or in the street (14.1%) (Table 2). PREVAILING PATHOLOGY

Cardiovascular pathologies were most common (29.9%), followed by trauma-induced musculoskeletal problems (21.9%), and respiratory diseases (13.8%). No prevailing pathology was present in 17% of the cases (Table 2). CRITICALITY SCORE ASSIGNED BY OPERATOR

In the observed sample, the color codes assigned were as follows: red in 6.9%, yellow in 56%, green in 36.8%, and white (ie, not urgent at all) in 0.3%. CONCORDANCE IN CRITICALITY SCORE

The EOC operators and scene responders agreed in only 31.6% of patients with a green code and in 26.7% of patients with a yellow code. GREEN-BLACK CODE CASES

During 2011, 15 of 62,392 dispatches (1:4,000) classified as nonurgent (green) by the EOC operators



were associated with a patient death (black code). The analyses performed in the general population were repeated for this particular subgroup; however, the CI was set at 95% because the subgroup was smaller (Table 3). In addition, telephone conversations were analyzed to evaluate the quality of communication and the occurrence of incorrect assessments during calls. The response time in the green-black code subgroup was significantly shorter (54.26 seconds; 95% CI, 44-65 seconds) when compared with the sample. Most phone calls lasted less than 60 seconds (66%). In those undertriaged cases (green code), operators had not documented all the major items of the MPDS protocol (consciousness, breathing, circulation) on the dispatch form and a BLS-staffed ambulance (volunteer crew) was sent instead of an ALS-staffed ambulance. When volunteers with BLS training assessed the criticality of the situation, they called the EOC for medical support so that a second ambulance with a nurse and a physician was sent. The first ambulance arrived within 8 minutes (standard time for urban areas) in 25% of cases. Because of the nonurgent emergency code, the mean response time of the first ambulance was about 17 minutes (95% CI, 6-29 minutes). The mean response time for rural areas was 18 minutes (95% CI, 9-26 minutes), indicating that the 20-minute standard response time for rural areas was generally accomplished (86%). When compared with the mean age of all the patients treated (61.8 years), the patients in the green-black code subgroup were significantly older (mean age, 81.6 years; 95% CI, 77-86 years), as shown in Table 3. Q UAL ITATIVE ASS ESS MENT O F TEL EPHO NE CONVERSATIONS

As proposed by the Fele method, we divided conversations into 4 parts: incoming call receipt, problem description, problem identification, and call ending.

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Incoming Call Receipt

TABLE 4

When taking an incoming call, operators should immediately identify the service as well as themselves by saying “Emergency Operations Center 118, I am a nurse.” Operators generally did identify the service (86.7%). Problem Description When taking emergency calls, operators ask for details according to a set of standard questions. They may go through the whole list of questions (accurate interrogation), ask only a few questions (inaccurate interrogation), or just listen (simple listening). The interview was accurate in 4 cases (26.7%), the interview was inaccurate in 8 cases (53.3%), and operators simply listened in 3 cases (20%). Problem Identification To quickly obtain vital information about patient status and scene conditions, the operator should act according to the MPDS protocol, asking the caller whether the patient is alert and breathing. Operators asked both questions (alert and breathing) in 1 case (6.7%), asked only 1 question (alert or breathing) in 5 cases (33.3%), and did not ask either question in 9 cases (60%). Call Ending At the end of the conversation, operators reassured callers, telling them that an ambulance was on its way, in 13 cases (86.7%). To evaluate the accuracy of telephone conversations, we assigned a score between 0 points (0%) and 6 points (100%) to the described variables (Table 4). The mean score of the 15 telephone conversations was 54.4% (95% CI, 43.7%-65.2%). Discussion

This study focused on the qualitative aspects of EOC RN operator activity, with the aim of detecting the possible causes of underestimation of the severity of health emergencies subsequently associated with so-called greenblack code cases. The 15 calls associated with the greenblack code cases were routed to the operators by automatic switching equipment. This study has several limitations, primarily related to the lack of a common reference model for measuring the effectiveness of the dispatch process at EOCs. The few existing studies on this topic referred to different organizational settings and were specifically focused on indicators such as dispatch accuracy, ambulance response times, and concordance between severity codes

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Quality assessment of telephone conversations Item

Opening (service identification) Yes No Problem explanation Not accurate Quite accurate Accurate Problem identification (awareness and breathing) Neither question Only 1 question Both questions Closure (reassurance) Yes No

Points

1 0 0 1 2 0 1 2 1 0

assigned by dispatchers and the actual emergency scenario found by medical teams on their arrival. Assuming that the green-black code cases are sentinel events, we compared the 15 deaths with the overall activity of the EOC considered in this study via a retrospective analysis. The aim was to detect possible differences in the activity of operators (dispatch appropriateness and effectiveness), the demographic characteristics of the patients, or the telephone conversations. Our data refer to a local EOC, which means that the results cannot be generalized. The mean length of telephone conversations was 65 seconds. The mean dispatch initiation time was 95 seconds, with the limit of 120 seconds—a standard accepted by experts 9—generally being respected (82.5%). At times, collecting data from the caller was difficult and time-consuming, and therefore the delay was not attributable to the operators. Although the proficiency level of operators when creating a dispatch depends on several variables, a regression analysis showed that the variable “operator” was not strictly related to the whole green-black code phenomenon. Because of the small sample size, it is not possible to establish a relationship between the duration of a dispatch and the criticality code assigned. With regard to the thoroughness of completing the dispatch form, we observed that items referring to symptoms and events (chest pain, trauma, car accident, sudden illness) were often left blank (85.7%). Symptoms and events more likely to be reported are “chest pain” (5.6%) and “car accident” (4.7%), perhaps

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because such occurrences require implementation of specific protocols such as acute myocardial infarction and prehospital trauma care. Operators generally tend to overestimate the condition of patients reporting chest pain. 20 The vast majority of calls were for medical emergencies occurring at home (76.9%), which is consistent with national statistics. Given their prevalence, 21 cardiocirculatory problems were predominant (29.9%), followed by musculoskeletal problems (21.9%) and a number of “other pathologies” (17.4%). The mean duration of telephone conversations was more or less the same in both the sample (range, 43.8-64.8 seconds) and the green-black code subgroup (range, 61.5-69.4 seconds). All 15 green-black code emergency calls were made by a relative or, in 1 case, by a caregiver. When compared with the sample, the 15 patients in the subgroup were older (mean age of 81.6 years vs 61.8 years). The presence of chronic conditions and the older age of the patients may have led callers to underestimate the severity of the situation. Dispatch was not accurate in 11 cases. Operators did not document all elements of the dispatch form when interrogating callers, with vital signs (awareness, breathing) being only partially assessed, if not entirely neglected. All of the previously listed factors could have contributed to under-triage. When we analyzed the telephone conversations using the Fele method, it appeared that in all cases callers described a vague and generally not alarming situation (dysuria, constipation, leg pain for 3 days). The caller’s description of the problem as nonurgent probably strongly influenced the operator’s decision on the type of criticality code to be assigned. Our analysis shows that callers had not been interrogated accurately enough. Such underestimations inevitably resulted in dispatch of an ambulance equipped only with a volunteer-based crew to a “green code” scene (therefore neither emergency lights nor sirens were activated). Volunteers, after assessing the emergency scenario, called the EOC for medical support, so precious time was wasted waiting for an ALS-staffed ambulance. Limitations

This article describes the Italian EMS Triage system, which is performed by nurses. This model could differ from EMS systems of other Countries. Implications for Emergency Nurses

Triage is essential for the early recognition and treatment of seriously ill patients, and it reduces morbidity and mortality rates. In Italy, telephone triage of EMS calls is performed by



experienced nurses with at least 2 years’ seniority in the emergency department. Regular retraining may help the RN operators avoid under-triage by focusing on the MPDS protocol. It is important that nurses act in accord with the MPDS protocol, asking the caller about the patient’s status and scene condition, particularly when the caller reports seemingly non–life-threatening situations, to assign the appropriate EMS response priority level.

Conclusions

Even if green-black code cases are rare (1/4,000 interventions), they represent sentinel events indicative of an EMS system failure. Nurses working at EOCs usually assess patients’ conditions and make important decisions with very limited time (60-120 seconds). The introduction of specific training based on the Fele method could improve both the quality and effectiveness of telephone triage. The training could involve simulations of EMS calls, as well as the analysis and discussion of real cases of under-triaged EMS calls. From a methodologic point of view, the results of this research could be useful in creating a near-miss and adverse events database. Further research is needed to better understand the green-black code phenomenon and to analyze the role of communication in the assignation of an underestimated priority code. REFERENCES 1. Psathas G. Talk and social structure. In: Psathas G, (ed.), Conversation Analysis: The Study of Talk-in-Interaction. Thousand Oaks, CA: Sage Publications; 1995:58-61. 2. Dick WF, Baskett PJ. Recommendations for uniform reporting of data following major trauma—the Utstein style. A report of a working party of the International Trauma Anesthesia and Critical Care Society (ITACCS). Resuscitation. 1999;42(2):81-100. 3. Cummins RO, Chamberlain DA, Abramson NS. Recommended guidelines for uniform reporting of data from out-of-hospital cardiac arrest: the Utstein style. A statement for health professionals from a task force of the American Heart Association, the European Resuscitation Council, the Heart and Stroke Foundation of Canada, and the Australian Resuscitation Council. Circulation. 1991;20(8):960-75. 4. Ministry of Health. Mattoni-outcome project. Reconnaissance of the legislation, experiences, trials, relative to emergency and 118 in regional and national level. NHS Mattone 11-ER-118 System. Avaialble at: http://www.mattoni.salute.gov.it. Published January 21, 2007. Accessed October 12, 2013. 5. Leprohon J, Patel VL. Decision-making strategies for telephone triage in emergency medical services. Med Decis Making. 1995;15(3):240-53. 6. DeGroot HA. Patient classification systems and staffing. Part 1, problems and promise. J Nurs Admin. 1994;24(9):43-51.

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7. Forslund K. Operators experiences of emergency calls. J Telemed Telecare. 2004;10(5):5290-7.

16. PeräKylä A, Vehvilainen S. Conversation analysis and the professional stocks of interactional knowledge. Discourse Soc. 2004;14(6):727-50.

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17. Zimmerman H. The interactional organization of calls for emergency. In: Drew P, Heritage J, (eds.), Talk at Work: Interaction in Institutional Settings Cambridge, England: Cambridge University Press; 1992:418-69. 18. Slovis CM, Carruth TB, Seitz WJ, Thomas CM, Elsea WR. A priority dispatch system for emergency medical services. Ann Emerg Med. 2000;14(11):1055-6. 19. Wilson S, Cooke M, Morrell R, Bridge P, Allan TEmergency Medicine Research Group. A systematic review of the evidence supporting the use of priority dispatch of emergency ambulances. Prehosp Emerg Care. 2002;6(1):42-9. 20. Clawson J, Olola CH, Heward A, Scott G, Patterson B. Accuracy of emergency medical dispatchers’ subjective ability to identify when higher dispatch levels are warranted over a Medical Priority Dispatch System automated protocol’s recommended coding based on paramedic outcome 385 data. Emerg Med J. 2007;24(8):560-3. 21. Clawson J, Olola C, Heward A, Patterson B, Scott G. The Medical Priority Dispatch System’s ability to predict cardiac arrest outcomes and high acuity pre-hospital alerts in chest pain patients presenting to 9-9-9. Resuscitation. 2008;78(3):298-306. 22. Curka PA, Pepe PE, Ginger VF, Sherrard RC, Ivy MV, Zachariah BS. A priority dispatch system for emergency medical services. Ann Emerg Serv. 1985;22(11):1055-60. 23. Fele G. L’Analisi Della Conversazione. Bologna, Italy: Il Mulino; 2007:91-116.

9. Thakore S, McGugan EA, Morrison W. Emergency ambulance dispatch: is there a case for triage? J R Soc Med. 2002;95(3):126-9. 10. Wilde ET. Do emergency medical system response times matter for health outcomes? Health Econ. 2013;22(7):790-806. 11. Focarile F. Indicatori di Qualità nell’Assistenza Sanitaria. Turin, Italy: Centro Scientifico Torinese; 1998. 12. Harden RD. Critical appraisal of papers describing 359 triage systems. Acad Emerg Med. 1999;6(11):1166-71. 13. van der Wulp I, van Stel HF. Adjusting weighted kappa for severity of mistriage decreases reported reliability of emergency department triage systems: a comparative study. J Clin Epidemiol. 2009;62(11):1196-201. 14. Corbetta C. Single emergency number 112: the test of Varese. In: Zoli A, (ed.), I quaderni di AREU. Itacacomunicazione; 2010:21-3. 15. Greggio M, Scapparone P, Costanza R, Leigheb F, Panella M. I codici di gravità nell’emergenza sanitaria territoriale: comparazione tra i codici attribuiti dalla Centrale Operativa 118 dell’ASO di Alessandria e quelli assegnati sul luogo dell’evento. Acts of the XII National Conference of Public Health Rome, Italy: Edizioni Iniziative Italiane; 2011:623. Avaialble at: http://www.societaitalianaigiene.org/site/new/image/docs/ atticongressi/201110roma.pdf. Accessed April 29, 2013.

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Analysis of emergency medical services triage and dispatch errors by registered nurses in Italy.

The major elements of an effective emergency medical services (EMS) system include a single telephone access number, accurate assessment of the urgenc...
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