peak-load unit utilization 1 running head: peak ... - hsdl

Peak-Load Unit Utilization 1

Running head: PEAK-LOAD UNIT UTILIZATION

Evaluation of Peak-Load Unit Utilization in the Seminole County Fire Department

Ivan A. Mustafa

Seminole County Fire Department, Sanford, Florida

September 2009


CERTIFICATION STATEMENT I hereby certify that this paper constitutes my own product, that where the language of others is

set forth, quotation marks so indicate, and that appropriate credit is given where I have used the

language, ideas, expressions, or writings of another.

Signed: _________________________________


Abstract

The Seminole County Fire Department operates a part-time peak-load transport unit to

supplement available units for response during heavy call volume periods. The problem is that

since the unit was placed in service nearly seven years ago, no comprehensive review has been

performed to evaluate the impact of this unit deployment to augment available units during

heavy call volume periods helping reduce the need for mutual aid requests from adjacent

jurisdictions. This document included a comprehensive literature review and used descriptive

research to evaluate the effectiveness of the unit utilization and deployment plan. In addition, it

reviewed alternative peak-load staffing models used by other agencies; identified the most

common times of the day and days of the week when there is a need for additional unit staffing

based on computer aided dispatch records and historical data analysis. Once these parameters

were identified, the effectiveness of the current utilization modelwas evaluated. This evaluation

explored whether the peak-load model is effective in reducing mutual aid responses in its current

form. The results revealed the current plan has had a positive impact in reducing the need for

mutual aid requests and dispelled the idea that abolishing the use of a peak-load unit and

replacing it with a full-time truck was more efficient. The data also uncovered a large service gap

where frequent requests for mutual aid are still needed to handle the daily calls for service.

Based on these findings the recommendations included the expansion of coverage days and

hours; adding an additional peak-load unit to close the identified service gap and offered

modifications to the current model if the expansion of coverage and units is not immediately

feasible in an effort to minimize the need for mutual aid requests.


Table of Contents Certification Statement 2

Abstract 3

Table of Contents 4

Introduction 5

Background and Significance 9

Literature Review 12

Procedures 22

Results 25

Discussion 29

Recommendations 32

References 37

Appendices

Appendix A: Response zone maps 39

Appendix B: Response data result tables 40

Appendix C: Hourly response data graphs 43


Evaluation of Peak-loadUnit Utilization in the

Seminole County Fire Department

Introduction

The Seminole County Fire Department (SCFD) headquartered in Sanford, Florida

provides an all hazards approach response services to all unincorporated areas of Seminole

County. In addition to a full-time complement of response units, SCFD operates a single peak-

load transport unit 40 hours per week to supplement units available for response during heavy

call volume periods. Tuesday through Friday the peak-load transport unit serves in the southwest

and south central portions of the county (see Appendix A, figure 1 for a geographical map of the

response area). Peak-load refers to a number of strategies used by fire and EMS agencies in an

effort to match the resource deployment to the fluctuations in demand (Sachs, 1999). Although

there is a relative perception that the addition of the single peak-load transport unit has had a

positive impact in reducing the need for mutual aid responses from neighboring cities and

Orange County Fire Department, SCFD has not performed a thorough data analysis to support

this perception. In fact, it is unclear if the peak-load unit has indeed reduced the need for mutual

aid responses or better yet, whether the money spent to place this unit in service with

supplemental overtime staffing has had a positive impact in reducing the need for mutual aid

responses throughout the entire response zone.

The addition of a single peak-load transport unit into the response matrix is only one

small variable in a very complex equation. Despite the rapid growth over the last two decades,

cost constraints, lack of unconditional support from governing bodies and the inherent

adaptability of fire rescue services of doing more and providing comprehensive coverage with

limited resources, it has been a very difficult battle to gain the needed support from the


community and the governmental bodies to embrace an aggressive expansion plan that parallels

the pace of the county’s growth. When the subject of paralleling the fire department’s expansion

to the community growth rate is brought up, most agree is necessary but no one has a firm grasp

of how to effectively make it a reality.

Generating additional funds or budget increases needed for the expansion of fire and

emergency services has been incredibly difficult in the current economy. In Florida, citizens

often revolt complaining about the lack of services or failure of the public safety agencies

whenever the state is hit by natural disasters (such as tropical systems) but are hesitant to provide

the necessary budget support to prepare for such events. It seems that no one wants to make an

investment in the preparedness of fire and emergency services to handle the response demands.

Despite the lack of necessary support, community leaders are quick to point a finger at the

emergency services leadership when these events do happen and the community is faced with an

inadequate complement of resources or contingency plans to mitigate a given problem or event.

Florida agencies have been particularly hard hit when it comes to finances. In 2007, a

major reduction in homeowners’ taxes was voted into law. This vote dealt a devastating blow to

governmental agencies. Major cuts have been made including project elimination, scaling back

services and even layoffs, all while the community and population continues to grow. This

growth continues to increase the demand for emergency services, further taxing fire and EMS

services well beyond their capabilities.

Another variable affecting the problem is the public’s misconception of what constitutes

and emergency, causing the routine overload of resources due to unnecessary calls for

emergency services. The American College of Emergency Physicians (ACEP) defines

emergency services as “any health care service provided to evaluate and / or treat any medical


condition such that a prudent layperson possessing an average knowledge of medicine and

health, believes that immediate unscheduled medical care is required” (ACEP, April, 2009, p. 1).

In this definition, the concept of an emergency lends itself to a very subjective inclusion

criterion, leaving it up to the individual’s perception to determine if it is in fact an emergency. As

a result, EMS services respond to calls that are not emergencies, events that could be easily

handled without EMS intervention.

Another common problem that burdens the EMS system routinely is the public’s

perception that if a person arrives to the emergency department by ambulance they would be

given priority room assignment and an immediate evaluation, circumventing the already

overcrowded waiting rooms. This is simply not true. Perceptions of this type continue to tax the

system resources and are indirectly partly responsible for the research and content of this project.

Eliminating frivolous 9-1-1 calls can potentially minimize the need for mutual aid responses

when Seminole County does not have available units for response.

This project complements the theme and management principles discussed in the

National Fire Academy Executive Development program by utilizing scientific research to

identify gaps, deficiencies or limitations in the current peak-load utilization model to reduce the

need for mutual aid responses. It also offers recommendations for changes that will eliminate the

stated problem through adaptive change and participatory management. Finally, it provides

essential information to SCFD’s management team to overcome these difficulties.

As an agency embracing an all hazards approach to emergency services, SCFD supports

the current United States Fire Administration (USFA) strategic plan by upholding its mission to

provide comprehensive fire and emergency medical services of the highest quality to the citizens

and visitors of Seminole County. This project specifically relates tothe USFA’s 2009-2013


Strategic Plan Goal number 3which states to “improve the fire and emergency services’

capability for response to and recovery from all hazards” (United States Fire Administration

[USFA], 2009, p. 8). It is the intent of this project to support such goal by examining deployment

methods or alternative shift ideas to maximize our response capabilities. To support this goal,

SCFD must first acknowledge the eroding economic picture and concentrate on what must be

done to maximize the use of current resources to offer a comprehensive package of essential

services to the citizens we swore to protect.

One strategy employed by SCFD to alleviate the problem of frequent depletion of

resources resulting from explosive growth and development in the unincorporated areas of the

county, was to place a single peak-load ALS transport unit in service. Despite this addition, the

department continues to have difficulty maintaining an adequate number of available units for

response in the south central and southwest unincorporated areas of the county relying heavily in

mutual aid units from nearby city departments and the neighboring Orange County Fire

Department to assist with handling the high number of calls for service. It is in this particular

area that this project will focus its attention.

To evaluate the effectiveness of operating a single peak-load ALS transport unit in

reducing the need for mutual aid requests, the following research questions are addressed: (a)

define what methods do other departments utilize to supplement transport units during heavy call

load periods; (b) identify what times of day and days of the week when a significant increase in

call volume results in not enough SCFD units being available for response; (c) the optimal times

to deploy a peak-load transport unit based on the historical response data; (d) is the current

utilization model for the peak-load transport unit effective in reducing the need for mutual aid

requests during heavy call load periods; and (e) if this model is effective, how would adding an


additional peak-load unit to the response area help to further reduce the use of mutual aid units

during heavy call load periods.

Background and Significance

Seminole County located north of Orlando, Florida with an area of 344 square miles is

composed of a mix between residential, commercial and light industrial properties (Seminole

County Government, 2008). The population density is concentrated in the southern portion of the

county with the heaviest load in the south central and southwest areas. The Seminole County Fire

Department (SCFD) is an all hazards response department serving all the unincorporated areas.

SCFD was officially consolidated on October 1st, 1974 from a number of volunteer agencies that

provided only fire protection in unincorporated areas at the time (Seminole County Government,

2009). The creation of the county department also started the transition from an all volunteer

force to a full-time paid fire department. In 1976, Chief Fire Administrator Gary Kaiser

introduced the Emergency Medical Services (EMS) component to the agency by training and

certifying all personnel as Emergency Medical Technicians (EMT) and expanding the scope of

services offered to the community to include medical responses. His ultimate vision was to

provide the most advanced medical care to the citizens. In 1980, SCFD upgraded the EMS

services to an Advanced Life Support (ALS) model, training firefighter personnel to be certified

as paramedics.

As the unincorporated areas of Seminole County became more densely populated in the

following decade, the department expanded services opening new fire stations in the Heathrow,

Red Bug Road area and signing a formal agreement with Orange County Fire Department to

build a joint station in the area adjacent to the University of Central Florida. Despite these

additions between 1987-1995, and the resulting increase of full-time paid personnel to staff these


stations, SCFD continued to see a deficit in the amount of units available for response at times of

heavy call load demand. As the county continued to experience explosive growth, SCFD fell

behind in its ability to expand coverage. For almost a decade, SCFD was unable to garnish the

support needed from the county government to effectively implement a growth plan that would

parallel the rapid expansion of the population and industry within the county. This resulted in an

exponential deficit in available response units compared to the total size and density of the

service area.

The deficit of an adequate amount of response units was also heightened when in 2002

SCFD underwent a merger with the Altamonte Springs Fire Department and in 2008 with the

Winter Springs Fire Department. These mergers resulted in the addition of the former city units

and stations to the total unit inventory for the department, but it also added the cities’ response

jurisdictions to the total service area of SCFD. These jurisdictions are both heavily populated and

have a large mix of residential and industrial properties.

Following the merger with the City of Altamonte Springs Fire Department, SCFD saw a

significant increase in call volumes especially in the south central and southwest urban portion of

the county resulting in a significant increase in mutual aid responses from adjacent cities to serve

county jurisdictions. SCFD obtained authorization to deploy a single part-time / peak-load ALS

transport unit staffed for a total of 40 hours per week, broken into 10 hours per day from 0800

hours to 1800 hours from Tuesday through Friday. The main purpose of placing this unit in

service was to help reduce the need for mutual aid unit requests at times of heavy call load

demands. The unit was given the call sign designation of Rescue 14 (R14) in accordance with the

master unit designation plan for the county. The deployment of R14 has been the only addition

of a part-time unit to the entire operational fleet in the last ten years.


Seminole County has a current population of 415,786 in its 344 square miles. This

number represents a 27% increase in the population compared to the 2000 United States Census

population of 365,196 (Seminole County Government, 2008). Although the population has

increased dramatically, SCFD has had a less than 1% increase in the fleet of units available for

response. Currently SCFD operates 19 fire stations, 17 advanced life support (ALS) capable fire

suppression engines, 18 ALS transports/rescues, two (ALS) aerial apparatus and one (ALS)

heavy rescue/special operations squad. In 2008 SCFD responded to 27,854 emergency calls with

18,463 being Emergency Medical Services responses (Forrest, 2009, p. 1).

Perhaps one of the most significant factors stimulating the need for this research evolved

from the fact that the cities within the county are objecting to the routine use of their units out of

their city jurisdictions to serve unincorporated areas of the county. They perceive an imbalance

between the numbers of times their transport units are being called away from their primary city

response areas to assist in calls for service on county jurisdictions vs. the times when county

units respond into their respective cities to provide mutual aid. By definition mutual aid or

automatic aid agreements specify that “another agency will help, and in return the other agency

can expect help when necessary” (Evans & Dyar, 2009, p. 362). Fire and EMS services have

relied on mutual aid and automatic aid agreements as the backbone of emergency services

support for a number of decades (Evans & Dyar). For purposes of this paper the term “mutual

aid” is used to denote both types of aid responses, mutual aid (requiring approval from the other

agency’s chief officers and automatic aid (responses prearranged on a response matrix and sent

automatically by the dispatch center).

Because there has been no comprehensive evaluation of the impact that R14 has had to

reduce the need for mutual aid, it is difficult for SCFD’s leadership to defend against such claims


made by the cities within the first response agreement. This research intends to identify the

actual numbers and percentages of mutual aid responses into county jurisdictions, providing the

department’s leadership with much needed data to address, discuss and clarify questions

regarding the perception of an imbalance in mutual aid responses.

Literature Review

In the United States Emergency Medical Services are provided by a wide variety of

public, private, hospital based, not for profit, third service agencies, and public-private

partnerships or public utility models that respond to emergency medical calls. These services are

further separated into full-time paid, part-time paid, volunteer, on call status and a large number

of personnel staffing variations. This research focuses on methods to augment staffing by full-

time paid agencies. A comprehensive literature review yielded few reports on peak-load staffing

and their impact in reducing mutual aid requests for EMS responses. No reports from full-time

paid fire departments regarding the reduction of mutual aid need were discovered. The literature

does have more data on effective utilization, peak-load staffing and combination deployments.

This report narrows the literature review to fire based full-time paid departments and single

service EMS agencies having the closest similarities to Seminole County Fire Department.

Models used by other departments to supplement unit availability come in many different

forms. Current literature has few documents that specifically address unit augmentation during

heavy call load periods but has ample data on how to maximize unit utilization based on

projected heavy call load patterns and relocating units from other districts into depleted areas in a

concept known as move ups.

Because each response agency and area has unique peculiarities, identifying a common

model that is most effective for departments is as complicated and abstract as coming up with a


formula for time travel. Political, geographical and budgetary variables to name a few, regardless

of the jurisdiction’s size are almost as varied and unique as human beings themselves. No one

plan or model will serve two similar jurisdictions. Current published models found in the

literature are divided into two major categories depending on the type of agency that provides

EMS services.

Fire department based EMS and single service public or private EMS agencies operate in

a distinctively separate fashion. I call this the great divide. Historically, fire based EMS services

have been well embedded in the community under a traditional neighborhood protection plan.

The basic fire department model consists of a number of fixed bases or stations geographically

distributed serving a predetermined response area and staffed by personnel in a specific 24 hours

on 48 hours off work schedule. In this system, units are located and respond within specific

stations, and then attempt to return to their station after the completion of a call (Dean, 2008).

The premise behind this model is that an equal amount of units are available for response 24

hours a day regardless of call load. This model does not take into account common variations in

service demands or peak-load hours derived from historical data analysis. The fixed base model

does employ the concept of move ups as the solution to augment unit available for response in

areas where the assigned units are committed or the response zone is depleted of units. The

National Wildfire Coordination Group (NWCG) defines move ups as a system of redistributing

remaining emergency units among a network of stations that have a surplus of available

resources to areas where the assigned response units have been depleted or actively committed to

calls for service in order to offer the best possible response for additional calls for service

(National Wildfire Coordination Group [NWCG], November, 2008). Move ups differ from other

types of fluid unit allocations as they are reactionary in nature. The dispatch center will only


move response units to depleted districts in direct response to an increase in demand that has

already taken place.

Despite the crumbling budget picture affecting all agencies as discussed in the

introduction, fire departments continue to staff primarily in the traditional fixed 24/48 schedule

with a constant amount of units available for response. Fire departments continue clinging to the

fixed location, community stance position as the public’s perception of the fire department still

embraces the concept of fire stations located just around the corner to quickly respond in their

time of need. This fixed station model offers a security blanket to the citizens of the community.

Fire Department administrators have a firm belief that responses from a fixed location

have a much better chance to reach an incident within their district, usually in less than eight

minutes. A study by Dean (2008) reported that doubling the number of locations from which

transport units are dispatched from (for example from 2 to 4) had a six minute reduction in the

response time mean value. This report helps support a fixed based model. Based on this data,

depending on the community development and increased demands for additional coverage the

traditional approach has been to further subdivide densely populated areas with the highest call

volumes into smaller sections. The departments then add additional stations and units to maintain

the desired response time goal. This approach may be effective in reducing response times but

continues to be very difficult to sustain. It also lacks effectiveness as it cannot be implemented

rapidly. Merely increasing the number of personnel, adding stations and units is perhaps not the

most cost effective or efficient choice (Fitch, 2004). Community leaders are increasingly

questioning this doctrine as it results in an excess of available units during low response volume

times and decreased utilization effectiveness (Williams, 2008).


Fire departments find themselves in a much difficult position when performing dual fire

and EMS responsibilities. They must plan and prepare for both complex fire type events and

routine EMS calls using one primary model. The problem lies in the inherent and vastly different

need for resources between a fire type event and a routine EMS call. Attempts at transitioning or

splitting from this fixed staffing and deployment system to a variable peak-load plan has been

almost impossible. The fixed deployment model is still effective for fire responses, hazardous

materials incidents and other large scale emergency operations which have no specific or

predictable pattern. The fixed schedule can be further justified as these incidents require large

amounts of equipment and personnel responding to a single incident at any given time,

performing emergency operations in an orchestrated fashion under the National Incident

Management System. The reality today is that these labor and equipment intensive events are

certainly occurring less frequently but yet, the fire service administrators cannot afford to

decrease or change staffing solely on the basis of the relative infrequency of complex incidents.

In contrast, the average EMS medical call does not require large amounts of personnel and

equipment per call when compared to fire type incidents. The great majority of EMS calls can be

efficiently handled with a crew of two to five personnel (Evans & Dyar, 2009).

The single service EMS agencies historically have had much more difficulty in justifying

a constant number of units being deployed 24 hours per day and have resorted to adopt strategies

that “take into account predictable patterns in order to maximize coverage and curtail costs”

(Fitch, 2004, p. 172). The essence of their plan is to maximize the coverage during peak-load

periods without necessarily expanding their unit and personnel numbers and associated costs.


EMS services serving strictly a medical response function have a much easier time in exploring

alternative staffing models, peak-load models and supplemental / geographic deployment models

as they focus to provide a single service.

Perhaps the most widely recognized and used model for alternative staffing and

geographic placement of units is known as System Status Management (SSM). Single service

EMS agencies tasked with providing a specific medical response objective are able to focus their

attention to effective unit deployment and movement while attempting to contain cost.

System Status Management concept surfaced in the 1970’s as envisioned by economist

and EMS Pioneer Jack Stout (Fitch, 2004). SSM revolves around the concept of analyzing

historical data to identify the times of day and days of the week when predictable increases in

call volume would strain the EMS system beyond its capabilities. Stout first defined what the

product needed to be in order to use the resources to their fullest potential. He identified the

unit-hour as the nucleus of SSM. A unit-hour is defined as a properly staffed and equipped

ambulance that is available to the system for one hour to respond to properly triaged calls for

service (Fitch). Next, a total of 168 hours per week were separated as individual blocks to

identify the actual number of units needed for response at any given hour of the day. The

historical data was then stratified into two categories: chronological demand (defined as the

volume of calls projected at any given point in the time of day or day of the week) and

geographical demand (identifies specific areas with the most calls at any given time or day).

Once peak-load periods were identified, the number of units deployed and the work schedules

were be adjusted to have more available units during heavy call load periods and reducing the

available units during traditionally low volume times. SSM also moved from a fixed base of

operations model to a planned set of predetermined post locations where units would be staged to


cover all response areas in the most effective way, minimizing response times. Post locations are

defined as strategically planned positions within the community where transport units would

stand anticipating the next call. These posts could be anywhere, the local corner fuel station, a

grocery store parking lot, or adjacent to a government building. These are selected based on the

data which places the unit at the most central location of a response area offering the best

advantage to reduce response times during peak-load periods when resources are scarce (Fitch).

SSM relies heavily on computer generated, statistical preplanned deployment strategies that

would change each time a single unit is dispatched to a call. To compare between SSM and

traditional move ups, SSM uses a proactive approach in an attempt to have the right number of

units staged at the areas that most likely will generate the next call for service before the area is

depleted of resources while move ups are done in reaction to an already existing unit deficit.

System Status Management has merits and certainly has flaws. SSM has been under

scrutiny for quite some time. Williamson and Bledsoe (2004) have publicly denounced that

SSM’s proclaimed ability to reduce response times and enhances patient care is a myth that lacks

scientific evidence. They report that most of the published documents on SSM were found in

trade magazines and were authored by those with a vested interest in implementing SSM as a

standard EMS practice (Williamson &Bledsoe). In fact, the city of Tulsa, Oklahoma

implemented SSM and reported that their response times were reduced very little

(an average of 37 seconds) while at the same time increasing the unit maintenance and fuel costs

an average of 46% as the units were constantly moving between predetermined post locations.

Bledsoe also states that the concept of reviewing recent historical data (times vary from 20

weeks to one year historical data review) for purposes of predicting future calls are statistically

insignificant to make a reasonable prediction of future call loads. In fact, he argues that


statisticians would recommend 20-40 years of historical data to have a reasonable chance at

future call prediction (Williamson & Bledsoe).

Another study by Cadigan & Bugarin (1989) explored ways to predict demand analyzing

current and historical data, compared it to commonly used rule of thumb formulas in order to

identify whether these formulas can realistically predict future service demand. The results

revealed that formulas cannot accurately predict future emergency response and transport

demands. These formulas do not take into account fluctuation in the population from those

traveling through or visiting the service areas.These variations in total population numbers do not

have specific patterns and therefore cannot be accurately predicted.

Although dramatic reductions in response times were originally documented by the

proponents of this model, the concept of SSM failed to account for the human variable in the

response units causing a major flaw in the model. Crews working full-time 24 hour shifts were

frequently awakened to move between post locations in the middle of the night, thus depriving

the personnel of needed rest. This problem also affected their performance and clear mind when

handling calls. Personnel often complained that they never had an opportunity to get rest

between responses and the long periods of sitting in the unit at a post location dramatically

increased sick leave usage. The incidence of reported back and leg problems as a result from the

prolonged sitting skyrocketed in systems using SSM (Morneau and Stothar, 1999).

Morneau and Stothar (1999) conducted studies on the deleterious effects on personnel

when working on a system status model and current ambulance design. Their primary argument

against system status management is that it forces paramedics to remain in a constant upright

sitting position in an ambulance when for extended periods of time. Their survey revealed that

71% of respondents complained of back problems or discomfort more often than before SSM


was established. Much more sobering was that the survey identified 88% of paramedics

complained and / or have had back problems within their first six years of employment. Morneau

and Stothar’s research also took a look at the design, seat ergonomics and crew cab space of

modern ambulances and concluded that current designs increase the frequency and / or worsen

back problems when crews are forced to remain in a roaming mode for long periods of time.

Another unexpected finding in their research involved the ever increasing use of SSM allowed

managers to reduce the total number of available ambulances by increasing the frequency of unit

movement. This opened the door for agencies to place fewer ambulances in service,

compromising the coverage of two independent areas by placing only one unit for response

between them instead of one unit per area. This practice resulted in an inherent lack of an

adequate amount of ambulances in the response areas regardless of call volume.

Despite the proclaimed advantages of SSM, the concept became related to discontent,

regarded as an undesirable deployment method by the paramedics who endure the constant

punishment of a perennial moving strategy. In systems using SSM, the EMS personnel resisted

the post relocations and frequent moves that were computer and data driven. A trend of increased

sick leave usage, higher attrition and poorer performance were also reported each time the SSM

concept was instituted by agencies.

Another staffing and deployment plan variant used by large metropolitan departments

involves a tiered-response model. Early proponents of advanced life support systems promoted

the staffing of large numbers of ALS transports by two paramedics. Stout, Pepe & Mosesso, Jr.

(2000) contend that an all ALS system is not cost effective or efficient. Staffing solely with

paramedics in ALS units will lead to diluted skills for the paramedics, extended response times

when units are already committed to other incidents thereby not able to solve the problem of


decreased unit availability and need for mutual aid responses. In their argument, they identify

that the majority of EMS calls for service (85%) only required basic life support (BLS)

assistance. They profess that a tiered-response system consisting of a combination of basic life

support units staffed by emergency medical technicians and advanced life support units staffed

by paramedics could offer better coverage and maintain shorter response times for trained

professionals to reach the patient. The initial BLS response would assess the patient’s condition,

determine if ALS is needed and coordinate further care without overburdening other units which

in turn remain available for response.

In their review, Stout et al. (2000) also observed that an all ALS paramedic system does

not provide adequate opportunities for performing critical skills thus reducing the abilities of the

paramedics within the system. In contrast, they state that fewer paramedics in a tiered-response

have more frequent, intensive clinical exposure and application of critical skills, maintaining

their performance at peak levels. Although there is merit to the proficiency argument it is

important to note that skill performance during calls is only one portion of a multi-faceted

approach used to maintain a proficient skill level. What they fail to point out is that proficiency is

developed through a combination of learning, continued practice and refinement accomplished

through established in house scheduled training programs. A paramedic cannot be expected to

perform critical skills perfectly without a structured program for refresher training. Just because

a paramedic performs a specific critical skill 30 times per month doesn’t necessarily mean that it

is performed perfectly.

A tiered-response system certainly has merits when configured for a specific area and

used in combination with a system that takes into account temporal and geographic demands for

service. In essence, a tiered-response system must be orchestrated in concert with a system status


management program. The tiered-response also has some inherent disadvantages. Because the

system is inherently “tiered” it reduces operational efficiency and fragments the level of care. In

addition, there is the possibility of dispatching a BLS unit to call where ALS should have been a

priority. This problem is rooted back to the information provided to the dispatch center. The

dispatchers can only make response decisions based on the information given. Poor information

communicated to the 9-1-1 dispatcher may result in the delay of responses or inappropriate

responses. An EMS system can have the most efficient plan for tiered-response EMS delivery

and still not meet the service demands because the person initiating the call may not have the

correct or adequate information in order for the EMS system to dispatch the closest and most

appropriate unit to the incident.

The literature review revealed the two major types of unit deployment doctrines

embraced by each specific emergency services model to meet either their single or dual response

role. Both doctrines have inherent merits, liabilities and can potentially cause problems if not

properly implemented and managed. Articles explore a number of variants in models, staffing

and deployment plans that result from agencies taking one of the two major deployment

doctrines, adapting the general concept to meet specific requirements for the community and

refining it to fit the needs of the jurisdiction. Despite an exhaustive search, no documents explore

specifically the use of peak-load units to extend the unit availability in an effort to reduce the

need for mutual aid responses. The existing literature clearly states how important it is to choose

an appropriate unit deployment and staffing model that best fits the jurisdiction. It also revealsthe

complexity and uniqueness of each plan. Regardless of preference, all authors stressed that any

deployment plan is fluid in nature and must be constantly evaluated and fined tuned to maintain

its effectiveness.


In summary, it is up to each agency to choose what deployment doctrine is best suited to

provide the most efficient response coverage, constantly monitoring and adjusting it to maintain

optimal effectiveness in the delivery of emergency services.

Procedures

This project evaluates the impact that a single peak-load ALS transport unit (R14) has

had in reducing the need to request mutual aid responses when the demand for services exceeds

the supply of available full-time ALS transport units. To assess the model currently used by

SCFD, a comprehensive literature review was conducted at the National Fire Academy Learning

Resource Center for documents and research that addressed deployment models, supplemental

staffing, and peak-load staffing or agencies with similar operational deployment models.

Next, Computer Aided Dispatch (CAD) historical response data was obtained from a 12

month period between January 1, 2008 and December 31, 2008. The initial data was separated

into the northern vs. the southern portions of the county split by battalion response zones and

filtered to include calls for EMS services resulting in transports only. Calls for EMS services

where non-transport units responded or calls that did not result in a transport to a hospital were

excluded. These calls were excluded based on the fact that they have little impact on the number

of available transport units within the system. In the filtered data set, the total percentage of

mutual aid responses was calculated. The data was then separated into the response zones within

the south central and southwest portions of the county. In SCFD’s comprehensive response

matrix, the south central and southwest portion is mostly serviced by units from Battalion 1 (B1)

stations and two units from Battalion 2 (B2) stations (see Appendix A, Figure 1 for geographic

map of the battalion response zones). Stations assigned to B1 include: 11, 12, 13, 14 and 22 (see

Appendix A, figure 2 for map of the station zones). Stations within B2 include: 23, 26, 27 and


65. Only small portions of station 23 and 27 are served by R14. The other transport units

assigned to stations in B2 (26 and 65) were filtered out as R14 does not routinely cover or

respond to these areas.

Each station district is subdivided further into a number of map response areas (MRA’s).

These break down each individual district into more manageable geographic pieces to help

identify the closest units that are assigned to respond to all types of requests for service. This

project looked at the number of times R14 responded to each MRA for each day of the week the

unit is in service. This analysis helped identify which station district or response zone

consistently used R14 to handle additional calls when the primary assigned transport unit was

already committed to another incident.

Using the results of the data analysis, this project compared the current deployment

model to the identified trends of peak demand to determine if this model matches the actual need

for unit supplementation. Based on the data, recommendations of alternative deployment hours,

increasing coverage and adding an additional peak-load unit were presented.

Assumptions

In the literature review and research, an assumption is made that the background

information obtained from the research is true, correct and factual information. The report also

assumes the data retrieved from the CAD historical archives has not been modified, altered or in

any way tampered with before the data was analyzed.

Limitations

The data used in this project focuses only on rescue responses for emergency medical

services to include motor vehicle crashes with injuries. It does not include responses to fire,

hazardous materials calls or incidents that are not medical in nature.


This research is also limited to reviewing data from the average or routine daily

responses. It does not take into account incidents resulting in mass casualty events, natural or

manmade disasters or events of such magnitude that regardless of the agency’s size and

configuration, the demand will far exceed the supply of available units.

SCFD operates a 100% ALS department. Fire engines, aerial towers and the special

operations squad are all ALS, intended to reduce response times to keep them within a five

minute self-imposed response standard. For purposes of this research, the non-transport units

have been excluded from the statistical data review. Further, this research was limited to the

evaluation of how a single peak-load ALS transport unit has contributed to the reduction in

mutual aid requests when demand exceeds available unit supply. It is not the intent of this project

to explore staffing models (regular duty assignment vs. overtime coverage), cost estimation of

the deployment and personnel compensation related to peak-load unit augmentation to maximize

cost effectiveness as related to personnel cost.

The research offers a multitude of articles on adequate staffing for the fire service. Most

of these articles concentrate on staffing needs related to adequate personnel numbers on fire

response units to meet the standards set forth in the National Fire Protection Association (NFPA)

1710 titled “Standard for the organization and deployment of fire suppression operations,

emergency medical operations, and special operations to the public by career fire departments”

(National Fire Protection Association, 2009) but few articles actually extended into the realm of

supplemental staffing solely for routine EMS response. Additionally, the literature review was

narrowed to information and deployment strategies from full-time paid fire or EMS agencies,

excluding combination paid and volunteer, all volunteer and on call agencies. Due to the inherent

complexity and variety of deployment plans and time constraints for this project, only the major


deployment models that are suitable for consideration by SCFD were discussed. It is not the

intent of this project to provide the reader with an all inclusive review of every widely

recognized deployment model or strategy.

Results

The first question posed in this research project inquired as to what methods other

departments utilize to supplement transport unit availability during heavy call load periods.

Through the literature review, it was clearly noted that because the unique idiosyncrasies

inherent to each jurisdiction or emergency service agencies, it is difficult to declare which is the

undisputedly preferred method of unit supplementation. The literature review clearly shows how

each type of agency, fire based vs. single service EMS have a specific preferred method to

deploy units. The great divide between fire based EMS and single service EMS agencies is still

alive and well today.

Fire based EMS services contend with managing a dual-responsibility role, providing an

all hazards protection umbrella of services. These agencies must staff and deploy units for a

myriad of events that are manpower and labor intensive, along with providing units for routine

EMS responses. The complexity of maximizing adequate coverage for a wide range of events

lends itself to be more suitable for the traditional full-time fixed shift schedule, with units based

out specific stations covering a predetermined response area. This method results in an excess of

units being staffed during low volume periods. To help maximize the agency’s effectiveness,

creative deployment plans for certain units must be considered. Although the traditional fixed

based concept provides a broad baseline of response units, this method should not be the sole

type of deployment to meet the service demands.


For agencies providing strictly EMS coverage, using the concept of peak-load staffing

and modified system status management to combine fixed station locations in response zones

supplemented by peak-load units deployed at different times of the day based on demand is a

more prevalent choice. Single EMS agencies certainly benefit from using SSM to maximize

coverage and minimize cost, but they should not forget to take into account the human

component of the response system, namely the EMT’s and paramedics who are forced to deal

with long periods of time sitting on a transport unit. In this system, the frequent post station

changes, the stress from never having rest periods and the abuse inflicted into their bodies from

prolonged sitting takes a large toll on personnel. Systems using SSM have traditionally

experienced an increase in sick leave usage and attrition that could be related to using this

deployment plan.

Perhaps the most important finding extracted from the literature review is the fact that

although each type of agency subscribes to a primary method of deployment, solely using a fixed

station/shift method or entirely subscribing to SSM is not the answer. Agencies must look into

alternative plans or hybrid models that will maximize coverage while being cost effective. No

one concept or method is a cure all for the needs of each agency.

The second research question asked to identify what days of the week and times of the

day having the highest call volume which results in not enough SCFD units being available for

response. The aggregate data (combining B1 and B2) for total number of responses ranged from

912 to 1029 responses per day; the day of the week having the highest call volume was Thursday

with 1029 responses, followed by Monday with 1026 responses, and Friday with1022 responses

(see Appendix B, table 3). In contrast, the percentage of mutual aid response needs is highest on

Wednesdays at 11.1%. Wednesday sits in the middle of the total number of calls for the week’s


data. It was followed by Monday at 9.9%, Thursday with 8.4% and then Tuesday with 7.8%.

Saturday and Sunday represent the days with the lowest need for mutual aid responses at 3.4 and

4% respectively (see Appendix B, Table 3).

The data was also filtered to identify the actual number of responses of R14 into the

MRA’s within each station response zone by day of the week. R14 responded most frequently to

MRA 121 in station 12’s zone with 15% of the total runs, followed by MRA 131 (station 13) and

MRA 141 (station 14) both with 11% of the total responses. When combining all the MRA’s in

each station response zone, station 13 area required the highest number of supplemental

responses at 36.95%, followed by station 12 with 28.57% of the total responses. (see Appendix

B, table 5).

Another important analysis included the separation of the data by battalion response

zones. The results show the biggest demand for mutual aid responses into county jurisdictions

comes from the B2 response area. It is in this particular area that the largest coverage gap was

identified. In the original deployment plan for the peak-load unit, R14 was to primarily serve the

B1 response area. The data from B1 reflect the impact of the peak-load in reducing the overall

mutual aid requests as the response percentage is very low, averaging 0.8% of the total calls. On

the days that R14 is deployed, the need for mutual aid requests remained constant at 0.8% also.

In contrast, the need for mutual aid responses into B2 service area runs an average of 6.4% of all

the responses (includes all days). The data between B1 and B2 areas shows the number of

responses and percentages for mutual aid requests based on the days of the week are constant

(see Appendix B, tables 1 and 2). It is important to also note that the days yielding the highest

need for mutual aid requests are within those when R14 is already deployed. Saturdays and

Sundays consistently have some the lowest number of runs and percentages.


The data was also analyzed to identify which are the optimal times to deploy a peak-load

transport units based on the current data. The data of the total responses by hour for every day

ranged from 160 to 210 responses with a median of 185 responses between 0800 and 2100 hours.

The number of responses for the hours of the day had consistent numbers across all days of the

week. Calls for service ranged from 167 between 0800 and 0900 hrs and peaked at the 1400 to

1500 hrs with 210 responses. The number of responses falls between 1500 and 1800 hrs to 166

responses when R14 goes out of service. Between 1800 and 1900 hrs revealed a sharp increase in

the number of calls for service to 183 then the curve drops off down to the baseline of 160 calls

between 2000 and 2059 hrs (see Appendix C, graph 1). Although there are fluctuations in the

total responses per hour in the middle portion of the day on a couple of hours, these low periods

did not significantly impact the justification to have R14 in service.

Comparing the responses by hour on the days that R14 is in service, Tuesday through

Friday, calls for service ranged from 88 to 133 with a median of 111 responses distributed

consistently across the deployment days. Again, a sharp increase in the number of responses

occurred between 0900 and 1059 hrs and leveled off between 1100 and 1659 hrs. Between 1700

and 1800 hrs the responses dropped to 88 when R14 goes out of service. Similar to the previous

model a marked increase in the number of calls for service is seen with a total of 120 responses

in the hour following the demobilization of R14. From that point a fast decline after 1900 hrs

shows the responses down to a low of 92 (see Appendix C, graph 2).

The data was taken a step further by analyzing the response volume per unit and hour of

the day between Tuesday and Friday to help determine the times of the day with the biggest

demand for supplemental transport unit augmentation with a goal of determining what are the

optimal times of deployment for a peak-load unit. Surprisingly, the morning averages start high,


with R14 shown as the busiest transport between 0900 and 1259 hrs. Deploying this unit

promptly at 0800 hrs helps to pick up much of the excess demand for responses early in the day.

R14 responses are equal to R12 and R13 (traditionally the busiest transports) between 1300-1359

hrs, then takes the lead again from 1400 to 1600 hrs. From there it begins a steady decline until

R14 is demobilized at 1800 hrs. What happens next on the graph helps clearly illustrates the

effect that R14 has had in helping cover the service area and the need to reconsider the actual

demobilization time. Between 1800 and 2059 hrs, R12 response numbers skyrocket, followed by

R13 run numbers. A transport with fairly low volume, R11 also reveals an increase in the

number of runs as this unit begins to pick up calls previously handled by R14 (See Appendix C,

Graph 3).Under the current deployment plan, demobilizing R14 at 1800 hrs poses a strain to the

remaining units particularly in station 11, 12, 13 response zones. To maximize the utilization of

R14 to assist in responses and reduce the need for mutual aid, it will be necessary to reconsider

extending the deployment times to 2000 hrs.

Discussion

The fourth research question addresses whether the current model of peak-load transport

unit utilization effective in reducing the need for mutual aid requests during heavy call load

periods. Although the leadership of SCFD had a general idea that deploying R14 as peak-load

unit was effective in reducing mutual aid responses, the analysis substantiated that idea solidly.

The R14 is not deployed on Saturdays, Sundays or Mondays. The data cannot support deploying

R14 on Saturdays and Sundays, but does show a need to include Monday in the deployment plan.

The unit does have a positive impact in reducing mutual aid requests on the normal deployment

days (Tuesday to Friday). The current R14 deployment plan falls short to include Mondays; this

day has a typical heavy call volume and can certainly benefit from having the additional unit


available for response. Because R14 is primarily deployed to supplement unit responses in the

B1 response zone, the need for mutual aid responses is rather small. In the B2 response zone, not

having a dedicated peak-load transport unit to supplement the full-time units causes a much

higher need for mutual aid responses. It is important to evaluate this gap. Recommendations

include the addition of an additional peak-load unit to serve primarily the B2 area and to provide

backup in B1 area.

Next, this project looked whether the current deployment times are optimal in providing

the maximum benefit on the deployment days. The data showed that R14 remained busy for the

majority of the deployment period consistently throughout the service days. In fact, it showed

R14 taking the lead with the highest number of responses between 0900 and 1259 hrs. From

there it remained parallel with R12 and R13 for the highest number of responses. Between 1400

and 1559 hrs it takes the lead again, then slowly dropping off until R14 goes out of service at

1800 hrs. After 1800 hrs a marked increase in response demand was noted. The absence of R14

caused a concurrent increase in the number of responses for R12 with the highest number

followed by R13 and R11. The peak demand then tapers off after 2100 hrs. In the current plan,

demobilizing R14 at 1800 hrs is actually detrimental to the overall effectiveness of the current

model. Considering all the facts and the data adding two more hours of service to R14

deployment plan would help alleviate the increased demand for responses from the regular

transport units and reduce the need for mutual aid requests. The additional hours would have an

almost negligible additional cost while yielding an extra unit and maximizing the effective

deployment of this peak-load transport.

Finally, the utilization and deployment model of R14 has certainly made a positive

impact in reducing the need for mutual aid requests and responses in the B1 response zone.


Whenever R14 is in service, the need for mutual aid responses is very low, averaging 0.8% of the

total calls. The data also showed a large coverage gap in the B2 response zone. In this area, the

need for mutual aid responses to cover county jurisdictions averaged 6.8% with as high as 10%

from the total calls in the two districts adjacent to the B1 response zone, station 23 and 27.

Adding a second peak-load unit to cover this area and share in the response coverage currently

assigned to R14 would help minimize the need for mutual aid responses in a similar way than

R14 did within the B1 response zone. Comparatively the data supports the conclusion that the

use of the single peak load unit in B1 has had a significant impact in reducing the total need for

mutual aid responses. In contrast to B2, not having a peak-load unit routinely servicing the area

reveals a much higher need for mutual aid responses despite the fact that the total call volume in

B2 is much smaller (39%) compared to the total call volume in B1 area.

Of course, proponents of the fixed base 24 hour available units would like to see just

additional 24 hr transport units placed in service. One of the original options that have always

been in the response matrix is to abolish the peak-load unit concept and deploy this unit in the

traditional 24 hour response model. Based on the analysis of the data this option is certainly

viable but not the most efficient. Keeping a transport unit in service 24 hours per day, seven days

per week would make the actual personnel staffing problems disappear. If supported, a 24 hour

transport would have two personnel regularly assigned to the unit eliminating the need to explore

alternative staffing options. This option would be easy to implement, but it comes with an added

price tag in terms of personnel cost. In addition, regressing to adding a 24 hr truck would require

the additional expenses of determining the best station location or substation and the associated

facility construction and maintenance costs, whereas peak-load units can deploy from existing

facilities to cover the areas of greatest need. Having the additional 24 hr units would make it easy


to staff but it fails to address the units’ optimal efficient deployment and ways to maximize unit

supplementation without incurring in additional or excessive costs. Instead, employing a peak-

load unit in a model similar to system status management gives it adaptability and mobility.

The fixed station model can be complemented with a hybrid system status deployment

plan where the peak-load unit is assigned to a high call volume area but does not force the unit or

personnel to stand by at post locations. The unit can be assigned to a station area where the unit

reports to the assigned station until the next call for response is received. Allowing the unit to go

to a station eliminates the concerns with prolonged sitting on the unit and gives the crews the

opportunity to rest, complete reports and perform activities of daily living.

Recommendations

The deployment and utilization of R14 as a peak-load unit has certainly had a positive

impact in the reduction of mutual aid requests in the B1 response area based on the data analysis.

In its current deployment plan the data shows how much of an impact it has had. The data does

show however, that there is room for improvement. The current plan deploys R14 Tuesday

through Friday from 0800 hrs to 1800 hrs for a total of 40 unit hours. To maximize R14

deployment effectiveness, I offer the following recommendations:

1. Increase the total number of available unit hours from 40 to 60 hours per week. The

deployment hours would be equally distributed by adding Monday to the schedule

and increasing the daily hours from 10 to 12 hrs. This model would capture the calls

for service currently covered by mutual aid units on Mondays along with responses

beyond 1800 hrs. Adding the additional two hours into the daily schedule would also

capture a high percentage of calls received between 1800 and 1959 hrs. The data does

not support adding unit hours beyond 2000 hrs.


2. Move R14 from its current base at station 11 to station 12. The data consistently

shows the majority of the responses that R14 is dispatched (65% of all responses) are

in stations 12 and 13. This would focus R14’s response area and reduce actual

response times to help meet SCFD’s self-imposed performance measure of a 5-

minute response time.

3. Develop a modified system status plan to help identify how R14 would be used to

supplement high response demands by staging the unit at the stations in the affected

areas based on need. This model must address how personnel will be given adequate

breaks between calls, provide for suitable living facilities and avoiding the use of

generic post locations as staging areas.

This project wanted to address if the use of a single peak-load unit had a positive impact

on minimizing mutual aid requests, how would additional peak-load units help to further reduce

this need? The data clearly showed that the use of mutual aid units to cover the B2 response area

is much higher when compared to B1 response area even though B1 has triple the amount of

total calls. Based on the impact that R14 has had in reducing the need for mutual aid responses in

the B1 response area, the data also supports the following recommendations:

1. Deploy a second peak-load unit to service the B2 response area (station 23 and 27)

and station 22’s area (currently part of B1 area). R14 and the second peak-load unit

would have an even distribution of response areas.

2. The deployment schedule for the second peak-load transport unit would consist of 50

unit hours of service per week, Monday through Friday from 0800 hrs to 1800 hrs. By

demobilizing this unit at 1800 hours it staggers the unit demobilization times in an

effort to minimize the impact of the peak-load unit reduction gradually.


3. Base the second peak-load truck out of Fire Station 27. This assignment gives this

unit a central response location to a broad range of districts through an easily

accessible road network.

4. Potential coverage expansion of this unit in the future to include station 26 area.

Expansion of the coverage area would be determined from further CAD data analysis

one the unit has been deployed for six months.

Having two peak-load trucks dividing the south central and southwestern portions of the

county will provide maximum coverage during the times when these units are really needed,

avoiding the unnecessary staffing of units during traditionally low call volume times.

Supplementing unit availability in a peak-load model to maximize unit availability when it is

needed the most will show how SCFD is making a conscious effort to provide the best possible

coverage while curtailing costs and eliminating unnecessary staffing and operational costs.

The above recommendations call for an increase in effective unit hours of R14 and the

addition of a second transport unit to the peak-load plan. In the event that these recommendations

are not feasible, the following alternative recommendation could help improve coverage during

protracted high demand hours. It involves the modification of the actual hours of deployment

each day. R14 would be placed in service from 1000 hrs through 2000 hrs, Tuesday through

Friday. The change in hours would help reduce the need for mutual aid responses during peak

demand hours in the later hours of the day by balancing the supply to the demand. It fails to

address the need of having a peak-load unit available on Mondays when historically there have

been a high number of mutual aid responses. It also opens a portion of the morning hours each

day lacking adequate coverage. The modification of hours would also represent an

inconvenience to those employees choosing to work an overtime shift on this unit when coming


off from their regularly assigned work shift. This modification of the start time would represent a

two hour break or downtime between shifts. Changing the deployment hours is only an

alternative in the event the primary recommendations cannot be exercised to help balance the

current response model. This recommendation would not resolve several of the deficiencies

discussed in this paper.

This research shows the positive impact that a single peak-load transport unit has had to

reduce mutual aid responses. The recommendations surfacing from the data analysis support the

expansion of peak-load unit hours and days, the adding of a second peak-load unit to cover

deficient areas within the south central and southwest portions of the County. Future research is

recommended to look at how to staff these units. Currently, R14 is staffed strictly by employing

personnel assigned as an overtime shift. More research is needed to identify if strictly utilizing

overtime staffing is the most effective model. If SCFD decides to deploy a second peak-load

truck, it would be imperative to address the staffing question. Combining the two units, one at 60

hours per week, one at 50 hours per week, totaling 110 effective unit hours multiplied by two

personnel total 220 overtime hours each week. Justifying the overtime cost could become a

problem in these lean economic times. The research must also take a critical look at alternative

staffing concepts including the use of single certified (non-fire certified) paramedics and EMT’s

and alternative work schedules based on 10 and 12 hour work days, shifting away from the

traditional 24/48 hour schedule.

It is important to point out that creating an augmentation plan to supplement unit

availability during times of peak demand for service is just one piece of the puzzle. Further

research can also be focused in enhancing the public’s knowledge in this area. Frivolous calls for

service regularly tax the response capabilities of EMS agencies. Devising a public education


campaign using creative ways to increase the citizens’ awareness of the differences between

what constitutes an incident requiring lifesaving interventions by EMS vs. the use of EMS as a

glorified taxi ride to the hospital would help reduce the overall demand therefore reducing the

need for unit supplementation with a consequential reduction in mutual aid requests from

neighboring jurisdictions.

Another suggestion for future research must address the second portion of the claim from

the cities within the county. This research has shown that a maximum of 11% of responses in B2

response zone are handled by mutual aid units. The next chapter would be to evaluate the

percentage of time that county units respond into city jurisdictions to provide a reciprocal

service. Analyzing the actual data comparing the number of times the cities and county units are

dispatched as mutual aid would help clarify this perception of an imbalance in the response

numbers.

In conclusion, the utilization of R14 as a peak-load unit has made a positive impact in the

overall reduction of mutual aid responses into county jurisdictions. Adding a second peak-load

unit would help to close the gap in portions of county jurisdictions still using a much higher

percentage of mutual aid responses to cover these areas. Although peak-load units have not had

the greatest support in fire based EMS operations, the data analysis clearly shows that it does

have its merits and should be given careful consideration when chiefs and managers are looking

at maximizing the available budget dollars.


References

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Annals of Emergency Medicine, 18, 618-621.

Evans, B. E., & Dyar, J. T. (2009). Management of EMS. Upper Saddle River, NJ: Pearson

Prentice Hall.

Fitch, J. J. (2004). Prehospital care administration (2nd ed.). Woodinville, WA: KGB Media.

Forrest, D. (2009). 2008 Annual response data. Retrieved from

http://www.seminolecountyfl.gov/dps/pdf/ems_AlarmStatsLastYear.pdf

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fire suppression operations, emergency medical operations, and special operations to the

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http://www.nfpa.org/freecodes/free_access_document.asp?id=171010

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Appendix A

Figure 1: Geographic map of the battalion response zones

Figure 2: Fire station response zones


Appendix B

Table 1: Response data from Battalion 1 area

B1 (11, 12, 13, 22) SUN MON TUE WED THU FRI SAT Total

SCFD units 642 724 706 680 738 743 638 4871

City unit into county JZ* 3 7 6 8 3 8 7 42

% city units into county 0.4% 0.9% 0.8% 1.1% 0.4% 1% 1% 0.8%

Total responses 645 731 712 688 746 751 645 4913 Table 2: Response data from Battalion 2 area

B2 (23, 27) SUN MON TUE WED THU FRI SAT Total

SCFD units 259 270 242 274 261 257 270 1833

City unit into county JZ* 8 25 18 29 22 14 9 125

% city units into county 3% 9% 7% 10% 8% 5% 3% 6.8%

Total responses 267 295 260 303 283 271 279 1958 Table 3: Response aggregate data (B1 and B2)

Aggregate Data from B1 and B2 SUN MON TUE WED THU FRI SAT

Total responses by day 912 1026 972 991 1029 1022 924

% city units into county 3.4% 9.9% 7.8% 11.1% 8.4% 6% 4%

Table 4: Percent of responses divided by station district

Station 11 12 13 14 16 22 Total

% responses per district 9.85% 28.57% 36.95% 14.78% 7.39% 2.46% 100%

*JZ: Jurisdiction


Table 5: R14 Responses by MRA filtered by station response zones and day of the week.

Station 11

MRA 111 Total = 8 % Tuesday 4

4% Wednesday 1 Thursday 2

Friday 1



Friday 0



Friday 0

MRA 116 Total = % Tuesday 0

0.6% Wednesday 0 Thursday 1

Friday 0

Station 12



Friday 9



Friday 4



Friday 2



Friday 0

Station 13



Friday 7



Friday 3




Friday 8



Friday 4



Friday 2 Station 14



Friday 7



Friday 0

Station 16



Friday 6



Friday 2

Station 22



Friday 0



Friday 1

Miscellaneous MRA responses in stations 11, 13, 14, 16, 22

MRA Total = 13 % Tuesday 2


Friday 2


Appendix C

Graph 1: Total responses by hour per week

Graph 2: Total responses by hour between Tuesday and Friday


Graph 3: Response volume per unit and hour of day between Tuesday and Friday

peak-load unit utilization 1 running head: peak ... - hsdl

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