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Article |

Bridging the Emergency Medical Services for Children Information Gap FREE

Theresa C. Murdock, MD; Jane F. Knapp, MD; M. Denise Dowd, MD, MPH; Jack P. Campbell, MD
[+] Author Affiliations

From the Department of Pediatrics, Division of Emergency Medicine, Children's Mercy Hospital (Drs Murdock, Knapp, and Dowd) and the Department of Emergency Medicine, Truman Medical Center (Dr Campbell), Kansas City, Mo.


Arch Pediatr Adolesc Med. 1999;153(3):281-285. doi:10.1001/archpedi.153.3.281.
Text Size: A A A
Published online

Objective  To determine the epidemiological features of pediatric usage of prehospital emergency medical services (EMS) in a defined urban population.

Methods  Residents of Kansas City, Mo, younger than 15 years who used EMS during the calendar years 1993-1995 were included. In this geographic area there is a single provider of prehospital care; all numerator data were taken from this single source. Denominator data were provided by 1995 intercensal estimates based on the 1990 US Census. Rates were calculated as an annual average and reported as the number of children transported per 1000 persons per year.

Results  There were a total of 7296 pediatric EMS transports during the study period, for an annual rate of 21.9. Infants younger than 1 year had the highest rate (47.4), followed by those aged 1 to 4 years (26.2), 10 to 14 years (17.5), and 5 to 9 years (17.3). Medicaid was the insurer for half and 27% were uninsured. One quarter of the patients used EMS more than once. Children living in ZIP codes in the lowest median income tertile were 5.8 times more likely to use EMS than those in the upper income tertile (95% confidence interval, 5.4-6.3). One third of all transports occurred between the hours of 4 and 8 PM.

Conclusions  Children using the Kansas City EMS were more likely to be infants, insured by Medicaid or uninsured, and live in low-income ZIP codes. Further study is needed to determine if this increased usage is due to greater incidence and severity of illness and injury, lack of transportation, lack of education, or other factors.

Figures in this Article

THE INSTITUTE of Medicine report on emergency medical services (EMS) for children, published in 1993, identified major informational gaps in both the quality and quantity of knowledge regarding pediatric prehospital emergency care. Specifically, the report noted, "Without a broad and reliable base of information, it is hard for anyone . . . to determine in any systematic way how successful EMS-C [emergency medical services for children] systems are in providing appropriate, timely care or what they ought to do to improve performance and patient outcomes."1 Furthermore, it suggested that assembling descriptive data to answer basic questions should be a high research priority.

Data are especially limited for the pediatric prehospital care component of EMS. Frequently cited studies on prehospital care of children are now almost a decade old.24 Newer data exist, including studies in both urban and rural settings, but these studies are not population-based and generalizability is limited.58 The need for up-to-date population-based assessment of the prehospital care of children remains critical to effective EMS planning.

There are several reasons why population-based studies are rare. Prehospital care systems are frequently fragmented, with multiple agencies involved in a single geographic area, making the process of data collection, aggregation, and analysis a monumental task. Recordkeeping is often not standardized or is incomplete, creating serious weakness in the quality and quantity of information. Pediatric emergency transports are far less frequent than adult emergency transports, making meaningful evaluation difficult in many systems. The ability to perform an accurate, population-based description of pediatric prehospital care is greatly enhanced by and identified by a system that can eliminate or minimize these barriers. The Kansas City, Mo, prehospital care system is a well-described public utility model.9,10 It uses a single provider and a statewide standardized form with established, reported 100% record review. All information collected by EMS teams are entered into a computerized electronic database. The Kansas City system, therefore, presented an opportunity to study the characteristics of prehospital care in a defined population. The aim of this study was to describe the population-based epidemiological features of usage of prehospital pediatric care and to ascertain differences among population subgroups.

All residents of Kansas City younger than 15 years (1995 population aged 0-14 years=110,862) who were transported by the Kansas City prehospital EMS (Metropolitan Ambulance Service Trust) for the calendar years 1993-1995 were included for analysis. Those whose ZIP code of residence were incomplete or absent on the ambulance record were excluded from the study. Calls in which an ambulance responded but the patient was not transported were not included in the analysis.

The Metropolitan Ambulance Service Trust is the exclusive provider of ambulance service to Kansas City. The system serves a 350-square-mile area with a base population of approximately 500,000. It is an all advanced life support system, with 51,000 average annual responses. Each unit is staffed by a paramedic and an emergency medical technician. All paramedics complete a minimum of 16 hours of pediatric training.

Paramedics complete a Missouri State standardized prehospital transport form for every patient encounter. This form includes the following information: demographics (sex, age, address, date, and time); the assigned level of priority to which the ambulance responded and left the scene; insurance provider; chief complaint; paramedic's assessment of the patient and classification byInternational Classification of Diseases, Ninth Revision (ICD-9) external injury codes (E-codes); transport destination; and procedures and medications given. These "run sheets" are sent to a central office where the information is abstracted and entered into a computerized electronic database. All information for this study was obtained from this single electronic database. In addition to demographic information, other data obtained for the study included the number of times the system was accessed, insurance status, day of week of transport, time of transport, ZIP code of patient, and chief complaint.

Primary diagnosis codes were grouped for analysis in the following manner. Nine diagnostic groups were defined based on the primary diagnosis code assigned by the paramedic. Trauma/poisoning was defined as all patients with the diagnosis of fracture(s), hemorrhage, hematoma, overdose, poisoning, inhalation, motor vehicle crash, fall, environmental injury, other injury, shooting, stabbing, accident, suicide, assault, fight, amputation, submersion, or burn.Respiratory included all patients with respiratory distress, respiratory failure, pulmonary edema, pneumonia, or tracheal obstruction. Gastrointestinal included any conditions related to the gastrointestinal system including feeding problems. Thecardiac group included all arrythmias, cardiogenic shock, and nontraumatic cardiac arrest. The pain group included all persons with the primary complaint of pain from causes other than trauma such as headache or sickle cell crisis. The neurologic group included unconsciousness (not related to poisoning), seizures, stroke, behavioral problems, and coma. The fever group included all patients with suspected sepsis or fever. Theobstetric/gynecologic group included those patients with the diagnosis of vaginal bleeding, infants delivered in the field or impending delivery, or abortion. The other group included diagnoses that did not fit in the aforementioned categories and unknown diagnoses.

Intercensal estimates for 1995 provided denominator population data on age, sex, and the median household income for the ZIP code of the patients enrolled in this study (based on the 1995 Claritas estimate, Kansas City, Mo). Pediatric transport rates were expressed as number of transports per 1000 population and expressed as an annual average for the 3-year period. Relative risks were obtained using the ratio of incidence rate in the population of interest to that of the reference population. Reference groups were designated as the category with the lowest rate for the variable of interest. Ninety-five percent confidence intervals (CIs) were obtained around the relative risk using the method of Greenland and Robins.11

Intergroup differences were compared using χ2 tests where appropriate. Probability values of less than .05 were considered to be statistically significant.

An ecological analysis of ambulance usage was performed using ZIP code as the unit of analysis. Simple linear regression analysis was performed to produce a model with median income as the independent variable and rate of transports per 1000 population per year in the ZIP code as the dependent variable. Ninety-five percent CIs for predicted rate were calculated.

Of the 152,850 transports performed by the Kansas City ambulance service during the 3-year study period, 9200 (6%) were for individuals aged younger than 15 years. After excluding nonresidents and those whose ZIP code was missing or inaccurate, 7296 transports were left for analysis. The annual transport rate for children was 21.9 per 1000 persons per year.

Characteristics of the study population are summarized in Table 1. Children aged 1 to 4 years constituted the largest group of transports (33.7%). However, infants younger than 1 year had the highest ambulance usage rate at 47.4 per 1000 persons per year. This was almost 3 times as high as the rate of the 5- to 9-year-old reference group. Males accounted for 55% of the transports and had a usage rate incidence rate of 23.6 per 1000 population per year for a relative risk of 1.2 (95% CI, 1.1-1.2) when compared with females.

Table Graphic Jump LocationTable 1. Characteristics of Children Transported by Ambulance in Kansas City, Mo, 1993-1995*

Medicaid was the insurer for 51% while 21% of the study group was covered by commercial insurance. Twenty-seven percent of all children were uninsured.

There was a significant inverse linear relationship between the number of transports and median family income in ZIP code of residence. Figure 1 illustrates this relationship by plotting the rate of transports for a given median income in a ZIP code. The ZIP codes in the inner urban core were among the poorest and were those with the highest transport rates.

Place holder to copy figure label and caption
Figure 1.

The relationship between rate of transports and median family income. The regression line is surrounded by the 95% confidence intervals for the predicted transport rate.

Graphic Jump Location

Figure 2 illustrates the significant fluctuation in number of transports by the hour of the day. Peak usage occurred from 4 to 8 PM hours with lowest usage from 4 to 8 AM (P<.001). There was significant variation observed by day of the week, with the highest number of transports observed on Fridays (n=1135) and the least number on Wednesdays (n=958). Additionally, volume of transports varied by month, with a high in March and May (669 each) to a low in September (544) (P<.001).

Place holder to copy figure label and caption
Figure 2.

Pediatric emergency medical services transports by hour of the day.

Graphic Jump Location

Of the 6342 patients, 5730 (90%) were transported a single time during the 3-year study period. Six hundred twelve patients accessed the system more than once, accounting for 1566 or 21.4% of the total number of transports in the year (Table 2). These 612 patients accounted for 9.6% of the total number of patients transported. The most common diagnosis of patients using EMS more than once for the same complaint were seizures (36%) and respiratory distress (26%).

Table Graphic Jump LocationTable 2. Children Using the Ambulance for More Than 1 Transport in the 3-Year Study Period

Transports of patients younger than 1 year were primarily medically related (75%) while older children were transported for trauma/poisoning or a pain-related complaint. Examples of the most frequent trauma diagnosis were lacerations, motor vehicle crashes, and assaults or child abuse. In fact, 9.9% of the transports for the 1- to 4-year-old age group were for child abuse.

Diagnoses by age categories are depicted in Table 3. The top 3 complaints were trauma/poisoning (36.9%), pain (18.1%), and respiratory problems (15.6%). Infants younger than 1 year were transported primarily for respiratory symptoms followed by trauma/poisoning and neurologic complaints. Among all age groups, those aged 1 to 4 years had the highest percentage of transports for trauma/poisoning, followed by neurologic and respiratory complaints. Older children were transported for trauma/poisoning followed by pain and respiratory symptoms. There were 38 nontraumatic cardiac arrests in the group aged younger than 1 year.

Table Graphic Jump LocationTable 3. Numbers and Percentages of Diagnoses of Pediatric Patients by Paramedics' Initial Assessment by Age Group*

The Institute of Medicine report has emphasized that EMS data on children are needed at the local, state, and national level; the particular kinds of data needed at each level may vary but, in all cases, data collected for one level should be useful at every level below.1 This study provides population-based information available for systems evaluation and planning for Kansas City and for reference and comparison with other systems.

This study is the first to define prehospital transport usage rates for a given population of children. It demonstrates that rate of usage of prehospital care decreases up to age 15 years and that infants are at highest risk. Trauma continues to be a significant problem, necessitating prehospital care throughout childhood. Pain has not previously been recognized and reported in this country as a condition requiring transport in children. Residents from poorer ZIP codes use the system more frequently and approximately 10% of the patients are responsible for one fifth of the transports.

Children younger than 15 years represented 6% of all EMS transports. This is close to the 4% reported in a recent multistate pediatric prehospital transport study.5 Others have reported a rate of pediatric transports as high as 10% but these studies have included a broader age range of children and were not population based.2,3 The definition of a pediatric transport has varied widely between studies. Our age cutoff was chosen for convenience and to be compatible with US Census groupings. Studies that report percentages of children of various ages transported are not ideal for comparisons between systems. For example, a study reporting the highest percentage of transports in children aged 15 to 18 years is difficult to compare with this study. We find the highest percentage of transports in children aged 1 to 4 years but did not study children older than 15 years. More generalizable information for comparison between systems and longitudinally within a system is obtained from usage rates. These rates are population based and not related to a percentage of the total number of children included. In this study, infants had the lowest percentage of transports but the highest usage rates. Overall, usage rates decreased up to age 15 years and there were statistically significant differences between the children younger than 5 years and the 5- to 9-year-old reference group. Although we do not have information on severity of illness, infants had the highest number of cardiac arrests and, based on usage rate of transport, are the highest-risk group. The practical application of these data is not limited to prehospital care systems. Primary care physicians can use this information to target parents of infants for prevention strategies. This might include anticipatory guidance on when and how to access ambulance transport for emergency care, arrangements for home health care visits for sick infants, or recommendations for training in basic life support.

Data on the demographic characteristics of the patient population such as age, sex, and residence are essential for understanding who needs care. This study confirms the work of others showing a male predominance,2,3,5 a majority of calls during daylight and evening hours,3 and spring seasonality.12 Residents from ZIP codes with the lowest median income had higher usage rates. We were not able to adjust the usage rate for severity of illness or injury, which significantly limited our ability to interpret the meaning of the relationship between median income and usage rate. Future work will be important to determine whether variation of usage by socioeconomic status is due to severity of illness, lack of information or understanding of disease process, lack of transportation, or other factors. Half of the transports were by individuals insured with Medicaid (51%). This is not as high as the 73% of Medicaid- and health maintenance organization Medicaid–insured patients transported reported by Camusso-Richardson et al.13 That study went on to show that many of the individuals with Medicaid insurance had no medical justification for taking the ambulance to the hospital. The percentage of children younger than 15 years of age insured by Medicaid in Kansas City is approximately 35%, making Medicaid-insured patients overrepresented in those using the ambulance.

This study also found evidence that multiple usage by a small group existed; 9.6% of the patients accounted for 21.4% of the transports. This phenomenon has been observed before. During a 12-month study in Hawaii, 3.5% of the patients accounted for 7.8% of the transports. Associations with multiple transports included handicapping conditions, male sex, trauma, wheezing, and Medicaid insurance.4 A study from New Mexico found that 11.1% of the patients younger than 21 years had multiple transports.14 The payment source for repeatedly transported patients was primarily self-pay and Medicaid. The proportion of transports funded by Medicaid among repeat users was twice that of singly transported patients.

Pain was a large diagnostic group in our study. Prior studies have shown that pain may be the most common reason for emergency department visits and is a frequent reason to seek medical care in any outpatient setting.15,16 No other epidemiological studies on prehospital care in children have reported pain as a reason for transport.

This study has several limitations. Twenty percent of the sample was lost owing to missing data and the accuracy of the data from the database could not be verified. Patients who should have been included may have been eliminated due to birth date or ZIP coding errors. Diagnostic code groupings determined by paramedics may have been incorrect and may not be comparable to other studies.

Emergency medical services for children represent a continuum of care. Information from the prehospital transport of children can help improve care at several levels. With good descriptive data, primary care providers, planners, evaluators, and researchers can begin to answer the more significant questions regarding system performance and prevention of unnecessary usage. Future in-depth work needs to be undertaken to examine the transports from the poorer areas of the city and the repeat user of the prehospital system.

Accepted for publication August 18, 1998.

Presented at the annual meeting of the Ambulatory Pediatric Association, New Orleans, La, May 3, 1998.

We thank John Jarrell, Delynn Piper, and Stephen D. Simon, PhD, for all their help with the database. We gratefully acknowledge Metropolitan Ambulance Service Trust and especially Martha Hoover for her commitment to this project.

Reprints: Theresa C. Murdock, MD, Department of Pediatrics, Pediatric Emergency Medicine Maricopa Hospital, 2601 E Roosevelt, Phoenix, AZ 85008.

Editor's Note: Let your imagination loose, and think of how many cross-correlations you might look for with these sort of data.—Catherine D. DeAngelis, MD

Durch  JSedLohr  KNed Emergency Medical Services for Children.  Washington, DC National Academy Press1993;
Tsai  AKallsen  G Epidemiology of pediatric prehospital care. Ann Emerg Med. 1987;16284- 292
Link to Article
Seidel  JSHornbein  MYoshiyama  K  et al.  Emergency medical services and the pediatric patient: are the needs being met? Pediatrics. 1984;73769- 772
Yamamoto  LGWiebe  RAMaiava  DM  et al.  A one-year series of pediatric prehospital care: I (ambulance runs), II (prehospital communication), III (interhospital transport services). Pediatr Emerg Care. 1991;7206- 214
Link to Article
Joyce  SMBrown  DENelson  EA Epidemiology of pediatric EMS practice: a multistate analysis. Prehospital Disaster Med. 1996;11180- 187
Seidel  JSHenderson  DPWard  P  et al.  Pediatric prehospital care in urban and rural areas. Pediatrics. 1991;88681- 690
Svenson  JENypaver  MCalhoun  R Pediatric prehospital care: epidemiology of use in a predominantly rural state. Pediatr Emerg Care. 1996;11180- 187
Pyles  LAChafin  CMHawkins  PI  et al.  Analysis of State EMS Run Form Data for Pediatric and Adult Patients.  Washington, DC National Congress on Childhood Emergencies1998;
Campbell  JPGratton  MCGirkin  JP  et al.  Vehicle-at-scene to patient-access intervals measured with computer-aided dispatch. Ann Emerg Med. 1995;25182- 186
Link to Article
Stout  J The public utility model, part II: the principal elements. J Emerg Med Serv. 1980;534- 41
Greenland  SRobins  JM Estimation of a common effect parameter from sparse follow-up data. Biometrics. 1985;4155- 68
Link to Article
Johnston  CKing  WD Pediatric prehospital care in a southern emergency medical service system. South Med J. 1988;811473- 1476
Link to Article
Camusso-Richardson  KWilde  JAPetrack  EM Medically unnecessary pediatric ambulance transports: a medical taxi service? Acad Emerg Med. 1997;41137- 1141
Link to Article
Braxterman  KSapien  RFullerton  L  et al.  Repeat ambulance use by the pediatric patient.  Poster presented at: Pediatric Academic Societies Annual Spring Meeting May 3, 1998 New Orleans, La
Frolund  FFrolund  C Pain in general practice: pain as a cause of patient-doctor contact. Scand J Prim Health Care. 1986;497- 100
Link to Article
Crook  JRideout  EBrowne  G The prevalance of pain complaints in a general population. Pain. 1984;18299- 314
Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.

The relationship between rate of transports and median family income. The regression line is surrounded by the 95% confidence intervals for the predicted transport rate.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Pediatric emergency medical services transports by hour of the day.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Characteristics of Children Transported by Ambulance in Kansas City, Mo, 1993-1995*
Table Graphic Jump LocationTable 2. Children Using the Ambulance for More Than 1 Transport in the 3-Year Study Period
Table Graphic Jump LocationTable 3. Numbers and Percentages of Diagnoses of Pediatric Patients by Paramedics' Initial Assessment by Age Group*

References

Durch  JSedLohr  KNed Emergency Medical Services for Children.  Washington, DC National Academy Press1993;
Tsai  AKallsen  G Epidemiology of pediatric prehospital care. Ann Emerg Med. 1987;16284- 292
Link to Article
Seidel  JSHornbein  MYoshiyama  K  et al.  Emergency medical services and the pediatric patient: are the needs being met? Pediatrics. 1984;73769- 772
Yamamoto  LGWiebe  RAMaiava  DM  et al.  A one-year series of pediatric prehospital care: I (ambulance runs), II (prehospital communication), III (interhospital transport services). Pediatr Emerg Care. 1991;7206- 214
Link to Article
Joyce  SMBrown  DENelson  EA Epidemiology of pediatric EMS practice: a multistate analysis. Prehospital Disaster Med. 1996;11180- 187
Seidel  JSHenderson  DPWard  P  et al.  Pediatric prehospital care in urban and rural areas. Pediatrics. 1991;88681- 690
Svenson  JENypaver  MCalhoun  R Pediatric prehospital care: epidemiology of use in a predominantly rural state. Pediatr Emerg Care. 1996;11180- 187
Pyles  LAChafin  CMHawkins  PI  et al.  Analysis of State EMS Run Form Data for Pediatric and Adult Patients.  Washington, DC National Congress on Childhood Emergencies1998;
Campbell  JPGratton  MCGirkin  JP  et al.  Vehicle-at-scene to patient-access intervals measured with computer-aided dispatch. Ann Emerg Med. 1995;25182- 186
Link to Article
Stout  J The public utility model, part II: the principal elements. J Emerg Med Serv. 1980;534- 41
Greenland  SRobins  JM Estimation of a common effect parameter from sparse follow-up data. Biometrics. 1985;4155- 68
Link to Article
Johnston  CKing  WD Pediatric prehospital care in a southern emergency medical service system. South Med J. 1988;811473- 1476
Link to Article
Camusso-Richardson  KWilde  JAPetrack  EM Medically unnecessary pediatric ambulance transports: a medical taxi service? Acad Emerg Med. 1997;41137- 1141
Link to Article
Braxterman  KSapien  RFullerton  L  et al.  Repeat ambulance use by the pediatric patient.  Poster presented at: Pediatric Academic Societies Annual Spring Meeting May 3, 1998 New Orleans, La
Frolund  FFrolund  C Pain in general practice: pain as a cause of patient-doctor contact. Scand J Prim Health Care. 1986;497- 100
Link to Article
Crook  JRideout  EBrowne  G The prevalance of pain complaints in a general population. Pain. 1984;18299- 314
Link to Article

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