This is a two-phase study to address the high rates of infection by a specific resistant staphylococcal
bacterium in children who live in the Atlanta area. First, we will look at children who received care from
Children’s Healthcare of Atlanta (CHOA) at Egleston, Hughes Spalding, and Scottish Rite hospitals and
have a positive culture due to methicillin resistant Staphylococcus aureus (MRSA). We will compare these
children with those who have a methicillin sensitive Staphylococcus aureus culture (MSSA). The outcome
of the study in this phase consists of three components: (1) We will develop the methodology to extract
and integrate the variables of interest from the medical information and laboratory databases at these
locations so that comparisons can be made between those children who are infected by the resistant bacteria
to those children who are not. (2) We will develop efficient information monitoring techniques to
prospectively identify patients at the time of admission to the hospital, who have had a history of resistant
Staphylococcal infection. (3) Additionally, we will provide automatic integration of relevant medical and
laboratory variables in real-time for these patients. Another result of this phase of investigation is to
develop an automated system of determining whether or not patients are infected by a MRSA strain
originating from the hospital or from the community at large. This will be based on whether or not these
patients become infected within a specified time of their admission to the hospital, e.g., 48 hours, and the
specific antimicrobial susceptibility pattern of the bacterium isolated from the patient (phenotype of the
bacterium). In the second phase of this research, we plan to geo-code databases on all children who have
positive cultures for Staphylococcus aureus from January 2002 through December 2006 from the hospitals
and use geographic information system tools to determine which risk factors may contribute to infection by
these resistant staphylococcal strains. For example, presence of clustering of patients infected by CAMRSA will be identified based on the mapping of these patients’ residences. Incidence of infection and
other population information to determine certain risk factors can be derived by applying GIS to data
obtained from US Census Bureau. This population information can be grouped according to certain
boundaries, e.g., block groups, blocks, or census tracts. This research project will serve to link
communication and information technologies at three different hospitals in order to have a better
understanding of the epidemiology of children infected by CA-MRSA. The results generated by this
research will directly and indirectly impact the delivery of healthcare and assist with the development of
health policy guidelines as it pertains to infection control and healthcare quality within these three children
hospital sites. This research can be seen as a step towards the HSI vision of shaping the next health care
transformation (1).
Development of a system to combine data and information on children infected with certain resistant
bacteria from the three children’s hospitals servicing Atlanta area has the advantage of providing a
seamless access of information and may serve as a testbed towards enabling children health care
transformation to disease- prevention and health-focused (1). Concretely, this powerful tool can be used to
look at the impact and costs associated with hospitalization of these children. Infection control and quality
assurance programs can also use the information from such a system to critically look and address some of
the health guidelines and specific costs associated with containing the spread of resistant bacteria. This
integration of medical information with laboratory information is also useful from a research standpoint as
it creates the infrastructure needed to obtain data more efficiently. Although the existing technology at
Egleston and Scottish Rite sites provides for identification of patients who have a history of “multiple
resistant organisms”, this project will refine that process so that real time identification, specifically of
children infected by MRSA, can be linked to a database for collection of relevant medical and laboratory
information for prospective data analysis. Currently, there is no integration or method of “flagging,”
prospectively or retrospectively, those patients with MRSA at Hughes Spalding. Moreover, there is no
direct linkage of information between Hughes Spalding and the other two hospitals. Because many
physicians and other healthcare providers will provide services for all three locations, developing a linkage
of information systems will facilitate communication and, hence, better delivery of healthcare at all three
sites.
2. Broader impacts
Analysis of the data will provide valuable information regarding the epidemiology of those children who
are infected by CA-MRSA. Specifically, the information gained from using GIS will determine what risk
factors lead to the acquisition of this particular MRSA which originated from the community. The real time
aspect of the project will define the changing epidemiology of this bacterium as it moves from the
community into hospitals. This information gained has a significant impact on our healthcare system as we
strive to develop infection control policies to contain the transmission of resistant bacteria within the
hospital setting. The data can also provide insights as to the costs of treating such bacterial infections in our
hospitalized children. Development of this system will also improve the timing in which these children are
identified and result in a more efficient delivery of treatment. Perhaps more importantly, development of
real time data collection and integration across different informational systems will provide the backdrop
needed, so that this technology can be applied to population-based databases involving other emerging
infectious disease pathogens. One area of surveillance might include the Active Bacterial Core Surveillance
of the Emerging Infections Program Network, a collaboration between CDC and state health departments
and universities participating in the Emerging Infections Program Network(2). This collaboration was
developed in response to the increasing number of emerging infectious diseases of which CA-MRSA is one
of them. Developing the capability to efficiently integrate epidemiologic and clinical data across different
surveillance systems is an extremely valuable tool in the battle to decrease the spread of these pathogens
within our communities. Although GIS tools have been used in other medical areas, there are few studies
using GIS to look at clinical and molecular epidemiology of resistant bacteria in the US. There are major
health policies that can be impacted by findings based upon population-based studies using GIS
technology. For instance, communities identified to be at high risk for a specific phenotype of MRSA can
be targeted to receive services including empiric treatment tailored against that particular circulating
phenotype.
3. Background and Significance
Antibiotic resistant bacteria are becoming an increasing problem in the United States and worldwide as
they cause serious and, often times, life-threatening infections in the face of a limited armaterium of
antibiotic agents. Resistant bacteria usually originate from hospitals whereby selection pressure from
frequent antibiotic exposure leads to the development of different mechanisms of resistance. However, one
resistant bacterium today is believed to have originated from the community and not from the hospital—
community-associated methicillin resistant Staphylococcus aureus (CA-MRSA). Nationally, the incidence
of CA-MRSA infections is increasing at an alarming rate (3, 4). Morbidity associated with infection
caused by this bacterium range from minor skin or soft tissue infections (SSTI) to severe illnesses
(pneumonia, septic shock, bone infections) resulting often times in death (3, 5-8). The clinical presentation
is believed to be related to virulent factors of CA-MRSA (3). CA-MRSA reflect a particular strain of
resistant Staphylococcus aureus, namely, USA clone 300. These strains have a typical antimicrobial
susceptibility pattern which is characteristic of the phenotype which originated from the community-resistance to the antibiotics oxacillin or resistance to both oxacillin and erythromycin. We propose to
develop a model to systematically merge existing microbiology laboratory database information with
electronic medical record information to identify patients with resistant Staphylococcus aureus. From this
centralized database, we begin to differentiate which patients have infection by bacterial strains that
originated from the community versus those whose strains are acquired from within the hospitals. There are
few studies that have identified which risk factors are associated with infection by CA-MRSA. For
example, few studies have systematically addressed whether or not race/ethnicity, younger age, geographic
location (i.e., specific neighborhoods), crowding, or socioeconomic status increase the risk for infection.
Paramount to improving the healthcare delivery to children who are infected with this resistant bacterium is
quick identification of those children who are potentially infected so that proper and correct antibiotic
therapy can be given. We propose to use geographic information system tools to identify potential risk
factors for the acquisition of this resistant bacterium. Additionally, we propose to develop a system of
rapid identification of children who may have these risk factors for resistant bacterial infection at the time
they present for healthcare. Identifying those children who have risk factors for infection by CA-MRSA
based on area of residence or other demographic information can improve the delivery of preventative or
empiric treatment for clinical diseases caused by such resistant bacterial infections.
Using two approaches will provide key information regarding the epidemiology of those children who
are infected by CA-MRSA.
Aims
• To merge databases from laboratory, medical information databases, and electronic medical records
and identify children who have been infected with both resistant and non-resistant Staphylococcus
aureus through automated information update monitoring and tracking techniques.
• To identify risk factors for CA-MRSA using geographic information system tools and visual and
automated data mining methods.
Data Collection Assumptions:
Data variables of interest. For patients who had Staphylococcus aureus isolated from a clinical culture, the
following information will be obtained from the laboratory (See Appendix I for list of laboratory variables):
Patient medical record number, body site where culture was obtained, hospital location of patient at the
time of specimen collection, date of culture collection, time for culture to become positive, bacterial isolate
specimen number and complete antimicrobial susceptibility pattern. Demographic information on all
patients from whom Staphylococcus aureus was isolated will be obtained through the Medical Information
Department at each children’s hospital. (See Appendix I for list of medical information variables.) In
addition, information on patient days, by hospital unit, will be obtained for hospital administrative
databases.
Merging of medical information with laboratory information systems (See Appendix II for Timeline for
Proposal). It is anticipated that this phase of the proposal will be completed during the first quarter of the
funding period.
 At Scottish Rite and Egleston Hospitals. All clinical culture results from the period January 2002
through December 2006 will be obtained by downloading information from computer systems
used by Egleston and Scottish Rite campuses. Duplicate isolates will be excluded. This
information will be translated into a format by which GIS technology can be applied.
 At Hughes Spalding Hospital. Similarly, at Hughes Spalding, all clinical culture results from the
same period will be obtained. Methodology to extract and merge data from laboratory and
medical information systems at Hughes Spalding Hospital will involve the following:
1. The design of a consolidated database that will combine laboratory database of Hughes Spalding
Children’s Hospital with its medical information database in an effective manner. This requires
the design of a consolidated database schema such that the consolidated database can be used
efficiently for several purposes: (1) timely collecting and integrating of medical data and
laboratory data of those patients who have a positive culture; (2) timely detecting and flagging of
those patients who have a history of methicillin resistant Staphylococcus aureus (MRSA)
infection; (3) timely tracking of all patients and the interested variables that present with positive
culture for MRSA; and (4) providing efficient translation of consolidated data into a format by
which GIS tools can be applied.
2. The concrete methods for combining and linking both laboratory and medical information systems
at Hughes Spalding Hospital include (1) techniques for creating and maintaining a clinical cultures
positive database for Staphylococcus aureus from 1/2002 to 12/2006; (2) techniques for dynamic
joins of laboratory and medical information of the patients in real time with user-friendly graphical
interfaces for pediatric doctors and researchers to use; and (3) techniques for automated extraction
of interesting data items from the consolidated database for performing statistical analysis and data
mining.
Data Distribution Requirements:
Establishing a database prospectively at all three hospitals. Active surveillance for Staphylococcus aureus
infections will be performed on all patients with positive cultures. This phase of the project will be started
during the second quarter of the funding period and will be ongoing thereafter. This collection will occur in
real-time and involve the following measures:
1. Timely and efficient tracking of significant updates on patients with positive clinical cultures,
including the list of variables we have identified (see Appendix I). An example of such monitoring
services is to track patients whose cultures became positive within 48 hours of admission.
2. Providing end-user level facilities, such as GUI, visualization tools, data mining tools, to allow
pediatricians and pediatric researchers to analyze patients’ data and perform statistical data
analysis in real time.
3. Providing system-level facilities to support complex triggers for monitoring significant updates of
laboratory and clinical information.
4. The engineering and development of a real-time database update monitoring system on top of the
consolidated database, which not only will link laboratory database of Hughes Spalding Children’s
Hospital to its medical information database automatically in real time, but also will provide
efficient and reliable methods and techniques for identifying, tracking and alerting in real time the
significant updates on both laboratory data and clinical data of patients of interest.
Geo-coding databases of all children infected with Staphylococcus aureus based on antibiotic resistance
pattern. We will geo-code all patients with positive Staphylococcus aureus cultures for the study period
and will begin this process during the second half of the funding period. This geo-coded dataset will then
be sorted based on patients’ antibiotic resistance pattern as defined in Appendix I. Specifically, we will
group patients into those with CA-MRSA phenotype, non CA-MRSA phenotype and MSSA case controls.
Using ArcView 9.1 (Environmental Systems Research Institute (ESRI), Redlands, California) and
statistical software (e.g., SPSS, SAS), we will determine if certain demographic traits are associated with
risk for infection for the respective groups. Population information to look at possible risk factors including
housing conditions (e.g., overcrowding), race, and household income will come from census data. For
example, Fridkin et al suggested in their population-based study the risks in Atlanta associated with
increased incidence of infection included being younger than two years or black (9). Similarly, risks
associated with either infection or colonization by CA-MRSA in studies of adults include history of
incarceration or HIV infection(10). Spatial clustering of isolates will also be assessed to determine whether
specific strains of resistant MRSA occur in specific communities.
Analysis plan. Data will be collected both retrospectively and prospectively in order to obtain complete
data for the time period of January 2002 through December 2006. The data will be used to determine
monthly rates of infection or colonization due to CA-MRSA. The incidences and rates of CA-MRSA, HAMRSA and nosocomial-MRSA will be determined. The denominator for each of these determinations is
based on the total number of cultures positive for Staphylococcus aureus. We will also determine the
incidence and rate of patients who presented to the emergency department for evaluation and treatment of
SSTI. The denominator for this will be based on the total monthly number of patients seen in the
emergency department. Finally, we will determine rates of infection or colonization from MRSA isolates
that are CA-MRSA phenotype but cultures were obtained and became positive after 48 hours of admission.
These results will be compared to other MRSA phenotypes, which were collected from patients after 48
hours of admission. Comparisons of clinical diagnoses, length of hospital stay, and demographic
information will be made between those patients who had cultures positive for CA-MRSA by phenotype
and those who culture for HA-MRSA. Additionally, similar information will be obtained from a similar
group of patients with cultures positive for MSSA. The laboratory and medical information variables will
be merged into a single database, which will be analyzed using SPSS version 11 (SPSS, Inc.) and SAS V.8
(SAS Institute, Cary, NC). Prevalence and overall incidence for positive cultures due to CA-MRSA, nonCA-MRSA, MSSA per year will be determined. Rates of CA-MRSA, MSSA, Nosocomial-MRSA and HAMRSA skin and soft tissue infections will be determined and analyzed using time series analyses. Study
protocol will be submitted for approval by Georgia Institute of Technology, Children’s Healthcare of
Atlanta, Grady Health System, and Morehouse School of Medicine Institutional Review Boards.
Potential Use of Findings
Results from this study will inform the healthcare community about incidence of CA-MRSA and identify
specific risk factors for infection. This information will be necessary in order for us to develop specific
health policy guidelines within communities at high risk for infection. Recommendations on which
antibiotics should be selected for empiric therapy can be based on the information gained from this study.
For example, if a patient presents for a skin infection and has one of the identified risk factors, treatment
with antimicrobial agents targeting CA-MRSA can be made. This will minimize the overuse and misuse of
broad spectrum antibiotics. The information gained by implementing this proposal will help develop
specific infection control measures which should be adopted by hospitals and other healthcare settings in
order to prevent the spread of this resistant bacterium. Developing and refining the methodology for this
project has significance in applying the technology towards other population based datasets. For example,
the Centers for Disease Control and Prevention have established an active ongoing surveillance system of
specific harmful pathogens through its Active Bacterial Core Surveillance. These are population based
surveillance systems from across the US. Seamless integration of the various information systems can
simplify the process of determining which pathogens pose the greatest infectious disease threat as well as
provide a way to systematically look for risks associated with infection by these pathogens.