the golden years

THE POTENTIAL IMPACTS OF AN AGING POPULATION ON AMBULANCE SERVICES

IN WESTERN NEWFOUNDLAND

M a d i s o n M u g g r i d g eJ u n e 2 0 1 1

The Golden Years:

Content

BackgroundAbout this projectMethodologyResultsDiscussionGIS in the future?

Background Information

• Paramedicine and Medical Transport (PMT) division of Western Health.

• Responsible for servicing a large chunk of Newfoundland’s west coast, which contains over 77,500 people, more than 15% of Newfoundland and Labrador’s population.

• Over 34% of patients serviced by the PMT division live in Corner Brook.

• Responsible for transporting people not only between hospital and home, but also between facilities.

Background Information (Cont’d)

• Western Health controls 2 hospitals, 4 rural health centres, 2 long term care centres, 1 enhanced assisted living model, 31 medical clinics, 21 Population Health Branch site locations, and the Humberwood Centre.

• 263 acute care beds, 356 long term care beds, 4 palliative care beds, 2 slow-paced rehab beds, 2 respite care beds, and 2 ICU beds.

About This Project..

• Worked in correspondence with Western Health’s PMT division to draw conclusions about the relationship between ambulance dispatch reasons, age, gender, and location.

• Impact baby boomers are going to have on healthcare in the near future based on patterns in the past.

• Census data was also an important part of this study because it displayed trends in the past that could lead to better planning for the future.

About This Project..

Started the project with a single spreadsheet of data supplied by Western Health’s PMT division.

Contained 16 fields of data including dispatch reasons, age, gender, origin, destination, ambulance type, etc.

Challenge: Redundancy and duplicates within the dataset (Dispatch Reason).

Methodology

• First order of business? Removing redundancies and duplicates from the dataset.

• Creating separate categories that all shared a common naming convention into which all of the records in the dataset could be grouped.

• 27 Dispatch Reasons in all (originally hundreds).

Final Dispatch Reasons

• Convalescence: The returning of a patient to a hospital for recovery procedures prior to having an illness.

• Echocardiogram: Sonogram of the heart. Also known as a cardiac ultrasound.

• Endoscopy: Procedure in which an endiscope is inserted into an organ or hollow cavity of the body.

• Cath Lab: Lab where patients go to undergo catheterization procedures.

• Palliative Care: Comfort care offered to relieve and prevent the suffering of severely or terminally ill patients.

• Pandemic Surge: When a hospital fills to capacity and patients must be transferred between facilities.

Distance and Cost

• After deciding on the dispatch reason categories, the next step was to create two new fields, “Distance” and “Cost($)”.

• Western Health website and Statistics Canada website used for calculations.

• Ambulance Cost: $215 dollars for trips <120km ($100 base rate + $115 user fee). Trips >120km = $215 base rate + $0.95/km for every km over 120.

Data Normalization (Cont’d)

• Like the Dispatch Reason field, the OriginCity, DestinationCity, Origin, and Destination fields were normalized.

• 16 Origin, 29 Destination, 10 OriginCity, 18 DestinationCity.

• Ambulance dispatch dataset now normalized with all duplicates and redundancy removed.

Population Data Preparation

• Population data was needed in order to draw conclusions about past trends in the populations of Western Newfoundland communities.

• Using the past to plan for the future.

• For the purpose of this study, census data was collected for the census years of 1991 to 2006.

• Statistics Canada website and Community Account website.

Population Data Overview

• For all of the census data collected (excluding the data for 1991), the populations were divided into 8 age range categories with a count of how many people fell within that age range per location.

• One primary collection was complete, a new field was added (“Percentage Change”).

• Percentage Popn Change = ((New Popn – Old Popn)/New Popn) x 100

• % Population Change fields for each year were then sorted so the lowest % change were located on top. All years and % change records were then compiled into one large list.

Dispatch Data Analysis

• New tab opened in Microsoft Excel (“DispatchReasonAgeData”)

• For each dispatch reason, calculations were done to find mean, median, and modal ages for total patients, males, and females. Age ranges per gender, number of instances per gender, and standard deviation per gender also calculated.

• This data was later used to compile charts and graphs to better illustrate the trends that existed within it.

Dispatch Data Analysis (Cont’d)

• New tab was created in ambulance dispatch spreadsheet (“PROJECTDATA”).

• For each dispatch reason and origin & location, the counts and average ages for males and females were calculated.

• This data was also used to create graphs and charts for better visual representation of its patterns.

Representing Data Visually

• A new tab was created within the ambulance dispatch .xls file.

• Within this tab, pie charts were created for each Origin to Destination and Gender that contained information on the number of people per dispatch reason within that location.

• 40+ pie charts generated.

Pie Chart Examples

Representing Data Visually (Cont’d)

• Next, tables and histograms were created to illustrate the number of males or females per each defined age group that used ambulance services for every dispatch reason.

• Separate histograms were created for males and females and placed next to each other for easier comparison.

Histogram Examples


• Histograms were also created for males and females that represented the average ages for each gender per dispatch for each origin to destination. reason

Histogram Examples


• Lastly, histograms were created that represented overall trends within the ambulance dispatch dataset.

Histogram Examples


As well as completing more than 150 graphs and charts to visually represent data, maps were also created.

Spatially link dispatch data to locations in Western Newfoundland.

Shapefiles downloaded from ESRI.

Point shapefile created that included community names, line shapefile created containing arrows between locations.

Point shapefile was then related to the population spreadsheet so that all community records contained population information for each census bracket, and age category.

Data can be queried.

Map Example

Results

Aging baby boomers in Western Newfoundland are going to have a drastic impact on Western Health ambulance services.

Of all 4000+ records in the ambulance dispatch dataset, 77% were for patients aged 55 and over.

For all but two dispatch reasons in the dataset (Pandemic Surge, Post Dialysis), the mean and median ages for every record were over 55.

More females using ambulance services than males.

Females vs. Males

• On average, females

requiring ambulance services

were older than males.

Females vs. Males (Cont’d)

• Males on average have a wider age range per dispatch reason.

An Unexpected Pattern

• Highest percentage of reasons for dispatch are Convalescence, Specialist Appointment, and Discharge Home.

• Reasons not typically considered emergencies.

• These non-emergency dispatch reasons are costing Western Health $556,839.95 according to the year and a half of data that was provided for this study.

• A large percentage of patients (65.4%) are using ambulance services as a means of being taxied from one location to another rather than transported for urgent medical purposes.

Population Trends

Strong patterns emerged throughout the data that suggested a centralization of Western Newfoundland populations in and around larger centres.

Smaller communities that lie in more rural areas are experiencing a steady decline (sometimes of a -100% population change) in the majority of their age categories while larger, more urban centres such as Corner Brook are experiencing an increase in many age groups.

Western Newfoundland is experiencing a centralization of its people.

Discussion

The influx of elderly people in this portion of the province is going to cause an immense strain on the healthcare system if not properly prepared for.

Another issue that Western Health ambulance dispatch is going to have to deal with is the use of their services as more of a taxi than emergency transport. With the baby boomers aging as they are, the numbers of people using the ambulance system in this way is only going to increase.

With populations clustering in more urban areas, taking into consideration the results of this study could help Western Health better plan placement of ambulance dispatch centres within the district so they are more cost-efficient and timely.

Conclusion

GIS is a tool that can be applied to more fields that just Geography, Forestry, Natural Resources, etc.

In the medical field alone, GIS is being used for mapping the spread of diseases, showing the amount and type of health services that people receive depending on where they live, to assess how well patients are served by doctors and staff at any individual site, evaluating marketing programs, deciding on health service placement, data integration and management.

Pharmaceutical companies find that GIS helps them target physicians most likely to use their product, make more balanced sale territories and routes.

Using GIS for doing statistical analysis on ambulance dispatch data is only the beginning.

Source: GIS in Health Organizations -Laura Lang

“The outlook for GIS in the health disciplines appears unlimited”

Source: GIS in Health Organizations - Laura Lang

Acknowledgements

David Buckle - Regional Director of Paramedicine & Medical Transport

Darin Brooks – GIS Instructor (College of the North Atlantic)

Neala Griffin – GIS Instructor (College of the North Atlantic)

All of the members of the 2010-2011 GIS Applications Specialist program

Questions?

the golden years

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