Sarra A. Nanou

24491 Prospect Avenue, Suite B Loma Linda, CA 92354
Phone: (909)796-1195
Sarra@elender.com

GIS ROLE IN PUBLIC HEALTH

 

ABSTRACT

GIS methodology is used in this project to find a feasible plan to solve a public health tragedy growing worse day by day. Unwed teenage mothers are not getting proper pre-natal care in the County of San Bernardino. This was resulting in a large increase in babies being born with birth defects. The monumental expenses of caring for these babies was surpassed only by the human suffering of these children and there care givers. The task for GIS would fully tax it's capabilities. GIS must pinpoint the area where this care was needed in a county with an area of 19,319 square miles, populated by only 1,591,000 people. This solution must provide that care, financed by extremely limited income from so few people, and cover an area larger than some of our states. GIS would not only perform the task assigned to it, GIS would point to the solution, and provide the presenter of that solution with the tools to attain the funding required. This should firmly entrench GIS as a prominent and permanent part of problem solving in the field of Public Health.

INTRODUCTION

To establish a program to provide the following, to the largest group of unwed teenage mothers, is my goal.

  1. Regular Pre-natal Care Examination.
  2. Clinical Instructions.
  3. Follow-up on compliance.
  4. Registration and Tracking.
  5. Education for motherhood.

The problems uncovered by research, were as follows:

  1. Most pregnant teenagers were of the lower ( under $18,000 a year) socioeconomic group.
  2. The 19,319 square miles county area had little public transportation.
  3. There was no available space in public buildings.
  4. Of the 1,591,000 population there was no centralized base. This was created by recent closures of Norton Airforce Base, Edwards Airforce Base, and other large employers in the County.
  5. The agricultural industry had disappeared rapidly due to the demands for residential housing for rapidly expanding growth in adjacent Los Angeles County. This created a group of bedroom communities with isolated pockets of unemployed or lower income families.
  6. An all ready over burdened county budget had created a void of information that could be used to solve the problems.
  7. The construction of new buildings was cost prohibitive.
  8. Their was no transportation for these teenagers.
  9. The price for medical staffing was astronomic.

And there are special problems faced by these unwed teenagers facing motherhood.

  1. They were to shy to go to a doctor, especially males.
  2. Because of their long involvement in the educational field, most doctors were not conversant with "street" problems, and this placed them as a part of the "establishment".
  3. Children are self-centered and teenagers are children. They do not want to be seen by strangers in their "fat and ugly" condition and want to stay in their neignborhood where they feel comfortable.
  4. The "gang" problem of crossing boundary lines of rival gangs creates danger for these mothers-to-be. Upon recognizing these problems the only approach was to follow the humorous advice of " you eat an elephant one bite a time." GIS was to take the first bite and it was a big ones and as it would also serve to point to the solution of all of the problems.

 

We would use GIS ArcView version 2.1.

The following data would be utilized:

  1. Zipcodes would be our geographical divisions of the county.
  2. Census data would provide projection, location of lower SES (Socioeconomic group under $ 18,000 annual income) and probable residence of females under 18.
  3. Data from the County of San Bernardino, Department of Public Health available for 1994 that listed pregnant mothers as they registered during their clinic visits in three trimesters.

The GIS capablities employed were as follows:

  1. Select by theme (within) California zipcode map the map for San Bernardino County zipcode layer.
  2. Link tables of San Bernardino group blocks map, which contain low SES (annual average income <$ 18,000.00), and females with San Bernardino County blocks map, which contain teen age population group (i.e. age < 18 years). This layer consist of joint data from both maps for female, less than eighteen years of age, and have average annual income less than $18,000.00.
  3. Create a layer using the data obtained from the Public Health Information System at California Departmen of Public Health Services, and join attribute table of zipcode map of San Bernardino Counnty with source table of the data obtained from the aforesaid department to create a new layer that contain only the trimesters of the data for all registered pregnant mothers in 1994 at San Bernardino County as well as the mmothers that have no prenatal care or who have unknown follow-up information.
  4. The zipcode and registered mothers joined file is converted to the shape file as polygon (area).
  5. Add event theme by address matching to the theme edited for the post office addresses obtained from hazmat file, so that it can be used as a point legend to represent the health care provider point location feature.
  6. Use the layer in step two and step four and then create a layer for base map used to filter the data for both layers ( i.e. zipcodes for the data joined with for the third trimester mothers and the layer for low SES females joined with the teem age of less than 18 years of age.
  7. Add the point theme created in step 6 to the layer in step 5.
  8. Use the layer created in step 6 to edit legends for the data of the second and the first trimester teen age mothers without repeating steps 1 to 5.
  9. Create a graphic grid map for the whole San Bernardino County in scale that represent real world scale of 1.5 mile cel size grid. But this is not possible, because to transfer this grid map to GIS grid map is not convertable, and also to create a grid map through ArcInfo is not possible too, due to insufficient ArcInfo related grid map creating coverage. Creating these four layers using joint tables, select by theme, and hot link, edit legends and display, and loxking, we obtained San Bernardino zipcodes geographical units colored with attributes for the number of visits of the teenage pregnant mothers registered in their third trimester. Then this was used as a reference hot spot map for editing other legends of the first and second trimesters.
  10. Mobile Medical Units Stops are programmed by using the following data:

In delineating the hot spots, that represent low SES, female pregnant teenage mothers and within polygons generated by same color zipcodes for the specific number of mothers in need for prenatal care by using zipcodes as the spatial pattern results where the mobile clinic stops can determine the high prevalence of teenage mothers location that need prenatal care.

RESULTS

GIS took that information, sparse as it was, and led me to the problem solution.

The County of San Bernardino has 24 incorporated cities with only 4 of them with population over 100,000. The largest is San Bernardino with only 185,000. Of the 1,591,000 inhabitants only 285,000 are in unincorporated areas. All this is spread over the almost 20,000 square miles.

Without transportation to the clinic the solution was to take the clinic to them. "MOBILE MEDICAL CLINICS FOR PRENATAL CARE". The average person will walk about ¾ of a mile without too much complaint. Therefore, GIS would use 1.5 mile diameter circles around the hot spots to locate the stops for the mobile units.

Instead of creating other problems this solved more problems than have previously been mentioned. Doctors don't make "House Calls". But teen age girls don't like doctors anyway. Therefore, solve that problem and the medical staffing expense by utilizing MID-WIVES. My previous experience in the use of TELEMEDICINE as a communication tool would provide the assistance of doctor when required.

The presentation developed through the utilization of GIS would be the "sales tool" to obtain funding by pointing up the savings realized by reducing birth defects. Although human suffering, and reducing it, is my personal goal, the economic factor must be faced and conquered and GIS allowed me that success.

DISCUSSION

At the zipcode location of any stop of the Mobile Health Clinic the midwives will examin and refer the patients to the medical center located within that zipcode. The follow-up schedule of the stops is within a cell size of one and a half mile of grid map. By doing this no one will have to walk more than ¾ a mile distance since most of these people can not afford transportation and would not get this service.

RECOMMENDATION

My recommendation is that San Bernardino County Public Health Department should investigate the prenatal care available for the lower SES mothers and provide funds for this project. Mobile clinics will be as an outreach plan for them. By setting schedules in high schools throughout the County, the information will be provided to the pregnant teenage mothers and available to those who might become that way.

CONCLUSION

In delineating hot spots by using these zipcodes we can determine the high prevalence of teenage mothers that need prenatal care. This service will reduce the incidence of birth defects and provide proper neonatal care. This will eliminate the excess medical expenses of maintaining the health of these children. It will reduce health providers financial burden to care for babies with birth defects. Unless we recognize and correct these problems in this manner, the tragedy and human suffering will continue as will medical expenses which will continue to rise.

 

REFERENCES

 

Sarra A. Nanou

24491 Prospect Avenue, Suite B Loma Linda, CA 92354

Phone: (909)796-1195

Sarra@elender.com