An analysis of the demand for a hemodialysis facility in the Ponca City, Oklahoma, medical service area

              An Analysis of the Demand
for a Hemodialysis Facility in the
Ponca City, Oklahoma, Medical Service Area
Photo: www.renalmanagement.com
Oklahoma Cooperative Extension Service
Rural Development
Oklahoma State University
Oklahoma Office of Rural Health
Rural Health Policy & Research Center
Oklahoma State University
December 2009
AE-09132
An Analysis of the Demand for a Hemodialysis Facility
in the Ponca City, Oklahoma, Medical Service Area
Lara Brooks- Assistant State Extension Specialist, OSU, Stillwater
405-744-4857; FAX 405-744-9835
Fred C. Eilrich - Assistant State Extension Specialist, OSU, Stillwater
405-744-6083
Brian Whitacre - Extension Economist, OSU, Stillwater
405-744-9825
Stan Ralstin - District Rural Development Specialist, OSU, Enid
580-237-7677
Larry Klumpp - Kay County Extension Director, OSU, Newkirk
580-362-3194
Val Schott - Director, Oklahoma Office of Rural Health, Oklahoma City
405-842-3101
Oklahoma Cooperative Extension Service
Rural Development
Oklahoma State University
Oklahoma Office of Rural Health
Rural Health Policy & Research Center
Oklahoma State University
December 2009
1
An Analysis of the Demand for a Hemodialysis Facility
in the Ponca City, Oklahoma, Medical Service Area
This report will examine the need for a hemodialysis facility in the Ponca City,
Oklahoma medical service area. This report briefly describes the process decision makers can
utilize to help determine the demand for a hemodialysis facility. Specifically, the study will:
1. Determine the medical service area and population;
2. Estimate the number of potential patients in the medical service area; and
3. Estimate the number of dialysis stations for a hemodialysis facility in the medical
service area.
No recommendations will be made. The information included in this report is designed to assist
local decision-makers in assessing the need and potential for a hemodialysis facility.
Introduction
The need for hemodialysis (commonly referred to as kidney dialysis) treatment continues
to increase. One of the most common causes of kidney failure is diabetes. The latest report by
the American Diabetes Association (2008) shows that among adults, diabetes increased in both
men and women and in all age groups, but still disproportionately affects the elderly. Over 23
percent of the population 60 years and older had diabetes in 2007. The aging “Baby Boomer”
population continues to impact the need for hemodialysis treatments. Furthermore, race and
ethnicity remains an influential determinant in diabetes prevalence. After adjusting data from a
2004 -2006 national survey for population age differences, the rate of diagnosed diabetes was
highest among American Indians and Alaska Natives (16.5 percent). This was followed by
African Americans (11.8 percent) and Hispanics (10.4 percent), which includes rates for Puerto
2
Ricans (12.6 percent), Mexican Americans (11.9 percent), and Cubans (8.2 percent). By
comparison, the rate for Asian Americans was 7.5 percent, with Whites at 6.6 percent.
With this increased need for treatment facilities, hospital administrators could be
considering the option of adding a kidney dialysis treatment unit to their current facilities or
community leaders might be exploring the possibilities of a center in their area. The Center for
Medicare and Medicaid (CMS) identify four types of dialysis facilities or units: 1) Renal
Transplantation Center; 2) Renal Dialysis Center; 3) Renal Dialysis facility (free-standing); and
4) Self Dialysis Unit. In the short term, a kidney dialysis unit will require a significant financial
investment. Over the longer term (3 years or more), a dialysis unit could provide a much needed
service to the residents and could prove to be a cost effective service for the hospital or the
community.
Rural hospitals, in particular, are looking for cost effective or “profit generating” medical
services that will fill the need in the community as well as assist with the financial stability of the
hospital. Rural leaders, including hospital administrators, will need to take a serious look at the
potential market for dialysis patients; the most critical criteria for success of a center being
patient participation.
Hemodialysis units provide medical treatment for end-stage renal disease (ESRD) caused
primarily by the chronic diseases of diabetes and/or hypertension (high blood pressure). The
need for hemodialysis units is increasing as people live longer and more people develop the
diseases that lead to kidney (renal) failure. Also, improvements in dialysis technologies, care,
and related drugs enable dialysis patients to live longer on dialysis. The increased number of
patients requiring hemodialysis has placed an increased demand on urban and rural communities
to provide hemodialysis units that are within a one-hour drive to the patient’s home. According
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to the 2009 USRDS Annual Data Report, the number of dialysis units nationwide grew by 18
percent between 2002 and 2007. Nearly 60 percent of patients were treated in units owned by
one of the four largest dialysis organizations. In 2007, hospital-based and independently owned
units accounted for 15.4 percent and 17.6 percent of all units, respectively.
Rural hemodialysis units provide the patient with needed services that are easily
accessible with minimal travel time. Preferably a family member or a friend drives the
hemodialysis patient to and from the treatment facility, especially if the facility is a significant
distance from the patient’s residence. However it is not uncommon for the patient to transport
him/herself because treatments are so frequent. If the patient is driven, the driver waits at the
facility while the patient receives treatment (which takes approximately 4-5 hours) then drives
the patient home. In instances of bad weather, the travel to and from the treatment unit may take
more time and be more stressful to both the patient and/or the driver. For the patient who needs
hemodialysis yet does not live within easy commuting distance of a treatment unit, the only
option may be to move to a community that has a unit. This means the patient may incur
additional expense in relocating and may no longer have a social support system available to
him/her in the local community. It also adds to current problem of decreasing population
numbers experienced by numerous rural communities.
The information provided in this study is a starting point for the hospital administrator,
board members, or potential investor to use in determining whether their community can support
this medical service. It should be combined with information on the costs of installing and
running a hemodialysis facility to determine whether implementation is feasible.
Several national and local providers of dialysis services are available to partner with local
communities, hospitals, physicians, and investors to develop and operate a dialysis facility. A
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hemodialysis facility can enter into a management contract or joint venture arrangement with
many of the regional or national corporations involved in the business of providing hemodialysis
services. Looking further into these contracts and the associated costs is a logical next step for
communities/hospitals, who feel they have sufficient demand to support a hemodialysis center.
The management contract could provide the facility with 1) consultation services from a clinical
nutritionist and a social worker; 2) in-service training programs for staff; 3) computer programs
for clinical documentation of services, billing and collections, and laboratory work; 4)
purchasing or leasing capacity for equipment; 5) purchasing capacity for expendable supplies;
and 6) quality assurance procedures for documentation to CMS. Purchasing equipment and
supplies as part of a corporate group would enable the center to obtain these items at less cost.
Corporate groups also have the capacity of doing their own market feasibility study. Under a
joint venture arrangement, the corporate partner also shares in development expenses, capital
expenditures, start-up and ongoing working capital requirements, and operating expenses.
The End Stage Renal Disease (ESRD) Program was established in 1972 by federal
legislation that extended Medicare coverage to almost all individuals with ESRD who require
either dialysis or transplantation to sustain life. There are currently eighteen ESRD Networks
who provide information on the Medicare-approved hemodialysis and transplant centers
functioning in their region (ESRD Networks, 2009). The United States Renal Data System
(USRDS) is a national data system that collects, analyzes, and distributes information about
ESRD from the ESRD Networks. The USRDS defines dialysis patients as either prevalent or
incident. A prevalent patient is a one who is currently receiving renal replacement therapy or
having a functioning kidney transplant (regardless of when the transplant was performed), or the
number of people on hemodialysis at a given time. An incident patient is one who is starting
5
renal replacement therapy for end stage renal disease during the calendar year or the new patients
starting hemodialysis during a calendar year. Both definitions (prevalence or incidence) exclude
persons with acute renal failure, persons with chronic renal failure who die before receiving
treatment for ESRD, and persons whose ESRD treatments are not reported through CMS. Data
on prevalent and incident patients is available at the national, state, and county level from the
USRDS website (www.usrds.org) from the Renal Data and Extraction Reference (RenDER)
database.
The monetary proportion of Medicare devoted to ESRD treatments has remained fairly
constant around 6-6.5 percent since 2000; this is due to both expenditures increasing at a similar
rate (USRDS 2009 Annual Data Report). Total expenditures reached $24 billion in 2007 or 5.8
percent of the Medicare budget. While it appears that ESRD expenditures experienced a
significant decrease in 2007, Part D prescription costs are included in the Medicare budget, but
not for ESRD patients. Therefore, once these costs are included, it is most likely the impact will
be much larger on the Medicare budget. Medicare begins to pay for hemodialysis after the
patient has been receiving treatments for 90 days. Hemodialysis treatments covered by Medicare
totaled nearly $17.6 billion in 2007 (USRDS 2009 Annual Data Report). If the patient has health
care coverage, it will pay for treatments for the period of time identified in the policy, and then
the patient will apply for Medicare. If the patient does not have any other coverage and is unable
to pay for treatment, the hemodialysis facility absorbs the cost for three months until the patient
qualifies for Medicare. Most new patients on hemodialysis do not have any other health care
coverage.
The total number of reported patients receiving ESRD therapy on December 31, 2007
was 527,283; a 2.3 percent increase over the previous year. Among the prevalent patients,
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368,544 or nearly 70 percent were undergoing dialysis. The number of new patients totaled
around 110,000, nearly the same as 2006. The racial and ethnic disparities in ESRD persist, with
2007 rates in African American and Native American populations being 3.7 and 1.8 times greater
than the rate among Whites; and the rate in the Hispanic population being 1.5 times greater than
rates for non-Hispanics.
Medical Service Area
Estimating potential patient participation in a hemodialysis unit requires defining the
service area for the unit, identifying the population of the service area and calculating the
prevalence and incidence rates for different age and racial groups. Figure 1 shows the proposed
medical service area with the surrounding hemodialysis facilities according to the latest
Oklahoma Medical Facilities Directory (November, 2009) obtained from the Oklahoma State
Department of Health website (www.health.ok.us) and Kansas hemodialysis facilities according
to the Kansas State Department of Health and Environment website (www.kdheks.gov). The
proposed service area for the Ponca City hemodialysis facility is derived by considering the
relative travel distances to the alternative centers. The proposed medical service area includes all
of the zip codes shown in Table 1. Table 1 presents the 2000 census estimates and 2000
estimates from ESRI (a different data source) for comparison purposes. Zip code delineations
are arbitrary and change frequently resulting in slight differences between the two estimates. Zip
Code data is not available from the U.S. Census for 2009. Therefore, population from the 2009
ESRI estimates will be utilized in estimating number of patients and stations. The 2009 ESRI
estimated population of the medical service area is 70,756. As is common in this part of the
country, the service area decreased in population since 2000. The largest population in the
medical service area is Ponca City with a combined population of 32,843 people (zip codes
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74601 and 74604). The zip code for Arkansas City KS, 67005 is the next largest zip code area
with 15,273. The total population by race and age for the proposed service area is given in
Table 2 and Table 3, respectively.
Tables 4 and 5 present the total prevalence and incindence data for the state of
Oklahoma and the three Oklahoma counties (Kay, Noble, and Osage) along with the state of
Kansas and the three Kansas counties (Chatauqua, Cowley, and Sumner) included in the service
area. Data is also presented by race and age for both Oklahoma and Kansas. Note that at the
county level, data is not reported by USRDS if fewer than 11 patients exist. In Table 4,
Chatauqua County reported fewer than 11 patients for all three years displayed; therefore, there
is no data for this particular county. The same is true in Table 5 for Noble County, Chatauqua
County, and Sumner County when incident patients are displayed.
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Figure 1. Proposed Service Area
Ponca City Proposed Service Area for
Hemodialysis Facility
SOURCE: Oklahoma State Department of Health, Kansas Department of Health and
Environment, Bureau of Child Care and Health Facilities
Proposed Hemodialysis Service Area
Location of Existing Hemodialysis Units
1. Renal Care Group-Enid, OK
2. FMC Stillwater Dialysis Center- Stillwater, OK
Stillwater Dialysis Center- Stillwater, OK
3. Renal Care Group-Ponca City, OK
4. Winnfield Dialysis Center- Winnfield, KS
5. Renal Treatment Centers- Derby, KS
6. East Wichita Dialysis Center- Wichita, KS
NE Wichita Dialysis Center- Wichita, KS
Renal Care Group- Wichita, KS
Renal Care Group (East)- Wichita, KS
Renal Care Group (West)- Wichita, KS
Wichita Dialysis Center- Wichita, KS
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Table 1
Population of Proposed Service Area
Zip Code Area 2000 Census 2000 ESRI 2009 ESRI
74630 Billings 770 848 774
74651 Red Rock 713 717 730
74644 Marland 635 571 582
74650 Ralston 732 685 660
74637 Fairfax 2,063 2,138 2,017
74604 Ponca City 13,295 13,246 13,109
74601 Ponca City 20,400 20,532 19,734
74631 Blackwell 8,378 8,355 7,995
74646 Nardin 255 221 227
74636 Deer Creek 303 256 236
74632 Braman 605 602 606
74647 Newkirk 3,731 3,710 3,614
74652 Shidler 1,076 995 997
74633 Burbank 424 521 520
74641 Kaw City 555 551 534
67140 South Haven 894 870 819
67051 Geuda Springs 485 496 471
67005 Arkansas City 16,256 16,238 15,273
67038 Dexter 676 651 669
67102 Maple City 45 52 53
67024 Cedar Vale 1,082 1,229 1,136
TOTAL 73,373 73,484 70,756
SOURCE: U.S. Census Bureau, 2000 Census Data, ESRI 2009 Community Sourcebook of Zip
Code Demographics, 22nd ed., ESRI Business Solutions
10
Table 2
Population by Race for Proposed Service Area
Age Census 2000 ESRI 2000 % of
Total
ESRI 2009 % of
Total
White 62,247 62,334 84.8 60,130 83.7
A. American 1,527 1,530 2.1 1,348 1.9
N. American 7,615 7,635 10.4 8,374 11.7
Other 1,984 1,985 2.7 2,018 2.8
Total 73,373 73,484 71,871
SOURCE: U.S. Census Bureau, 2000 Census Data, ESRI 2009 Community Sourcebook of Zip
Code Demographics, 22nd ed., ESRI Business Solutions
Table 3
Population by Age for Proposed Service Area
Age Census 2000 ESRI 2000 % of
Total
ESRI 2009 % of
Total
0-19 21,520 21,548 29.3 21,386 29.8
20-44 22,175 22,216 30.2 21,484 29.9
45-64 17,178 17,207 23.4 16,439 22.9
65-74 6,273 6,279 8.5 6,213 8.6
75+ 6,227 6,233 8.5 6,348 8.8
Total 73,373 73,484 71,871
SOURCE: U.S. Census Bureau, 2000 Census Data, ESRI 2009 Community Sourcebook of Zip
Code Demographics, 22nd ed., ESRI Business Solutions
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Table 4
Prevalence1 of Hemodialysis Patients for the State of Oklahoma with Kay, Noble, and
Osage Counties and the State of Kansas with Chatauqua, Cowley and Sumner Counties
2005 2006 2007
Total
State of Oklahoma 3,195 3,317 3,513
Kay County 37 48 51
Noble County 15 13 11
Osage County 25 31 29
State of Kansas 2,049 2,139 2,209
Chatauqua County * * *
Cowley County 22 27 25
Sumner County 19 19 16
Race (Oklahoma)
White 1,764 1,872 1,980
African American 775 794 839
Native American 583 586 630
Other 73 65 64
Age (Oklahoma)
0-19 15 15 14
20-44 488 491 519
45-64 1,373 1,424 1,525
65-74 724 759 804
75+ 595 628 651
Race (Kansas)
White 1,419 1,482 1,525
African American 546 572 593
Native American 34 35 35
Other 50 50 56
Age (Kansas)
0-19 7* 5* 8*
20-44 271 273 281
45-64 800 843 872
65-74 460 496 509
75+ 506 522 538
SOURCE: The data reported here have been supplied by the United States Renal Data System (USRDS). The
interpretation and reporting of these data are the responsibility of the author(s) and in no way should be seen as an
official policy or interpretation of the U.S. Government.
1Prevalent patient - A patient receiving renal replacement therapy or having a functioning kidney transplant
(regardless of when the transplant was performed.)
*If less than 11 patients, data is not reported; number included in total count for all years. The numbers have been
supplied based upon secondary data from RenDER.
N/A- Data Not Available
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Table 5
Incidence1 of Hemodialysis Patients for the State of Oklahoma with Kay, Noble, and Osage
Counties and the State of Kansas with Chatauqua, Cowley and Sumner Counties
2005 2006 2007
Total
State of Oklahoma 1,035 1,079 1,133
Kay County 10 17 11
Noble County * * *
Osage County * 12 *
State of Kansas 675 709 683
Chatauqua County N/A N/A *
Cowley County * 11 *
Sumner County * * *
Race (Oklahoma)
White 690 717 735
African American 168 192 194
Native American 166 158 188
Other 11* 12* 16*
Age (Oklahoma)
0-19 5* 4* 6*
20-44 129 118 144
45-64 399 405 459
65-74 255 289 264
75+ 247 263 260
Race (Kansas)
White 525 538 529
African American 132 151 134
Native American * * 11
Other * * 9*
Age (Kansas)
0-19 7* 5* 6*
20-44 75 61 66
45-64 227 249 250
65-74 157 191 157
75+ 209 203 204
SOURCE: The data reported here have been supplied by the United States Renal Data System (USRDS). The
interpretation and reporting of these data are the responsibility of the author(s) and in no way should be seen as an
official policy or interpretation of the U.S. Government.
1Incident patient - A patient starting renal replacement therapy for end-stage renal disease during the calendar year.
*If less than 11 patients, data is not reported; number included in total count for all years. The numbers have been
supplied based upon secondary data from RenDER.
N/A- Data Not Available
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Estimating Patient Participation
The number of patients receiving hemodialysis changes during the year due to deaths of
existing patients and the addition of new patients. Estimating potential patient participation in a
hemodialysis facility requires calculating the prevalence and incidence rates for different age and
racial groups. Coefficients have been calculated for Oklahoma and Kansas that indicate the
number of hemodialysis patients per 100,000 population for both prevalence and incidence for
each state. The coefficients are the latest available based on the 2007 data from the RenDER
database. The number of projected hemodialysis patients is estimated by multiplying these
coefficients with a service area’s population.
The coefficients allow for prediction of patients by three methods: (1) population by race;
(2) population by age; and (3) total population. The prevalence coefficients calculate the number
of current hemodialysis patients. Table 6 shows the coefficient for each of the three methods,
along with prevalent predictions by race, age, and total population for the Ponca City proposed
medical service area.
Similarily, incidence coefficients for age, race, or total population are used to calculate
the number of new patients (rounded to the nearest person) that will receive treatment without
Medicare reimbursement for the first three months. Table 7 shows these coefficients along with
the incidence predictions by race, age, and total population for the Ponca City proposed medical
service area. Again, these coefficients are based on the latest available information. Populations
are taken from 2009 ESRI zip code data.
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Table 6
Estimated Number of Current (Prevalent) Hemodialysis Patients
for the Proposed Service Area
2009 ESRI
Oklahoma
Population
2009 ESRI
Kansas
Population
Oklahoma
Coefficients1
Kansas
Coefficients1
Estimated
Oklahoma
Current Patients
Estimated
Kansas
Current
Patients
Total
Oklahoma
and Kansas
Patients
Race
White 42,560 17,570 72.9 64.0 31.0 11.2 42.2
African
American
726 622 318.4 378.0 2.3 2.4 4.7
Native
American
7,507 867 260.4 157.7 19.6 1.4 21.0
Other 1,542 477 16.7 25.3 0.3 0.1 0.4
Total 52,335 19,536 53.2 15.1 68.3
Age
0-19 15,577 5,807 1.4 1.0 0.2 0.1 0.3
20-44 15,600 5,885 42.6 30.0 6.6 1.8 8.4
45-64 11,938 4,502 168.4 124.1 20.1 5.6 25.7
65-74 4,598 1,615 317.5 291.2 14.6 4.7 19.3
75+ 4,622 1,727 286.2 289.0 13.2 5.0 18.2
Total 52,335 19,536 54.7 17.2 71.9
Total
Population
Service Area 52,335 19,536 97.4 79.5 51.0 15.5 66.5
SOURCE: ESRI 2009 Community Sourcebook of Zip Code Demographics, 22nd ed., ESRI Business Solutions, United States Renal System Renal Data
Extraction and Reference (RenDER)
1Coefficients based on 2009 ESRI estimated population and 2007 RenDER data represent the number of current (prevalent) hemodialysis patients per 100,000
population.
The data reported here have been supplied by the United States Renal Data System (USRDS). The interpretation and reporting of these data are the responsibility
of the author(s) and in no way should be seen as an official policy or interpretation of the U.S. Government.
15
Table 7
Estimated Number of New (Incident) Hemodialysis Patients
for the Proposed Service Area
2009 ESRI
Oklahoma
Population
2009 ESRI
Kansas
Population
Oklahoma
Coefficients1
Kansas
Coefficients1
Estimated
Oklahoma New
Patients
Estimated
Kansas New
Patients
Total Kansas
and Oklahoma
Patients
Race
White 42,560 17,570 27.1 22.2 11.5 3.9 15.4
African
American
726 622 73.6 85.4 0.5 0.5 1.0
Native
American
7,507 867 77.7 49.6 5.8 0.4 6.2
Other 1,542 477 4.2 4.1 0.1 0.0 0.1
Total 52,335 19,536 17.9 4.8 22.7
Age
0-19 15,577 5,807 0.6 0.8 0.1 0.0 0.1
20-44 15,600 5,885 11.8 7.0 1.8 0.4 2.2
45-64 11,938 4,502 50.7 35.6 6.1 1.6 7.7
65-74 4,598 1,615 104.3 89.8 4.8 1.5 6.3
75+ 4,622 1,727 114.3 109.6 5.3 1.9 7.2
Total 52,335 19,536 18.1 5.4 23.5
Total
Population
Service Area 52,335 19,536 31.4 24.6 16.4 4.8 21.2
SOURCE: ESRI 2009 Community Sourcebook of Zip Code Demographics, 22nd ed., ESRI Business Solutions, United States Renal System Renal Data
Extraction and Reference (RenDER)
1Coefficients based on 2009 ESRI estimated population and 2007 RenDER data represent the number of current (prevalent) hemodialysis patients per 100,000
population.
The data reported here have been supplied by the United States Renal Data System (USRDS). The interpretation and reporting of these data are the responsibility
of the author(s) and in no way should be seen as an official policy or interpretation of the U.S. Government.
16
Estimating Number of Dialysis Stations
Table 6 suggests that between 67 and 72 prevalent patients exist in the proposed service
area, while Table 7 indicates that an additional 21-24 incident patients are in the area. This
implies a range of 88-96 patients in total. In the analysis that follows, 90 patients (68 prevalent,
22 incident) is used to determine the number of dialysis stations needed.
Table 8 estimates the number of stations, annual treatments, and potential maximum
expansion for the proposed service area including both the Oklahoma service area and Kansas
service area. Table 9 estimates the number of stations, annual treatments, and potential
maximum expansion for the Oklahoma service area only. Since there is an existing facility in
Ponca City, Table 10 takes the Oklahoma service area and removes 52 patients that are possibly
already receiving treatment at the existing facility. Each of the options presents variations in the
number of stations and staffing levels. The total cost per station decreases as the number of
stations increase. However, due to the significant capital investment, decision makers will have
to investigate the best alternative mix of stations and staffing. This report presents several
alternatives that can be considered to provide the necessary treatments for the proposed medical
service area. The alternatives range from a three day per week treatment option with two
treatments per day to six days per week with three daily treatments. The first column (of Table
8) presented allows for 2 daily treatments three days a week. This would require a total of 45
stations to meet the demand of the 90 estimated patients, resulting in total annual treatments of
14,040. This scenario would allow for expansion to 90 patients with current staffing for the 45
stations. The numbers at the bottom of the table represent the maximum capacity for 45 stations
if staffing allowed for three daily treatments, six days a week. The maximum expansion capacity
would be 270 patients or 42,120 annual treatments. Three other options for staffing versus
17
number of stations are provided. As the analysis shows, anywhere from 15 to 45 actual stations
could be used to service the needs of the proposed service area.
Table 9 reduces the medical service area to only Oklahoma counties, due to the relative
proximity of the Winnfield center for Kansas residents (Figure 1). This table suggests that 35
stations running 2 daily treatments three days per week would be required to meet the needs of
the Oklahoma service area. If a center were to run 6 days a week, 3 treatments per day, then
only 12 stations would be able to satisfy the area demand.
Table 10 estimates the number of stations with only the Oklahoma service area, and
current patients of the existing facility have been taken in consideration. Therefore, this table
estimates that a center running 2 daily treatments three days a week would require 9 stations to
meet the demand of the 18 patients with 2,808 annual treatments. The 18 patients is found from
subtracting the total Oklahoma service area from the estimated 52 current patients of the existing
facility. It is estimated that the current facility currently has 12 units, and they are operating 6
days a week with three rotations on MWF and two rotations on TRS. With that taken in
consideration, the maximum capacity for column one, 9 stations would be 54 patients or 8,424
annual treatments. Three other options for staffing and number of stations are provided. With
this particular service area and the presence of another facility, the range of stations is 3-9.
To determine the best solution for the number of stations in a hemodialysis unit, local
decision makers will need to consider the capital investment of equipment and building space for
additional stations versus the annual operating cost for the additional staffing needed to provide
services for more patients with fewer stations.
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Table 8
Estimating Number of Stations and Annual Treatments
for the Proposed Service Area
3-day
week
2 x/day
3-day
week
3 x/day
6-day
week
3&1
x/day
6-day
week
3 x/day
Number of Stations
A. Number of current patients estimated from coefficients 68 68 68 68
B. Expected number of new patients estimated from coefficients 22 22 22 22
C. Total estimated number of patients (A + B) 90 90 90 90
D. Number of daily treatments per M.W.F. rotation per station 2 3 3 3
E. Number of daily treatments per T.Th.Sat. rotation per station 0 0 1 3
F. Total Number of daily treatments for all rotations (D + E) 2 3 4 6
G. Number of stations required (C/F) 45 30 22.5 15
H. Actual number of stations (round up to whole number) 45 30 23 15
Number of annual treatments
I. Number of annual treatments from prevalent patients
(A x 3 x 52) 10,608 10,608 10,608 10,608
J. Number of annual treatments from new patients (B x 3 x 52) 3,432 3,432 3,432 936
K. Total number of annual treatments (I + J) 14,040 14,040 14,040 14,040
L. Maximum number of patients based on current staffing
(H x F) 90 90 92 90
M. Maximum number of annual treatments based on current
staffing (L x 3 x 52) 14,040 14,040 14,352 14,040
Maximum Capacity based on number of Stations w/ 6-day week, 3X/day
Actual Number of Stations 45 30 23 15
Total Patients 270 180 138 90
Total Annual Treatments 42,120 28,080 21,528 14,040
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Table 9
Estimating Number of Stations and Annual Treatments
for the Proposed Service Area, Oklahoma Only
3-day
week
2 x/day
3-day
week
3 x/day
6-day
week
3&1
x/day
6-day
week
3 x/day
Number of Stations
A. Number of current patients estimated from coefficients 53 53 53 53
B. Expected number of new patients estimated from coefficients 17 17 17 17
C. Total estimated number of patients (A + B) 70 70 70 70
D. Number of daily treatments per M.W.F. rotation per station 2 3 3 3
E. Number of daily treatments per T.Th.Sat. rotation per station 0 0 1 3
F. Total Number of daily treatments for all rotations (D + E) 2 3 4 6
G. Number of stations required (C/F) 35 23.3 17.5 11.6
H. Actual number of stations (round up to whole number) 35 23 18 12
Number of annual treatments
I. Number of annual treatments from prevalent patients
(A x 3 x 52) 8,268 8,268 8,268 8,268
J. Number of annual treatments from new patients (B x 3 x 52) 2,652 2,652 2,652 2,652
K. Total number of annual treatments (I + J) 10,920 10,920 10,920 10,920
L. Maximum number of patients based on current staffing
(H x F) 70 69 72 72
M. Maximum number of annual treatments based on current
staffing (L x 3 x 52) 10,920 10,764 11,232 11,232
Maximum Capacity based on number of Stations w/ 6-day week, 3X/day
Actual Number of Stations 35 23 18 12
Total Patients 210 138 108 72
Total Annual Treatments 32,760 21,528 16,848 11,232
20
Table 10
Estimating Number of Stations and Annual Treatments
for the Proposed Service Area, Oklahoma Only with Consideration of Existing Facility
3-day
week
2 x/day
3-day
week
3 x/day
6-day
week
3&1
x/day
6-day
week
3 x/day
Number of Stations
A. Number of current patients estimated from coefficients 53 53 53 53
B. Expected number of new patients estimated from coefficients 17 17 17 17
Total estimated number of patients (A + B) 70 70 70 70
Minus Existing Facility Patients -52 52 52 52
C. New Total 18 18 18 18
D. Number of daily treatments per M.W.F. rotation per station 2 3 3 3
E. Number of daily treatments per T.Th.Sat. rotation per station 0 0 1 3
F. Total Number of daily treatments for all rotations (D + E) 2 3 4 6
G. Number of stations required (C/F) 9 6 4.5 3
H. Actual number of stations (round up to whole number) 9 6 5 3
Number of annual treatments
I. Total number of annual treatments (C*3*52) 2,808 2,808 2,808 2,808
J. Maximum number of patients based on current staffing
(H x F) 18 18 20 18
K. Maximum number of annual treatments based on current
staffing (J x 3 x 52) 2,808 2,808 3,120 2,808
Maximum Capacity based on number of Stations w/ 6-day week, 3X/day
Actual Number of Stations 9 6 5 3
Total Patients 54 36 30 18
Total Annual Treatments 8,424 5,616 4,680 2,808
21
Summary
Many assumptions have been made in the preceding analysis. These include items that may
change such as the population of the service area or service area delineation. For example, the
service area depicted here may change due to the exit or entry of dialysis facilities. Should this
occur, revised estimates of hemodialysis patients and stations should be made.
This analysis identifies the potential demand for hemodialysis in the Ponca City service
area. The largest number of patients is prevalent patients. These patients are already receiving
treatment at a hemodialysis facility, possibly one displayed in the previous map. The likelihood of
the prevalent patients switching to Ponca City to receive treatment is unknown, and should be
evaluated in lieu of simply assuming the patients will use a Ponca City-based facility. It should also
be noted that there is an existing facility in Ponca City. Therefore, one should consider the number
of established patients at the existing facility, and they should be removed from the potential
demand scenario.
In order to fully investigate the feasibility of a dialysis center, the costs allocated with
opening and operating must be compared to the anticipated revenue it will bring in. This report has
focused on the potential number of users and stations for a dialysis center in Ponca City, OK. The
next step in this process would be to determine how costly setting up such a center would be; not
only for equipment and space, but in terms of personnel as well. Contacting a provider in this
industry should provide answers to many of the associated questions.
Hemodialysis stations can be very costly to start up and staff. Therefore, all assumptions
should be closely examined by local decision-makers to verify that they reflect local conditions.
Local data should be included when available. If further analysis is needed, please contact the
authors on the cover page or your county extension office listed on the cover page of this document.
22
References
American Diabetes Association, Diabetes 4-1-1 Facts, Figures and Statistics at a Glance,
www.diabetes.org.
ESRI 2008 Community Sourcebook of Zip Code Demographics, 22nd ed., ESRI Business
Solutions.
Lawler, MK, & Doeksen, GA. (2002). Guidebook Estimating the Economic Viability of a
Hemodialysis Center. Stillwater, OK: Oklahoma State University.
United States Renal Data System. USRDS 2009 Annual Data Report: Atlas of End Stage Renal
Disease in the United States. National Institutes of Health, National Institute of Diabetes
and Digestive and Kidney Diseases, Bethesda, MD. 2009.
United States Renal Data System. www.usrds.org (accessed November 2009).