Onsite Medical Clinic Feasibility Study

An Analysis Prepared for

Escambia County School District

Presented By:

November 2011

TABLE OF CONTENTS

Executive Summary ............................................................................... 1

Data and Assumptions ........................................................................... 4

The Cost of Operating a Clinic ............................................................... 6

Potential Claim Savings ........................................................................ 11

Wellness and Disease Management Opportunities ....................... 15

Other Considerations........................................................................... 18

Appendices

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1. Executive Summary

The Escambia County School District (“the District”) engaged Gallagher Benefit Services (“GBS”) to

conduct a study of the feasibility of operating one or more primary care medical clinics for the benefit of

employees, retirees, and their eligible dependents covered under the District’s health insurance plan.

The plan is self-funded and is administered by United Healthcare (“UHC”). There are currently over

5,500 employees and 8,800 total members covered under the plan, and annual claim costs under the

plan are approximately $40 million.

The GBS study consisted of the following 3 separate sections.

1. We estimated the cost of operating the clinic(s). Because of the range of costs relating to the

administrative fees that we have seen from different clinic vendors, we estimate the cost using

high and low administrative cost assumptions. We also assumed that more than one location

would be necessary to provide access to all District employees. In the work that follows, we use

the term clinic to mean the clinic concept, regardless of the number of locations.

2. We estimated the potential reduction in claims paid under the health plan due to a combination

of services provided directly at the clinic and a reduction in unnecessary services attributable to

the “gatekeeper’ function played by the clinic. We made the estimates using two different

assumptions about the % of primary care physician (PCP) office visits that are redirected to the

clinic. We termed the assumptions “moderate” and “high” utilization.

3. We estimated the potential for other health plan savings related to improved health of covered

members as a result of wellness and disease management initiatives supported by the clinic.

This is the most subjective component of the study.

The projected first year results of the study are summarized in the following table. The savings

associated with step 3 above are not included in this table as they are projected to emerge over a longer

period of time.

Moderate Utilization High Utilization

Administrative Fee Assumption Low High Low High

Estimated Direct Claim Savings $1,359,838 $1,359,838 $1,970,658 $1,970,658

Projected Clinic Expense $1,911,912 $2,431,080 $2,360,765 $2,879,933

Total First Year Savings/(Cost) ($552,074) ($1,071,242) ($390,107) ($909,275)

The key conclusions we draw from the table are as follows.

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The single most important conclusion is that in order for a clinic to have any significant favorable

impact on health care costs, it is imperative that it includes programs that successfully affect the

health of the covered population in a way that reduces future medical trend. The pure exchange

of services from external physicians to clinic providers will not generate enough savings to

provide a significant return, given the expense of operating the clinics.

It is likely that in the first year of operation, the clinics will cost more than they will save, so the

net financial impact will be negative. Assuming increased utilization, it is reasonable to expect

to reach break even in the second year.

The most critical factor in the financial success of the clinic is the level of utilization. To the

extent employees use the facilities as a substitute for seeing their PCP and the clinic successfully

manages referrals and testing than is currently the case, the direct savings can be expected to

come close to covering the operating costs of the clinics in the first year and exceed the cost in

future years. If the levels assumed in the study are not reached (and they are by no means easy

targets), the clinic will produce a significant net loss.

There is a wide variation in the models and costs offered by clinic vendors. Our study assumes a

physician based model, with an MD supported by an RN and a Medical Assistant. Other models

use Nurse Practitioners or Physician Assistants. The choice of vendor will affect administrative

fees, professional salary expenses, and savings potential.

In addition to the “hard dollar” analysis above, we considered the potential for the clinics to support

programs aimed at improving the health of plan members. The District has an unusually high frequency

of chronic disease conditions, as documented in the following table produced by our proprietary data

warehouse application known as GBS Insider, based on claims incurred between July 2010 and June

2011.

Clinical Category # of

Claimants % of

Claimants

Benchmark % of

Claimants

Non Claimants 684 10.2% 21.0%

Healthy Claimants 2,377 35.5% 35.6%

Acute Claimants 292 4.4% 4.8%

Chronic Claimants 3,339 49.9% 38.6%

Total 6,692 100.0% 100.0%

We also looked at the results for prior periods and found an even higher frequency of chronic

conditions. The % of claimants that our algorithm identifies as chronic was right at 50% for the 2010/11

year, but was 55% in each of the two prior years. The difference may be related to the 2010/11 data not

being complete, as it does not include claims paid after June 30, 2011. The actual chronic % compares

to our (age adjusted) benchmark of just under 40%. This is a significant difference, as the chronic

claimants have consistently represented 90% of the District’s health plan claims.

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We also use GBS Insider to develop a Health Risk Index (HRI), which is a measure of the average health

risk of the population. Because the District’s population is older than our standard population, due at

least in part to the number of retirees covered by the plan, we expect a higher HRI for the District than

for our standard population. In fact, against a standard HRI of 1.00, our model produces an expected

HRI of 1.26 for the District, while the actual HRI for the 2010/11 year was 1.36, or 8% higher than

expected. If a clinic can successfully reduce the HRI to the expected level using programs outlined

below, the annual claim savings would be in the order of $3 million. It is unrealistic to expect all

members to use the clinic, so the likelihood of reducing the HRI to at or below the normative level is

small, but even moving it 1/3 of the way toward the norm is worth an estimated $1 million per year. So

while the direct savings related to replacing external medical services with clinic services might

ultimately generate small savings, it is the clinic’s ability to improve the health of the population that has

the potential to flatten the medical trend and generate significant long term savings.

The role of a clinic in reducing the frequency of, and claims related to, chronic claimants includes two

key functions.

Engaging the 45% to 50% of members who are not currently considered chronic in actions that

will minimize the probability that they will develop chronic conditions. We will label this effort

as Wellness initiatives.

Engaging the 50% to 55% of members who are already identified as having chronic conditions in

activities designed to encourage compliance with their treatment plans and promote the most

efficient care. We will label this effort as Disease Management.

A review of the Disease Burden report from our GBS Insider database shows much higher than expected

frequencies of diabetes, congestive heart failure, and circulatory disease. Many of the conditions that

fall under these categories are lifestyle related. An effective on site medical clinic can play an important

role in promoting healthier lifestyles and ultimately reducing the frequency of these diseases and

improving the efficiency of the care for members who already have them.

In summary, if approximately 1/3 of the members covered by the District plan can be encouraged to use

a clinic for primary care and preventive services, and if the members that do use the clinic are actively

engaged in wellness and disease management programs, we believe a clinic can successfully reduce

health claim costs by more than the cost of operating the clinic. Furthermore, greater savings can be

expected in the long term if the clinic can successfully reduce medical trend by even 1% to 2%, which we

believe is a very attainable target.

The following sections document the assumptions and methods used to derive the values presented in

the table above, and address in more detail the potential savings related to wellness and disease

management initiatives that could be provided through the clinic.

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2. Data and Assumptions

The study uses data from the following sources:

Claims data, including utilization, unit cost, and clinical measures, is based on the District’s data

for the 3 years ending June 30,2011.

The claim data is provided to GBS from UHC through quarterly data feeds and GBS stores the

data in our proprietary data warehouse application known as GBS Insider.

As a test of our own data, we also used reports of District experience prepared by UHC.

Data regarding the cost of operating clinics is taken from GBS experience with clients who have

implemented clinics and from RFPs and RFIs we have been involved with on behalf of clients

considering a clinic model.

The study is based on key assumptions regarding what portion of primary medical services can be

redirected to the clinic, how effectively the clinic will serve as a “gatekeeper” for specialist referrals and

diagnostic testing, and what impact the clinic will have on future medical trends. We have used data

from our own clients to develop a starting point for these assumptions, but we expect to see variation

between clients in the results. In prior RFPs and RFIs, we have asked vendors for input on these

assumptions as well, and although the vendors tend to be (in our opinion) somewhat optimistic in

setting utilization and effectiveness assumptions, their feedback is valuable as a reasonableness test of

our assumptions. Finally, in order to recognize the range of possible results depending on how a clinic is

received by plan members, we prepared results using two separate sets of utilization assumptions.

Under the “Moderate” utilization scenario, we assumed that 25% of primary care services would

be redirected to the clinic.

Under the “High” utilization scenario, we assumed that 35% of primary care services would be

redirected to the clinic.

Under both scenarios, we assumed that the clinic would have some success in controlling

unnecessary use of specialist referrals and diagnostic testing, and that a portion of the generic

prescription drugs would be dispensed through the clinic. We assumed a greater impact on

these services under the High utilization scenario than under the Moderate scenario.

We did not make any assumptions about how health risk or medical trend will be affected and how

those factors would affect future claim costs. Each employer needs to decide how aggressively it wants

to pursue wellness and disease management initiatives through a clinic, and there is a wide range of

available options. As a result, we have quantified the apparent opportunity but have not made any

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assumptions about how the District would pursue the opportunity and what the impact of those efforts

would be.

There is no standard medical delivery system for clinics. We assumed that the clinic would use an MD

based delivery system, but there are other options that would affect both the cost of operating a clinic

and the expected return. For example, some vendors prefer delivery systems based on RNs or physician

assistants (PAs), with MD involvement limited to oversight. Those models will generally have lower

professional staffing fees, but may also have less ability to treat as many conditions or to perform the

gatekeeper function. Overall, we do not believe that one system has an inherent financial advantage

over the other available systems and that the results of the study would be similar regardless of the

delivery system we assumed.

The assumptions are set out in more detail in the following sections of this report.

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3. The Cost of Operating a Clinic

In order to estimate the cost of a operating a clinic, we first have to understand the volume of services

that are expected to be provided. The volume is a function of the number of eligible employees and the

assumed utilization rate for those employees. The following chart shows the location of the District’s

covered employees and retirees by county, and our estimate of the % of employees in each county that

would have reasonable access to clinics located in Escambia County.

% of Estimated Estimated

County Employees Total % Eligible Eligible

Escambia (FL) 4,877 88.1% 100% 4,877

Santa Rosa 464 8.4% 100% 464

Baldwin (AL) 92 1.7% 50% 46

Escambia (AL) 42 0.8% 50% 21

Okaloosa

14 0.3% 0% -

Other 46 0.8% 0% -

Total 5,535 100.0% 97.7% 5,408

Of the 5,535 employees on the census file we used, a vast majority would be expected to have access to

a clinic assuming that at least two locations are offered. It is possible to operate a single location, but

that would reduce the access considerably. A geo access study can determine what % of employees live

(or work) within an acceptable distance of one or more given locations.

Based on the current member to employee ratio, we estimate that if 5,408 employees would have

reasonable access to a clinic, then there are approximately 8,600 total members with access.

Professional Staffing Costs

Based on the historical frequency of primary care visits adjusted to calendar year 2012, we expect the

8,600 eligible members to have a total of approximately 21,800 primary care office visits in 2012. Under

the Moderate utilization assumption, we assume 25% of these visits, or 5,450 visits, will go through the

clinic. Under the High utilization scenarios, 35% of the visits, or 7,630 visits, go through the clinic.

We use the expected number of visits to develop an estimate of the number of hours the clinic needs to

operate in order to provide the expected services. Key assumptions in this step are:

There will be 3 office visits per hour.

Only 60% of the appointments at a clinic actually replace an office visit. The other 40% are a

combination of services for which the member would not have sought treatment in the absence

of a clinic, and visits related to health risk assessments or other wellness programs that also do

not replace a visit. This assumption is based on GBS experience, but will vary by employer.

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The optimal utilization of available appointments is 85%. Vendors generally tell us that clinics

that operate at 100% capacity will results in problems for employees getting appointments or

walk in treatment and that will eventually hurt utilization. The vendors generally suggest that a

clinic should have between 80% and 90% of the available appointment time scheduled.

Based on these assumptions, the recommended number of available appointment hours is developed as

follows for the Moderate and High utilization assumptions.

Moderate High

% of PCP Visits Directed Through Clinic 25% 35%

Target Physician Visits in Clinic 5,452 7,633

% of Visits in Clinic Replacing a PCP Visit 60% 60% Total Available Visits Needed to Meet Target Utilization 9,087 12,721

Visits per Hour 3 3

Required Physician Hours 3,029 4,240

Target Utilization of Available Appointment Time 85% 85%

Target Available Appointment Hours 3,563 4,989

Required Hours per Week (50 weeks per year) 71 100

Recommended # of Locations 2 3

Recommended Weekly Hours per Location 35 35

Under the Moderate utilization scenario, we project a total of 3,563 appointment hours will be needed,

while under the High utilization scenario we project 4,989 hours will be needed. Assuming 50 weeks per

year that equates to 71 hours per week for the Moderate scenario and 100 hours per week for the High

scenario. Based on these results, we have assumed 2 locations operating at 35 hours per week for the

Moderate scenario and 3 locations operating at 35 hours per week for the High scenario.

We have assumed that each location would have an MD, an RN, and a Medical Assistant (MA). This is a

fairly typical model for the MD based clinic. We have estimated hourly rates based on current RFP and

RFI responses from a range of clinic vendors. The following table summarizes the resulting projected

professional staffing costs.

Moderate Utilization High Utilization

Hourly Rate Hours/Week Annual Cost Hours/Week

Annual Cost

MD $120 35 $218,400 35 $218,400

RN $35 35 $63,700 35 $63,700

Medical Assistant $20 35 $36,400 35 $36,400

Subtotal Per Location

$318,500

$318,500

# of Locations

2

3

Total Staffing Cost

$637,000

$955,500

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We project an annual cost of $318,500 per location based on a 35 hour week, and produces total annual

costs of between $637,000 (Moderate) and $955,500 (High).

Administrative Expenses

Clinic vendors will also pass along an administrative fee for their services. The fee covers a variety of

services such as hiring professional staff, obtaining insurance, communication services, reporting,

maintaining systems, integrating data with the plan’s TPA, and other services that vary by provider.

Some vendors charge a separately identified administrative fee, while others combine their

administrative fees with provider staffing and supplies in a single fee. We felt that for purposes of this

study it made more sense to separately identify the administrative expenses. Because of the range we

see in the market, we present both Low and High cost scenarios.

Per Capita Fees (PEPM) Low $15

High $23

Annual Fees Low $973,440

High $1,492,608

For a population of approximately 5,400 employees, we project the annual administrative fees will be

somewhere in the $1 to $1.5 million range. It is possible to negotiate lower fees, but for a full service

clinic we think this is a reasonable estimate.

Drugs and Supplies

We assumed that the clinic would include a generic drug dispensary to take advantage of unit costs

savings available on generic drug purchasing. We estimated drug utilization based on current patters

and assumptions about how many drugs would be dispensed through the clinic. Those assumptions are

described in more detail in the Cost Savings section. We also estimated the cost of supplies (latex

gloves, syringes, and other medical supplies) based on responses to other RFPs and RFIs. The estimated

cost of drugs and supplies is shown in the following table.

Generic drugs Utilization # of Drugs Cost Per Drug Annual Cost

Moderate 21,608 $5 $108,038

High 29,244 $5 $146,219

Supplies Utilization Annual Visits Cost Per Visit Annual Cost

Moderate 9,087 $5 $45,433

High 12,721 $5 $63,606

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Rent

We estimated the cost of renting a medical facility. In the event the District is able to use its own

property to house the clinic, this expense would be eliminated. Following is our estimate of the cost of

renting clinic space.

# of Square Feet Total Annual Cost/ Total

Utilization Locations Per Location Square Feet Square Foot Annual Cost

Moderate 2 2,000 4,000 $20 $80,000

High 3 2,000 6,000 $20 $120,000

Other Expense

We also estimated the cost of other expenses such as obtaining necessary licenses, insurance, and

cleaning services, is estimated as a % of the cost of rent. This will be a relatively minor expense, as

shown below.

Licenses, Insurance, Cleaning, etc. Assumed % of Rent 10%

Moderate Utilization - Annual $8,000

High Utilization - Annual $12,000

Start Up Expenses

Finally, we estimated the start up costs of starting the clinics. These expenses would be incurred in the

first year of operation, although some may be amortized. The start up expenses will depend on whether

a facility needs to be built out or if the District is able to rent space that is already compatible with use

as a clinic. The build out cost will also depend on whether the District is able to use its own staff to do

the build out. It is important to note that building out a medical facility requires adherence to codes and

requirements that are stricter than a regular build out.

Based on other RFP submissions, we estimate the build out costs for a space not currently used as a

medical facility to be as follows:

Typical Build Out Expense for location not currently used as a medical facility $30,000

Moderate Utilization (2 Locations) $60,000

High Utilization (3 Locations) $90,000

For a facility that is currently in use as a medical facility, the build out expense will be nominal.

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Summary of Expenses

The total of all estimated expenses is summarized in the following table.

Moderate Utilization High Utilization

Administrative Fee Assumption Low High Low High

Professional Salaries $637,000 $637,000 $955,500 $955,500

Administrative Fees $973,440 $1,492,608 $973,440 $1,492,608 Equipment and Supplies $153,472 $153,472 $209,825 $209,825

Rent

$80,000 $80,000 $120,000 $120,000

Other $8,000 $8,000 $12,000 $12,000

Total Annual Expense $1,851,912 $2,371,080 $2,270,765 $2,789,933

Start Up Expense $60,000 $60,000 $90,000 $90,000

Total First Year Expense $1,911,912 $2,431,080 $2,360,765 $2,879,933

Under Moderate utilization, we project annual expenses, before start up costs, to be between $1.85

million and $2.4 million. The build out cost, if required, for 2 location s is estimated to be $60,000.

Under High Utilization, we project annual expenses, before start up costs, to be between $2.3 million

and $2.8 million. The build out cost, if required, for 3 location s is estimated to be $90,000.

The key conclusion from this section is that operating a clinic is expensive and will only make financial

sense if there are significant potential savings.

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4. Potential Claim Savings

Hard Dollar Savings

Clinic vendors tout savings that can be classes as direct, or hard dollar, savings, and indirect, or soft

dollar, savings. This analysis focuses on the hard dollar savings. We will comment on soft dollar savings

at the conclusion of this section.

A clinic offers the opportunity to save costs on two broad types of services:

Services that are provided directly in the clinic, such as primary and preventive care visits and

generic drugs, and

Services that are often over utilized for which the clinic can serve as a gatekeeper that reduces

unnecessary utilization, such as specialist visits, diagnostic tests and brand name drugs.

Vendor estimates of the potential for these savings vary depending on their model and steps taken to

encourage clinic utilization. The higher the utilization, the greater the potential for generating both

types of savings. In order to promote clinic utilization, employers often waive all or most employee cost

sharing for services performed in the clinic. As cost sharing in general has increased in recent years, this

has become a more meaningful incentive. Some employers who offer HRA/HSA programs increase

funding of spending or reimbursement accounts for using the clinic. Some employers use the clinic as a

focal point for wellness activities in an attempt to engage employees in clinic use.

Based on our experience with employers who have implemented clinics, and on information provided in

responses to RFPs and RFIs, we prepared the following Moderate and High utilization assumptions.

Moderate High

% of Services in Clinic Primary Care/Preventive Care Visits 25% 35%

Generic Drugs 15% 20%

% of Services Avoided Specialist Visits 10% 15%

Outpatient Diagnostic Services 10% 15%

Brand Drugs 5% 8%

Vendors believe it is possible to see even higher clinic utilization over time, and while we agree with that

there are practical limits that cannot be ignored. For example, clinics do not normally offer pediatric

services, so most children visits will not be directed to a clinic. Covered spouses who do not work for

the District may not find the clinic locations to be convenient. In addition, individuals with chronic

conditions are most likely to have established physician relationships and may be more reluctant to use

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a clinic. Since those with chronic illnesses have the highest frequency of visits, this means that the

people responsible for the largest share of costs may be least likely to use a clinic. All of these factors

suggest that reaching levels such as 50% or more of Primary Care visits going through a clinic is difficult

and even over a period of years may not be possible.

We developed the current utilization and unit costs for services that could be affected by the clinic using

reports from GBS Insider. Those reports provided historical utilization per 1000 covered members and

average plan cost for the selected services. We adjusted the historical data to an assumed starting point

of January 1, 2012 using normative utilization and unit cost trend assumptions. We also assumed that

for services such as diagnostic services and brand drugs, the services eliminated would be less expensive

than the average service in that category. The logic for that is that most serious visits and tests are less

likely to be eliminated.

The baseline 2012 utilization for services that can reasonably be expected to be affected by a clinic is

summarized below.

Baseline Utilization and Unit Cost

Type of Service Service # of

Services Unit Cost Annual Claims

Preventative Preventative Medicine 3,151 $ 110 $ 346,620

Immunizations 3,952 $ 40 $ 159,263

Subtotal

$ 505,883

Other Physician PCP 18,657 $ 54 $ 1,015,992

Specialist 16,236 $ 37 $ 601,219

Consultation 1,397 $ 148 $ 206,999

Lab/Pathology 30,469 $ 27 $ 829,614

Radiology 17,313 $ 71 $ 1,225,637

Other 22,511 $ 56 $ 1,250,397

Subtotal

$ 5,129,858

Outpatient

Facility Diagnostic 6,524 $ 507 $ 3,307,051

Pharmacy Generic 126,713 $ 10 $ 1,242,065

Brand 52,015 $ 129 $ 6,698,791

Subtotal

$ 7,940,856

Total for These Services $ 16,883,648

We project the total claim cost, assuming current plan design and enrollment, for members eligible to

use the clinic based on their location, to be $16.9 million. Keeping in mind that we expect it to cost

somewhere between $2 and $3 million to operate a clinic, depending on the utilization and model, it will

take significant reductions in the cost of these services just to break even.

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The following table shows the resulting projected annual claims for each of the indicated service

categories, and in total, as well as the total projected savings for both the Moderate and High utilization

scenarios.

Moderate High

Type of Service Service Baseline Utilization Utilization

Preventative Preventative Medicine $346,620 $259,965 $225,303

Immunizations $159,263 $119,447 $103,521

Subtotal $505,883 $379,412 $328,824

Other Physician PCP $1,015,992 $761,994 $660,395

Specialist $601,219 $547,109 $520,055

Consultation $206,999 $190,439 $182,159

Lab/Pathology $829,614 $763,245 $730,060

Radiology $1,225,637 $1,139,843 $1,096,945

Other $1,250,397 $1,162,869 $1,119,106

Subtotal $5,129,858 $4,565,499 $4,308,719

Outpatient Facility Diagnostic $3,307,051 $3,075,558 $2,959,811

Pharmacy Generic $1,242,065 $1,055,755 $993,652

Brand $6,698,791 $6,447,587 $6,321,984

Subtotal $7,940,856 $7,503,342 $7,315,636

Total for These Services $16,883,648 $15,523,811 $14,912,990

Estimated Annual Savings $1,359,838 $1,970,658

The projected savings for each service type are shown below.

Moderate High

Type of Service Service Utilization Utilization

Preventative Preventative Medicine $86,655 $121,317

Immunizations $39,816 $55,742

Subtotal $126,471 $177,059

Other Physician PCP $253,998 $355,597

Specialist $54,110 $81,165

Consultation $16,560 $24,840

Lab/Pathology $66,369 $99,554

Radiology $85,795 $128,692

Other $87,528 $131,292

Subtotal $564,359 $821,139

Outpatient Facility Diagnostic $231,494 $347,240

Pharmacy Generic $186,310 $248,413

Brand $251,205 $376,807

Subtotal $437,514 $625,220

Total for These Services $1,359,838 $1,970,658

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The key finding here is that even using relatively aggressive utilization assumptions, the hard dollar

savings are less than the projected cost of operating a clinic. This does not mean that the clinic is not

financially viable, as utilization should increase over time and the clinic does provide a tool for affecting

health care costs in other ways. This is discussed in more detail in the following section.

It has also been our experience that some vendors will suggest that other types of direct claim savings

are possible through a clinic. Some will suggest that a clinic can reduce emergency room (ER) use, for

example. We have also seen suggestions that inpatient utilization can be reduced. Our experience with

employers who have implemented a clinic does not support these claims, at least in the near term. The

clinic will provide only primary care, so anything requiring more acute treatment should be referred to

the proper setting. Certainly there are ER visits that are unnecessary and there may be cases where an

employee might avoid an ER visit by going to the clinic, but these should be very infrequent. A

successful clinic might affect inpatient admissions in the long run (as will be discussed in the next

section), but that will depend entirely on how the clinic is integrated with the employer’s wellness and

disease management programs.

We have not included savings related to occupational health (workers compensation, fit for duty

physicals, etc.). Using a clinic for workers compensation services is possible but the potential for

material savings is limited. Savings for required physicals are much more significant for employers that

have their own police and fire staff, such as cities and counties.

Soft Dollar Savings

Most clinic vendors promote the notion of soft dollar savings. Sources of soft dollar savings include

things like the following:

Reduced absenteeism since employees can receive medical treatment without being away from

work for long periods of time.

Enhanced productivity while at work (“presenteeism”)

Reduced employee turnover and recruiting costs

Increased compliance with treatment plans that will lower long term costs

Although we agree that an employer may benefit to some degree from each of these items, we have not

made any attempt to quantify these sources of savings. For the most part, we do not have any credible

baseline against which to measure these items, and in some cases it is hard to measure them at all. We

do not suggest that these items have no value, but we believe they are too subjective and hard to

measure to be included in a feasibility study.

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5. Wellness and Disease Management Opportunities

In the prior section, we concluded that the potential for direct claims savings under reasonable clinic

utilization assumptions was likely to be less than the cost of operating a clinic in the first year of

operation. Despite that conclusion, long term savings are possible if the clinic can be used to improve

the performance of other aspects of the health insurance program. Two likely candidates for

improvement are wellness and disease management programs.

Wellness programs can be defined as initiatives aimed at preventing employees from moving down the

health spectrum from healthy to less healthy. Most wellness programs focus on promoting exercise,

healthy eating habits, smoking cessation, weight loss, and appropriate wellness visits and screenings. A

number of published studies have suggested that 50% or more of health care costs can be linked to

lifestyle issues. If those studies are accurate, even small improvements in the overall wellness of a

population could have a material impact on health care claims.

Disease management programs can be defined as initiatives aimed at ensuring that individuals who

already have health conditions that require treatment actively participate in treatment plans that

provide efficient care leading to the best possible health outcomes. Some conditions, such as diabetes,

asthma, heart disease, and cancer, are natural candidates for disease management. Disease

management programs also exist for a number of other conditions that are less obvious, ranging from

behavioral health to rehabilitation therapy.

A successful clinic can be used to promote employee participation in both wellness and disease

management programs. Participation can be encouraged through plan design incentives, premium

credits, and enhanced employer funding of healthcare reimbursement or savings accounts. While

similar incentives can be developed in the absence of a clinic, the convenience of a clinic may make

employees more likely to participate and remain engaged in these programs.

In order to estimate the potential impact of improved wellness and disease management programs, it is

necessary to understand the prevalence of manageable conditions and the general level of wellness in

the population. Using GBS insider, we reviewed the prevalence of various health risk conditions in the

District population, as well as the overall health risk in the population. We found the following (see the

referenced reports in the Appendix section of this report):

The average demographic risk factor for the District has consistently been in the 1.45 to 1.50

range. This is very high, suggesting a much older population that our norm.

The population includes a significant number of retirees. Of the 8,800 members, nearly 1,300

are retirees, and average demographic factor for the retirees is approximately 2.35. The

demographic risk factor for active employees is still very high, at 1.30 to 1.35.

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The population has an unusually high prevalence of chronic conditions. Over the last 3 years,

our clinical algorithms suggest that 50% to 55% of the population is considered a chronic

claimant, compared to our norm of just under 40%.

The population has a much lower incidence of non claimants that our norms would predict. Our

benchmark is that right around 20% of members would have no claims, but the District has

consistently been at 10%.

The Health Risk Index (HRI), a measure of the overall health status of the population, has been

consistently high, with scores of close to 1.60 for years ending June 30 2009 and 2010. The

score for the year ending June 30, 2011 is better, at 1.36, but that figure is under stated because

we do not have the runout claim data from the 2010/11 year included at this time.

Our health risk model has consistently predicted that the risk scores would improve, but we

have not seen that yet. There may be some improvement in 2010/11, but we won’t know for

sure until we get the runout data included. The fact that the risk scores have not “regressed to

the mean” suggests the either the disease management efforts to date have not been successful

or that the healthier lives have been getting less healthy at a faster rate than expected.

The Disease Burden report shows relatively high frequencies of diabetes, circulatory disease,

and malignancies. These are all conditions that lend themselves to effective disease

management.

Based on these results, we conclude that the District’s health claims could be reduced by a more robust

disease management program, and that the District would also benefit from an effective wellness plan.

Quantifying the potential savings is not as precise as estimating current direct savings that might be

achieved through a clinic, but we can mare a reasonable estimate. Following is a summary of the health

risk index and claims by claimant category for the 12 months ending June 30, 2011.

Clinical Category # of Claimants % of

Claimants

Benchmark % of

Claimants

Retrospective Health Risk

Index % of Total

Claims

Non Claimants 684 10.2% 21.0% 0.000 0.0%

Healthy Claimants 2,377 35.5% 35.6% 0.337 7.5%

Acute Claimants 292 4.4% 4.8% 1.084 2.4%

Chronic Claimants 3,339 49.9% 38.6% 2.381 90.1%

Total 6,692 100.0% 100.0% 1.3591 100.0%

Chronic claimants account for 90% of the total claim cost. If we assume that a % change in the HRI

corresponds to a comparable % change in the health claim cost, then for each 1% by which a successful

disease management program is able to reduce the HRI for chronic claimants, we estimate a claim

savings of 0.9%, or approximately $350,000.

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A successful wellness program will reduce key risk factors and that will also translate to lower HRI

scores, although that may be more a result of a change in the mix of the categories above. Preventing

members from moving from healthy claimants to chronic claimants will keep the overall HRI lower and

will reduce claim costs over time. Each 1% shift from chronic to healthy claimant in the table above

reduces the overall HRI by over 1.5%, which we estimate would translate to annual claim savings of

approximately $600,000.

These potential savings are likely to occur over a longer time period of perhaps 2 to 3 years at best.

Also, estimating claim savings by looking at changes in the HRI is complicated by the fact that even in the

absence of any disease management or wellness program, there is often movement in the HRI from year

to year. If one year has an unusually high frequency of serious illnesses, it is common that the next year

is not as bad, as experience tends to move back to “normal” over time. In order to attribute savings to

these programs, it is necessary to track experience for given conditions over time and compare the

progression of risk scores before and after the programs are introduced, taking into consideration the

progression of the scores in an environment with no such programs.

Finally, many employers are taking stronger steps in this area without using a clinic, so the real question

is how much can the performance of these programs be improved by using a clinic. Disease

management and wellness vendors will generally agree that the biggest barrier to success is that not

enough employees are truly engaged in the programs. To the extent a clinic serves as a tool for

increasing the engagement level of employees, the programs should be more effective. A discussion of

strategies for promoting employee engagement through a clinic is beyond the scope of this report, but

we recommend that if the District does issue an RFP for clinic vendors, the approaches taken by vendors

to engage employees be given a material weight in the evaluation process.

After all the caveats and unknowns, the question remains: How much can a well designed clinic

contribute to health plan savings by improving the health risk of the covered population? Based on the

theoretical analysis, there is more potential for savings related to health improvement than for avoiding

office visits and other medical procedures and prescriptions. Our history with clients has been mixed,

but it is also somewhat limited as we still have only a relatively small sample of clients that have

implemented clinics. Based on what we have seen, it is possible to slow the growth of healthcare costs

though more effective wellness and disease management programs, and we certainly have examples of

clinics successfully engaging employees in health promotion activities. Therefore, we believe a clinic can

play a role in slowing the growth of healthcare costs and that the magnitude of potential savings is at

least as significant as the short term direct cost savings that can be achieved.

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6. Other Considerations

As we prepared this report, there were other issues that presented themselves that we think are worth

noting.

One key factor that drives clinic utilization is the location of the facility. For school districts, this is often

an issue because employees are spread out over several work locations and it is often difficult to find a

single location for a clinic that provides ready access to all employees. In our work, we assumed either 2

or 3 separate locations would be necessary to provide access to all District employees. As part of the

study, we looked at the home zip codes of all employees to determine just how spread out the

population is. We also had a concern that the over 1,000 retirees might be spread around the country

and would therefore have no ability to access a clinic in Escambia County. The results of our study

suggested that 88% of plan participants live in Escambia County and would have reasonable access to a

clinic. We also found that 8.4% lives in Santa Rosa County and would presumably have reasonable

access as well, and that another 2.5% reside in neighboring Alabama counties of Baldwin and Escambia.

We assumed that half of the lives living in the two Alabama counties would have reasonable access. In

total, we estimate that almost 98% of covered employees and retirees combined could have reasonable

access to a clinic if the locations are carefully selected.

A second issue we think is important to note is that we are just starting to see clinic vendors try to

partner with medical TPAs. One of the problems we have experienced with clients that have introduced

clinics is the lack of sufficiently detailed reporting about the nature of services performed in the clinic

and the inability to integrate that data with the medical TPA data. As clinics mature, we expect some of

the reporting issues will be resolved, but it remains an issue today with many vendors. The possible

partnering of clinic vendors and medical TPAs might also prove to be one method of addressing this

issue. One example of this partnering is the combination of Blue Cross Blue Shield of Florida (BCBSFL)

and clinic vendor Healthstat, which we understand has started in the Escambia County area.

The possible partnering of vendors is, from our standpoint, not entirely a benefit to employers. There is

a great deal of variation between clinic models and we don’t believe an employer should be steered to

one model over another because of their choice of medical vendor. Just as GBS would not bring a

packaged TPA solution to an employer, we see problems with a carrier bringing a packaged clinic

solution. Our job is to determine the best TPA for each employer and we feel the same way about a

choice of clinic vendors.

Finally, we think it is important to keep in mind that while employer sponsored clinics have been around

in some form for decades, the more recent explosion in this field has not been going on long enough to

have a great deal of credible history. This analysis is based more on our assumptions and what if

scenarios than it is on hard data. While we believe our findings are reasonable, and consistent with the

experience that we do have, there is still an element of uncertainty regarding the long term results

under clinics programs. The District should keep this uncertainty in mind when evaluating its options

regarding clinics.