The Effectiveness of Soldier Medical Readiness Councils in ...

MILITARY MEDICINE, 178, 7:715, 2013

The Effectiveness of Soldier Medical Readiness Councilsin Reducing and Shaping the Population of Soldiers

Not Medically Deployable

LTC Richard G. Malish, MC USA*; MAJ Gail L. Maxwell, SP USA†; MAJ Anthony D. Arnett, MC USA*;CPT Jessica M. Cassidy, AN USA*; COL Ronald J. Place, MC USA*

ABSTRACT The population of Soldiers not medically fit for deployment has created readiness problems for the U.S.Army in recent years. To address this issue, the 3rd Infantry Division created councils of experts to address the size of itsmedically nondeployable population. Our results demonstrate success in effectively reducing the subpopulation of Soldierswho have been medically nondeployable for long periods of time by enforcing their return to duty or medical retirement.This study also demonstrates that council-based management affects the composition of the medically-not-ready population.Traditional approaches allow a minority subpopulation of Soldiers with poor prognoses to dwell within the nondeployablepopulation for long periods of time (6–18+ months), whereas the healthier majority recovers within the first 6 months. Thiscreates a dynamic in which remaining in the population for longer time periods increases the probability of being medicallyretired. Our study demonstrates that councils consistently and actively shape the character of the group such that thoseremaining in the medically-not-ready population for longer periods of time do not have an increased risk of medicalretirement. Soldier Medical Readiness Councils have already been adopted by the Army. This article provides evidenceto support their efficacy.

BACKGROUNDAs the duration of current conflicts has lengthened, the pro-

portion of medically nondeployable (MND) Soldiers has

grown in the all-volunteer Army. The cost of this phenome-

non is hidden during regular training cycles but revealed

during predeployment accountability exercises. In 2008, the

problem reached a pinnacle when multiple deploying units

required 11th hour substitutions of healthy individuals for

disabled Soldiers to meet health standards for deployment.

Other units brought their unfit Soldiers with them to Iraq

or Afghanistan.1 In 2010, 16% of Soldiers were estimated to

be unfit for deployment.2 In 2011, an article in the national

press estimated the absolute size of the nondeployable popu-

lation at 90,000. It went on to credit Army Surgeon General

LTG Eric Schoomaker with the following statement: “the

problem of a growing population of [MND] soldiers has

begun to erode the readiness of the Army.”3

The etiology of the growing MND population is multifacto-

rial. Repetitive deployments undoubtedly play a role. Second,

the size of the group, until recently, has remained hidden as a

result of the lack of a strategic methodology for accurately

defining and tracking ill and injured yet marginally functional

Soldiers. Third, a cultural divide exists between the medical

and operational communities. Medical providers enter into a

“therapeutic alliance” with Soldiers and may act as advocates

for their ongoing recovery for months after injuries prove

themselves likely to be permanently unfitting for further mili-

tary service. Delays in referring Soldiers to medical retirement

boards hurt operational unit readiness and frustrate com-

manders. Finally, the medical evaluation (retirement) board

(MEB) process is complex and includes multiple administra-

tive and clinical steps. Soldiers can become lost within the

labyrinth unless they adopt a proactive approach to both learning

the intricacies of the process and ensuring timely appointments.

This is important because Soldiers enrolled in the medical

retirement process, even though identified as nondeployable,

remain assigned to their go-to-war positions.

Soldiers diagnosed with permanent disability of enough

severity to disqualify them from ongoing active service rep-

resent a fraction of the MND population and one of 2 sub-

populations. This subpopulation is described as the “MEB

population” because such Soldiers are referred to medical

retirement boards as soon as identified. The second, larger (and

thus arguably more important operationally) subpopulation is

those Soldiers with ongoing conditions of presumed tempo-

rary duration (also known as “medically not ready [MNR]”).

Beginning in 2009, the 3rd Infantry Division (ID) and the

Fort Stewart, Georgia (FSGA), and Hunter Army Airfield

leadership began addressing the factors contributing to the

MND population within our community of 24,000 active duty

Soldiers. To fully characterize our two MND subpopulations,

we hired eight registered nurses specifically to track them.

We concurrently created products (spreadsheets, educational

MEB “roadmaps,” and written procedures) to ensure unifor-

mity in reporting and oversight. Our local tracking instru-

ments provided the required detail to maintain by-name

knowledge of medical appointments, referrals, milestones,

and general progress—items lacking in the Army’s web-based

*Winn Army Community Hospital, 1061 Harmon Avenue, Fort Stewart,

GA 31314.

†Division Surgeon Section, 3rd Infantry Division Headquarters, 942 Doctor

Ben Hall Place, Building HQ 001, Fort Stewart, GA 31314.

doi: 10.7205/MILMED-D-13-00003

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medical readiness database (the Medical Protection System

or “MEDPROS”).

A picture of our MNR and MEB subpopulations came into

focus. We identified a significant quantity of Soldiers who

had been MND for excessive periods of time. Many existed

in the MNR population in violation of Army Regulation (AR)

40-501 (Standards of Medical Fitness), which states that

“referral to a [MEB] will be made within 1 year of being

diagnosed with a medical condition(s) that does not appear

to meet medical retention standards, but the referral may be

earlier if the medical provider determines that the Soldier will

not be capable of returning to duty within 1 year.”4 The

majority of extreme long-duration outliers were Soldiers

with musculoskeletal conditions unresponsive to multi-

disciplinary treatment.

Our visualization techniques received attention by the

U.S. Army Medical Command (MEDCOM). In July 2010,

that body designated our personnel, procedures, and systems

as one of the first two “Medical Management Centers

(MMCs)” in the Army. MEDCOM has since disseminated the

concepts, funding, and resources to establish MMCs across

Army installations.

It is important to note that the improved visibility of the

MND population offered by the MMC did not automatically

result in influence upon it. It was, however, a key preliminary

step and necessary for ultimate change to occur. With a firm

understanding of the scope of the problem at FSGA, we

considered courses of actions to solve it. Because a degree

of general apathy with AR 40-501 contributed to the pre-

dicament, we suspected that petitions to change regulation,

without enforcing changes in behavior, would likely yield

minimal results. The root cause of the growing MND popula-

tion was not a shortfall in policy but inadequate enforcement

(by providers) of timely medical dispositions in accordance

with existing policy. Compassionate, informed, and accurate

medical decision-making needed to acquire the added charac-

teristics of vigilance and suitable speed.

We considered reeducating Army health care providers

on AR 40-501 to influence them to more consistently make

prompt disposition decisions and to exceed the 1 year stan-

dard only by exception. In the end, we dismissed this option

because we feared that it would undermine provider–patient

trust and demoralize our health care system by asking pro-

viders to be a combination of caregiver and policeman—

functions capable of creating clashes of ethics and conscience.

Ultimately, to reduce the size and impact of the popula-

tion, we created 43 Soldier Medical Readiness Councils

(SMRCs) beginning in late 2010. SMRCs are multidisci-

plinary teams of unit- and hospital-based clinicians, adminis-

trators, nurses, and unit leaders. The committees meet on a

monthly basis to review and manage MND populations by

unit. In each SMRC meeting, primary care providers, nurse

case managers, or supervising physicians present the medical

history, treatment course, and prognosis of ill and injured

Soldiers under review. Once educated on individual Soldiers,

the councils make disposition decisions in three areas. First,

the councils ensure that individual Soldiers receive a fair

chance to recover in accordance with consensus experience

and guidelines published in Army regulation. The best out-

come is a Soldier’s full return to duty (RTD). If recovery

stalls at a functional level unfit for service with little hope

for improvement, the SMRCs make certain that MNR Sol-

diers are rapidly transitioned into the MEB system. Identify-

ing and acting upon this transition point (known as the

Medical Retention Decision Point or MRDP) is the most

important mission of SMRCs. Finally, SMRCs identify

actions to encourage efficient navigation of the MEB process.

SMRCs exist at the battalion (400–900 Soldiers), brigade

(6 battalions or 3500–4000 Soldiers), and division (6 bri-

gades or 24,000 Soldiers) echelons. At each level, the coun-

cils focus on populations according to the time they have

existed in the MND classification. At the Division SMRC,

for example, the 3rd ID Surgeon chairs the meeting and

evaluates medical reports and plans for Soldiers that have

been MND for greater than 240 days and not yet in the MEB

system. Brigade and battalion teams place similar focus

on Soldiers who have been MND for 180 days and 90 days,

respectively. This methodology results in an automatic eleva-

tion of MND Soldiers to more senior levels of the SMRC

hierarchy the longer they remain physically unable to deploy.

It aligns the pyramidal shape of the Army command structure

with the tiered shape of the MND population when visualized

as a function of time within the nondeployable classification

and maintains manageable ratios of patients to councils

across the population (Fig. 1).

Critical to SMRCs are external medical specialists who

ensure that bias is absent from decisions. At the division level,

the Winn Army Community Hospital Deputy Commander for

Clinical Services (DCCS or Chief of the Medical Staff) and the

Supervising MEB provider contribute insight and experience

into medical decision-making. Because SMRC outputs are

provided to commanders, the teams accept accountability for

progress or lack thereof. Of interest, operational commanders

are also frequently patient advocates because of shared experi-

ences, loyalty, and compassion. Furthermore, the process for

obtaining an alternate Soldier is time-consuming and likely

to result in a less-experienced replacement.

Notably, all SMRCmembers were present within the instal-

lation’s pre-existing personnel roster. Therefore, apart from

hiring the eight registered nurses to staff the MMC, the only

costs associated with the SMRC concept at the 24,000-man

division-level were those of commitment and time.

METHODSWe were interested in the answers to two research questions:

(1) Were SMRCs effective in reducing the size of the MND

population? (2) What was the effect of the councils on the

composition of the MNR population?

To evaluate the effectiveness of SMRCs, we prospectively

measured the number of Soldiers in the MNR and MEB

MILITARY MEDICINE, Vol. 178, July 2013716

Effectiveness of Medical Councils on Reducing the Population of MND Soldiers

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subpopulations (excluding the pregnant and postpartum frac-

tion) before the initiation of the strategy, during its imple-

mentation, and in its steady state. To do so, we divided the

timeline of medical nondeployability into three time duration

bins: short (90–180 days), middle (181–365 days), and long

(>365 days). We trended the absolute size of the population

in each bin over time as we erected the SMRC strategy. We

hypothesized that SMRCs would reduce the size of the MNR

and MEB subpopulations in all three bins with escalating

effect in the middle and long-duration time categories. This

was based on the assumption that SMRCs would mitigate

inappropriate dwell in both subpopulations as a result of

provider–patient alliances, lack of patient incentive to RTD

(or civilian life), and lack of command emphasis.

Our second research question focused on the effects of

SMRCs on the composition of the MNR population. If left

unregulated, MNR populations will adopt a makeup in which

those lasting the longest within the classification are those

most likely to be medically retired. We used the term “unnat-

ural selection” to describe this phenomenon because increas-

ing time in the MNR category shapes the population such that

Soldiers requiring medical retirement outlast those healthier

individuals who recover and RTD. This is a fundamental

characteristic of a system that relies solely on spontaneous

recovery to dictate its character. Absent enforced decision-

making, the process is abetted by provider–patient alliances,

unconstrained by time, and insensitive to the imperative that

Army units remain fully and constantly combat-ready. We

hypothesized that SMRCs, by enforcing timely medical

decision-making, would change the composition of the MNR

population to allow only those with clinical equipoise

(possessing an equal probability of retirement or RTD) to per-

sist within the population as time elapsed.

To test this hypothesis (which we titled “equipoise

advancement”), we prospectively followed a cohort of Sol-

diers from their entry into the MNR population until the

population reached complete disposition. To be eligible for

inclusion in the cohort, Soldiers had to have duty restrictions

associated with medical conditions (nonpregnancy-related)

of at least 30 days. We measured the size of the population

at 30-day intervals and took note of the means by which the

population decreased in size. At each 30-day interval, we

recorded the absolute number of Soldiers who were either

medically retired or returned to duty. In doing so, we created

a profile of the behavior of the population of Soldiers with

presumed temporary disability over time. Unlike previous

profiles, this was the first created for an Army population

actively managed by panels of leaders and medical experts.

RESULTSWe deployed the SMRC strategy in a phased manner. The

division-level SMRC was first introduced in October 2010.

Brigade and battalion SMRCs were mandated in the summer

of 2011. Figure 2 demonstrates our effectiveness over time.

FIGURE 1. Figure representing a graphic depiction of the SMRC methodology. The MNR and the MEB populations grow smaller with time(attributable to medical dispositions and completion of administrative steps). This allows more senior SMRCs to evaluate Soldiers as they dwell withinthe populations for longer amounts of time. SMRCs ensure that Soldiers return to duty at optimal rates. SMRCs also identify Soldiers who have stalledin recovery (the MRDP) and enter them into the retirement process. Once in the MEB process, SMRCs make certain that Soldiers continuously advancetowards final disposition.



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The figure indicates an initial and sustained reduction in the

MND population for Soldiers in the long-duration time bin

(Fig. 2C). The population in the middle duration bin is nota-

ble for reduction in size for the MNR category and no change

of the size of the MEB population (Fig. 2B). The population

in the short-duration time bin increased for both subpopula-

tions (Fig. 2A).

These results indicate that the division-level SMRC was

effective in achieving dispositions for Soldiers who have

been MND for more than a year (late outliers). The findings

in the middle-duration time bin are encouraging considering

the fact that the establishment of brigade and battalion

SMRCs lagged behind the division-level SMRC and did

not achieve operating capability until the summer months

of 2011. The increasing size of the subpopulations in the

short-duration time bin was unexpected and attributable

to an external Army-level policy decision. In March 2011,

the Army transitioned to an electronic system to identify

MND Soldiers (e-profile). The transition from paper to elec-

tronic filing of nondeployability information greatly increased

the MMC’s visibility of Soldiers in the MND category and had

particularly strong influences on the largest and least managed

population. The fact that this population growth (as a result

of increased visibility) was contained within the short-duration

bin, however, provides additional support for the effectiveness

of SMRCs at the higher end of the hierarchy.

Figure 3 shows the data collected to inform our second

research question. Specifically, it demonstrates the cumulative

results over time. Of 953 Soldiers in the cohort, 752 (78.9%)

were eventually returned to duty. A small population left ser-

vice before medical disposition (54, 5.6%)—either voluntarily

or by nonmedical “chapter” action. The remaining 147

(15.4%) reached the MRDP and were entered into the MEB

process. Of interest in this data is the “cross-over” of disposi-

tion likelihood between 90 and 120 days. A minority of Sol-

diers (431 or 45%) achieved a disposition by the 90-day

milestone. By 120 days, however, most Soldiers (647 or 68%)

had achieved a disposition. By 180 days, only 158 remained

in the MNR cohort—indicating that dispositions had been

made in 86% of Soldiers by 6 months. The remaining popula-

tion reached final dispositions at slower rates. All had a deci-

sion by 365 days as mandated by AR 40-501.

Figure 4 demonstrates the proportion of each possible

disposition at each 30-day interval. At no point was medical

retirement a more likely disposition than recovery and RTD.

The frequency of the medical retirement disposition

remained relatively constant at all points after the 120 day

mark, fluctuating between 22 and 30% (mean 25%). This

profile suggests that, in the MNR population managed

by SMRCs, increasing time selects neither more disabled

Soldiers (unnatural selection) nor those with clinical equi-

poise (indicating that the decision could go either way) but

those with a higher probability of recovery.

DISCUSSIONBecause of our early experience, the Army adopted the

SMRC concept and mandated its use across all formations

in 2011. This decision was based on plausibility of efficacy

and not evidence. The purpose of this project was to provide

early data to either support the Army’s decision or reverse it.

Because this study was a real-world implementation of an

untested process, it was subject to the limitations inherent

in that design. First, we were unable to isolate the population

such that the SMRC policy was the only novel variable acting

upon it. As an example, the introduction of electronic track-

ing significantly increased the size of the tracked MND

FIGURE 2. Figure showing the division of the MND population into groups by type (MNR and MEB) and time in category (short, middle, and longduration). The size of the short-duration (A) population increased with time during the observation period. This was as a result of capturing more ofthe population by utilizing electronic tracking mechanisms. Without intervention, the size of the middle- (B) and long-duration (C) populations wouldlikewise be expected to increase in a proportional manner. Because of active population management achieved by SMRCs, the size of the long-durationpopulation instead decreased. SMRCs “cap” the amount of time Soldiers remain unavailable to their units.



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population independently of our size-mitigation strategy.

Second, our process was primarily aimed at creating effect

and only secondarily interested in pure scientific experiment.

This methodology mandated observation bias and made the

creation of chronological or population controls impractical.

Instead, we continuously monitored our efforts by comparing

the size and character of the population to itself at an earlier

increment of time. A third limitation in our data is that statis-

tical power continuously became weaker as population sizes

became smaller. In other words, predictive power was highest

in the earliest MNR timeframe and weakest at the latest

extreme because of attrition of data points. Finally, all of our

data capture was local. As such, we did not address whether

or not the management process had effects upon the final

compensation packages offered to Soldiers. An ideal-world

study would provide stronger validation of the process.

FIGURE 4. Figure showing the comparison of the percentage of MEB decisions versus RTD and other (administrative separation) decisions accordingto time in the MNR category. The numbers in the columns represent the absolute number of each decision made in that time interval. The percentage figuresin the boxes indicate the proportion of all decisions for that interval that resulted in a MEB.

FIGURE 3. Figure demonstrating the cumulative number of disposition decisions by type as a function of time. By 180 days, a large majorityof disposition decisions were made. The rate of dispositions reached a relative plateau for the remaining 180 days.



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In spite of these limitations, our data informed our two

research questions and provides early evidence of the suc-

cess of the SMRC concept. First, while we were unable to

reduce the entire MND population because of the limitations

mentioned earlier, we effectively eliminated long-duration

outliers in both subpopulations. The absence of a control

group precludes a firm conclusion, but we believe that an

informed and active committee-based management team

effectively changed the character of the MNR population as

predicted by our second research question. In our managed

population, time progression selected for those with higher

probabilities of recovery and RTD. Our “equipoise advance-

ment” hypothesis fell short because it failed to capture the

full population. Not only did those with clinical equipoise

remain within the population but so too did those predicted

to recover. In other words, SMRCs continuously removed

the minority with failing recovery trajectories from the MNR

population as time proceeded forward. We offer this “natural

selection” process as an explanation for the observed time-

dependent disposition profile. Figure 5 illustrates how SMRCs

shape the MNR composition (Fig. 5B) as compared to an

unmanaged process (Fig. 5A).

Those seeking to implement this strategy may benefit from

some of our lessons learned. First, SMRCs primarily achieve

their value in managing the MNR subpopulation of MND

Soldiers. Passage of the MEB population through the retire-

ment process requires minimal medical decision-making.

Here, SMRCs offer oversight only. We have found that

improved flow through the MEB process is best achieved

by dedicated Lean Six Sigma-type programs targeted at

achieving efficiencies and eliminating waste. As such, SMRC-

generated improvement in population management will likely

occur with the MNR subpopulation first. This is reflected in our

data. Second, we found that the population in the long-duration

time bin (the late outliers) is the easiest to affect rapidly. This is

because this population is most likely to have already exhausted

treatment options. In addition, because of the hierarchal nature

of the SMRC design, this population will invariably be evalu-

ated by the senior-most SMRC in the organization. MND

populations at earlier time frames require tougher decisions by

multiple councils. Finally, we used an unmeasured “best guess”

to link SMRC echelons (battalion, brigade, and division) with

time-based medical evaluations (90, 180, 240 days). As

SMRCs mature as learning organizations, it is possible that

decisions for particular illnesses could be made earlier.

Beyond increasing the throughput of the MND process,

the SMRC concept achieved a set of favorable conditions that

is not easily measured quantitatively. The concept did not

change policy but proposed a methodology to better enforce

existing policy. In doing so, it allowed medical providers

to continue their role as patient advocates. It displaced

responsibility for medical separation decisions on the SMRC

system at large. At the organizational level, it allowed the

medical community to efficiently and vigilantly “Conserve

the Fighting Strength” of its combat-arms partners. Indeed,

the SMRC process at Fort Stewart and Hunter Army Airfield

FIGURE 5. Figure demonstrating how SMRCs influence the composition of the MNR population. (A) In unmanaged populations, the passage of time“concentrates” Soldiers who will eventually require an MEB. (B) SMRCs, in contrast, “advance” those likely to recover.



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created a new relationship between medical and operational

partners. This was evident in senior-level command meetings

in which commanders voiced fewer complaints about the

MNR and MEB systems and trumpeted more of their suc-

cesses. The committees facilitated dialog, increased transpar-

ency, fostered teamwork (in reducing no-show appointments,

for example), and ultimately built trust.

CONCLUSIONThe SMRC concept was developed in a collaborative fashion

by the 3rd ID and Winn Army Community Hospital. After

local feasibility testing, the concept was briefed to the Forces

Command Deputy Commander, the Vice Chief of Staff of the

Army, and the Chief of Staff of the Department of Veterans

Affairs. In February 2012, it became Army policy. The data

presented herein provide initial evidence of efficacy and will

hopefully catalyze ongoing Department of Defense-wide dis-

tribution. In the interim, data collection is ongoing at Fort

Stewart. In coming years, we expect to publish disposition

profiles according to type of illness and injury. These will

serve to inform Soldiers, clinicians, and commanders about

the probability and timing of recovery from the most common

medical problems encountered by Soldiers.

ACKNOWLEDGMENT

We thank Major General Robert B. Abrams, Commander of the 3rd Infantry

Division, for his efforts in support of this project. Contributions included

time, energy, support, compassion, creativity, and thoughtfulness.

REFERENCES

1. Zoroya G: U.S. deploys more than 43,000 unfit for combat. USA Today,

2008. Available at http://usatoday30.usatoday.com/news/military/2008-

05-07-nondeploy_N.htm?csp=34; accessed 13 November, 2012.

2. Zoroya G: Army sees sharp rise in unfit soldiers. USA Today, 2010.

Available at http://usatoday30.usatoday.com/news/military/2010-03-02-

unfit-soldiers_N.htm; accessed 13 November, 2012.

3. Zoroya G: Many soldiers not fit for combat for medical, other reasons.

USA Today, 2011. Available at http://usatoday30.usatoday.com/news/

military/story/2011-11-03/army-unfit-for-combat/51061380/1?csp=34news&

utm_source=feedburner&utm_medium=feed2010-03-02-unfit-soldiers_N

.htm; accessed 13 November, 2012.

4. Headquarters, Department of the Army: Army Regulation (AR) 40-501

Standards of Medical Fitness. Washington, DC, Government Printing

Office, 2007 (Rapid Action Revision, 2011).



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