0399 upper limb prostheses - aetna better health...oct 11, 2019 · myoelectric utilizes muscle...
TRANSCRIPT
(https://www.aetna.com/)
Upper Limb Prostheses
Clinical Policy Bulletins Medical Clinical Policy Bulletins
Number: 0399
*Please see amendment for Pennsylvania Medicaid at the end of this CPB.
Aetna considers the following prosthetic devices medically necessary when an artificial limb is
used to anatomically replace an absent or nonfunctioning body part with an artificial substitute:
I. Artificial arms (whole extremity or a portion thereof);
II. Artificial terminal devices (e.g., hand. hook, finger).
Aetna considers myoelectric upper limb prostheses and hand prostheses (e.g., the Dynamic
Mode Control hand, the i-LIMB, the Liberty Mutual Boston Elbow prosthetic device, the LTI
Boston Digital Arm System, the Ottobock bebionic hand, the OttoBock System Electrohand, and
the Utah Elbow System) medically necessary for members with traumatic amputation or
congenital absence of upper limb at the wrist or above (e.g., forearm or elbow) when the
following criteria are met:
Person has adequate cognitive and neurologic ability to utilize a myoelectric prosthetic
device; and The remaining musculature of the arm(s) contains the minimum microvolt threshold to
allow op eration of a myoelectric prosthetic device; and
A standard body-powered prosthetic device can not be used or is insufficient to meet
the functional needs of the person in performing activities of daily living; and
Absence of a comorbidity that cou ld interfere with m aintaining function of the
prosthesis (eg, neuromuscular disease).
Last Review
10/11/2019
Effective: 10/09/2000
Next
Review: 04/10/2020
Review
History
Definitions
Clinical Policy
Bulletin
Notes
www.aetna.com/cpb/medical/data/300_399/0399.html Proprietary 1/20
Aetna considers myoelectric upper limb and hand prostheses experimental and investigational
for all other indications because their effectiveness for indications other than the ones listed
above has not been established.
Aetna considers implantable myoelectric sensors for upper limb prostheses and hand prostheses
experimental and investigational because their effectiveness has not been established.
Aetna considers partial-hand myoelectric prostheses (e.g., ProDigits) experimental and
investigational because their effectiveness has not beenestablished.
Aetna considers transcranial direct current stimulation for enhancing performance of myoelectric
prostheses experimental and investigational because of insufficientevidence.
Aetna considers targeted muscle re-innervation for improved control of myoelectric upper limb
prostheses and treatment of painful post-amputation neuromas experimental and investigational
because its effectiveness has not been established.
Aetna considers the following medically necessary when used in conjunction with approved
prosthetic devices:
I. Supplies and accessories necessary for effective functioning of allowed equipment;or
II. Repairs or adjustments to medically necessary prosthetic devices that are required due
to bone growth or reasonable weight loss or reasonable weight gain and normal wear
and tear during normal usage of the device, or
III. Replacement of medically necessary prosthetic devices when repairs or adjustments fail
and/or are not possible.
Non-Medically Necessary Prostheses
Aetna considers the following not medically necessary:
Duplication or upgrade of a functional prosthesis; or
Prosthetic devices or prosthetic components that are primarily for cosmesis; or
Prosthetics used for activities other than normal daily living, including, but may not be
limited to, those utilized primarily for leisure or sporting activities such as skiing or
swimming; or
Repair or replacement of a prosthesis for appearance, comfort, convenience or
individual abuse, misuse or neglect; or
Repair or replacement of parts of a duplicate prosthesis; or
www.aetna.com/cpb/medical/data/300_399/0399.html Proprietary 2/20
Water prosthesis (designed to be used for showering, swimming, etc.).
For myoelectric prostheses of the lower extremity see
CPB 0578 - Lower Limb Prostheses (../500_599/0578.html).
Notes: Most Aetna plans cover prosthetic devices that temporarily or permanently replace all or
part of an external body part that is lost or impaired as a result of disease, injury or congenital
defect. The surgical implantation or attachment of covered prosthetics is covered, regardless of
whether the covered prosthetic is functional (i.e., regardless of whether the prosthetic improves
or restores a bodily function).
Prosthetic devices must be ordered or provided by a physician or under the direction of a
physician.
Evaluation of the member, measurement and/or casting, and fitting/adjustments of the prosthesis
are included in the allowance for the prosthesis. There is no separate payment for these
services.
There is no separate payment if CAD-CAM technology is used to fabricate a prosthesis.
Reimbursement is included in the allowance of the codes for a prosthesis.
Powered base items are those that contain the power source (battery). At the time that a base
item is billed, all necessary batteries and/or battery chargers are considered as included in the
payment for the powered base item. There is no separate payment for batteries (L7360, L7364,
and L7367) and/or battery chargers (L7362, L7366, and L7368) billed concurrently with a
powered base item.
Myoelectric utilizes muscle activity from the residual limb for control of joint movement.
Electromyographic signals from the limb stump are detected by surface electrodes, amplified and
then processed by a controller to drive battery powered motors that move the hand, wrist and
elbow. These devices operate on rechargeable batteries and require no external cables or
harnesses.
www.aetna.com/cpb/medical/data/300_399/0399.html Proprietary 3/20
The myoelectric hand prosthesis is an alternative to conventional hook prostheses for patients
with traumatic or congenital absence of forearm(s) and hand(s). The myoelectric prostheses are
user controlled by contraction of specific muscles triggering prosthesis movement through
electromyographic (EMG) signals. These prostheses have a stronger pinch force, better grip,
and are more flexible and easier to use than conventionalhooks..
Myoelectric control is used to operate electric motor-driven hands, wrist, and elbows. Surface
electrodes embedded in the prosthesis socket make contact with the skin and detect and amplify
muscle action potentials from voluntarily contracting muscle in the residual limb. The amplified
electrical signal turns on an electric motor to provide a function (e.g., terminal device operation,
wrist rotation, elbow flexion). The newest electronic control systems perform multiple functions,
and allow for sequential operation of elbow motion, wrist rotation and hand motions.
Myoelectric hand prostheses provide improved function and range of functional position as
compared to “hook” prostheses. Myoelectrical hand prostheses can be used for patients with
congenital limb deficiencies and for patients with amputations sustained as a result of trauma or
surgery. The device is appropriate for both above-the-elbow and below-the-elbow amputees,
and for both unilateral and bilateral amputees. Patients must possess a minimum microvolt
threshold (i.e., minimum strength of microvolt signals emitting from the remaining musculature of
the arm) and pass a control test to be considered acandidate.
Myoelectrical hand prostheses are indicated for persons at least 1 year of age or older. Children
with congenital absence of the forearm(s) and hand(s) are usually fitted with a conventional
passive prosthesis until approximately age 12 to 16 months, at which time they may be fitted with
a myoelectrical prosthesis.
Myoelectrical hand prostheses generally come with a 1-year warranty for parts and labor. The
motor and drive mechanisms typically last 2 to 3 years and may need to be replaced after this
period. When used on a child, the sockets may need to be replaced every 12 to 18 months due
to growth. With heavy use the entire prosthesis might require replacement by the 5th year.
The Work Loss Data Institute's clinical guideline on "Shoulder (acute & chronic)" (2011) listed
myoelectric upper extremity (hand and/or arm) prosthesis as one of the interventions/procedures
that were considered and recommended.
Ostlie and colleagues (2012) described patterns of prosthesis wear, perceived prosthetic
usefulness, as well as the actual use of prostheses in the performance of activities of daily life
(ADL) tasks in adult acquired upper-limb amputees (ULAs). Cross-sectional study analyzing
population-based questionnaire data (n = 224) and data from interviews and clinical testing in a
www.aetna.com/cpb/medical/data/300_399/0399.html Proprietary 4/20
referred/convenience sample of prosthesis-wearing ULAs (n = 50). Effects were analyzed using
linear regression; 80.8 % wore prostheses and 90.3 % reported their most worn prosthesis as
useful. Prosthetic usefulness profiles varied with prosthetic type. Despite demonstrating good
prosthetic skills, the amputees reported actual prosthesis use in only about 50 % of the ADL
tasks performed in everyday life. In unilateral amputees, increased actual use was associated
with sufficient prosthetic training and with the use of myoelectric versus cosmetic prostheses,
regardless of amputation level. Prosthetic skills did not affect actual prosthesis use. No
background factors showed significant effect on prosthetic skills. The authors concluded that
most major ULAs wear prostheses. They stated that individualized prosthetic training and fitting
of myoelectric rather than passive prostheses may increase actual prosthesis use in ADL.
There are many brands of myoelectric hand prostheses on the market. Brands of myoelectrical
hand prostheses include the Otto Bock myoelectrical prosthesis (Otto Bock, Minneapolis, MN),
the Liberty Mutual Boston Elbow prosthetic device (Liberty Mutual, Boston, MA), and the Utah
Elbow System (Motion Control, Salt Lake City, UT).
Partial-hand myoelectric prostheses are designed to replace the function of digits in individuals
missing 1 or more fingers as a result of a partial-hand amputation. This type of prosthetic device
requires a very specific range of amputation, i.e., amputation level through, or just proximal to,
the metacarpal-phalangeal level of 1 or more digits.
Putzi (1992) reported the case of a young man who had 2 traumatic amputations and burns
covering 80 % of his body. Due to his severe burns, fitting a conventional prosthesis was a
problem because normal procedures did not apply in his case. The patient was fitted with a
myoelectric partial-hand prosthesis. The author concluded that this reconstruction of the
myoelectric prosthesis was a satisfactory solution in providing the patient with as much hand and
arm mobility as possible in light of his condition. By using basic principles of orthotics and
prosthetics, and exercising ingenuity in using existing proven components, it is possible to
provide improvement in function and cosmetics to an individual with a partial-hand amputation.
Lake (2009) provided a review of progressive partial-hand prosthetic management. The author
noted that partial-hand prosthetic management represents an exciting new frontier in the
specialty of upper limb prosthetics. The application and benefit of treating this level are
apparent. Presently, this level is very difficult because of the vast surgical presentations,
traumatic nature of the resultant limb difference, as well as the complicated biomechanics
present as a result of the afore-mentioned 2 issues. Lake (2009) noted that electric prosthetic
management requires specialized care that does not have its foundation rooted in any of the
current, yet progressive upper limb care protocols used by today's specialists. Future research
will entail electronic handling, fabrication, fitting protocols and techniques, as well as surgical
www.aetna.com/cpb/medical/data/300_399/0399.html Proprietary 5/20
considerations. As fitting techniques and componentry evolve, so will the clinical protocols. The
author stated that an unique opportunity exists at the partial-hand level as this specialty enters a
new prosthetic paradigm where evidence-based rehabilitation and sound research practices are
expected by both the medical community as well as reimbursement agencies.
Currently, there is insufficient peer-reviewed evidence that examined the clinical value (e.g.,
improved function and health-related quality of life) of partial-hand myoelectric prostheses.
Dutta et al (2014) noted that functional electrical stimulation (FES) can electrically activate
paretic muscles to assist movement for post-stroke neurorehabilitation. Here, sensory-motor
integration may be facilitated by triggering FES with residual EMG activity. However, muscle
activity following stroke often suffers from delays in initiation and termination which may be
alleviated with an adjuvant treatment at the central nervous system (CNS) level with transcranial
direct current stimulation (tDCS) thereby facilitating re-learning and retaining of normative
muscle activation patterns. This study on 12 healthy volunteers was conducted to investigate
the effects of anodal tDCS of the primary motor cortex (M1) and cerebellum on latencies during
isometric contraction of tibialis anterior (TA) muscle for myoelectric visual pursuit with quick
initiation/termination of muscle activation, i.e., “ballistic EMG control” as well as modulation of
EMG for “proportional EMG control”. The normalized delay in initiation and termination of
muscle activity during post-intervention “ballistic EMG control” trials showed a significant main
effect of the anodal tDCS target: cerebellar, M1, sham (F(2) = 2.33, p < 0.1), and interaction
effect between tDCS target and step-response type: initiation/termination of muscle activation
(F(2) = 62.75, p < 0.001), but no significant effect for the step-response type (F(1) = 0.03, p =
0.87). The post-intervention population marginal means during “ballistic EMG control” showed 2
important findings at 95 % confidence interval (CI [critical values from Scheffe's S procedure]): (i)
Offline cerebellar anodal tDCS increased the delay in initiation of TA contraction while M1
anodal tDCS decreased the same when compared to sham tDCS; and (ii) Offline M1 anodal
tDCS increased the delay in termination of TA contraction when compared to cerebellar
anodal tDCS or sham tDCS. Moreover, online cerebellar anodal tDCS decreased the learning
rate during “proportional EMG control” when compared to M1 anodal and sham tDCS. The
authors concluded that these preliminary findings from healthy subjects showed specific, and at
least partially antagonistic effects, of M1 and cerebellar anodal tDCS on motor performance
during myoelectric control. They stated that these results are encouraging, but further studies
are needed to better define how tDCS over particular regions of the cerebellum may facilitate
learning of myoelectric control for brain machine interfaces.
www.aetna.com/cpb/medical/data/300_399/0399.html Proprietary 6/20
Pan et al (2015) stated that most prosthetic myoelectric control studies have shown good
performance for unimpaired subjects. However, performance is generally unacceptable for
amputees. The primary problem is the poor quality of EMG signals of amputees compared with
healthy individuals. To improve clinical performance of myoelectric control, these researchers
explored tDCS to modulate brain activity and enhance EMG quality. These investigators tested 6
unilateral transradial amputees by applying active and sham anodal tDCS separately on 2
different days. Surface EMG signals were acquired from the affected and intact sides for eleven
hand and wrist motions in the pre-tDCS and post-tDCS sessions. Auto-regression (AR)
coefficients and linear discriminant analysis (LDA) classifiers were used to process the EMG
data for pattern recognition of the 11 motions. For the affected side, active anodal tDCS
significantly reduced the average classification error rate (CER) by 10.1 %, while sham tDCS
had no such effect. For the intact side, the average CER did not change on the day of sham
tDCS but increased on the day of active tDCS. The authors concluded that these findings
demonstrated that tDCS could modulate brain function and improve EMG-based classification
performance for amputees. They stated that iIt has great potential in dramatically reducing the
length of learning process of amputees for effectively using myoelectrically-controlled multi-
functional prostheses.
Implantable Myoelectric Sensors
Pasquina and colleagues (2015) stated that advanced motorized prosthetic devices are currently
controlled by EMG signals generated by residual muscles and recorded by surface electrodes on
the skin. These surface recordings are often inconsistent and unreliable, leading to high
prosthetic abandonment rates for individuals with upper limb amputation. Surface electrodes are
limited because of poor skin contact, socket rotation, residual limb sweating, and their ability to
only record signals from superficial muscles, whose function frequently does not relate to the
intended prosthetic function. More sophisticated prosthetic devices require a stable and reliable
interface between the user and robotic hand to improve upper limb prosthetic function.
Implantable Myoelectric Sensors (IMES) are small electrodes intended to detect and wirelessly
transmit EMG signals to an electro-mechanical prosthetic hand via an electro-magnetic coil built
into the prosthetic socket. This system is designed to simultaneously capture EMG signals from
multiple residual limb muscles, allowing the natural control of multiple degrees of freedom
simultaneously. In a case report, these investigators reported the status of the first Food and
Drug Administration (FDA)-approved clinical trial of the IMES System. This study is currently in
progress, limiting reporting to only preliminary results. The first subject has reported the ability to
accomplish a greater variety and complexity of tasks in his everyday life compared to what could
be achieved with his previous myoelectric prosthesis. The authors concluded that the interim
www.aetna.com/cpb/medical/data/300_399/0399.html Proprietary 7/20
results of this study indicated the feasibility of utilizing IMES technology to reliably sense and
wirelessly transmit EMG signals from residual muscles to intuitively control a 3 degree-of-
freedom prosthetic arm.
Bergmeister et al (2016) noted that myoelectric prostheses lack a strong human-machine
interface, leading to high abandonment rates in upper limb amputees. Implantable wireless
EMG systems improve control by recording signals directly from muscle, compared with surface
EMG. These devices do not exist for high amputation levels. These researchers presented an
implantable wireless EMG system for these scenarios tested in Merino sheep for 4 months. In a
pilot trial, the electrodes were implanted in the hind limbs of 24 Sprague-Dawley rats. After 8 or
12 weeks, impedance and histocompatibility were assessed. In the main trial, the system was
tested in 4 Merino sheep for 4 months. Impedance of the electrodes was analyzed in 2 animals;
EMG data were analyzed in 2 freely moving animals repeatedly during forward and backward
gait. Device implantation was successful in all 28 animals. Histologic evaluation showed a tight
encapsulation after 8 weeks of 78.2 ± 26.5 µm subcutaneously and 92.9 ± 31.3 µm on the
muscular side. Electromyographic recordings showed a distinct activation pattern of the triceps,
brachialis, and latissimus dorsi muscles, with a low signal-to-noise ratio, representing specific
patterns of agonist and antagonist activation. Average electrode impedance decreased over the
whole frequency range, indicating an improved electrode-tissue interface during the implantation.
All measurements taken over the 4 months of observation used identical settings and showed
similar recordings despite changing environmental factors. The authors concluded that the
findings of this study showed the implantation of this EMG device as a promising alternative to
surface EMG, providing a potentially powerful wireless interface for high-level amputees.
Partial-Hand Myoelectric Prostheses
Earley et al (2016) stated that although partial-hand amputees largely retain the ability to use
their wrist, it is difficult to preserve wrist motion while using a myoelectric partial-hand prosthesis
without severely impacting control performance. Electromyogram (EMG) pattern recognition is a
well-studied control method; however, EMG from wrist motion can obscure myoelectric finger
control signals. Thus, to accommodate wrist motion and to provide high classification accuracy
and minimize system latency, these researchers developed a training protocol and a classifier
that switches between long and short EMG analysis window lengths. A total of 17 non-amputee
and 2 partial-hand amputee subjects participated in a study to determine the effects of including
EMG from different arm and hand locations during static and/or dynamic wrist motion in the
classifier training data. They evaluated several real-time classification techniques to determine
which control scheme yielded the highest performance in virtual real-time tasks using a 3-way
ANOVA. These investigators found significant interaction between analysis window length and
the number of grasps available. Including static and dynamic wrist motion and intrinsic hand
www.aetna.com/cpb/medical/data/300_399/0399.html Proprietary 8/20
muscle EMG with extrinsic muscle EMG significantly reduced pattern recognition classification
error by 35 %. Classification delay or majority voting techniques significantly improved real-time
task completion rates (17 %), selection (23 %), and completion (11 %) times, and selection
attempts (15 %) for non-amputee subjects, and the dual window classifier significantly reduced
the time (8 %) and average number of attempts required to complete grasp selections (14 %)
made in various wrist positions. Amputee subjects demonstrated improved task timeout rates,
and made fewer grasp selection attempts, with classification delay or majority voting techniques.
Thus, the authors concluded that the proposed techniques showed promise for improving control
of partial-hand prostheses and more effectively restoring function to individuals using these
devices.
Adewuy et al (2016) noted that pattern recognition-based myoelectric control of upper-limb
prostheses has the potential to restore control of multiple degrees of freedom. Though this
control method has been extensively studied in individuals with higher-level amputations, few
studies have investigated its effectiveness for individuals with partial-hand amputations. Most
partial-hand amputees retain a functional wrist and the ability of pattern recognition-based
methods to correctly classify hand motions from different wrist positions is not well studied. In
this study, focusing on partial-hand amputees, these researchers evaluated (i) the performance
of non-linear and linear pattern recognition algorithms, and (ii) the performance of optimal
EMG feature subsets for classification of 4 hand motion classes in different wrist positions
for 16 non-amputees and 4 amputees. The results showed that linear discriminant analysis
and linear and non-linear artificial neural networks performed significantly better than the
quadratic discriminant analysis for both non-amputees and partial-hand amputees. For
amputees, including information from multiple wrist positions significantly decreased error (p < 0.001)
but no further significant decrease in error occurred when more than 4, 2, or 3 positions
were included for the extrinsic (p = 0.07), intrinsic (p = 0.06), or combined extrinsic and intrinsic
muscle EMG (p = 0.08), respectively. Finally, the authors found that a feature set determined by
selecting optimal features from each channel outperformed the commonly used time domain
(TD) (p < 0.001) and time domain/autoregressive feature sets (p < 0.01). This method can be
used as a screening filter to select the features from each channel that provide the best
classification of hand postures across different wrist positions. They stated that these findings
suggested that some of the widely used TD features were better suited for use with intrinsic
muscle EMG data than extrinsic muscle data for good control across multiple wrist positions.
Moreover, they noted that further analysis of data from amputees completing tasks with the wrist
in different positions in a virtual environment or with a physical prosthesis is needed.
www.aetna.com/cpb/medical/data/300_399/0399.html Proprietary 9/20
Adewuy et al (2017) stated that that the use of pattern recognition-based methods to control
myoelectric upper-limb prostheses has been well studied in individuals with high-level
amputations but few studies have demonstrated that it is suitable for partial-hand amputees, who
often possess a functional wrist. These investigators evaluated strategies that allow partial-hand
amputees to control a prosthetic hand while allowing retain wrist function. EMG data were
recorded from the extrinsic and intrinsic hand muscles of 6 non-amputees and 2 partial-hand
amputees while they performed 4 hand motions in 13 different wrist positions. The performance
of 4 classification schemes using EMG data alone and EMG data combined with wrist positional
information was evaluated. Using recorded wrist positional data, the relationship between EMG
features and wrist position was modeled and used to develop a wrist position-independent
classification scheme. A multi-layer perceptron artificial neural network classifier was better able
to discriminate 4 hand motion classes in 13 wrist positions than a linear discriminant analysis
classifier (p = 0.006), quadratic discriminant analysis classifier (p < 0.0001) and a linear
perceptron artificial neural network classifier (p = 0.04). The addition of wrist position data to
EMG data significantly improved performance (p < 0.001). Training the classifier with the
combination of extrinsic and intrinsic muscle EMG data performed significantly better than using
intrinsic (p < 0.0001) or extrinsic muscle EMG data alone (p < 0.0001), and training with intrinsic
muscle EMG data performed significantly better than extrinsic muscle EMG data alone (p < 0.001).
The same trends were observed for amputees, except training with intrinsic muscle
EMG data, on average, performed worse than the extrinsic muscle EMG data. These
researchers proposed a wrist position-independent controller that simulated data from multiple
wrist positions and was able to significantly improve performance by 48 to 74 % (p < 0.05) for
non-amputees and by 45 to 66 % for partial-hand amputees, compared to a classifier trained
only with data from a neutral wrist position and tested with data from multiple positions. The
authors concluded that sensor fusion (using EMG and wrist position information), non-linear
artificial neural networks, combining EMG data across multiple muscle sources, and simulating
data from different wrist positions were effective strategies for mitigating the wrist position effect
and improving classification performance.
The authors stated that these results were limited in that the training and testing data sets were
from the same day and experimental session. Although pattern recognition control deteriorated
when classifiers were trained and tested with data collected from different days or sessions, a
recent study has shown that between-day performance improved and approached within-day
performance when subjects performed contractions over 11 consecutive days. These results
implied that subjects were better able to make more consistent contractions when training over
multiple days. It was thus possible that the mapping between EMG features and wrist position
would be stable if subjects were trained over multiple days. They stated that further multi-day
experiments are needed to determine if the neural network maintains its performance across
sessions. One important consideration regarding the neural network regression model was that
www.aetna.com/cpb/medical/data/300_399/0399.html Proprietary 10/20
these researchers assumed each feature was independent and thus the change in feature as a
function of wrist position was predicted separately for each feature. Consequently these
researchers lost any some mutual information across the features. Even with this loss of
information, the performance using the model-generated data particularly with intrinsic and
extrinsic muscles performed just as well as the real data set, implying that the issue was not
critical. Perhaps this was because there were enough data from enough features to overcome
this. It was possible however, that preserving the relation and co-variability between features
would better allow the model-generated data to more accurately predict the feature changes and
improve performance. Another potential drawback was that the analyses were performed off-line
and with only 4 hand motion classes (2 grasps, hand open and no movement). The authors
expected classification error to increase when more hand grasps were available to the classifier
though future work is needed to evaluate the extent to which wrist position information improves
error and to determine if the performance of the simulated dataset generalize to more grasps.
The relationship between off-line error and real-time performance is unclear. Some previous
research had demonstrated a minimal correlation between off-line performance and usability with
a virtual task; however other studies have shown significant correlation between off-line
classification error and real-time control. These researchers stated that although the findings of
this study were promising, further real-time experiments in a virtual environment or with a
physical prosthesis are needed.
Targeted Muscle Re-Innervation
Kuiken and co-workers (2017) stated that myoelectric devices are controlled by EMG signals
generated by contraction of residual muscles, which thus serve as biological amplifiers of neural
control signals. Although nerves severed by amputation continue to carry motor control
information intended for the missing limb, loss of muscle effectors due to amputation prevents
access to this important control information. Targeted muscle re-innervation (TMR) was
developed as a novel strategy to improve control of myoelectric upper limb prostheses. Severed
motor nerves are surgically transferred to the motor points of denervated target muscles, which,
after re-innervation, contract in response to neural control signals for the missing limb; TMR
creates additional control sites, eliminating the need to switch the prosthesis between different
control modes. In addition, contraction of target muscles, and operation of the prosthesis, occurs
in response to attempts to move the missing limb, making control easier and more intuitive. The
authors concluded that TMR has been performed extensively in individuals with high-level upper
limb amputations and has been shown to improve functional prosthesis control. The benefits of
TMR are being studied in individuals with trans-radial amputations and lower limb amputations;
TMR is also being investigated in an ongoing clinical trial as a method to prevent or treat painful
amputation neuromas.
www.aetna.com/cpb/medical/data/300_399/0399.html Proprietary 11/20
Vadala and colleagues (2017) stated that TMR is a novel surgical technique developed to
improve the control of myoelectric upper limb prostheses. Nerves transected by the amputation,
which retain their original motor pathways even after being severed, are re-directed to residual
denervated muscles that serve as target for consequent re-innervation. Once the process is
complete, re-innervated muscles will contract upon voluntary activation of transferred nerves
while attempting to move missing regions of the amputated limb, generating EMG signals that
can be recorded and used to control a prosthetic device. This allows creating new control sites
that can overcome major drawbacks of conventional myoelectric prostheses by offering a more
natural and intuitive control of prosthetic arms. These researchers noted that TMR has been
widely performed in individuals who underwent shoulder disarticulation amputation and trans-
humeral amputation since proximal amputations do not leave enough functional muscles
exploitable to control independent degree of freedoms of multi-articulated prostheses. The
authors concluded that TMR application is currently under investigation in patients suffering
further distal amputations, as well as for treating and preventing painful post-amputation
neuromas.
Bowen and associates (2017) noted that there are approximately 185,000 amputations each
year and nearly 2 million amputees currently living in the United States. About 25 % of these
amputees will experience chronic pain issues secondary to localized neuroma pain and/or
phantom limb pain. The significant discomfort caused by neuroma and phantom limb pain
interferes with prosthesis wear, subjecting amputees to the additional physical and psychological
morbidity associated with chronic immobility. Although numerous neuroma treatments are
described, none of these methods is consistently effective in eliminating symptoms. Targeted
muscle re-innervation is a surgical technique involving the transfer of residual peripheral nerves
to redundant target muscle motor nerves, restoring physiological continuity and encouraging
organized nerve regeneration to decrease and potentially prevent the chaotic and mis-directed
nerve growth, which can contribute to pain experienced within the residual limb. These
researchers stated that TMR represents one of the more promising treatments for neuroma pain.
Prior research into "secondary" TMR performed in a delayed manner after amputation has
shown great improvement in treating amputee pain issues because of peripheral nerve
dysfunction. "Primary" TMR performed at the time of amputation suggested that it may prevent
neuroma formation while avoiding the risks associated with a delayed procedure. In addition,
TMR allows the target muscles to act as bio-amplifiers to direct bioprosthetic control and
function. The authors concluded that TMR has the potential to treat pain from neuromas while
enabling amputee patients to return to their ADL and improve prosthetic use and tolerance.
They stated that recent research in the areas of secondary (i.e., delayed) and primary TMR aims
to optimize efficacy and efficiency and demonstrated great potential for establishing a new
standard of care for amputees.
www.aetna.com/cpb/medical/data/300_399/0399.html Proprietary 12/20
Moreover, these investigators stated that if successful, primary TMR will reduce the total number
of surgeries, thus eliminating recovery time and other risks associated with additional operations.
It is their hope that prevention of neuroma and phantom limb pain (NPLP) symptoms will lead to
earlier, more consistent, and comfortable prosthesis use and improved health outcomes overall.
The results of primary TMR will continue to be examined through close patient follow-up to
determine its long-term effects on NPLP prevention.
CPT Codes / HCPCS Codes / ICD-10 Codes
Information in the [brackets] below has been added for clarification purposes. Codes requiring a 7th character are represented by "+":
Code Code D escription
CPT codes not covered for indications listed in the CPB:
- no specific code:
Other CPT codes related to the CPB:
24900 -24935,
25900 -25931,
26910 - 29652
Surgical amputation, upper extremity
HCPCS codes covered if selection criteria are met:
L6000 Partial hand, thumb remaining
L6010 Partial hand, little and/or ring finger remaining
L6020 Partial hand, no finger remaining
L6050 Wrist disarticulation, molded socket, flexible elbow hinges, triceps pad
L6055 Wrist disarticulation, molded socket with expandable interface, flexible elbow hinges,
triceps pad
L6100 Below elbow, molded socket, flexible elbow hinge, triceps pad
L6110 Below elbow, molded socket, (muenster or northwestern suspension types)
L6120 Below elbow, molded double wall split socket, step-up hinges, half cuff
L6130 Below elbow, molded double wall split socket, stump activated locking hinge, half
cuff
L6200 Elbow disarticulation, molded socket, outside locking hinge, forearm
L6205 Elbow disarticulation, molded socket with expandable interface, outside locking
hinges, forearm
L6250 Above elbow, molded double wall socket, internal locking elbow, forearm
www.aetna.com/cpb/medical/data/300_399/0399.html#dummyLink2 Proprietary 13/20
Code Code Description
L6300 Shoulder disarticulation, molded socket, shoulder bulkhead, humeral section,
internal locking elbow, forearm
L6310 Shoulder disarticulation, passive restoration (complete prosthesis)
L6320 Shoulder disarticulation, passive restoration (shoulder cap only)
L6629 Upper extremity addition, quick disconnect lamination collar with coupling piece,
Otto Bock or equal
L6632 Upper extremity addition, latex suspension sleeve, each
L6680 Upper extremity addition, test socket, wrist disarticulation or below elbow
L6687 Upper extremity addition, frame type socket, below elbow or wrist disarticulation
L6703 Terminal device, passive hand/mitt, any material, any size
L6704 Terminal device, sport/recreational/work attachment, any material, any size
L6706 Terminal device, hook, mechanical, voluntary opening, any material, any size, lined
or unlined
L6707 Terminal device, hook, mechanical, voluntary closing, any material, any size, lined or
unlined
L6708 Terminal device, hand, mechanical, voluntary opening, any material, any size
L6709 Terminal device, hand, mechanical, voluntary closing, any material, any size
L6711 Terminal device, hook, mechanical, voluntary opening, any material, any size, lined
or unlined, pediatric
L6712 Terminal device, hook, mechanical, voluntary closing, any material, any size, lined or
unlined, pediatric
L6713 Terminal device, hand, mechanical, voluntary opening, any material, any size,
pediatric
L6714 Terminal device, hand, mechanical, voluntary closing, any material, any size,
pediatric
L6715 Terminal device, multiple articulating digit, includes motor(s), initial issue or
replacement
L6721 Terminal device, hook or hand, heavy duty, mechanical, voluntary opening, any
material, any size, lined or unlined
L6722 Terminal device, hook or hand, heavy duty, mechanical, voluntary closing, any
material, any size, lined or unlined
L6810 Addition to terminal device, precision pinch device
www.aetna.com/cpb/medical/data/300_399/0399.html#dummyLink2 Proprietary 14/20
Code Code Description
L6880 Electric hand, switch or myoelectric controlled, independently articulating digits, any
grasp pattern or combination of grasp patterns, includes motor(s)
L6882 Microprocessor control feature, addition to upper limb prosthetic terminal device
L6890 Addition to upper extremity prosthesis, glove for terminal device, any material,
prefabricated, includes fitting and adjustment
L6925 Wrist disarticulation, external power, self-suspended inner socket, removable
forearm shell, Otto Bock or equal electrodes, cables, two batteries and one charger,
myoelectronic control of terminal device
L6935 Below elbow, external power, self-suspended inner socket, removable forearm shell,
Otto Bock or equal electrodes, cables, two batteries and one charger, myoelectronic
control of terminal device
L6945 Elbow disarticulation, external power, molded inner socket, removable humeral shell,
outside locking hinges, forearm, Otto Bock or equal electrodes, cables, two batteries
and one charger, myoelectronic control of terminal device
L6955 Above elbow, external power, molded inner socket, removable humeral shell,
internal locking elbow, forearm, Otto Bock or equal electrodes, cables, two batteries
and one charger, myoelectronic control of terminal device
L6965 Shoulder disarticulation, external power, molded inner socket, removable shoulder
shell, shoulder bulkhead, humeral section, mechanical elbow, forearm, Otto Bock or
equal electrodes, cables, two batteries and one charger, myoelectronic control of
terminal device
L6975 Interscapular-thoracic, external power, molded inner socket, removable shoulder
shell, shoulder bulkhead, humeral section, mechanical elbow, forearm, Otto Bock or
equal electrodes, cables, two batteries and one charger, myoelectronic control of
terminal device
L7007 - L7008 Electric hand, switch or myoelectric controlled, adult or pediatric
L7009, L7045 Electric hook, switch or myoelectric controlled, adult or pediatric
L7190 - L7191 Electronic elbow, variety village or equal, myoelectronically controlled, adolescent or
child
L7259 Electronic wrist rotator, any type
L7368 Lithium ion battery charger
L7400 Addition to upper extremity prosthesis, below elbow/wrist disarticulation, ultralight
material (titanium, carbon fiber or equal)
www.aetna.com/cpb/medical/data/300_399/0399.html#dummyLink2 Proprietary 15/20
Code Code Description
L7403 Addition to upper extremity prosthesis, below elbow/wrist disarticulation, acrylic
material
L8465 Prosthetic shrinker, upper limb, each
HCPCS codes not covered for indications listed in the CPB:
Implantable myoelectric sensors for upper limb prostheses and hand prostheses, water prosthesis:
No specific code
L6026 Transcarpal/metacarpal or partial hand disarticulation prosthesis, external power,
self-suspended, inner socket with removable forearm section, electrodes and
cables, two batteries, charger, myoelectric control of terminal device, excludes
terminal device(s)
Other HCPCS codes related to the CPB:
L7360 Six volt battery, each
L7362 Battery charger, six volt, each
L7364 Twelve volt battery, each
L7366 Battery charger, twelve volt, each
L7367 Lithium ion battery, rechargeable, replacement
L7368 Lithium ion battery charger, replacement only
ICD-10 codes covered if selection criteria are met:
Q71.00 - Q71.53
Q71.811 - Q71.93
Reduction defects of upper limb
S48.011+ -
S48.929+
Traumatic amputation of shoulder and upper arm
S58.011+ -
S58.929+
Traumatic amputation of elbow and forearm
S68.411+ -
S68.429+,
S68.711+ -
S68.729+
Traumatic amputation of hand
www.aetna.com/cpb/medical/data/300_399/0399.html#dummyLink2 Proprietary 16/20
Code Code Description
S48.911+,
S48.921+,
S58.911+, S58.921+
[S48.912+,
S48.922+,
S58.912+,
S58.922+ also
required]
Traumatic amputation of shoulder and upper arm and forearm, level unspecified
(complete) (partial), bilateral
Z89.011 - Z89.239 Acquired absence of upper limb
ICD-10 codes not covered for indications listed in the CPB (not all-inclusive):
G00 - G99 Diseases of nervous system [neuromuscular disease that interferes with prosthesis
function]
T87.31 Neuroma of amputation stump, right upper extremity
T87.32 Neuroma of amputation stump, left upper extremity
1. Nader M. The artificial substitution of missing hands with myoelectrical prostheses.
Clin Orthop. 1990;(258):9-17.
2. Silcox DH, Rooks MD, Vogel RR, et al. Myoelectric prostheses. A long-term follow-up
and a study of the use o f alternative prostheses. J Bone Joint Surg Am.
1993;75(12):1781-1789.
3. Weaver SA, Lange LR, Vogts VM. Comparison of myoelectric and conventional
prostheses for adolescent amputees. Am J Occup Ther. 1988;42(2):87-91.
4. Scott RN, Parker PA. Myoelectric prostheses: State of the art. J Med Eng Technol.
1988;12(4):143-151.
5. Kritter AE. Myoelectric prostheses. J Bone Joint Surg Am. 1985;67(4):654-657.
6. Stein RB, Walley M. Functional comparison of upper extremity amputees using
myoelectric and conventional prostheses. Arch Phys Med Rehabil. 1983;64(6):243-248.
7. Leonard JA, Meier RH. Upper and lower extremity prosthetics. In: Rehabilitation
Medicine: Principles and Practice. 2nd ed. JA DeLisa, ed. Philadelphia, PA: J.B. Lippincott
Co.; 1993:507, 514-515.
8. Otto Bock, Inc. Myoelectrical prostheses. Minneapolis, MN: Otto Bock; 1999. Available
at: http://www.ottobockus.com/. Accessed June 11, 2001.
www.aetna.com/cpb/medical/data/300_399/0399.html#dummyLink2 Proprietary 17/20
9. Motion Control, Inc. The Utah Arm. Salt Lake City, UT: Motion Control; 1999. Available
at: http://www.utaharm.com/. Accessed June 11, 2001.
10. Routhier F, Vincent C, Morissette MJ, et al. Clinical results of an investigation of
paediatric upper limb myoelectric prosthesis fitting at the Quebec Rehabilitation
Institute. Prosthet Orthot Int. 2001;25(2):119-131.
11. Esquenazi A. Amputation rehabilitation and prosthetic restoration. From surgery to
community reintegration. Disabil Rehabil. 2004;26(14-15):831-836.
12. Hsu MJ, Nielsen DH, Lin-Chan SJ, Shurr D. The effects of prosthetic foot design on
physiologic measurements, self-selected walking velocity, and physical activity in
people with transtibial amputation. Arch Phys Med Rehabil. 2006;87(1):123-129.
13. Butter M, Rensma A, van Boxsel J, et al. Robotics for Healthcare. Final Report. Version 5.
Prepared by TNO for the European Commission, DG Information Society. Delft, The
Netherlands: Netherlands Organization for Applied Scientific Research (TNO); October
3, 2008.
14. Egermann M, Kasten P, Thomsen M. Myoelectric hand prostheses in very young
children. Int Orthop. 2009;33(4):1101-1105.
15. Kelly BM, Pangilnan PH Jr, Rodriguez GM, et al. Upper limb prosthetics. eMedicine
Physical Medicine and Rehabilitation. New York, NY: Medscape; January 14, 2009.
16. Castellini C, Fiorilla AE, Sandini G. Multi-subject/daily-life activity EMG-based control of
mechanical hands. J Neuroeng Rehabil. 2009;6:41.
17. Otr OV, Reinders-Messelink HA, Bongers RM, et al. The i-LIMB hand and the DMC plus
hand compared: A case report. Prosthet Orthot Int. 2010;34(2):216-220.
18. Putzi R. Myoelectric partial-hand prosthesis. J Prosthet Orthot. 1992;4(2):103-108.
19. Lake C. Experience with electric prostheses for the partial hand presentation: An eight-
year retrospective. J Prosthet Orthot. 2009;21(2):125-130.
20. Work Loss Data Institute. Shoulder (acute & chronic). Encinitas, CA: Work Loss Data
Institute; 2011.
21. Ostlie K, Lesjo IM, Franklin RJ, et al. Prosthesis use in adult acquired major upper-limb
amputees: Patterns of wear, prosthetic skills and the actual use of prostheses in
activities of daily life. Disabil Rehabil Assist Technol. 2012;7(6):479-493.
22. Dutta A, Paulus W, Nitsche MA. Facilitating myoelectric-control with transcranial direct
current stimulation: A preliminary study in healthy humans. J Neuroeng Rehabil.
2014;11:13.
23. Pan L, Zhang D, Sheng X, Zhu X. Improving myoelectric control for amputees through
transcranial direct current stimulation. IEEE Trans Biomed Eng. 2015;62(8):1927-1936.
24. Carey SL, Lura DJ, Highsmith MJ, et al. Differences in m yoelectric and body-powered
upper-limb prostheses: Systematic literature review. J Rehabil Res Dev. 2015;52(3):247-
262.
www.aetna.com/cpb/medical/data/300_399/0399.html#dummyLink2 Proprietary 18/20
25. Pasquina PF, Evangelista M, Carvalho AJ, et al. First-in-man demonstration of a fully
implanted myoelectric sensors system to control an advanced electromechanical
prosthetic hand. J Neurosci Methods. 2015;244:85-93.
26. Bergmeister KD1, Hader M, Lewis S, et al. Prosthesis control with an implantable
multichannel wireless electromyography system for high-level amputees: A large-
animal study. Plast Reconstr Surg. 2016;137(1):153-162.
27. Earley EJ, Hargrove LJ, Kuiken TA. Dual window pattern recognition classifier for
improved partial-hand prosthesis control. Front Neurosci. 2016;10:58.
28. Adewuyi AA, Hargrove LJ, Kuiken TA. Evaluating EMG feature and classifier selection for
application to partial-hand prosthesis control. Front Neurorobot. 2016;10:15.
29. Adewuyi AA, Hargrove LJ, Kuiken TA. Resolving the effect of wrist position on
myoelectric pattern recognition control. J Neuroeng Rehabil. 2017;14(1):39.
30. Kuiken TA, Barlow AK, Hargrove L, Dumanian GA. Targeted muscle reinnervation for
the upper and lower extremity. Tech Orthop.2017;32(2):109-116.
31. Vadala G, Di Pino G, Ambrosio L, et al. Targeted muscle reinnervation for improved
control of myoelectric upper limb prostheses. J Biol Regul Homeost Agents. 2017;31(4
suppl 1):183-189.
32. Bowen JB, Wee CE, Kalik J, Valerio IL. Targeted muscle reinnervation to improve pain,
prosthetic tolerance, and bioprosthetic outcomes in the amputee. Adv Wound Care
(New Rochelle). 2017;6(8):261-267.
33. Centers for Medicare & Medicaid Services (CMS). Leg, Arm, Back, and Neck Braces,
Trusses, and Artificial Legs, Arms, and Eyes. Medicare Benefit Policy Manual, Chapter
15, Section 130. Baltimore, MD: CMS; revised October 1,2003.
www.aetna.com/cpb/medical/data/300_399/0399.html#dummyLink2 Proprietary 19/20
Copyright Aetna Inc. All rights reserved. Clinical Policy Bulletins are developed by Aetna to assist in administering plan benefits and
constitute neither offers of coverage nor medical advice. This Clinical Policy Bulletin contains only a partial, general description of plan or
program benefits and does not constitute a contract. Aetna does not provide health care services and, therefore, cannot guarantee any
results or outcomes. Participating providers are independent contractors in private practice and are neither employees nor agents of Aetna
or its affiliates. Treating providers are solely responsible for medical advice and treatment of members. This Clinical Policy Bulletin may be
updated and therefore is subject to change.
Copyright © 2001-2019 Aetna Inc.
www.aetna.com/cpb/medical/data/300_399/0399.html#dummyLink2 Proprietary 20/20
AETNA BETTER HEALTH® OF PENNSYLVANIA
Amendment to Aetna Clinical PolicyBulletin Number: 0399
Upper Limb Prosthesis
There are no amendments for Medicaid.
www.aetnabetterhealth.com/pennsylvania revised 10/10/2019
Proprietary