Assessment of Patient-Reported Physical Function in Persons With Upper Extremity Amputation

Resnik, Linda; Stevens, Phillip M.; Ni, Pengsheng; Borgia, Matthew; Clark, Melissa A.

doi:10.1097/phm.0000000000002044

Cited by 7 publications

(8 citation statements)

References 25 publications

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“…Our finding that there were no differences in PROMIS-13 UE AMP scores between current prosthesis users and nonusers has been previously reported and suggests a limitation of the measure in being able to distinguish persons with ULA by prosthesis use 20 . However, our study found that prosthesis nonusers with unmet need had lower PROMIS-13 UE AMP scores as compared with nonusers without unmet need.…”

Section: Discussionsupporting

confidence: 62%

“…Participants also indicated reasons (more than one could be chosen) for abandoning or never using a prosthesis. The survey also included the Patient-Reported Outcomes Measurement Information System 13-item short form measure of UL function scored with amputation-specific Rasch calibration (PROMIS-13 UE AMP) 20 …”

Section: Methodsmentioning

confidence: 99%

“…The survey also included the Patient-Reported Outcomes Measurement Information System 13-item short form measure of UL function scored with amputation-specific Rasch calibration (PROMIS-13 UE AMP). 20…”

Section: Surveymentioning

confidence: 99%

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Prevalence and Predictors of Unmet Need for Upper-Limb Prostheses: An Observational Cohort Study

2023

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Introduction No prior studies have examined the prevalence of unmet prosthesis need among prosthesis nonusers. Objectives The aim of this study was to describe the prevalence of unmet need for an upper-limb prosthesis and identify independent covariates associated with unmet need for a prosthesis. Study Design This study is a telephone survey of 742 persons with upper-limb amputation (ULA). Methods Differences between users and nonusers and between nonusers with and without an unmet need were compared statistically. Covariates associated with unmet need P ≤ 0.2 in bivariate analyses were included in a multivariate logistic regression model predicting unmet need. Results Odds of unmet need were higher for those who stopped using a prosthesis within the past year compared with 20 years or more ago (odds ratio [OR], 4.30; 95% confidence interval [CI], 1.28–14.51) and those on disability (OR, 4.01; 95% CI, 0.95–16.85). Odds of unmet need were lower for those with higher upper-limb function scores (OR, 0.94; 95% CI, 0.96–1.00), who were unemployed versus employed/student (OR, 0.15; 95% CI, 0.02–0.98), and those who had abandoned a prior prosthesis because it was “too much fuss” (OR, 0.41; 95% CI, 0.18–0.92). Conclusions Unmet need was prevalent, impacting approximately 50% of persons with upper-limb amputation who were not using a device and 14% who reported never having used a prosthesis. Independent correlates of greater unmet included worse upper-limb function, prosthesis use within the prior year, and disability status. Correlates of lesser unmet need included being unemployed and having abandoned a prosthesis because it was perceived as an undue burden. Further studies are needed to understand barriers to prosthesis use among nonusers with an unmet need. Clinical Relevance Persons with ULA who do not use a prosthesis should be reevaluated regularly to identify unmet needs. Our findings suggest recent prosthesis users, those with poorer upper-limb function, and those who are employed or on disability are more likely to have unmet needs.

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Section: Discussionsupporting

confidence: 62%

Section: Methodsmentioning

confidence: 99%

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Prevalence and Predictors of Unmet Need for Upper-Limb Prostheses: An Observational Cohort Study

2023

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“…The survey included demographic questions related to sex, Veteran status, race, and ethnicity. It also included the TAPES-Upper prosthesis satisfaction measure, 20 the OPUS CSD scale, 18 3 new subscales from a revised OPUS CSD (Comfort, Appearance, and Utility), 21 and additional items and measures related to psychosocial adjustment, 22 activity performance, 23,24 patient experience, 25 and residual limb health (details reported on elsewhere).…”

Section: Surveymentioning

confidence: 99%

Out-of-pocket costs and affordability of upper limb prostheses

Resnik

Borgia

Clark

et al. 2023

Prosthetics &Amp; Orthotics International

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Background: Given the funding policies in the Department of Veterans Affairs, the affordability of prostheses may be less of a concern among Veterans as compared to civilians. Objectives: Compare rates of out-of-pocket prosthesis-related payments for Veterans and non-Veterans with upper limb amputation (ULA), develop and validate a measure of prosthesis affordability, and evaluate the impact of affordability on prosthesis nonuse. Study design: Telephone survey of 727 persons with ULA; 76% Veterans and 24% non-Veterans. Methods: Odds of paying out-of-pocket costs for Veterans compared with non-Veterans were computed using logistic regression. Cognitive and pilot testing resulted in a new scale, evaluated using confirmatory factor and Rasch analysis. Proportions of respondents who cited affordability as a reason for never using or abandoning a prosthesis were calculated.Results: Twenty percent of those who ever used a prosthesis paid out-of-pocket costs. Veterans had 0.20 odds (95% confidence interval, 0.14-0.30) of paying out-of-pocket costs compared with non-Veterans. Confirmatory factor analysis supported unidimensionality of the 4-item Prosthesis Affordability scale. Rasch person reliability was 0.78. Cronbach alpha was 0.87. Overall, 14% of prosthesis never-users said affordability was a reason for nonuse; 9.6% and 16.5% of former prosthesis users said affordability of repairs or replacement, respectively, was a reason for abandonment. Conclusions: Out-of-pocket prosthesis costs were paid by 20% of those sample, with Veterans less likely to incur costs. The Prosthesis Affordability scale developed in this study was reliable and valid for persons with ULA. Prosthesis affordability was a common reason for never using or abandoning prostheses.

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“…A common approach is the use of in-clinic, performance-based measures to rate a patient’s ability to perform motor tasks explicitly connected with functional use [ 1 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ]. Additionally, self-report scales are used to quantify the amount and quality of UE functional use [ 10 , 22 , 23 , 24 , 25 , 26 , 27 ]. Neither method quantitatively measures UE use in the patient’s home or community environment.…”

Section: Introductionmentioning

confidence: 99%

Measurement of Functional Use in Upper Extremity Prosthetic Devices Using Wearable Sensors and Machine Learning

Bochniewicz

Emmer

Dromerick

et al. 2023

Sensors

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Trials for therapies after an upper limb amputation (ULA) require a focus on the real-world use of the upper limb prosthesis. In this paper, we extend a novel method for identifying upper extremity functional and nonfunctional use to a new patient population: upper limb amputees. We videotaped five amputees and 10 controls performing a series of minimally structured activities while wearing sensors on both wrists that measured linear acceleration and angular velocity. The video data was annotated to provide ground truth for annotating the sensor data. Two different analysis methods were used: one that used fixed-size data chunks to create features to train a Random Forest classifier and one that used variable-size data chunks. For the amputees, the fixed-size data chunk method yielded good results, with 82.7% median accuracy (range of 79.3–85.8) on the 10-fold cross-validation intra-subject test and 69.8% in the leave-one-out inter-subject test (range of 61.4–72.8). The variable-size data method did not improve classifier accuracy compared to the fixed-size method. Our method shows promise for inexpensive and objective quantification of functional upper extremity (UE) use in amputees and furthers the case for use of this method in assessing the impact of UE rehabilitative treatments.

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Assessment of Patient-Reported Physical Function in Persons With Upper Extremity Amputation

Cited by 7 publications

References 25 publications

Prevalence and Predictors of Unmet Need for Upper-Limb Prostheses: An Observational Cohort Study

Prevalence and Predictors of Unmet Need for Upper-Limb Prostheses: An Observational Cohort Study

Out-of-pocket costs and affordability of upper limb prostheses

Measurement of Functional Use in Upper Extremity Prosthetic Devices Using Wearable Sensors and Machine Learning

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