R3. Analysis of Datasets & Registries Related to Complex Rehabilitation Technology (CRT)

Project Leader(s): Brad E. Dicianno, MD & Mark R. Schmeler, PhD, OTR/L, ATP

Co-Leaders:  Gina P. McKernan, PhD, Richard M. Schein, PhD, MPH, & Gede Pramana, PhD

Other Project Personnel: Matt Mesoros

Partners: U.S. Rehab, National Seating & Mobility, Permobil, and UPMC Health Plan


Large datasets and registries are essential elements for the consideration of accountable and value-based healthcare and associated policy. The field of CRT is relatively new to using large datasets and registries, and therefore policies surrounding CRT have not necessarily been based on research with standardized outcome measures, uniform datasets, or other similar strategies.

The study involves analysis of several large datasets that will be made available through data use agreements. The datasets contain information about people (e.g. basic demographics and health outcomes) and devices they use (e.g. wheelchairs). We will be conducting descriptive analyses of the data to better understand the characteristics of the devices being used to answer questions such as, “how long do devices last before they need to be repaired,” “how much do repairs cost?”, and “do people using certain kinds of devices have health outcomes like pressure ulcers?”  The overall goal of the study is to use the information obtained to draft a new policy for insurance coverage of devices including wheelchairs.

The outcome of this project will be a large Uniform Dataset merged from multiple independent sources that includes variables of interest that can be used to inform a new value-based policy model for CRT. Specifically, knowing the average reasonable useful life (RUL) and overall cost of operating various types of CRT devices can assist in informing a payment strategy. For example, knowing mileage over time with associated service messages will be the first of its kind type analysis in the CRT industry to further inform expected RUL and maintenance routines. The comprehensive data set can also be leveraged beyond the purpose of this proposal for further investigations. Stakeholder groups and researchers may be interested to know how different variables are correlated to model predictive outcomes associated across types of devices, users, and their situation which can further promote levels of research evidence in the field of CRT.


As of June 1, 2022

Regular meetings are scheduled with our collaborating stakeholders. We have identified 5 datasets that are being used to create a uniform dataset and dictionary, and to investigate among variables:

Dataset 1: Functional Mobility Assessment and Uniform Dataset Registry (FMA/UDS) – The FMA/UDS is a person-reported outcomes registry related to satisfaction in performing Mobility Related Activities of Daily Living (MRADLs) and other factors of interest including health, function, and participation that are related to various types of Complex Rehabilitation Technology (CRT). The FMA/UDS is managed through a sponsored research agreement between the University of Pittsburgh and the Van G. Miller Group’s US Rehab subsidiary (VGM/US Rehab).

Dataset 2: Labor Tracker Wheelchair Repair Registry (WRR) – Within the existing RERC Project on Wheelchair Standards, Pitt investigators have developed a Wheelchair Repair Registry (WRR) to obtain a large dataset in order to better understand the type and frequency of failures across types of devices for research and development purposes. This project is also a collaboration between Pitt and VGM/US Rehab, who maintains Labor Tracker, which is a strategy for its members to document, track and manage wheelchair repairs that also includes procedures for insurance claims.

Dataset 3: Business Operations Data from National Seating and Mobility (NSM) – NSM is one of the largest suppliers of CRT, with over 240 branches nationwide. Due to the size and scope of the company, they maintain their own business operations data infrastructure. They maintain electronic records on all CRT cases, which includes information about the device and history of repairs.

Dataset 4: Permobil Connected Wheelchair (PCW) – Permobil is a global manufacturer of high-end powered wheelchairs. There is a feature called Permobil Connect that is able to collect and transmit information about the use and performance of the device, including battery health, frequency of battery charges, hours of use, distance traveled, utilization of power functions such as seat elevation and service messages (including device errors). Permobil is working with Pitt investigators on a subset of the data to be aggregated, de-identified, and shared.

Dataset 5: UPMC Health Plan Claims Dataset (UPMC-HP) – The University of Pittsburgh Medical Center Health Plan (UPMC-HP) is a Managed Care Organization (MCO) within, but independent of, the UPMC Health System, which is an Accountable Care Organization (ACO) serving over 3.7 million lives throughout Pennsylvania and neighboring states. The HP offers several health insurance products including commercial plans as well as Medicare and Medicaid managed care plans. The Health Plan routinely collaborates with investigators to share and analyze claims data to investigate utilization and the effectiveness of various treatments and services.

A question that has many components that team members are investigating include: How do the datasets differ in terms of the kinds of people, devices, settings, repair variables, and health factors that they contain?

A second question being investigated: How long do wheelchairs last before they have to be replaced? and How much does each type of wheelchair cost (initially plus maintenance and repairs) over its lifetime? A proposed methodology has been discussed and future results will be reported.

Dissemination Activities

Published Manuscripts

Schein, R. M., Yang, A., McKernan, G. P., Mesoros, M., Pramana, G., Schmeler, M. R., & Dicianno, B. E. (2021). Effect of the Assistive Technology Professional on the Provision of Mobility Assistive Equipment. Archives of physical medicine and rehabilitation, 102(10), 1895–1901. https://doi.org/10.1016/j .apmr.2021.03.024

Cuppett, M., Schein, R. M., Pramana, G., Dicianno, B. E., & Schmeler, M. R. (2022). Investigation of factors from assistive technology professionals that impact timeliness of wheelchair service delivery: a cross-sectional study. Disability and rehabilitation. Assistive technology, 1–5. Advance online publication. https://doi.org/10.1080/1 7483107.2022.2048099

Ruffing, J.J., Schmeler, M.R., Schein, R.M., & Mhatre, A. (2022). A cross-sectional descriptive analysis of complex rehabilitation technology (CRT) supplier opinions on the current state of wheelchair repair services. Disability and rehabilitation. Assistive technology, 1–6. Advance online publication. https://doi.org/10.1080/17483107.2022.2121007

Mesoros, M.J., Schein, R.M., Pramana, G., Schiappa, V.J., Schmeler, M.R., & Dicianno, B.E. (2022). Functional mobility, employment and safety benefits of seat elevating devices. Assistive technology : the official journal of RESNA, 1–6. Advance online publication. https://doi.org/10.1080/10400435.2022.2124469

Manuscripts in Review

Implementation and Lessons Learned from the Functional Mobility Assessment and Uniform Dataset Registry

  • submitted to Assistive Technology Special Issue on Outcomes

Manuscripts in Preparation

Other Dissemination Activities

McKernan, G., Schein, R.M., Schmeler, M.R., Pramana, G. Mesoros, M. & Dicianno, B.E. (2022, February). Impact of the Assistive Technology Professional in the Provision of Mobility Assistive Equipment. International Seating Symposium (ISS). https://www.seatingsymposium.us/eventschedule/event/

Dicianno BE. Archives of PM&R podcast to a follow-up on the manuscript, ‘Effect of the Assistive Technology Professional on the Provision of Mobility Assistive Equipment’ – awaiting the publication podcast link

Mesoros MJ, Schein RM, Pramana G, Schiappa VJ, Schmeler MR, Dicianno BE. (2022). Functional Mobility, Employment and Safety Benefits of Power Adjustable Seat Height. UPMC Rehabilitation Institute Research Day.

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