AN OPERATIONAL PERSPECTIVE OF THE CHANGING PROSTHETICS & ORTHOTICS LANDSCAPE
Bibliographic record
Abstract
Leading the growth of a private prosthetic and orthotic (P&O) practice, as clinician and founder, I developed a unique perspective of this rapidly changing profession. Many positive influences from my early career shaped my vison toward an innovative practice model, as well as the need to elevate the standard of care through education and the use of outcome measures. As the practice model expanded, advancements were made in electronic health records (EHR), best-in-class outsource fabrication, and clinical research. To better support clinicians and patients served, an organizational structure with an executive team was built. The practice model achieved operational efficiency through documenting best practices, developing a hiring and onboarding process, and establishing key performance indicators aligned with quality clinical care. As a regional clinical care organization, the practice model seized an opportunity to reach more patients through a partnership that brought the optimal strategic and cultural fit. Bringing our innovative P&O practice model together with expertise in lean facility design, scanning, fabrication, sensor technology, product development and clinical care experience from around the world, we can advance care standards and improve the patient experience in exciting new ways. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/35996/28414 How To Cite: Brandt JM. An operational perspective of the changing prosthetics & orthotics landscape. Canadian Prosthetics & Orthotics Journal. 2021; Volume 4, Issue 2, No.19. https://doi.org/10.33137/cpoj.v4i2.35996 Corresponding Author: Jeffrey M. Brandt, CPOAbility Prosthetics & Orthotics, 660 West Lincoln Highway, Exton, PA 19341, USA.E-Mail: jeff.brandt@abilitypo.comORCID ID: https://orcid.org/0000-0002-7377-9516
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.007 | 0.033 |
| Scholarly communication | 0.020 | 0.015 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".