The Military Orthopedics Tracking Injuries and Outcomes Network: A Solution for Improving Musculoskeletal Care in the Military Health System.

INTRODUCTION: Musculoskeletal injuries are an endemic amongst U.S. Military Service Members and significantly strain the Department of Defense's Military Health System. The Military Health System aims to provide Service Members, military retirees, and their families the right care at the right time. The Military Orthopedics Tracking Injuries and Outcomes Network (MOTION) captures the data that can optimize musculoskeletal care within the Military Health System. This report provides MOTION structural framework and highlights how it can be used to optimize musculoskeletal care. MATERIALS AND METHODS: MOTION established an internet-based data capture system, the MOTION Musculoskeletal Data Portal. All adult Military Health System patients who undergo orthopedic surgery are eligible for entry into the database. All data are collected as routine standard of care, with patients and orthopedic surgeons inputting validated global and condition-specific patient reported outcomes and operative case data, respectively. Patients have the option to consent to allow their standard of care data to be utilized within an institutional review board approved observational research study. MOTION data can be merged with other existing data systems (e.g., electronic medical record) to develop a comprehensive dataset of relevant information. In pursuit of enhancing musculoskeletal injury patient outcomes MOTION aims to: (1) identify factors which predict favorable outcomes; (2) develop models which inform the surgeon and military commanders if patients are behind, on, or ahead of schedule for their targeted return-to-duty/activity; and (3) develop predictive models to better inform patients and surgeons of the likelihood of a positive outcome for various treatment options to enhance patient counseling and expectation management. RESULTS: This is a protocol article describing the intent and methodology for MOTION; thus, to date, there are no results to report. CONCLUSIONS: MOTION was established to capture the data that are necessary to improve military medical readiness and optimize medical resource utilization through the systematic evaluation of short- and long-term musculoskeletal injury patient outcomes. The systematic enhancement of musculoskeletal injury care through data analyses aligns with the National Defense Authorization Act (2017) and Defense Health Agency's Quadruple Aim, which emphasizes optimizing healthcare delivery and Service Member medical readiness. This transformative approach to musculoskeletal care can be applied across disciplines within the Military Health System.

A High-Sensitivity International Knee Documentation Committee Survey Index From the PROMIS System: The Next-Generation Patient-Reported Outcome for a Knee Injury Population.

BACKGROUND: Patient-reported outcomes (PROs) measure progression and quality of care. While legacy PROs such as the International Knee Documentation Committee (IKDC) survey are well-validated, a lengthy PRO creates a time burden on patients, decreasing adherence. In recent years, PROs such as the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function and Pain Interference surveys were developed as computer adaptive tests, reducing time to completion. Previous studies have examined correlation between legacy PROs and PROMIS; however, no studies have developed effective prediction models utilizing PROMIS to create an IKDC index. While the IKDC is the standard knee PRO, computer adaptive PROs offer numerous practical advantages. PURPOSE: To develop a nonlinear predictive model utilizing PROMIS Physical Function and Pain Interference to estimate IKDC survey scores and examine algorithm sensitivity and validity. STUDY DESIGN: Cohort study (diagnosis); Level of evidence, 3. METHODS: The MOTION (Military Orthopaedics Tracking Injuries and Outcomes Network) database is a prospectively collected repository of PROs and intraoperative variables. Patients undergoing knee surgery completed the IKDC and PROMIS surveys at varying time points. Nonlinear multivariable predictive models using Gaussian and beta distributions were created to establish an IKDC index score, which was then validated using leave-one-out techniques and minimal clinically important difference analysis. RESULTS: A total of 1011 patients completed the IKDC and PROMIS Physical Function and Pain Interference, providing 1618 complete observations. The algorithms for the Gaussian and beta distribution were validated to predict the IKDC (Pearson = 0.84-0.86; R2 = 0.71-0.74; root mean square error = 9.3-10.0). CONCLUSION: The publicly available predictive models can approximate the IKDC score. The results can be used to compare PROMIS Physical Function and Pain Interference against historical IKDC scores by creating an IKDC index score. Serial use of the IKDC index allows for a lower minimal clinically important difference than the conventional IKDC. PROMIS can be substituted to reduce patient burden, increase completion rates, and produce orthopaedic-specific survey analogs.

Generating the American Shoulder and Elbow Surgeons Score Using Multivariable Predictive Models and Computer Adaptive Testing to Reduce Survey Burden.

BACKGROUND: The preferred patient-reported outcome measure for the assessment of shoulder conditions continues to evolve. Previous studies correlating the Patient-Reported Outcomes Measurement Information System (PROMIS) computer adaptive tests (CATs) to the American Shoulder and Elbow Surgeons (ASES) score have focused on a singular domain (pain or physical function) but have not evaluated the combined domains of pain and physical function that compose the ASES score. Additionally, previous studies have not provided a multivariable prediction tool to convert PROMIS scores to more familiar legacy scores. PURPOSE: To establish a valid predictive model of ASES scores using a nonlinear combination of PROMIS domains for physical function and pain. STUDY DESIGN: Cohort study (Diagnosis); Level of evidence, 3. METHODS: The Military Orthopaedics Tracking Injuries and Outcomes Network (MOTION) database is a prospectively collected repository of patient-reported outcomes and intraoperative variables. Patients in MOTION research who underwent shoulder surgery and completed the ASES, PROMIS Physical Function, and PROMIS Pain Interference at varying time points were included in the present analysis. Nonlinear multivariable predictive models were created to establish an ASES index score and then validated using "leave 1 out" techniques and minimal clinically important difference /substantial clinical benefit (MCID/SCB) analysis. RESULTS: A total of 909 patients completed the ASES, PROMIS Physical Function, and PROMIS Pain Interference at presurgery, 6 weeks, 6 months, and 1 year after surgery, providing 1502 complete observations. The PROMIS CAT predictive model was strongly validated to predict the ASES (Pearson coefficient = 0.76-0.78; R2 = 0.57-0.62; root mean square error = 13.3-14.1). The MCID/SCB for the ASES was 21.7, and the best ASES index MCID/SCB was 19.4, suggesting that the derived ASES index is effective and can reliably re-create ASES scores. CONCLUSION: The PROMIS CAT predictive models are able to approximate the ASES score within 13 to 14 points, which is 7 points more accurate than the ASES MCID/SCB derived from the sample. Our ASES index algorithm, which is freely available online (https://osf.io/ctmnd/), has a lower MCID/SCB than the ASES itself. This algorithm can be used to decrease patient survey burden by 11 questions and provide a reliable ASES analog to clinicians.

Incidence and Characteristics of Humeral Shaft Fractures After Subpectoral Biceps Tenodesis.

BACKGROUND: Biceps tenodesis is a procedure that can address biceps and labral pathology. While there is an increased risk of humeral fracture after biceps tenodesis, it has been described only in case reports. PURPOSE: To identify the incidence, demographics, and characteristics of humeral shaft fractures after biceps tenodesis. STUDY DESIGN: Case series; Level of evidence, 4. METHODS: The US Military Health System Data Repository was searched for patients with a Current Procedural Terminology code for biceps tenodesis between January 2013 and December 2016. The cohort of identified patients was then searched for those assigned a code for humeral fracture per the International Classification of Diseases, 9th Revision and 10th Revision. The electronic health records and radiographs of patients who were diagnosed with a humeral fracture were then evaluated to confirm that the fracture was related to the biceps tenodesis. Records were then reviewed for patient demographics, radiographs, operative reports, and clinical notes. RESULTS: A total of 15,085 biceps tenodeses were performed between January 2013 and December 2016. There were 11 postoperative and 1 intraoperative humeral fractures. The incidence of fracture was <0.1%. All fractures were extra-articular spiral fractures that propagated through the tenodesis site. Eight patients were treated with functional bracing, 3 with open reduction and internal fixation, and 1 with a soft tissue biceps tenodesis revision. Of 8 patients successfully treated nonoperatively, 6 regained full range of shoulder motion. Only 2 of the 4 patients who required operative treatment regained full range of shoulder motion. CONCLUSION: Humeral shaft fracture after biceps tenodesis is a rare complication that occurs in 7.9 out of 10,000 cases. Fractures occurred after various methods of fixation, including suture anchor, cortical button, and interference screw. Most patients were initially treated nonoperatively, and those who healed usually achieved full range of motion; however, those who required operative intervention often had restricted range of motion on final follow-up. Future studies should determine risk factors for fracture after biceps tenodesis.