Trajectory of Recovery in PROMIS Global Physical Health After Surgical Fracture Fixation.

INTRODUCTION: Patient-reported outcomes (PROs) provide data on the effect of conditions and treatments on patients' lives without third party interpretation. Mounting evidence suggests that PROs may be useful in elective procedure decision making, but its utility in trauma remains unclear. Longitudinally collected PROs may prove effective in identifying patients recovering below the norm. We sought to document recovery trajectory in patients with and without complication and to evaluate the sources of variability in functional recovery after injury. METHODS: This retrospective study included 831 patients with trauma, identified via Current Procedural Terminology (CPT) codes for surgical extremity and/or pelvic/acetabular fracture management between 2014 and 2018. Global Physical Health (GPH) scores collected via the PROMIS Global Health in a 14-month window after injury were analyzed using mixed-effects modeling. RESULTS: A curvilinear GPH recovery trajectory was observed where patients demonstrated an initial positive recovery trajectory (B = 1.28, P < 0.001) gradually decelerating over time (B = -0.07, P < 0.001). Patients who experienced complications requiring revision surgery demonstrated markedly lower GPH scores. Several notable predictors of postoperative physical health recovery were identified, including both between-person (B = 0.52, 95% CI, 0.48 to 0.56) and within-person (B = 0.41, 95% CI, 0.36 to 0.46) Global Mental Health (GMH) score, Body Mass Index (BMI) (B = -0.07, 95% CI, -0.12 to -0.02), two or more psychiatric diagnoses (B = -0.97, 95% CI, -1.84 to 0.09), Injury Severity Score 10 to 15 and 16+ (B = -2.62, 95% CI, -4.81 to 0.42 and B = -2.17, 95% CI, -3.60 to 0.74, respectively), readmission for complication (B = -2.64, 95% CI, -3.60 to 1.68), and lower extremity or multiextremity fracture (relative to upper extremity) (B = -3.61, 95% CI, 4.45 to 2.78, B = -4.11, 95% CI, -5.77 to 2.44, respectively). Additional analysis suggests that GMH scores are related to the presence of psychiatric diagnoses. DISCUSSION: This study establishes a normal course of recovery as reflected by PROMIS GPH score to serve as an index for monitoring individual postoperative course. Patients who experienced a complication demonstrated markedly lower GPH across all time points, potentially allowing earlier identification of at-risk patients. Furthermore, GMH may represent a modifiable risk factor that could profoundly affect physical recovery. LEVEL OF EVIDENCE: Level III (Prognostic Study = Retrospective Cohort).

Comparison of Social Media Utilization Among Vascular Surgeons, Interventional Cardiologists, and Interventional Radiologists at Academic Training Institutions.

BACKGROUND: Social media platforms, especially Twitter, are increasingly utilized across medical practice, education, and research. However, little is known about differences in social media use among physicians of varying specialties and its impact on recruitment of trainees. Our objective was to describe differences in social media use among vascular interventional proceduralists at academic training institutions. METHODS: We identified institutions with training programs in vascular surgery (VS), interventional radiology (IR), and interventional cardiology (IC). Faculty providers were identified in each specialty at these institutions. A standardized search was used to identify non-anonymous social media profiles on Facebook, Instagram, and Twitter in September 2019. Influencers were defined as physicians with more than 1,000 Twitter followers. Follow ratio was defined as the number of followers divided by the number of accounts followed. Between-specialty differences were analyzed. RESULTS: A total of 1,330 providers (n = 454 VS, n=451 IR, n = 425 IC) were identified across 47 institutions in 27 states. Across all physicians, a minority of providers utilize social media (Facebook: 24.9%, n = 331; Instagram: 10.8%, n = 143; Twitter: 18.0%, n = 240). VS were significantly more likely to use Instagram (P = 0.001) but there was not a significant difference in utilization of Facebook and Twitter. Among Twitter users, VS had fewer followers on average (median 178, inter-quartile range [IQR] 39-555) than IR (median 272, IQR 50-793, P = 0.26) and IC (median 286, IQR 71-1257, P = 0.052). IC were most likely to be influencers (30.9%, n = 25) followed by IR (17.9%, n = 15) and VS (10.7%, n = 8, P = 0.006). On average, interventional cardiologists had the highest follow ratio (mean 4.9 ± 7.1) compared to interventional radiologists (mean 3.2 ± 5.5) and vascular surgeons (mean 2.5 ± 3.3, P < 0.001). CONCLUSION: A minority of academic vascular interventional proceduralists utilize social media in a non-anonymous manner. On Twitter, interventional cardiologists are most likely to be influencers based on number of followers and, on average, have the highest follow ratio. Vascular surgeons could potentially benefit from pursuing greater influence and visibility on social media as a means to recruit trainees.

Online Ratings for Vascular Interventional Proceduralists Vary by Physician Specialty.

BACKGROUND: Multiple specialties offer vascular interventional care, creating potential competition for referrals and procedures. At the same time, patient/consumer ratings have become more impactful for physicians who perform vascular procedures. We hypothesized that there are differences in online ratings based on specialty. METHODS: We used official program lists from the Association for Graduate Medical Education to identify institutions with training programs in integrated vascular surgery (VS), integrated interventional radiology (IR), and interventional cardiology (IC). Faculty providers were identified in each specialty at these institutions. A standardized search was performed to collect online ratings from Vitals.com, Healthgrades.com, and Google.com as well as from online demographics. Between specialty differences were analyzed using chi-squared and analysis of variance tests as appropriate. Multivariable linear regression was used to identify factors associated with review volume and star rating. RESULTS: A total of 1,330 providers (n = 454 VS, n = 451 IR, n = 425 IC) were identified across 47 institutions in 27 states. VS (55.5%-69.4%) and IC (63.8%-71.1%) providers were significantly more likely to have reviews than IR (28.6%-48.8%) providers across all online platforms (P < 0.001 for all websites). Across all platforms, IC providers were rated significantly higher than VS and IR providers. Multivariable regression showed that provider specialty and additional time in practice were associated with higher review volume. In addition to specialty, review volume was associated with star rating as those physicians with more reviews tended to have a higher rating. CONCLUSIONS: On average, vascular surgeons have more reviews and are more highly rated than interventional radiologists but tend to have fewer reviews and lower ratings than interventional cardiologists. VS providers may benefit from encouraging patients to file online reviews, especially in competitive markets.

Translating coding lists in administrative claims-based research for cardiovascular procedures.

BACKGROUND: To effectively use administrative claims for healthcare research, clinical events must be inferred from coding data according to validated algorithms. In October 2015, the United States transitioned from the International Classification of Diseases Ninth Revision (ICD-9) to the Tenth Revision (ICD-10). We describe our method to derive new ICD-10 codes for outcomes after vascular procedures from our prior, validated ICD-9 codes. METHODS: We began with validated ICD-9 coding lists known to represent outcomes after lower extremity revascularization, thoracic aortic endograft placement, abdominal aortic aneurysm reintervention, and carotid revascularization. We used the publicly available general equivalence mapping tools to derive corresponding ICD-10 codes for each of the ICD-9 codes in our current lists. The resulting lists were then manually reviewed by multiple authors to ensure clinical relevance for appropriate event detection. Clinically nonrelevant and duplicated codes were removed. RESULTS: A total of 475 ICD-9 codes were translated to ICD-10 with a 98-fold increase (n = 46,630) in the total number of codes. Overall, we found that 77% of codes (n = 35,833) were either duplicated or not clinically relevant upon manual review. For example, for thoracic aortic endograft placement, 97 ICD-9 codes mapped to 14,661 ICD-10 codes in total. A total of 890 codes were removed as duplicates and 9035 codes were removed during manual clinical review. The resultant, reviewed list contained 4736 ICD-10 codes representing a 49-fold increase from the initial ICD-9 list. Findings were similar across the other procedures studied. CONCLUSIONS: ICD-10 has expanded the number of codes necessary to describe outcomes after vascular procedures. More than 75% of the codes obtained using the general equivalence mapping database were either duplicated or not clinically relevant. Manual review of codes by researchers with clinical knowledge of the procedures is imperative.