Top Three Healthcare Trends in Orthopaedics Affecting Musculoskeletal Care in the Elderly.

Several trends toward patient-centered multi-care models employing translational research strategies are currently emerging in orthopaedics. These align seamlessly with epigenetics discussions in pain, a clinical approach to pain management that prioritizes tailoring healthcare to individual needs, preferences, and circumstances. Recognizing the unique genetic and epigenetic factors influencing pain perception, healthcare providers can integrate personalized insights into their patient-centered approach, offering more targeted and effective pain management strategies tailored to each individual's experience. Custom 3D-printing technologies may also become increasingly relevant to more effectively and reliably treat painful degenerative structural abnormalities. They are expected to go hand-in-hand with the precision medicine redefinition of musculoskeletal care. More effective analysis of surgeons' clinical decision-making and patients' perception of high-value orthopaedic care is needed. Shared Decision Making (SDM) is critical to identifying the best solution for each patient and improving stakeholders' understanding of factors influencing the diverse prioritizing values of surgical or non-surgical treatments by payers, systems, and other providers. Identifying high-value orthopaedic surgeries via effective SDM in orthopedic surgery requires more than just presenting patients with information. The Rasch analysis of patient expectations can provide this nuanced approach that involves understanding patient values, addressing misconceptions, and aligning surgical recommendations with patient-specific goals. Optimizing orthopaedic treatment within the patient-centered framework can drive innovation in reimbursement policies that support the field more broadly. Research on separating high-value from low-value orthopaedic procedures may likely impact healthcare decision- makers' resource allocation.

Optimizing Voice Recognition Informatic Robots for Effective Communication in Outpatient Settings.

Aim/Objective Within the dynamic healthcare technology landscape, this research aims to explore patient inquiries within outpatient clinics, elucidating the interplay between technology and healthcare intricacies. Building upon the initial intelligent guidance robot implementation shortcomings, this investigation seeks to enhance informatic robots with voice recognition technology. The objective is to analyze users' vocal patterns, discern age-associated vocal attributes, and facilitate age differentiation through subtle vocal nuances to enhance the efficacy of human-robot communication within outpatient clinical settings. Methods This investigation employs a multi-faceted approach. It leverages voice recognition technology to analyze users' vocal patterns. A diverse dataset of voice samples from various age groups was collected. Acoustic features encompassing pitch, formant frequencies, spectral characteristics, and vocal tract length are extracted from the audio samples. The Mel Filterbank and Mel-Frequency Cepstral Coefficients (MFCCs) are employed for speech and audio processing tasks alongside machine learning algorithms to assess and match vocal patterns to age-related traits. Results The research reveals compelling outcomes. The incorporation of voice recognition technology contributes to a significant improvement in human-robot communication within outpatient clinical settings. Through accurate analysis of vocal patterns and age-related traits, informatic robots can differentiate age through nuanced verbal cues. This augmentation leads to enhanced contextual understanding and tailored responses, significantly advancing the efficiency of patient interactions with the robots. Conclusion Integrating voice recognition technology into informatic robots presents a noteworthy advancement in outpatient clinic settings. By enabling age differentiation through vocal nuances, this augmentation enhances the precision and relevance of responses. The study contributes to the ongoing discourse on the dynamic evolution of healthcare technology, underscoring the complex synergy between technological progression and the intricate realities within healthcare infrastructure. As healthcare continues to metamorphose, the seamless integration of voice recognition technology marks a pivotal stride in optimizing human-robot communication and elevating patient care within outpatient settings.

Impact of children with complex chronic conditions on costs in a tertiary referral hospital

ABSTRACT OBJECTIVES To investigate the impact of complex chronic conditions on the use of healthcare resources and hospitalization costs in a pediatric ward of a public tertiary referral university hospital in Brazil. METHODS This is a longitudinal study with retrospective data collection. Overall, three one-year periods, separated by five-year intervals (2006, 2011, and 2016), were evaluated. Hospital costs were calculated in three systematic samples of 100 patients each, consisting of patients with and without complex chronic conditions in proportion to their participation in the studied year. RESULTS Over the studied period, the hospital received 2,372 admissions from 2,172 patients. The proportion of hospitalized patients with complex chronic conditions increased from 13.3% in 2006 to 16.9% in 2016 as a result of a greater proportion of neurologically impaired children, which rose from 6.6% to 11.6% of the total number of patients in the same period. Patients' complexity also progressively increased, which greatly impacted the use of healthcare resources and costs, increasing by 11.6% from 2006 (R$1,300,879.20) to 2011 (R$1,452,359.71) and 9.4% from 2011 to 2016 (R$1,589,457.95). CONCLUSIONS Hospitalizations of pediatric patients with complex chronic conditions increased from 2006 to 2016 in a Brazilian tertiary referral university hospital, associated with an important impact on hospital costs. Policies to reduce these costs in Brazil are greatly needed.

Treatment Trends and Cost Associated With Peyronie's Disease.

INTRODUCTION: Providers may use several treatment options for patients with Peyronie's disease; however, it is unclear whether practice patterns have evolved over recent years and if this has impacted cost. AIMS: To investigate trends in the treatment of Peyronie's disease over time and the associated costs using a national, commercial insurance claims database. METHODS: A retrospective cohort study was conducted using claims from the Truven MarketScan database from 2007 to 2018 for men with Peyronie's disease. Cost was estimated as either the sum of prescription oral or injectable treatment costs or as the single net cost associated with the operative procedure. MAIN OUTCOME MEASURES: Frequency of use of various treatments for Peyronie's disease and associated costs were assessed as trends over the timeline by year. RESULTS: The estimated annual incidence of Peyronie's disease in this population rose from 61 to 77 per 100,000 patients over the included years, and the percent annual treatment rate rose from 17.8% to 26.2%. Colchicine was the most commonly prescribed oral agent in 2007 used in 22% of treated individuals; by 2018, pentoxifylline was the most common prescribed oral agent used in 33%. In 2007, 11% of treated patients received intralesional verapamil; however, by 2018, 24% received injectable collagenase, whereas <1% received intralesional verapamil. The mean annual, per-individual cost of Peyronie's disease treatment increased from $1,531 in 2007 to $10,339 in 2018. The cost increase was greatest for injectable therapies, which rose from $811 per individual in 2007 to $16,184 in 2018, a 19-fold increase. CONCLUSIONS: Diagnosis and treatment of Peyronie's disease is increasing over time. Pentoxifylline has become the most common oral prescription, whereas injectable collagenase has become most common injection. The mean cost associated with Peyronie's disease treatment increased more than 5 times from 2007 to 2018 corresponding with Federal Drug Administration's approval of injectable collagenase. Loftus CJ, Rajanahally S, Holt SK, et al. Treatment Trends and Cost Associated With Peyronie's Disease. Sex Med 2020;8:673-678.

Facility-level analysis of robot utilization across disciplines in the National Cancer Database.

To evaluate trends in contemporary robotic surgery across multiple organ sites as they relate to robotic prostatectomy volume. We queried the National Cancer Database for patients who underwent surgery from 2010 to 2013 for prostate, kidney, bladder, corpus uteri, uterus, cervix, colon, sigmoid, rectum, lung and bronchus. The trend between volumes of robotic surgery for each organ site was analyzed using the Cochran-Armitage test. Multivariable models were then created to determine independent predictors of robotic surgery within each organ site by calculating the odds ratio with 95% CI. Among the 566,399 surgical cases analyzed, 35.1% were performed using robot assistance. Institutions whose robotic prostatectomy volume was in the top 75 percentile compared to the bottom 25 percentile performed a larger percentage of robotic surgery on the following sites: kidney 32.6 vs. 28.8%, bladder 23.6 vs. 18.6%, uterus 52.5 vs. 47.7%, cervix 43.5 vs. 39.2%, colon 3.2 vs. 2.9%, rectum 10.7 vs. 8.9%, and lung 7.3 vs. 6.8% (all p < 0.0001). It appears that increased trends toward robotic surgery in urology have lead to increased robotic utilization within other surgical fields. Future analysis in benign utilizations of robotic surgery as well as outcome data comparing robotic to open approaches are needed to better understand the ever-evolving nature of minimally invasive surgery within the United States.

Social Media in Surgical Training: Opportunities and Risks.

BACKGROUND: Surgeon engagement with social media is growing rapidly. Innovative applications in diverse fields of health care are increasingly available. OBJECTIVE: The aim of this review is to explore the current and future applications of social media in surgical training. In addition, risks and barriers of social media engagement are analyzed, and recommendations for professional social media use amongst trainers and trainees are suggested. METHODS: The published, peer-reviewed literature on social media in medicine, surgery and surgical training was reviewed. MESH terms including "social media", "education", "surgical training" and "web applications" were used. RESULTS: Different social media surgical applications are already widely available but limited in use in the trainee's curriculum. E-learning modalities, podcasts, live surgery platforms and microblogs are used for teaching purposes. Social media enables global research collaboratives and can play a role in patient recruitment for clinical trials. The growing importance of networking is emphasized by the increased use of LinkedIn, Facebook, Sermo and other networking platforms. Risks of social media use, such as lack of peer review and the lack of source confirmation, must be considered. Governing surgeon's and trainee's associations should consider adopting and sharing their guidelines for standards of social media use. CONCLUSIONS: Surgical training is changing rapidly and as such, social media presents tremendous opportunities for teaching, training, research and networking. Awareness must be raised on the risks of social media use.