National trends in surgical subspecialisation in ophthalmology in the USA

Background/aimsTo assess surgical patterns in ophthalmology by subspecialty in the USA.MethodsOphthalmic surgeons were categorised as comprehensive/subspecialist based on billed procedures in the 2017–2018 Medicare Provider Utilization and Payment Data. Poisson regression models assessed factors associated with physicians performing surgeries in the core domain (eg, cataract extractions) and subspecialty domain. Models were adjusted for provider gender, time since graduation, geographical region, practice setting and hospital affiliation.ResultsThere were 10 346 ophthalmic surgeons, 74.7% comprehensive and 25.3% subspecialists. Cataract extractions were performed by 6.0%, 9.9%, 21.0%, 88.1% and 95.3% of specialists in surgical retina, neuro-ophthalmology/paediatrics, oculoplastics, glaucoma and cornea, respectively. Retina specialists were more likely to perform cataract surgery if they were 20–30 or>30 years in practice (relative risk: 2.20 (95% CI: 1.17 to 4.12) and 3.74 (95% CI: 1.80 to 7.76), respectively) or in a non-metropolitan setting (3.78 (95% CI: 1.71 to 8.38)). Among oculoplastics specialists, male surgeons (2.71 (95% CI: 1.36 to 5.42)), those in practice 10–20 years or 20–30 years (1.93 (95% CI: 1.15 to 3.26) and 1.91 (95% CI: 1.11 to 3.27), respectively) and in non-metropolitan settings (3.07 (95% CI: 1.88 to 5.02)) were more likely to perform cataract surgery. Only 26 of the 2620 subspecialists performed surgeries in two or more subspecialty domains.ConclusionsThere is a trend towards surgical subspecialisation in ophthalmology in the USA whereby some surgeons focus their surgical practice on subspecialty procedures and rarely perform surgeries in the core domain.

Factors for Adoption of Tracking Technology for Clinical and Supply Chain Use in US Hospitals: A Longitudinal Study (Preprint)

BACKGROUND Despite an increasing adoption rate of the tracking technologies (e.g., radio-frequency identification (RFID) and barcode) for hospitals in the United States (U.S.), scarce empirical studies examined hospital size, location, and types of hospital affiliations that are associated with the uptake, leaving the understanding towards the trend unclear. OBJECTIVE This study aimed to identify the hospital characteristics, geographic location, and hospital affiliation type attributive to adopting tracking technologies with a longitudinal dataset, and to compare critical factors associated with tracking technologies adoption for clinical and supply chain uses. We assume that hospital characteristics and hospital location have more impact on tracking technologies for clinical use, and types of hospital affiliation would have more impact on tracking technologies for supply chain use. METHODS This study was conducted based on national census data obtained from the American Hospital Association (AHA) Annual Survey and an AHA Information Technology Supplement survey. In the analysis, 3623 hospitals across 50 states in the U.S. from 2012 to 2015 were included. The effects of the hospital characteristics, location, and types of hospital affiliations were captured and assessed using population logistic regression models with the adjustment of the innate development of tracking technology over time. RESULTS We find that the proportion of hospitals where tracking technologies were implemented for clinical use increased from 36.3% to 54.6%, whilst that for supply chain increased from 28.6% to 41.3%. We also find that time effect and hospital size positively impact the hospital implementation of tracking technologies for both clinical and supply chain use. The implementation rate of tracking technologies for clinical use increased for the hospitals affiliated to the health systems compared to those that are not but decreased in the hospitals located in the rural area in contrast to those located in metro and micro areas. Over time, the implementation rate of tracking technologies for supply chain use increased for the hospital affiliated to a more centralized health system, against decentralized/independent or moderately centralized hospitals but decreased for for-profit hospitals compared to not-for-profit hospitals. CONCLUSIONS We provide a census assessment of tracking technologies adoption, including RFID and barcode in U.S. hospitals for clinical and supply chain uses, and offer a comprehensive overview of the hospital characteristics, location, and types of hospital affiliations associated with the tracking technology adoption. This study informs researchers, healthcare providers, and policymakers that hospital characteristics, location, and types of hospital affiliations have different impacts on both the level and rate of implementation of certain tracking technologies for clinical and for supply chain use. This study also has implications for developing smart hospitals using tracking technology infrastructure.

Abstract P124: Stroke Patient Transfer Destination is Influenced by Hospital Affiliation

Background: Acute ischemic stroke (AIS) patients are frequently transferred between hospitals, however it is not clear whether these transfers are optimized with respect to proximity and quality of the destination hospital. Our primary object was to identify hospital characteristics associated with sending and receiving AIS patients. Methods: Using a comprehensive statewide dataset, we identified all AIS patient transfers occurring between all 78 Massachusetts (MA) hospitals from 2007 and 2015. Hospital variables included hospital quality reputation (US News & World Report), hospital capabilities (stroke center status, annual stroke volume, and trauma center designation), and institutional affiliations (same vs. not). We also included network variables to control for the structure of hospital-to-hospital transfers. We used relational event modeling to account for complex temporal and relational dependencies associated with patient transfers. This method decomposes events into a decision to transfer, and if so, the receiving hospital destination, and models them using a discrete-choice framework. Results: Among 73,114 AIS admissions in MA during the 8-year study period, there were 7,189 (9.8%) transfers. After accounting for travel time between hospitals and structural network characteristics, factors associated with increased likelihood of being a receiving hospital included teaching hospital status, hospitals of the same or higher quality, the same or higher stroke center status, and the same hospital affiliation (Table). Conclusion: Patients experiencing AIS in MA are frequently transferred between hospitals. After accounting for multiple relevant hospital characteristics, hospital affiliation remains an important factor in determining transfer destination. While there may be some benefits to hospital affiliation, stroke systems of care should be designed to maximize patient benefit and leverage interfacility transfer accordingly.

Hospital Disaster Preparedness as Measured by Functional Capacity: a Comparison between Iran and Sweden

IntroductionHospitals are expected to continue to provide medical care during disasters. However, they often fail to function under these circumstances. Vulnerability to disasters has been shown to be related to the socioeconomic level of a country. This study compares hospital preparedness, as measured by functional capacity, between Iran and Sweden.MethodsHospital affiliation and size, and type of hazards, were compared between Iran and Sweden. The functional capacity was evaluated and calculated using the Hospital Safety Index (HSI) from the World Health Organization. The level and value of each element was determined, in consensus, by a group of evaluators. The sum of the elements for each sub-module led to a total sum, in turn, categorizing the functional capacity into one of three categories: A) functional; B) at risk; or C) inadequate.ResultsThe Swedish hospitals (n = 4) were all level A, while the Iranian hospitals (n = 5) were all categorized as level B, with respect to functional capacity. A lack of contingency plans and the availability of resources were weaknesses of hospital preparedness. There was no association between the level of hospital preparedness and hospital affiliation or size for either country.ConclusionThe results suggest that the level of hospital preparedness, as measured by functional capacity, is related to the socioeconomic level of the country. The challenge is therefore to enhance hospital preparedness in countries with a weaker economy, since all hospitals need to be prepared for a disaster. There is also room for improvement in more affluent countries.DjalaliA, CastrenM, KhankehH, GrythD, RadestadM, OhlenG, KurlandL. Hospital disaster preparedness as measured by functional capacity: a comparison between Iran and Sweden. Prehosp Disaster Med.2013;28(5):1-8.

Oncology Professional Services Agreements: A Model for Hospital Affiliation That Preserves Private Practice

Professional services agreements enable community-based oncology groups to affiliate with local hospitals in a win-win transaction that preserves a significant level of independence for the oncology group. This article describes the business and legal aspects of such agreements.