Convenient Care Trends

In this chapter, the author introduces several alternatives to traditional care provided in the physician office during regular business hours. While the settings where the care is delivered are different, the common characteristics among these alternatives are to have non-physician providers deliver care that is more convenient and less costly than that delivered in regular physician offices. Convenient care alternatives such as urgent care centers, retail clinics, worksite clinics, house call services, and virtual/online services are highlighted. These services are described as “disruptive innovations,” or powerful changes in which a larger population of less-skilled providers can provide care in more convenient, less expensive settings that historically was only provided by expensive specialists in centralized, inconvenient locations. Given the myriad of problems faced by the American healthcare systems, the authors argue that these innovations are well positioned to change the way healthcare is delivered for generations to come.

2019 ◽  
Vol 35 (2) ◽  
pp. 138-142 ◽  
Author(s):  
Mohsen Saidinejad ◽  
Audrey Paul ◽  
Marianne Gausche-Hill ◽  
Dale Woolridge ◽  
Alan Heins ◽  
...  

2019 ◽  
Vol 63 (11) ◽  
Author(s):  
Danielle L. Palms ◽  
Lauri A. Hicks ◽  
Monina Bartoces ◽  
Adam L. Hersh ◽  
Rachel Zetts ◽  
...  

ABSTRACT Using the 2014 IBM MarketScan commercial database, we compared antibiotic selection for pharyngitis, sinusitis, and acute otitis media in retail clinics, emergency departments, urgent care centers, and offices. Only 50% of visits for these conditions received recommended first-line antibiotics. Improving antibiotic selection for common outpatient conditions is an important stewardship target.


2020 ◽  
Vol 41 (S1) ◽  
pp. s506-s507
Author(s):  
Patricia Cummings ◽  
Rita Alajajian ◽  
Larissa May ◽  
Russel Grant ◽  
Hailey Greer ◽  
...  

Background: The rate of inappropriate antibiotic prescribing for acute respiratory tract infections (ARTIs) is 45% among urgent care centers across the United States. To contribute to the US National Action Plan for Combating Antibiotic-Resistant Bacteria, which aims to decrease rates of inappropriate prescribing, we implemented 2 behavioral nudges using the evidence-based MITIGATE tool kit from urgent-care settings, at 3 high-volume, rural, urgent-care centers. Methods: An interrupted time series (ITS) analysis was conducted comparing a preintervention phase during the 2017–2018 influenza season (October through March) to the intervention phase during the 2018–2019 influenza season. We compared the rate of inappropriate or non–guideline-concordant antibiotic prescribing for ARTIs across 3 urgent-care locations. The 2 intervention behavioral nudges were (1) staff and patient education and (2) peer comparison. Provider education included presentations at staff meetings and grand rounds, and patient education print materials were distributed to the 3 locations coupled with news media and social media. We utilized the CDC “Be Antibiotics Aware” campaign materials, with our hospital’s logo added, and posted them in patient rooms and waiting areas. For the peer comparison behavioral intervention, providers were sent individual feedback e-mails with their prescribing data during the intervention period and a blinded ranking e-mail in which they were ranked in comparison to their peers. In the blinded ranking email, providers were placed into categories of “low prescribers,” those with a ≤23% inappropriate antibiotic prescribing rate based on the US National Action Plan for Combating Antibiotic-Resistance Bacteria 2020 goal, or “high prescribers,” those with a rate greater than the national average (45%) of inappropriate antibiotic prescribing for ARTI. Results: Our results show that fewer inappropriate antibiotic prescriptions were written during the intervention period (58.8%) than during the preintervention period (73.0%), resulting in a 14.5% absolute decrease in rates of inappropriate prescribing among urgent-care locations over a 6-month period (Fig. 1). The largest percentage decline in rates was seen in the month of April (−35.8%) when compared to April of the previous year. The ITS analysis revealed that the rate of inappropriate prescribing was statistically significantly different during the preintervention period compared to the intervention period (95% CI, −4.59 to −0.59; P = .0142). Conclusions: Using interventions outlined in the MITIGATE tool kit, we were able to reduce inappropriate antibiotic prescribing for ARTI in 3 rural, urgent-care locations.Funding: NoneDisclosures: Larissa May repo, Speaking honoraria-Cepheid Research grants-Roche Consultant-BioRad Advisory Board-Qvella Consultant-Nabriva


Author(s):  
Joanne Huang ◽  
Zahra Kassamali Escobar ◽  
Todd S. Bouchard ◽  
Jose Mari G. Lansang ◽  
Rupali Jain ◽  
...  

Abstract The MITIGATE toolkit was developed to assist urgent care and emergency departments in the development of antimicrobial stewardship programs. At the University of Washington, we adopted the MITIGATE toolkit in 10 urgent care centers, 9 primary care clinics, and 1 emergency department. We encountered and overcame challenges: a complex data build, choosing feasible outcomes to measure, issues with accurate coding, and maintaining positive stewardship relationships. Herein, we discuss solutions to challenges we encountered to provide guidance for those considering using this toolkit.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Thomas Dimpfl ◽  
Dalia Elshiaty

PurposeCryptocurrency markets are notoriously noisy, but not all markets might behave in the exact same way. Therefore, the aim of this paper is to investigate which one of the cryptocurrency markets contributes the most to the common volatility component inherent in the market.Design/methodology/approachThe paper extracts each of the cryptocurrency's markets' latent volatility using a stochastic volatility model and, subsequently, models their dynamics in a fractionally cointegrated vector autoregressive model. The authors use the refinement of Lien and Shrestha (2009, J. Futures Mark) to come up with unique Hasbrouck (1995, J. Finance) information shares.FindingsThe authors’ findings indicate that Bitfinex is the leading market for Bitcoin and Ripple, while Bitstamp dominates for Ethereum and Litecoin. Based on the dominant market for each cryptocurrency, the authors find that the volatility of Bitcoin explains most of the volatility among the different cryptocurrencies.Research limitations/implicationsThe authors’ findings are limited by the availability of the cryptocurrency data. Apart from Bitcoin, the data series for the other cryptocurrencies are not long enough to ensure the precision of the authors’ estimates.Originality/valueTo date, only price discovery in cryptocurrencies has been studied and identified. This paper extends the current literature into the realm of volatility discovery. In addition, the authors propose a discrete version for the evolution of a markets fundamental volatility, extending the work of Dias et al. (2018).


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