Physician Behavior Changes Following CME on the Prospective Payment System in Long-Term Care: A Pilot Study

2002 ◽  
Vol 3 (1) ◽  
pp. 12-15 ◽  
Author(s):  
Ralf Habermann ◽  
Natasha Butts ◽  
James Powers ◽  
James W. Pichert
2002 ◽  
Vol 16 (2) ◽  
pp. 67-76 ◽  
Author(s):  
Scot Brayford ◽  
Jacqueline Buscarini ◽  
Christopher Dunbar ◽  
Alec Frank ◽  
Peter Nguyen ◽  
...  

2002 ◽  
Vol 16 (2-3) ◽  
pp. 67-76 ◽  
Author(s):  
Scot Brayford ◽  
Jacqueline Buscarini ◽  
Christopher Dunbar ◽  
Alec Frank ◽  
Peter Nguyen ◽  
...  

2020 ◽  
Vol 36 (S1) ◽  
pp. 41-42
Author(s):  
Tiantian Du ◽  
Junting Yang ◽  
Ying Li ◽  
Meng Zhang ◽  
Yuehua Liu

IntroductionWith the aging of population, miniaturization of family size and changes of diseases spectrum, the demand for long-term care of Chinese elderly is increasing, which is challenging the existing long-term care system. China is currently carrying out pilot work for a long-term care insurance system, and Jingmen is one of the pilot cities, however more detailed research on payment is needed. Therefore, this paper draws on case-mixed-adjusted prospective payment system to provide designs for long-term care insurance in pilot cities.MethodsAdopting a case analysis method, this paper focuses on system for payment of Skilled Nursing Facility under Part A of the Medicare program—Patient Driven Payment Model, and discusses the implementation plan of a long-term care insurance in Jingmen City from the perspectives of payment methods, payment grouping and payment standards.ResultsCurrently Jingmen adopts per-diem payment for long-term care insurance, so it is necessary to establish a payment based on population characteristics and demands. So, the patients should be classified into a group for each of the five case-mix adjusted components: physical therapy, occupational therapy, speech therapy, nursing and non-therapy ancillary. In addition, this payment model also includes a “variable per diem adjustment” to account for the changes in patient costs more accurately.ConclusionsThe theoretical system of a long-term care insurance payment method is developed, and a localization plan for case-mixed-adjusted prospective payment system for long-term care insurance is provided. Therefore, Jingmen long-term care insurance payment should adopt “case-mixed adjustment”, strengthening the relationship between individual clinical characteristics and payment.


2020 ◽  
Vol 41 (S1) ◽  
pp. s527-s527
Author(s):  
Gabriela Andujar-Vazquez ◽  
Kirthana Beaulac ◽  
Shira Doron ◽  
David R Snydman

Background: The Tufts Medical Center Antimicrobial Stewardship (ASP) Team has partnered with the Massachusetts Department of Public Health (MDPH) to provide broad-based educational programs (BBEP) to long-term care facilities (LTCFs) in an effort to improve ASP and infection control practices. LTCFs have consistently expressed interest in individualized and hands-on involvement by ASP experts, yet they lack resources. The goal of this study was to determine whether “enhanced” individualized guidance provided by an ASP expert would lead to antibiotic start decreases in LTCFs participating in our pilot study. Methods: A pilot study was conducted to test the feasibility and efficacy of providing enhanced ASP and infection control practices to LTCFs. In total, 10 facilities already participating in MDPH BBEP and submitting monthly antibiotic start data were enrolled, were stratified by bed size and presence of dementia unit, and were randomized 1:1 to the “enhanced” group (defined as reviewing protocols and antibiotic start cases, providing lectures and feedback to staff and answering questions) versus the “nonenhanced” group. Antibiotic start data were validated and collected prospectively from January 2018 to July 2019, and the interventions began in April 2019. Due to staff turnover and lack of engagement, intervention was not possible in 2 of the 5 LTCFs randomized to the enhanced group, which were therefore analyzed as a nonenhanced group. An incidence rate ratios (IRRs) with 95% CIs were calculated comparing the antibiotic start rate per 1,000 resident days between periods in the pilot groups. Results: The average bed sizes for enhanced groups versus nonenhanced groups were 121 (±71.0) versus 108 (±32.8); the average resident days per facility per month were 3,415.7 (±2,131.2) versus 2,911.4 (±964.3). Comparatively, 3 facilities in the enhanced group had dementia unit versus 4 in the nonenhanced group. In the per protocol analysis, the antibiotic start rate in the enhanced group before versus after the intervention was 11.35 versus 9.41 starts per 1,000 resident days (IRR, 0.829; 95% CI, 0.794–0.865). The antibiotic start rate in the nonenhanced group before versus after the intervention was 7.90 versus 8.23 antibiotic starts per 1,000 resident days (IRR, 1.048; 95% CI, 1.007–1.089). Physician hours required for ASP for the enhanced group totaled 8.9 (±2.2) per facility per month. Conclusions: Although the number of hours required for intervention by an expert was not onerous, maintaining engagement proved difficult and in 2 facilities could not be achieved. A statistically significant 20% decrease in the antibiotic start rate was achieved in the enhanced group after interventions, potentially reflecting the benefit of enhanced ASP support by an expert.Funding: This study was funded by the Leadership in Epidemiology, Antimicrobial Stewardship, and Public Health (LEAP) fellowship training grant award from the CDC.Disclosures: None


2020 ◽  
Vol 20 (4) ◽  
pp. 419-426
Author(s):  
Akito Tsugawa ◽  
Soichiro Shimizu ◽  
Daisuke Hirose ◽  
Tomohiko Sato ◽  
Hirokuni Hatanaka ◽  
...  

2007 ◽  
Vol 8 (5) ◽  
pp. 300-306 ◽  
Author(s):  
M MONTEROODASSO ◽  
P LEVINSON ◽  
B GORE ◽  
D EPID ◽  
L TREMBLAY ◽  
...  

2021 ◽  
Vol 6 ◽  
pp. 235
Author(s):  
Rachel Kwiatkowska ◽  
Nicola Yaxley ◽  
Ginny Moore ◽  
Allan Bennett ◽  
Matthew Donati ◽  
...  

Background: The SARS-CoV-2 pandemic has highlighted the risk of infection transmission in long-term care facilities (LTCF) and the vulnerability of resident populations. It is essential to understand the environmental spread of the virus and risk of indirect transmission to inform Infection Prevention and Control (IPC) measures in these settings. Methods: Upon notification of SARS-CoV-2 outbreaks, LTCF within a local authority in the South West of England were approached to take part in this pilot study. Investigators visited to swab common touch-points and elevated ‘non-touch’ surfaces and samples were analysed for presence of SARS-CoV-2 genetic material (RNA). Data were collected regarding LTCF infrastructure, staff behaviours, clinical and epidemiological risk factors for infection (staff and residents), and IPC measures. Criteria for success were: recruitment of three LTCF; detection of SARS-COV-2 RNA; variation in proportion of SARS-CoV-2 positive surfaces by sampling zone; potential to assess infection risk from SARS-CoV-2 positive surfaces. Results: Three LTCFs were recruited, ranging in size and resident demographics. Outbreaks lasted 63, 50 and 30 days with resident attack rates of 53%, 40% and 8%, respectively. The proportion of sample sites on which SARS-CoV-2 was detected was highest in rooms occupied by infected residents and varied elsewhere in the LTCF, with low levels in a facility implementing enhanced IPC measures. The heterogeneity of settings and difficulty obtaining data made it difficult to assess association between environmental contamination and infection. Elevated surfaces were more likely to test positive for SARS-CoV-2 RNA than common touch-points. Conclusions: SARS-CoV-2 RNA can be detected in a variety of LTCF outbreak settings. We identified variation in environmental spread which could be associated with implementation of IPC measures, though we were unable to assess the impact on infection risk. Sampling elevated surfaces could add to ongoing public health surveillance for SARS-CoV-2 and other airborne pathogens in LTCF.


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