Do service innovations influence the adoption of electronic health records in long-term care organizations? Results from the U.S. National Survey of Residential Care Facilities

2014 ◽  
Vol 83 (12) ◽  
pp. 975-982 ◽  
Author(s):  
Soumitra S. Bhuyan ◽  
He Zhu ◽  
Aastha Chandak ◽  
Jungyoon Kim ◽  
Jim P. Stimpson
2017 ◽  
Vol 5 (3) ◽  
pp. e35 ◽  
Author(s):  
Clemens Scott Kruse ◽  
Michael Mileski ◽  
Alekhya Ganta Vijaykumar ◽  
Sneha Vishnampet Viswanathan ◽  
Ujwala Suskandla ◽  
...  

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249588
Author(s):  
Henri Christian Junior Tsoungui Obama ◽  
Nessma Adil Mahmoud Yousif ◽  
Looli Alawam Nemer ◽  
Pierre Marie Ngougoue Ngougoue ◽  
Gideon Akumah Ngwa ◽  
...  

Background Different levels of control measures were introduced to contain the global COVID-19 pandemic, many of which have been controversial, particularly the comprehensive use of diagnostic tests. Regular testing of high-risk individuals (pre-existing conditions, older than 60 years of age) has been suggested by public health authorities. The WHO suggested the use of routine screening of residents, employees, and visitors of long-term care facilities (LTCF) to protect the resident risk group. Similar suggestions have been made by the WHO for other closed facilities including incarceration facilities (e.g., prisons or jails), wherein parts of the U.S., accelerated release of approved inmates is taken as a measure to mitigate COVID-19. Methods and findings Here, the simulation model underlying the pandemic preparedness tool CovidSim 1.1 (http://covidsim.eu/) is extended to investigate the effect of regularly testing of employees to protect immobile resident risk groups in closed facilities. The reduction in the number of infections and deaths within the risk group is investigated. Our simulations are adjusted to reflect the situation of LTCFs in Germany, and incarceration facilities in the U.S. COVID-19 spreads in closed facilities due to contact with infected employees even under strict confinement of visitors in a pandemic scenario without targeted protective measures. Testing is only effective in conjunction with targeted contact reduction between the closed facility and the outside world—and will be most inefficient under strategies aiming for herd immunity. The frequency of testing, the quality of tests, and the waiting time for obtaining test results have noticeable effects. The exact reduction in the number of cases depends on disease prevalence in the population and the levels of contact reductions. Testing every 5 days with a good quality test and a processing time of 24 hours can lead up to a 40% reduction in the number of infections. However, the effects of testing vary substantially among types of closed facilities and can even be counterproductive in U.S. IFs. Conclusions The introduction of COVID-19 in closed facilities is unavoidable without a thorough screening of persons that can introduce the disease into the facility. Regular testing of employees in closed facilities can contribute to reducing the number of infections there, but is only meaningful as an accompanying measure, whose economic benefit needs to be assessed carefully.


BMJ Open ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. e026426 ◽  
Author(s):  
Tessa Jansen ◽  
Robert A Verheij ◽  
Francois G Schellevis ◽  
Anton E Kunst

ObjectivesMajor long-term care (LTC) reforms in the Netherlands in 2015 may specifically have disadvantaged socioeconomically deprived groups to acquire LTC, possibly impacting the use of acute care. We aimed to demonstrate whether LTC reforms coincided with changes in the use of out-of-hours (OOH) primary care services (PCSs), and to compare changes between deprived versus affluent neighbourhoods.DesignEcological observational retrospective study using routinely recorded electronic health records data from 2013 to 2016 and population registry data.SettingData from 15 OOH PCSs participating in the Nivel Primary Care Database (covering approximately 6.5 million inhabitants) in the Netherlands. PCS utilisation data on neighbourhood level were matched with sociodemographic characteristics, including neighbourhood socioeconomic status (SES).ParticipantsElectronic health records from 6 120 384 OOH PCS contacts in 2013–2016, aggregated to neighbourhood level.Outcome measures and analysesNumber of contacts per 1000 inhabitants/year (total, high/low-urgency, night/evening-weekend-holidays, telephone consultations/consultations/home visits).Multilevel linear regression models included neighbourhood (first level), nested within PCS catchment area (second level), to account for between-PCS variation, adjusted for neighbourhood characteristics (for instance: % men/women). Difference-in-difference in time-trends according to neighbourhood SES was assessed with addition of an interaction term to the analysis (year×neighbourhood SES).ResultsBetween 2013 and 2016, overall OOH PCS use increased by 6%. Significant increases were observed for high-urgency contacts and contacts during the night. The largest change was observed for the most deprived neighbourhoods (10% compared with 4%–6% in the other neighbourhoods; difference not statistically significant). The increasing trend in OOH PCS use developed practically similar for deprived and affluent neighbourhoods. A a stable gradient reflected more OOH PCS use for each lower stratum of SES.ConclusionsLTC reforms coincided with an overall increase in OOH PCS use, with nearly similar trends for deprived and affluent neighbourhoods. The results suggest a generalised spill over to OOH PCS following LTC reforms.


2013 ◽  
Vol 41 (6) ◽  
pp. 554-557 ◽  
Author(s):  
Sheila Donlon ◽  
Fiona Roche ◽  
Helen Byrne ◽  
Siobhan Dowling ◽  
Meaghan Cotter ◽  
...  

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 1054-1054
Author(s):  
Stephen Frochen ◽  
Jennifer Ailshire ◽  
Seva Rodnyansky ◽  
Connor Sheehan

Abstract The U.S. is aging, and the older adult population and number of long-term care services are growing but not at corresponding rates and concentrations depending on location. Insufficient research has analyzed residential care at the neighborhood or city level of analysis, where geographical trends in growth often reveal notable patterns of long-term care unobserved at county and state levels of analyses. We merged the California Department of Social Services Residential Care for the Elderly Dataset with census place and tract data to chart the growth of facilities and beds per older adults in all of California and its three largest cities, including 805 facilities licensed from 1996 to 2015. During the study timeframe, residential care steadily increased in California by the number of facilities and beds relative to older adults. However, due to a consistently increasing older adult population, the Cities of San Diego and San Jose experienced gradual and intermittent decline in capacity per older adults, respectively, even as they added many beds to their inventories from the sporadic development of large assisted living and continuing care retirement communities. Additionally, San Jose and Los Angeles exhibited the most overlap in mapping densities of facility development and oldest old adults, with San Diego showing less intersection in cartographic analysis. Understanding facility development and care capacity trends can help local agencies and jurisdictions in the U.S. and other countries discern whether planning policies and other geographical and development factors appropriately encourage the development of residential care and other long-term care facilities.


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