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How to Convince People and Get Adherence to Hand Hygiene Practices? The Success of Ozires, the Humanoid Robot!
- Braulio Couto, Amanda Machado, Ana Clara Barbosa, , , , , Bruna Mendes, Maria da Glória Nogueira, Maria Luiza Peixoto, André Alvim, Jeruza Romaniello, Adriana Alves, Bruno Batista, Luciana Covello, Carlos Starling
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, pp. s254-s255
- Print publication:
- October 2020
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- Article
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Background: Our team has been fighting nosocomial infections since 1991. During our journey, we often ask why people do not wash their hands! Semmelweiss discovered in the 1840s that handwashing prevented deaths from puerperal sepsis, but we still need to convince healthcare workers about hand hygiene. One answer is that washing hands is an unsophisticated gesture, without any technology, so people just do not do it. How can we improve compliance with hand hygiene? We imagined a robot in our team to remind people to wash their hands. Then, in 2016 we met Meccanoid, a US$200 toy robot: a 4-foot-tall programmable humanoid robot with voice recognition capabilities. We made adaptions in the robot (mini-projector + audio amplifier + alcohol dispenser + spy camera), and we gave him a name (Ozires) and a purpose: He became a professor who teaches healthcare workers how, when, and why wash their hands! Here, we describe the multimodal strategy centered around Ozires. Methods: The multimodal strategy consists of 7 key elements: (1) the robot, accompanied by a infection control practitioner, performs audio and video lectures about hand hygiene techniques, motivational videos, data feedback; (2) the robot’s wood copies with sound alert with motion detector for hand hygiene are spread out in the whole hospital; (3) fridge magnet with robot prints (gifts for patients and healthcare professionals); (4) app for hand hygiene monitoring (Hands Clean); (5) adherence rates by professional category and individual feedback; (6) patient empowerment for hand hygiene; and (7) sound alert for hand hygiene in the patient room’s door. Results: After the insertion of Ozires in 3 ICUs of hospital A (pilot study), the hand hygiene (HH) rate increased from ~36%, between January and July 2016, to ~68% between August 2016 and October 2019. At hospital B, Ozires started his lectures in May 2018, throughout the hospital. Hand hygiene adherence increased from 23% between July and December 2017 to 60% between June 2018 and October 2019. In the 3 months before this multimodal strategy was implemented in hospital C (June–August 2019), and the mean rate of hand hygiene was 65%. With the robot, the hand hygiene rate increased to 94% (September–October 2019). Conclusions: The multimodal strategy centered around the robot Ozires works! Hand hygiene compliance increased significantly after the interventions. People listen the robot much more attentively than to their human colleagues, and healthcare worker behavior changed! We need to go further improve the program, but it is sustainable. Finally, we succeeded in convincing people to improve their hand hygiene practices.
Funding: None
Disclosures: None
Quality of Hospital Infection Control Programs in Low- and Middle-income Countries: A National Survey
- André Alvim, Gazzinell Gazzinell, Braulio Couto
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, p. s363
- Print publication:
- October 2020
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- Article
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- You have access Access
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Background: One of the strategies to reduce healthcare-associated infections (HAIs) and promote the quality of disease prevention and control actions is the creation of a hospital infection control program. This program is a set of deliberately and systematically developed actions aimed toward reducing the incidence and severity of infections to the maximum extent possible. In Brazil, studies on the subject still need to be improved; they focus on structural and process assessments, especially the survey of continuing education indicators as a quality requirement for the prevention of HAIs. The organizational context does not contribute to the success of the program, and difficulties remain in implementing recommendations and in implementing patient safety policies. Objective: To analyze hospital infection control programs in relation to quality components. Methods: This cross-sectional epidemiological study was conducted in health services located in the 5 official regions of Brazil: Midwest, Northeast, North, Southeast, and South. To select the study sites, nonprobabilistic sampling using the snowball technique was used. The potential study population consisted of 114 hospital infection control services. Health professionals responded to the structured instrument sent electronically via e-mail, and other health services near their locality, until reaching a national proportion. We used the “Hospital Infection Control Program Evaluation Questionnaire”; it consists of 36 multiple-choice questions. This tool was validated by 96 expert judges using the Cronbach’s alpha test (0.82) and the content validity index (0.88). A data analysis was performed using the multivariate principal component analysis technique (PCA). Results: Overall, 13 PCA components (Fig. 1) were used to build a score for measuring the performance of the hospital infection control program (ie, IQPC score). The Southern region had the best performance of the hospital infection control program (mi = 1.50; P = .02) (Fig. 2), private administration (mi = 0.45; P = .05), of hospitals that contained 300 beds or (mi = 1.38; P < .01), hospitals that used the NHSN criterion for HAI surveillance (mi = 2.12; P < .01), and those who searched prospective activity as a surveillance method (mi = 0.51; P < .01). Conclusions: The quality of nosocomial infection control programs still needs to be improved among health services, highlighting the need to invest in small, publicly managed hospitals that use retrospective active surveillance methods.
Funding: None
Disclosures: None