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Adverse Events Following Inuenza Immunization Reported by Healthcare Personnel Using Active Surveillance Based on Text Messages Lauren E. Tracey, Annette K. Regan, Donna B. Mak and Paul V. Efer Infection Control & Hospital Epidemiology / Volume 36 / Issue 05 / May 2015, pp 608 - 610 DOI: 10.1017/ice.2015.16, Published online: 05 February 2015
Link to this article: http://journals.cambridge.org/abstract_S0899823X15000161 How to cite this article: Lauren E. Tracey, Annette K. Regan, Donna B. Mak and Paul V. Efer (2015). Adverse Events Following Inuenza Immunization Reported by Healthcare Personnel Using Active Surveillance Based on Text Messages. Infection Control & Hospital Epidemiology, 36, pp 608-610 doi:10.1017/ice.2015.16 Request Permissions : Click here
Downloaded from http://journals.cambridge.org/ICE, IP address: 169.230.243.252 on 20 Apr 2015
608
infection control & hospital epidemiology
may 2015, vol. 36, no. 5
Gerais, Brazil; 6. Lagoon Hospitals, Lagos, Nigeria; 7. Breach Candy Hospital Trust, Mumbai, India; 8. Maine Medical Center, Portland, Maine, USA; 9. Boston Medical Center, Boston, Massachusetts, USA; 10. Johns Hopkins University, Baltimore, Maryland, USA. Received September 23, 2014; accepted December 17, 2014; electronically published January 29, 2015 Infect Control Hosp Epidemiol 2015;36(5):605–608 © 2015 by The Society for Healthcare Epidemiology of America. All rights reserved. 0899-823X/2015/3605-0021. DOI: 10.1017/ice.2015.11
references 1. Magill SS, Edwards JR, Bamberg W, et al. Multistate pointprevalence survey of health care-associated infections. N Engl J Med 2014;370:1198–1208. 2. Christian KA, Ijaz K, Dowell SF, et al. What we are watching—5 top global infectious disease threats, 2012: a perspective from CDC’s Global Disease Detection Operations Center. Emerg Health Threats J 2013;6:20632. 3. Hughes JM. Study on the efficacy of nosocomial infection control (SENIC Project): results and implications for the future. Chemotherapy 1988;34:553–561. 4. Hospital Compare Data. Healthcare-associated infections. The Official U.S. Government Site for Medicare website. http:// www.medicare.gov/hospitalcompare/Data/Healthcare-AssociatedInfections.html. Published 2014. Accessed April 2014. 5. SHEA Research Network. SRN studies and resources. The Society for Healthcare Epidmiology of America website. http://www.sheaonline.org/Research/SHEAResearchNetwork/SRNStudiesand Resources.aspx. Published 2014. Accessed April 2014. 6. National Center for Emerging and Zoonotic Infectious Diseases DoHQP. Guidance for control of carbapenem-resistant enterobacteriaceae (CRE). 2012 CRE Toolkit2012. 7. Garrett DO, Jarvis WR. The expanding role of healthcare epidemiology—home and long-term care. Infect Control Hosp Epidemiol 1996;17:714–717.
Adverse Events Following Influenza Immunization Reported by Healthcare Personnel Using Active Surveillance Based on Text Messages
Studies have demonstrated that healthcare personnel (HCP) have concerns about the potential side effects of trivalent inactivated influenza vaccine (IIV3).1–3 A recent meta-analysis of reasons HCP refuse IIV3 indicates the strongest predictors of vaccine acceptance are belief that the vaccine is safe and belief the vaccine does not cause the disease it is meant to prevent.1 Timely vaccine safety information for each new seasonal IIV3 vaccine can be used to reassure HCP. In addition, the ability to provide real-time safety profiling of new vaccines should form part of emergency preparedness planning—for
example, in the case of rapid development and rollout of vaccines in a pandemic. Despite ready access to vaccines and concerted efforts to promote uptake, influenza vaccination coverage among HCP in Australia has historically been low, ranging from 18% to 66%.4 In a review of 32 studies from the United States (13), Canada (5), Europe (11), and others (3), Hofmann et al found influenza vaccine coverage of less than 50% in HCP in the majority (26 [81%]) of these studies.5 In 2014, the Western Australian Department of Health developed the Follow-up and Active Surveillance of Trivalent Influenza Vaccine in HCP (FASTHealth) program. FASTHealth is a Short Message Service (SMS)-based, active influenza vaccine safety monitoring program intended to be implemented at the start of each season’s annual HCP vaccination program. The Western Australian Department of Health provides free IIV3 for staff working in government health facilities and maintains a centralized record-keeping system for recording HCP influenza immunization. In 2014, HCP were asked at the time of vaccination to participate in the FASTHealth program to monitor adverse events following immunization (AEFIs). HCP who consented and provided a mobile phone number were sent a text message (or “SMS”) 7 days after vaccination querying whether they had experienced any “reaction, fever or illness” following vaccination. A second SMS was sent 24 hours later to anyone who did not reply to the first message. HCP who responded “Yes” to either message were sent a link to a mobile phone survey to record the details of their AEFI. Those who opted not to complete the smartphone survey and those who did not reply to either SMS were telephoned to ascertain specifics of any AEFI via a standardized interview with a research nurse. Both surveys were identical in content and asked whether the participant experienced fever, headache, fatigue, vomiting, rash, rigors, convulsions, or swelling or pain at the injection site. Other reported potential adverse effects were recorded verbatim/as written. From March 19 through May 20, 2014, a total of 1,624 HCP, including medical, administration, and support staff, were sent an SMS soliciting whether they experienced an AEFI. Most were women (81%) and 18-44 years of age (56%); 835 HCP received intradermal IIV3 (Intanza: 51.4%) and 789 received an intramuscular IIV3 (Vaxigrip: 48.3%; Fluvax: 0.3%). Of those who were sent an SMS message, 1,432 (88%) replied. A total of 239 (17%) of the respondents replied affirmatively that they had experienced one or more reactions to the vaccine. Of those reporting reactions, 184 (77%) provided details regarding the AEFI: 66 via the mobile phone survey and 118 by telephone. The remaining 55 HCP were lost to follow-up. Among the 192 HCP who did not reply to the SMS, 65 (34%) were subsequently reached by telephone and 20 (31%) of these reported an event. In aggregate, 1,442 HCP provided complete information regarding the occurrence of AEFI, of which 204 (14.1% [95% CI, 12.2%-16.1%]) reported at least one reaction (Figure 1). No severe adverse events were reported. A total of 137 HCP reported at least one systemic symptom, most commonly
adverse events following immunization in hcp
figure 1.
609
Responses to the FASTHealth program March 19-May 20, 2014.
fatigue (3.8% [95% CI, 2.8%–4.8%]), headache (3.7% [95% CI, 2.7%–4.7%]), or respiratory symptoms (3.7% [95% CI, 2.7%–4.7%]). One hundred fifteen HCP reported redness, pain, or swelling at the injection site (8.0% [95% CI, 6.5%– 1.7%]). These results were in keeping with the documented safety profile of IIV3 vaccine. Use of SMS technology in the FASTHealth program allowed rapid, active surveillance of the safety of IIV3 offered free to HCP as part of the annual influenza program. Consistent with previous vaccine safety investigations of seasonal IIV3 in HCP, the proportion reporting a potential adverse effect was low.6,7 Because the antigenic components of the influenza vaccine can change from season to season and safety profiles from previous seasons’ formulations may not be applicable to current vaccines, it is particularly important to monitor the safety of IIV3 each year. Our findings demonstrate the feasibility of implementing a timely, resource-conserving, vaccine safety monitoring system among HCP each year during influenza vaccination season. Previous methods to capture AEFI following IIV3 in HCP mainly include self-report paper questionnaires, which require significantly more time to capture, record, and analyze the data.6–8 Smartphone penetration in Australia was reported at 65% in 2013, making it a suitable market for the use of such technology.8 In the same survey, smartphone use was reportedly
less common in the United Kingdom (62%) and the United States (56%); however, overall there is increasing smartphone penetration globally, and in future the use of this technology has applications any time a new vaccine is introduced.9 The information obtained can be used to reassure HCP regarding the reactogenicity of the vaccine and potentially used to improve uptake among HCP. Future studies should investigate communication strategies for informing HCP about the safety of IIV3. Considering the potential to prevent disease in HCP, their families, and their patients, opportunities to disseminate safety data to HCP in real time should be further explored.
acknowledgments We thank the research nurses at the Vaccine Trials Group, Telethon Kids Institute, for their work in telephone follow-up of the adverse events, and Sharon Gough, for her assistance in data management of the program. Financial support. Western Australian Department of Health. Potential conflicts of interest. All authors report no conflicts of interest relevant to this article.
Lauren E. Tracey, MPH;1 Annette K. Regan, MPH;1,2 Donna B. Mak, MPH;1,3 Paul V. Effler, MD1,2
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infection control & hospital epidemiology
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Affiliations: 1. Communicable Disease Control Directorate, Western Australian Department of Health, Perth, Western Australia, Australia; 2. School of Pathology and Laboratory Medicine, University of Western Australia, Perth, Western Australia, Australia; 3. School of Medicine, University of Notre Dame, Fremantle, Western Australia, Australia Address correspondence to Lauren E. Tracey, MPH, Communicable Disease Control Directorate, Western Australian Department of Health, 227 Stubbs Terrace, Shenton Park, Western Australia, 6008, Australia ([email protected]). Received August 25, 2014; accepted January 12, 2015; electronically published February 5, 2015 Infect Control Hosp Epidemiol 2015;36(5):608–610 © 2015 by The Society for Healthcare Epidemiology of America. All rights reserved. 0899-823X/2015/3605-0022. DOI: 10.1017/ice.2015.16
definitions of role model.3,4 For example, a University of Utah study of 66 nursing students found that HH compliance was positively influenced by the HH practices of their mentors.4 However, a Northwestern University study of 721 HCWs found a negative effect. If a senior health professional did not wash his or her hands, HCWs were less likely to wash their hands. However, no change in behavior was observed if a senior health professional did wash their hands.3 In our study, we analyzed ~3,000 HH observations to describe the impact of being in a group (≥2 people) with a leader modeling HH compliance to determine whether the HH practices of HCWs in groups are influenced by the HH practices of group role models.
references methods 1. Vasilevska M, Ku J, Fisman DN. Factors associated with healthcare worker acceptance of vaccination: a systematic review and metaanalysis. Infect Control Hosp Epidemiol 2014;35:699–708. 2. Skowronski DM, Parker R, Strang R. The importance of influenza immunizations for health-care workers. BCMJ 2000;42:91–93. 3. Loulergue P, Moulin F, Vidal-Trecan G, et al. Knowledge, attitudes and vaccination coverage of healthcare workers regarding occupational vaccinations. Vaccine 2009;31:4240–4243. 4. Seale H, MacIntyre CR. Seasonal influenza vaccination in Australia hospital health care workers: a review. Med J Aust 2011;195:336–338. 5. Hofmann F, Ferracin C, Marsh G, Dumas R. Influenza vaccination of healthcare workers: a literature review of attitudes and beliefs. Infection 2006;34:142–147. 6. McEvoy SP. A retrospective survey of the safety of trivalent influenza vaccine among adults working in healthcare setting in south metropolitan Perth, Western Australia, in 2010. Vaccine 2012;30:2801–2804. 7. Ankrah DNA, Mantel-Teeuwisse AK, De Bruin ML, et al. Incidence of adverse events among healthcare workers following H1N1 mass immunization in Ghana. Drug Safety 2013;36: 259–266. 8. Scheifele DW, Bjornson G, Johnston J. Evaluation of adverse events after influenza vaccination in hospital personnel. CMAJ 1990;142:127–130. 9. Think With Google. Our mobile planet: understanding the mobile consumer. Data sets and country reports. 2013. http://think.with google.com/mobileplanet/en/downloads/. Accessed January 1, 2015.
The Impact of Role Models on Hand Hygiene Compliance
Proper hand hygiene (HH) is the single most important factor in preventing healthcare-associated infections (HAIs), but HH compliance rates remain alarmingly low among healthcare workers (HCWs).1,2 Social dynamics may influence HH practices, but evidence supporting an effect of role models and leadership regarding HH is limited by small samples and loose
Study Population A total of 4 adult inpatient care units at a single tertiary care hospital were selected for study: a rehabilitation unit, an intensive care unit, and 2 observation units. HH stations, defined as either a sink or an alcohol-based hand rub (ABHR), were located both inside and outside of patient rooms. Only the intensive care unit had glass windows to allow viewing of HH stations inside a patient’s room; in-room HH stations in other units were not observed (to maintain patient privacy). Units were observed between February 14 and 28, 2014, by 21 graduate students (8 hours/student). Observers were trained in the use of a standardized observation tool employed for data collection. The tool was an HH observation tool used at UMHS with modifications. Definitions Data were collected at 4 HH opportunities: room entry, room exit, before gloves were put on, and after glove removal. Glove use followed hospital policy for standard precautions or contact precautions as appropriate. Successful HH was defined as the use of soap and water or ABHR when presented with an HH opportunity. Observations were classified as “group” or “individual,” where “group” was defined as 2 or more HCWs presented with the same HH opportunity at the same time. “Individual” was defined as any nongroup observation. A “group leader” was defined as the HCW with the highest apparent seniority in the group who was considered the HH role model for that group. If no leader was apparent, the group was regarded as leaderless. Observations were further stratified by unit and HCW type based on attire, including long white coats (eg, worn by attending physicians, residents, physician assistants, nurse practitioners), short white coats (eg, worn by students), scrubs (eg, worn by nurses), and other attire (eg, worn by environmental services, dietary, transport, etc.). Analysis We calculated HH compliance, defined as the proportion of successful HH events, separately for groups and individuals.
Control & Hospital Epidemiology:
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Adverse Events Following Inuenza Immunization Reported by Healthcare Personnel Using Active Surveillance Based on Text Messages Lauren E. Tracey, Annette K. Regan, Donna B. Mak and Paul V. Efer Infection Control & Hospital Epidemiology / Volume 36 / Issue 05 / May 2015, pp 608 - 610 DOI: 10.1017/ice.2015.16, Published online: 05 February 2015
Link to this article: http://journals.cambridge.org/abstract_S0899823X15000161 How to cite this article: Lauren E. Tracey, Annette K. Regan, Donna B. Mak and Paul V. Efer (2015). Adverse Events Following Inuenza Immunization Reported by Healthcare Personnel Using Active Surveillance Based on Text Messages. Infection Control & Hospital Epidemiology, 36, pp 608-610 doi:10.1017/ice.2015.16 Request Permissions : Click here
Downloaded from http://journals.cambridge.org/ICE, IP address: 169.230.243.252 on 20 Apr 2015
608
infection control & hospital epidemiology
may 2015, vol. 36, no. 5
Gerais, Brazil; 6. Lagoon Hospitals, Lagos, Nigeria; 7. Breach Candy Hospital Trust, Mumbai, India; 8. Maine Medical Center, Portland, Maine, USA; 9. Boston Medical Center, Boston, Massachusetts, USA; 10. Johns Hopkins University, Baltimore, Maryland, USA. Received September 23, 2014; accepted December 17, 2014; electronically published January 29, 2015 Infect Control Hosp Epidemiol 2015;36(5):605–608 © 2015 by The Society for Healthcare Epidemiology of America. All rights reserved. 0899-823X/2015/3605-0021. DOI: 10.1017/ice.2015.11
references 1. Magill SS, Edwards JR, Bamberg W, et al. Multistate pointprevalence survey of health care-associated infections. N Engl J Med 2014;370:1198–1208. 2. Christian KA, Ijaz K, Dowell SF, et al. What we are watching—5 top global infectious disease threats, 2012: a perspective from CDC’s Global Disease Detection Operations Center. Emerg Health Threats J 2013;6:20632. 3. Hughes JM. Study on the efficacy of nosocomial infection control (SENIC Project): results and implications for the future. Chemotherapy 1988;34:553–561. 4. Hospital Compare Data. Healthcare-associated infections. The Official U.S. Government Site for Medicare website. http:// www.medicare.gov/hospitalcompare/Data/Healthcare-AssociatedInfections.html. Published 2014. Accessed April 2014. 5. SHEA Research Network. SRN studies and resources. The Society for Healthcare Epidmiology of America website. http://www.sheaonline.org/Research/SHEAResearchNetwork/SRNStudiesand Resources.aspx. Published 2014. Accessed April 2014. 6. National Center for Emerging and Zoonotic Infectious Diseases DoHQP. Guidance for control of carbapenem-resistant enterobacteriaceae (CRE). 2012 CRE Toolkit2012. 7. Garrett DO, Jarvis WR. The expanding role of healthcare epidemiology—home and long-term care. Infect Control Hosp Epidemiol 1996;17:714–717.
Adverse Events Following Influenza Immunization Reported by Healthcare Personnel Using Active Surveillance Based on Text Messages
Studies have demonstrated that healthcare personnel (HCP) have concerns about the potential side effects of trivalent inactivated influenza vaccine (IIV3).1–3 A recent meta-analysis of reasons HCP refuse IIV3 indicates the strongest predictors of vaccine acceptance are belief that the vaccine is safe and belief the vaccine does not cause the disease it is meant to prevent.1 Timely vaccine safety information for each new seasonal IIV3 vaccine can be used to reassure HCP. In addition, the ability to provide real-time safety profiling of new vaccines should form part of emergency preparedness planning—for
example, in the case of rapid development and rollout of vaccines in a pandemic. Despite ready access to vaccines and concerted efforts to promote uptake, influenza vaccination coverage among HCP in Australia has historically been low, ranging from 18% to 66%.4 In a review of 32 studies from the United States (13), Canada (5), Europe (11), and others (3), Hofmann et al found influenza vaccine coverage of less than 50% in HCP in the majority (26 [81%]) of these studies.5 In 2014, the Western Australian Department of Health developed the Follow-up and Active Surveillance of Trivalent Influenza Vaccine in HCP (FASTHealth) program. FASTHealth is a Short Message Service (SMS)-based, active influenza vaccine safety monitoring program intended to be implemented at the start of each season’s annual HCP vaccination program. The Western Australian Department of Health provides free IIV3 for staff working in government health facilities and maintains a centralized record-keeping system for recording HCP influenza immunization. In 2014, HCP were asked at the time of vaccination to participate in the FASTHealth program to monitor adverse events following immunization (AEFIs). HCP who consented and provided a mobile phone number were sent a text message (or “SMS”) 7 days after vaccination querying whether they had experienced any “reaction, fever or illness” following vaccination. A second SMS was sent 24 hours later to anyone who did not reply to the first message. HCP who responded “Yes” to either message were sent a link to a mobile phone survey to record the details of their AEFI. Those who opted not to complete the smartphone survey and those who did not reply to either SMS were telephoned to ascertain specifics of any AEFI via a standardized interview with a research nurse. Both surveys were identical in content and asked whether the participant experienced fever, headache, fatigue, vomiting, rash, rigors, convulsions, or swelling or pain at the injection site. Other reported potential adverse effects were recorded verbatim/as written. From March 19 through May 20, 2014, a total of 1,624 HCP, including medical, administration, and support staff, were sent an SMS soliciting whether they experienced an AEFI. Most were women (81%) and 18-44 years of age (56%); 835 HCP received intradermal IIV3 (Intanza: 51.4%) and 789 received an intramuscular IIV3 (Vaxigrip: 48.3%; Fluvax: 0.3%). Of those who were sent an SMS message, 1,432 (88%) replied. A total of 239 (17%) of the respondents replied affirmatively that they had experienced one or more reactions to the vaccine. Of those reporting reactions, 184 (77%) provided details regarding the AEFI: 66 via the mobile phone survey and 118 by telephone. The remaining 55 HCP were lost to follow-up. Among the 192 HCP who did not reply to the SMS, 65 (34%) were subsequently reached by telephone and 20 (31%) of these reported an event. In aggregate, 1,442 HCP provided complete information regarding the occurrence of AEFI, of which 204 (14.1% [95% CI, 12.2%-16.1%]) reported at least one reaction (Figure 1). No severe adverse events were reported. A total of 137 HCP reported at least one systemic symptom, most commonly
adverse events following immunization in hcp
figure 1.
609
Responses to the FASTHealth program March 19-May 20, 2014.
fatigue (3.8% [95% CI, 2.8%–4.8%]), headache (3.7% [95% CI, 2.7%–4.7%]), or respiratory symptoms (3.7% [95% CI, 2.7%–4.7%]). One hundred fifteen HCP reported redness, pain, or swelling at the injection site (8.0% [95% CI, 6.5%– 1.7%]). These results were in keeping with the documented safety profile of IIV3 vaccine. Use of SMS technology in the FASTHealth program allowed rapid, active surveillance of the safety of IIV3 offered free to HCP as part of the annual influenza program. Consistent with previous vaccine safety investigations of seasonal IIV3 in HCP, the proportion reporting a potential adverse effect was low.6,7 Because the antigenic components of the influenza vaccine can change from season to season and safety profiles from previous seasons’ formulations may not be applicable to current vaccines, it is particularly important to monitor the safety of IIV3 each year. Our findings demonstrate the feasibility of implementing a timely, resource-conserving, vaccine safety monitoring system among HCP each year during influenza vaccination season. Previous methods to capture AEFI following IIV3 in HCP mainly include self-report paper questionnaires, which require significantly more time to capture, record, and analyze the data.6–8 Smartphone penetration in Australia was reported at 65% in 2013, making it a suitable market for the use of such technology.8 In the same survey, smartphone use was reportedly
less common in the United Kingdom (62%) and the United States (56%); however, overall there is increasing smartphone penetration globally, and in future the use of this technology has applications any time a new vaccine is introduced.9 The information obtained can be used to reassure HCP regarding the reactogenicity of the vaccine and potentially used to improve uptake among HCP. Future studies should investigate communication strategies for informing HCP about the safety of IIV3. Considering the potential to prevent disease in HCP, their families, and their patients, opportunities to disseminate safety data to HCP in real time should be further explored.
acknowledgments We thank the research nurses at the Vaccine Trials Group, Telethon Kids Institute, for their work in telephone follow-up of the adverse events, and Sharon Gough, for her assistance in data management of the program. Financial support. Western Australian Department of Health. Potential conflicts of interest. All authors report no conflicts of interest relevant to this article.
Lauren E. Tracey, MPH;1 Annette K. Regan, MPH;1,2 Donna B. Mak, MPH;1,3 Paul V. Effler, MD1,2
610
infection control & hospital epidemiology
may 2015, vol. 36, no. 5
Affiliations: 1. Communicable Disease Control Directorate, Western Australian Department of Health, Perth, Western Australia, Australia; 2. School of Pathology and Laboratory Medicine, University of Western Australia, Perth, Western Australia, Australia; 3. School of Medicine, University of Notre Dame, Fremantle, Western Australia, Australia Address correspondence to Lauren E. Tracey, MPH, Communicable Disease Control Directorate, Western Australian Department of Health, 227 Stubbs Terrace, Shenton Park, Western Australia, 6008, Australia ([email protected]). Received August 25, 2014; accepted January 12, 2015; electronically published February 5, 2015 Infect Control Hosp Epidemiol 2015;36(5):608–610 © 2015 by The Society for Healthcare Epidemiology of America. All rights reserved. 0899-823X/2015/3605-0022. DOI: 10.1017/ice.2015.16
definitions of role model.3,4 For example, a University of Utah study of 66 nursing students found that HH compliance was positively influenced by the HH practices of their mentors.4 However, a Northwestern University study of 721 HCWs found a negative effect. If a senior health professional did not wash his or her hands, HCWs were less likely to wash their hands. However, no change in behavior was observed if a senior health professional did wash their hands.3 In our study, we analyzed ~3,000 HH observations to describe the impact of being in a group (≥2 people) with a leader modeling HH compliance to determine whether the HH practices of HCWs in groups are influenced by the HH practices of group role models.
references methods 1. Vasilevska M, Ku J, Fisman DN. Factors associated with healthcare worker acceptance of vaccination: a systematic review and metaanalysis. Infect Control Hosp Epidemiol 2014;35:699–708. 2. Skowronski DM, Parker R, Strang R. The importance of influenza immunizations for health-care workers. BCMJ 2000;42:91–93. 3. Loulergue P, Moulin F, Vidal-Trecan G, et al. Knowledge, attitudes and vaccination coverage of healthcare workers regarding occupational vaccinations. Vaccine 2009;31:4240–4243. 4. Seale H, MacIntyre CR. Seasonal influenza vaccination in Australia hospital health care workers: a review. Med J Aust 2011;195:336–338. 5. Hofmann F, Ferracin C, Marsh G, Dumas R. Influenza vaccination of healthcare workers: a literature review of attitudes and beliefs. Infection 2006;34:142–147. 6. McEvoy SP. A retrospective survey of the safety of trivalent influenza vaccine among adults working in healthcare setting in south metropolitan Perth, Western Australia, in 2010. Vaccine 2012;30:2801–2804. 7. Ankrah DNA, Mantel-Teeuwisse AK, De Bruin ML, et al. Incidence of adverse events among healthcare workers following H1N1 mass immunization in Ghana. Drug Safety 2013;36: 259–266. 8. Scheifele DW, Bjornson G, Johnston J. Evaluation of adverse events after influenza vaccination in hospital personnel. CMAJ 1990;142:127–130. 9. Think With Google. Our mobile planet: understanding the mobile consumer. Data sets and country reports. 2013. http://think.with google.com/mobileplanet/en/downloads/. Accessed January 1, 2015.
The Impact of Role Models on Hand Hygiene Compliance
Proper hand hygiene (HH) is the single most important factor in preventing healthcare-associated infections (HAIs), but HH compliance rates remain alarmingly low among healthcare workers (HCWs).1,2 Social dynamics may influence HH practices, but evidence supporting an effect of role models and leadership regarding HH is limited by small samples and loose
Study Population A total of 4 adult inpatient care units at a single tertiary care hospital were selected for study: a rehabilitation unit, an intensive care unit, and 2 observation units. HH stations, defined as either a sink or an alcohol-based hand rub (ABHR), were located both inside and outside of patient rooms. Only the intensive care unit had glass windows to allow viewing of HH stations inside a patient’s room; in-room HH stations in other units were not observed (to maintain patient privacy). Units were observed between February 14 and 28, 2014, by 21 graduate students (8 hours/student). Observers were trained in the use of a standardized observation tool employed for data collection. The tool was an HH observation tool used at UMHS with modifications. Definitions Data were collected at 4 HH opportunities: room entry, room exit, before gloves were put on, and after glove removal. Glove use followed hospital policy for standard precautions or contact precautions as appropriate. Successful HH was defined as the use of soap and water or ABHR when presented with an HH opportunity. Observations were classified as “group” or “individual,” where “group” was defined as 2 or more HCWs presented with the same HH opportunity at the same time. “Individual” was defined as any nongroup observation. A “group leader” was defined as the HCW with the highest apparent seniority in the group who was considered the HH role model for that group. If no leader was apparent, the group was regarded as leaderless. Observations were further stratified by unit and HCW type based on attire, including long white coats (eg, worn by attending physicians, residents, physician assistants, nurse practitioners), short white coats (eg, worn by students), scrubs (eg, worn by nurses), and other attire (eg, worn by environmental services, dietary, transport, etc.). Analysis We calculated HH compliance, defined as the proportion of successful HH events, separately for groups and individuals.
