The ratio of 1 infection prevention resource for a 250 acute-care bed facility was considered the historical standard for hospital settings following the 1970 ’ s Centers for Disease Control and Prevention initiated study on the efficacy of nosocomial infection control project .
Since this time , the role and scope of infection prevention has changed significantly , particularly regarding increased requirements for regulatory reporting and response ." — Shanina
Knighton , PhD , RN , CIC
paper was that healthcare facilities are not one-sizefits-all , so that model is never going to work . There must be individual facility-level risk assessment used to determine what staffing looks like and then the calculator is intended to be a practical , easy way to do that , understanding that not every facility has the resources to do that sort of complex risk assessment .”
As Knighton , et al . ( 2024 ) observe , “ The ratio of 1 infection prevention resource for a 250 acute-care bed facility was considered the historical standard for hospital settings following the 1970 ’ s Centers for Disease Control and Prevention initiated study on the efficacy of nosocomial infection control project . Since this time , the role and scope of infection prevention has changed significantly , particularly regarding increased requirements for regulatory reporting and response . More recently reported ratios vary from a high of one IP per 152 beds to a low of one IP per 69 beds . This metric is limited in several ways . First , there is variability in the type of inpatient bed referenced ( licensed bed versus staffed bed ), which adds nuance to the application of the ratio . It also does not account for the complexity that may exist within a facility in both the size and scope of services provided . Facilities with extraordinarily complex or high-risk programs may require more robust infection prevention staffing than facilities without these programs . Given the “ one-size-fits-all ” nature of this metric , it falls short of providing the granular viewpoint needed to effectively staff an IP & C program .”
Instead , Shanina Knighton , PhD , RN , CIC , from the Case Western Reserve University ’ s Frances Payne Bolton School of Nursing , says , “ The best formula for infection prevention ( IP ) staffing , particularly to prevent healthcare-associated infections ( HAIs ), focuses on workload rather than simple patient or bed ratios . A more effective model , such as the WHO ’ s Workload Indicators of Staffing Need ( WISN ), evaluates specific tasks required of IPs — like surveillance and education — while accounting for facility size , patient acuity , and unique community needs . Research suggests that IP staffing must periodically adapt based on evolving demands , with active surveillance being a significant time investment , particularly for infections like CLABSIs .”
A more realistic approach to better standardization is possible , Knighton says .
“ This could involve augmented reality ( AR ) or extended reality ( ER ) technologies to automate task tracking ,” she explains . “ Unlike manual recording , AR / XR tools allow IPs to document inspections in realtime with automatic timestamping and data logging , reducing human error and improving accuracy . These tools also offer task reminders and visual guides , ensuring consistency . Beyond documentation , immersive XR training can standardize workflows more efficiently across teams . This streamlines workload analysis , aligning staffing metrics with real performance , and enables data-driven improvements in resource allocation .”
How IPs segment their day to fulfill their responsibilities has been studied , but as Knighton points out , a more granular viewpoint of how IP working hours are spent has not yet been quantified into a formal metric . As Knighton , et al . ( 2024 ) note , “ There is a large degree of heterogeneity reported in the literature . Administrative tasks and infection surveillance consistently ranked highest and account for between one-quarter and one-half of work hours . In settings where an individual has infection prevention responsibilities as part of a larger role , this may leave little time for other , more staff-centered and beneficial IP tasks ( like rounding and education ). Nonetheless , quantification of a metric that reflects the day-to-day tasks of an infection preventionist specific to the care setting within which they work will provide the most accurate assessment of staffing needs .”
No matter the metric used , the impact staffing has on patient outcomes cannot be denied .
“ The impact of IP staffing on patient outcomes is influenced by missed nursing care , limited IP rounding , workforce challenges , and resource constraints ,” Knighton emphasizes . “ Retiring nurses , budget cuts , and reliance on untrained or undertrained staff disrupt infection control efforts . As new equipment and innovative methods require continuous training across all healthcare roles , infection prevention must be integrated into every aspect of patient care . Moreover , IPs are essential not just on the frontlines but also in the C-suite , where they can shape policies that prioritize infection control and resource allocation effectively .
Knighton describes an ideal IP staffing model as one that is “ risk-based , flexible , and embedded across all levels of healthcare ,” she says . “ It would assign staffing proportionate to the complexity of care settings ( such as ICU versus outpatient clinics ) and ensure IPs are integrated into both frontline operations and executive leadership ( C-suite ) to influence policy and resource allocation . All healthcare workers — not just IPs — would receive regular infection prevention training . Automation tools ( like AR / XR ) would assist in real-time monitoring and documentation , improving efficiency without increasing administrative burdens .”
Knighton adds that the APIC staffing calculator is “ a valuable tool for determining the appropriate number of IPs based on various factors like facility type , patient volume , and infection rates . It helps present a business case to the C-suite by quantifying staffing needs and aligning them with patient safety outcomes , regulatory compliance , and cost savings from reduced infection rates . Utilizing this data can strengthen arguments for necessary resources and staffing levels in infection prevention programs .”
Regarding the Bartles , et al . ( 2024 ) paper , “ This study lays to rest any doubt about the critical need for appropriate levels of IP staffing , identifying an undeniable link between sufficient infection prevention and control resources and patient safety , as measured by rates of healthcare-associated infections ,” said 2024 APIC president Tania Bubb , PhD , RN , CIC , FAPIC , in a recent statement . “ I believe this calculator will be essential for ensuring that healthcare facilities can target optimal IP staff numbers and improve patient care . It ’ s an excellent example of the research and development APIC is doing to enhance infection prevention and control everywhere .”
APIC says it calls on hospital leadership to require use of the staffing calculator to evaluate the need for IP staff , and more importantly , make needed investments in IP staffing per the customized staffing
20 • www . healthcarehygienemagazine . com • november 2024