Improving Influenza Vaccination Rates Among Healthcare...

Improving Influenza Vaccination Rates Among Healthcare Personnel Using Three Behavioral Intervention Methods 1. The Situation/Challenge: According to the Centers for Disease Control and Prevention (CDC), the number of influenza (flu)-associated deaths in the United States ranges from a low of about 3,000 to a high of about 49,000, annually (CDC, 2010). Vulnerable populations—those with a compromised immune system, elderly, very young children, and critically ill—are especially susceptible to the influenza. (Poland, 2005). Pre-exposure vaccination is the most effective method of preventing influenza and influenza-related morbidity and mortality (Poland, 2005). However, flu vaccination is frequently contra-indicated for the vulnerable†¦show more content†¦According to the California Department of Public Health (CDPH), Senate Bill (SB) 739 (Chapter 526, Statutes of 2006) was adopted into law in 2006 to improve influenza vaccination rates among HCP in California acute care hospitals by requiring employees to be offered vaccine free of charge and either receive the vaccine or to sign a declination form if they choose not to be vaccinated (CDPH, 2014). Despite this law, during the 2012-2013 flu season, influenza vaccine coverage rates among hospital employees remained relatively low—74 percent—well below the 90 percent target rate (CDPH, 2014). 3. The 3 theories that will be applied: This document will review three possible behavioral interventions for increasing vaccination rates among HCP using the following theories of motivation: Reinforcement Theory, Goal-Setting Model, and Alderfer’s ERG Theory. a. Theory/Approach 1: Reinforcement theory will be applied to achieve higher influenza vaccination rates among HCP using rewards and negative consequences based on compliance/non-compliance behavior. i. Background (key works): Reinforcement theory is rooted in theory of operant conditioning based primarily on the work of the American behavior scientist B.F. Skinner (Borkowski, 2011). In contrast to Ivan Pavlov’ respondent conditioning controlled by