Controlling the spread of healthcare associated infections is a priority to reduce morbidity, mortality, and cost. Intervention decisions based on model or simulation outputs often depend on input data from one facility. Poor hand hygiene adherence contributes to the spread of disease and current measurement methods based on observation are error-prone. A recent study linking transmission to observed contact networks has revealed the need for more data on contact between providers and between providers and patients. Healthcare provider behaviors vary among individuals, wards, and facilities so larger scale studies are needed to understand behavior. Models to evaluate interventions must include multiple facilities and take these differences into account.
The objectives of this study are to: 1) collect and summarize provider-Veteran contact networks in Veterans Affairs Medical Centers (VAMC's), 2) test new methods for accurate measurement of hand hygiene adherence, and 3) evaluate control strategies for healthcare associated infection in simulations that incorporate these data. We will meet these objectives across facilities to evaluate variability in outcomes for each control strategy.
We will link patients to providers who write notes in their electronic health record, creating a contact network. We will use wireless sensors in three of these VAMC's to collect contact network and hand hygiene data. Wireless sensors detect proximity between people, occupancy of a room, and use of alcohol-based hand sanitizer (gel) and soap dispensers. There will be two two-week deployments at each site. We will also perform hand hygiene observations during half of the sensor deployments to estimate Hawthorne effect. An existing one-facility agent based model simulation will be expanded to accept contact network and hand hygiene adherence data. It can be calibrated to multiple facilities.
The data collected with sensors will also be used to estimate differences in contact network characteristics among wards and facilities. Hand hygiene rates will be assessed for differences among wards, health care provider roles, self-reported beliefs, and care situations. We will survey participants about their perceptions of hand hygiene and link responses to sensor data. Associations will be explored to help understand behaviors.
Expanded agent based model simulations will be used to evaluate a wide range of interventions at multiple facilities that aim to interrupt transmission. The interventions will be based on behavioral science, sensor data, survey responses, and literature.
For Aims 1 and 2, we collected sensor data from the provider participants in four inpatient units at the Salt Lake City VA hospital for four weeks in June and July, 2018. Surveys were completed by 53 provider participants (50% response rate); 43% had never been informed about their unit's hand hygiene adherence and 70% agree that they could improve their adherence. We conducted two focus groups with 9 provider participants, 75% of the planned number. The major theme was that basing hand hygiene adherence on room entry/exit does not appropriately reflect hand hygiene during the complex patterns of patient care. Participants are anxious for data summaries, which will be ready before January.
The study is inspiring healthcare providers to discuss hand hygiene and use of technology to measure adherence. The long-term impacts to Veterans' healthcare will be use of data and model outputs to support to improve infection control and engagement on topic of hand hygiene.
None at this time.
TRL - Development
Knowledge Integration, Natural Language Processing