Nurse's Role
Conditions
Keywords
Integrated smart pumps, Integrated technology, Chart review
Brief summary
This study looks at the effects of using "smart pumps" that connect with the Electronic Health Record (EHR) in 8 adult ICU units. We will interview nurses and healthcare team members to learn about any challenges with this technology. All nurses in these units will be invited to complete a survey on how easy the technology is to use. Some nurses will practice giving medications to "mannequins" in a simulation lab to see how they work with the pumps. We will also look at existing data to find out how many nurses use the technology and what types of alerts or errors come up. Finally, we will review patient charts to see if using the technology has increased or decreased errors in recording IV medication amounts.
Detailed description
This mixed-methods design study focuses on understanding the complexity and consequences of implementing the integrated smart pumps-EHR technology in 8 adult acute and intensive care units (ICUs) using a comprehensive evaluation approach. The evaluation will include (1) analyzing use manifestations in terms of nurse adoption, alarms, alerts, and error messages associated with technology use, (2) examining the usability of the integrated technology, and (3) identifying influential factors that facilitate or hinder technology adoption.
Interventions
None listed
Sponsors
The University of Texas Health Science Center at San Antonio
Baxter Healthcare Corporation
Study design
Observational model
OTHER
Time perspective
OTHER
Eligibility
Sex/Gender
ALL
Age
20 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Research Aims 1 (adoption rate) and 2 (frequency and types of alerts and programming error ). We will include all IV medications and fluids delivered via smart infusion pumps within the past 6 months. We anticipate the dataset to include more than 180,000 of medications and fluid administration events. * Research Aim 3 (documentation errors ). We will select 200 IV medications that were administered with solutions using chart audit. To be included, the selected IV medications should be diluted with at least 100 ml solution. The choice of the 100 ml cutoff point was based on it being the minimum volume for the majority of IV medication administrations. * Research Aims 4, 5, 6, and 7 (usability of the technology, nurse perception, predictors of nurse perception, nurse experience with technology). Eligibility criteria will be confined to registered nurses with at least an associate degree in nursing. * Research Aim 8 (multidisciplinary team experience with technology). The inclusion criteria for the group of multidisciplinary representatives encompass participation in pump implementation and pumps-related quality improvement initiatives.
Exclusion criteria
* Research Aims 1 and 2. Bolus medications will be excluded due to the distinct workflow associated with their administration. * Research Aim 3. Medications with solution volumes lower than 100 ml will be excluded. * Research Aims 4, 5, 6, and 7. Licensed vocational nurses (LVN) and licensed practical nurses (LPN) will be excluded due to their non-involvement in IV medication administration. Additionally, and for Research Aim # 7, the group of 48 nurses who will engage in the usability testing will not be part of the focus group interviews to ensure a broader participation among nurses. * Research Aim 8: Stakeholders from the different hospital's departments and councils (e.g., nursing, biomedical engineering, pharmacy, risk and management, technology committees, etc.) who were not part of the implementation process of infusion pumps in 2018 and 2020 or are not involved in continuous quality initiatives related to infusion pump adoption and quality measures tracking will be excluded.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Pump adoption rate | 6 months | Data from the pumps over the past 6 months will be reviewed and analyzed to understand how often nurses use the integrated pump-EHR (or electronic health record) technology versus manually programming the pumps when administering medications. Z-test will be used to test the difference in percentage in adoption rate. |
| Alerts messages | 6 months | Data from the pumps over the past 6 months will be reviewed to examine the difference in frequency of alert messages (including programming error messages) generated when manually programming the pump versus using the pump-EHR integrated technology. Data will be analyzed using chi-square. |
| Errors in documenting the volume of IV medications | 4 months | 200 patient charts will be reviewed to compare documentation errors in IV medication volumes when using pump-EHR integration versus manual pump programming. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Usability of the Pumps | 9 months | During observations of 48 nurses' interactions with the pumps in a simulated environment, we will identify the navigation paths nurses follow to program the pumps (through recording of nurse-pump navigation), examine usability errors (through recording of nurse-pump navigation), record the time taken by nurses to navigate the pumps to administer IV medications (through recording of nurse-pump navigation), assess perceived workload during pump navigation (using a survey), and assess nurse experience and perceived challenges during task completion (using the debriefing session). |
| Nurse perception of the usability of the integrated smart pump technology | 6 months | We will send a survey to all nurses who work in the 8 acute and intensive care units to understand their perceptions about the technology. Descriptive statistics will be used to analyze the results. |
| Factors that facilitate or hinder technology adoption | 11 months | We will use semi-structured interviews to explore bedside nurses' experiences with the integrated smart pump-EHR technology, including any challenges they face. Additionally, we will interview a multidisciplinary healthcare team to understand the organizational and contextual factors that help or hinder the adoption of this technology. All interviews will be transcribed by professionals from Rev, a transcription vendor. Data will be entered into nVivo software. The 4-stage content analysis methodology by Bengtsson (2016) will be used to categorize narrative data into themes. |
Countries
United States
Contacts
CONTACTAzizeh Sowan, PhD, RN, MSN, MSDA, MBA, FAAN
PRINCIPAL_INVESTIGATORAzizeh Sowan, PhD, RN, MSN, MSDA, MBA, FAAN
The University of Texas Health Science Center at San Antonio
Outcome results
None listed