Other Titles
Outcomes of Nursing Interventions [Session]
Abstract
Session presented on Monday, November 9, 2015:
Background & Significance: The Rothman Index (RI) provides a tool to continually track and trend the patient's condition based on data extracted from the Electronic Health Record (Wolters Kluwer Health, 2013). The patient's RI score is calculated from 26 data points. These data points originate from four categories: nursing assessments, vital signs, laboratory result, and cardiac rhythm (Rothman, Rothman, & Beals, 2013). The RI is a measure of patient progress or lack of progress over time (Rothman, Solinger, & Rothman, 2012, Yale-New Haven Hospital, 2013). Research has found the use of the RI in patient care can positively impact outcomes (Wolters Kluwer Health, 2013; Yale-New Haven Hospital, 2013; Bradley, Yakusheva, Horwitz, Sipsma, & Fletcher, 2013). The RI was implemented in 2011. Nursing staff viewing of the RI was minimal prior to August of 2012. Then intensive nursing staff education was presented and RI viewing increased. This study compared patient outcomes prior to the intensive education with patient outcomes post education. The population was medical surgical on two units.
Purpose: This research assessed the impact of increased nursing staff use of the RI on patient outcomes of medical-surgical units at Midwestern rural hospital. Research Questions: Does re-education have an impact on utilization of the RI? Does use of RI by nursing staff improve patients' outcomes?
Methods: The design was a retrospective study of data retrieved from medical records. Information Systems retrieved data from medical records of individuals admitted to two Medical-Surgical units. Data was collected during 3 time periods. The 3 time periods were chosen to coincide with low use (Group 1), post education use (Group 2) and sustained use post education (Group 3). These time periods were chosen based on previous studies of the RI that found its use by nursing staff improves patient outcomes.
Results: The total group of 8750 cases was tested for differences in discharge disposition (home or other than home) and patient outcomes. Cases discharged to home had higher RI scores than cases who were not discharged home p = .000. Significant differences between the disposition groups at the p = .000 were found for the following variables: discharge RI scores, length of stay, number of diagnosis, 30-day readmit, Rapid Response time, and R I views. The cases were also analyzed by groups. The groups were determined to be similar related to unit, age, length of stay, number of diagnosis, 30-day readmit, last RI, and DRGs. Significant findings were found between the groups in RI views and Rapid Response times. The lowest viewing of the RI was in Group 1, the group prior to re-education. The highest viewing of the RI was Group 2, the group immediately after re-education. Group 2 had significantly more (p = .008) staff views of the RI than Group 1. The numbers of viewing of the RI decreased for Group 3 but remained higher than Group 1, but were not statistically significant. Rapid response calls were lower for Groups 2 and 3 than in Group 1. There was a statistical significance (p = .008) between Group 1 and Group 2 in Rapid Response calls with Group 2 having fewer Rapid Response calls times. Rapid Response calls for Group 3 remained lower than Group 1 but were not statistically significant. Codes blue calls for Group1 was eleven, for Group 2 was ten and Group 3 was four.
Discussion & Implications: RI graph re-education resulted in increased graph viewing by nurses. We conclude that due to increased viewing nurses identified downward trends in the patient's overall condition leading to earlier intervention and prevention of deterioration to the point of necessitating a rapid response or Code Blue. Based on these patient outcomes it appears that routine re-education and requiring RI graph viewing at a minimum during all hand-off reports would be beneficial. Findings of the study will be shared with nursing leadership to set benchmarks for patient discharge.
References: Bradley, E. H., Yakusheva, O., Horwitz, L. I., Spsma, H., & Fletcher, J. (2013). Identifying patients at increased risk for unplanned readmission. Medical Care, 51 (9), 761. DOI 10,1097/MLR.0b013e3182a0f492 Rothman, S., Rothman, M. & Solinger, A. Placing Clinical Variables on a Common Linear Scare of Empirically Based Risk as a Step Towards Construction of a General patient Acuity Score from the Electronic Health Record: A Modelling Study. BMJ Open 2012:Rothman, M., Rothman, S. & Beals, J. Development and Validation of a Continuous Measure of Patient Condition Using the Electronic Medical Record. J Biomed Inform, 2013: 46(5), 837-848 Wolters Kluwer Health. (2013). Rothman Index may help to lower repeated hospitalization risk. Science Daily, 15 August 2013. www.sciencedaily.com/release/2013/08/130815113650.htm Yale-New Haven Hospital. Rothman Index powerful tool for early detection of subtle patient changes. (2013). The Bulletin, 36 (7), 1-2.
Sigma Membership
Pi Pi
Type
Presentation
Format Type
Text-based Document
Study Design/Type
N/A
Research Approach
N/A
Keywords:
Patient Outcomes, Staff Re-Eduction, Technology
Recommended Citation
Phillips, Penny; Shepherd, Marilyn; Jochem, Kathleen; and Moseley, Carol-Ann, "A retrospective study of the impact of educational intervention on the use of the Rothman Index System on patient outcomes" (2016). Convention. 37.
https://www.sigmarepository.org/convention/2015/presentations_2015/37
Conference Name
43rd Biennial Convention
Conference Host
Sigma Theta Tau International
Conference Location
Las Vegas, Nevada, USA
Conference Year
2015
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Review Type
Abstract Review Only: Reviewed by Event Host
Acquisition
Proxy-submission
A retrospective study of the impact of educational intervention on the use of the Rothman Index System on patient outcomes
Las Vegas, Nevada, USA
Session presented on Monday, November 9, 2015:
Background & Significance: The Rothman Index (RI) provides a tool to continually track and trend the patient's condition based on data extracted from the Electronic Health Record (Wolters Kluwer Health, 2013). The patient's RI score is calculated from 26 data points. These data points originate from four categories: nursing assessments, vital signs, laboratory result, and cardiac rhythm (Rothman, Rothman, & Beals, 2013). The RI is a measure of patient progress or lack of progress over time (Rothman, Solinger, & Rothman, 2012, Yale-New Haven Hospital, 2013). Research has found the use of the RI in patient care can positively impact outcomes (Wolters Kluwer Health, 2013; Yale-New Haven Hospital, 2013; Bradley, Yakusheva, Horwitz, Sipsma, & Fletcher, 2013). The RI was implemented in 2011. Nursing staff viewing of the RI was minimal prior to August of 2012. Then intensive nursing staff education was presented and RI viewing increased. This study compared patient outcomes prior to the intensive education with patient outcomes post education. The population was medical surgical on two units.
Purpose: This research assessed the impact of increased nursing staff use of the RI on patient outcomes of medical-surgical units at Midwestern rural hospital. Research Questions: Does re-education have an impact on utilization of the RI? Does use of RI by nursing staff improve patients' outcomes?
Methods: The design was a retrospective study of data retrieved from medical records. Information Systems retrieved data from medical records of individuals admitted to two Medical-Surgical units. Data was collected during 3 time periods. The 3 time periods were chosen to coincide with low use (Group 1), post education use (Group 2) and sustained use post education (Group 3). These time periods were chosen based on previous studies of the RI that found its use by nursing staff improves patient outcomes.
Results: The total group of 8750 cases was tested for differences in discharge disposition (home or other than home) and patient outcomes. Cases discharged to home had higher RI scores than cases who were not discharged home p = .000. Significant differences between the disposition groups at the p = .000 were found for the following variables: discharge RI scores, length of stay, number of diagnosis, 30-day readmit, Rapid Response time, and R I views. The cases were also analyzed by groups. The groups were determined to be similar related to unit, age, length of stay, number of diagnosis, 30-day readmit, last RI, and DRGs. Significant findings were found between the groups in RI views and Rapid Response times. The lowest viewing of the RI was in Group 1, the group prior to re-education. The highest viewing of the RI was Group 2, the group immediately after re-education. Group 2 had significantly more (p = .008) staff views of the RI than Group 1. The numbers of viewing of the RI decreased for Group 3 but remained higher than Group 1, but were not statistically significant. Rapid response calls were lower for Groups 2 and 3 than in Group 1. There was a statistical significance (p = .008) between Group 1 and Group 2 in Rapid Response calls with Group 2 having fewer Rapid Response calls times. Rapid Response calls for Group 3 remained lower than Group 1 but were not statistically significant. Codes blue calls for Group1 was eleven, for Group 2 was ten and Group 3 was four.
Discussion & Implications: RI graph re-education resulted in increased graph viewing by nurses. We conclude that due to increased viewing nurses identified downward trends in the patient's overall condition leading to earlier intervention and prevention of deterioration to the point of necessitating a rapid response or Code Blue. Based on these patient outcomes it appears that routine re-education and requiring RI graph viewing at a minimum during all hand-off reports would be beneficial. Findings of the study will be shared with nursing leadership to set benchmarks for patient discharge.
References: Bradley, E. H., Yakusheva, O., Horwitz, L. I., Spsma, H., & Fletcher, J. (2013). Identifying patients at increased risk for unplanned readmission. Medical Care, 51 (9), 761. DOI 10,1097/MLR.0b013e3182a0f492 Rothman, S., Rothman, M. & Solinger, A. Placing Clinical Variables on a Common Linear Scare of Empirically Based Risk as a Step Towards Construction of a General patient Acuity Score from the Electronic Health Record: A Modelling Study. BMJ Open 2012:Rothman, M., Rothman, S. & Beals, J. Development and Validation of a Continuous Measure of Patient Condition Using the Electronic Medical Record. J Biomed Inform, 2013: 46(5), 837-848 Wolters Kluwer Health. (2013). Rothman Index may help to lower repeated hospitalization risk. Science Daily, 15 August 2013. www.sciencedaily.com/release/2013/08/130815113650.htm Yale-New Haven Hospital. Rothman Index powerful tool for early detection of subtle patient changes. (2013). The Bulletin, 36 (7), 1-2.
Description
43rd Biennial Convention 2015 Theme: Serve Locally, Transform Regionally, Lead Globally.