Other Titles
Outcomes of nursing interventions [Session]
Abstract
Session presented on Monday, November 9, 2015:
Purpose and Research Questions: The purpose of this study was to assess the impact of nursing interventions on a skilled nursing unit (SNU) when a change in patient health status was identified. Patient characteristics were correlated with specific variables such as Rothman Index (RI) scores and 30-day readmission status. Nurses could then implement specific individualized interventions to improve patient outcomes. The study questions were: a) What are the characteristics of our SNU patients? and b) Can use of the RI discharge score alert the nurse to the need for increased interventions to lower the risk for 30-day hospital readmission?
Background and Significance: It is imperative that nurses use evidence based practice and research as a basis for making patient care decisions. This is especially important in the context of the rapidly changing healthcare environment of today. The SNU at our hospital was concerned about improving discharge outcomes and reducing hospital readmissions. Research studies have shown that when a patient with heart disease is admitted to a SNU that has specific nursing interventions developed for patients with heart disease, there are improved patient outcomes (Allen et al., 2011; Jacobs, 2011). This led to the idea that a study of our SNU patients would help nurses improve patient outcomes (Hain et al., 2012; Li et al., 2012). The RI software uses clinical measurements from the following four categories: nursing assessments, vital signs, laboratory results, and cardiac rhythms in an algorithm that translates to a RI score reflecting patient progress or lack of progress over time (Rothman et al., 2013). Bradley et al. (2013) concluded there was a strong relationship between the RI score at the time of discharge and unplanned readmissions within 30-days. They found cutoff points in the RI that helped the health care provider to identify patients at high risk for readmission which was considered to be the first step to reduce readmissions. Health care clinicians who use the latest RI score to individualize the patient's discharge plan may help to reduce the risk for 30-day readmissions (Yale-New Haven Hospital, 2013).
Design and Methodology: This was a retrospective study of information gathered from medical records of patients on a SNU during 2013. Variables were extracted from the medical records and sent to the principal investigator in the form of a Limited Data Set and analyzed with the statistical program SPSS Statistics Desktop, V22.0. Patients were classified into the following RI cutoff points related to their risk for 30-day readmission: high-risk (RI <70), medium risk (RI=70-79), low risk (RI=80-89), and lowest risk (RI = 90-100) (Bradley et al., 2013).
Discussion: Our SNU population had similar characteristics as populations identified in other studies, such as gender, race, education, and language. The analysis between our study group and the comparison group (Li et al., 2012) on the patient characteristics showed the following: our group of patients had a higher percentage in the <75 age group and a lower percentage in the >85 age group. Our group of patients showed a significant difference in percentage of married patients as compared to the comparison group. Our group of patients had a 29.3% of DNR orders as compared to 38.1% in the comparison group. Data analysis showed the following percentages by RI risk category for the 30-day patient readmission rate: RI high-risk group = 36.4%, RI medium risk group = 21.8%, RI low risk group = 28.6% and RI lowest risk group = 11.5%. This is comparable to the findings discussed in the Bradley et al. (2013) study.
Implication: Patient characteristics on our SNU in 2013 differed from some patient characteristics found in other studies. Prior to implementing evidence based interventions, our staff needs to look closely at how patient characteristics were applied in other studies. Nurses need to consider if a specific intervention could be used in our distinct patient population or if it needs to be modified to be effective within our population. Nurses need to identify any declining trend in the RI score and implement evidence based interventions to improve the overall patient condition as indicated by an increasing RI score. Our SNU needs to address the issue that 36.4% of our RI high-risk patients are readmitted within 30 days. An RI score in the high risk category (<70) at discharge should alert the nurse to implement interventions focused on individualized needs for health care and support services at home or an alternate health care facility. Nursing interventions should include education to promote health practices, to increase coping skills, and to ensure patient and family know when and how to contact health care providers to decrease potential 30-day readmissions.
References: Allen, L. A., Hernandez, A. F., Peterson, E. D., Curtis, L. H., Dai, D., Masoudi, F. A., Bhatt, D. L., Heidenreich, P. A., & Fonarow, G. C. (2011). Discharge to a skilled nursing facility and subsequent clinical outcomes among older patients hospitalized for heart failure. Circulation Heart Failure, 4, 293-300. Doi:10.1161/CIRCHEARTFAILURE.110.959171 Bradley, E. H., Yakusheva, O., Horsitz, L. I., Sipsma, H., & Fletcher, J. (2013). Identifying patients at increased risk of unplanned readmission. Medical Care, 51, 761-766. Hain, D. J., Tappen, R., Diaz, S., & Ouslander, J. G. (2012). Characteristics of older adults rehospitalized within 7-30 days of discharge: Implications for nursing practice. (2012). Journal of Gerontological Nursing. 38 : 32-44. Jacobs, B. (2011). Reducing heart failure hospital readmissions from skilled nursing facilities. Professional Case Management, 16, 18-24 .Li, Y., Cai, X., Yin, J., Clance, L. G., & Mukamel, D. B. (2012). Is higher volume of postacute care patients associated with a lower rehospitalization rate in skilled nursing facilities? Medical Care Research and Review, 69 , 103-118. Retrieved from http://mcr.sagepub.com/content/69/1/103 DOI: 10.1177/1077558711414274 Rothman, M., Rothman, S. & Beals, J. (2013). Development and Validation of a Continuous Measure of Patient Condition Using the Electronic Medical Record. J Biomed Inform: 46(5), 837-848. Wagner, L., & LaPorte, M. (December 2012). SNFs and hospitals team up to reduce readmissions. Provider: p. 11. Yale-New Haven Hospital. (2013). Rothman Index powerful tool for early detection of subtle patient changes. 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:
Nurse Sensitive Indicators, Patient Outcomes, Patient Characteristics
Recommended Citation
Moseley, Carol-Ann, "A retrospective study exploring nursing sensitive interventions for patients on a skilled nursing unit in a rural Midwest hospital" (2016). Convention. 74.
https://www.sigmarepository.org/convention/2015/presentations_2015/74
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 exploring nursing sensitive interventions for patients on a skilled nursing unit in a rural Midwest hospital
Las Vegas, Nevada, USA
Session presented on Monday, November 9, 2015:
Purpose and Research Questions: The purpose of this study was to assess the impact of nursing interventions on a skilled nursing unit (SNU) when a change in patient health status was identified. Patient characteristics were correlated with specific variables such as Rothman Index (RI) scores and 30-day readmission status. Nurses could then implement specific individualized interventions to improve patient outcomes. The study questions were: a) What are the characteristics of our SNU patients? and b) Can use of the RI discharge score alert the nurse to the need for increased interventions to lower the risk for 30-day hospital readmission?
Background and Significance: It is imperative that nurses use evidence based practice and research as a basis for making patient care decisions. This is especially important in the context of the rapidly changing healthcare environment of today. The SNU at our hospital was concerned about improving discharge outcomes and reducing hospital readmissions. Research studies have shown that when a patient with heart disease is admitted to a SNU that has specific nursing interventions developed for patients with heart disease, there are improved patient outcomes (Allen et al., 2011; Jacobs, 2011). This led to the idea that a study of our SNU patients would help nurses improve patient outcomes (Hain et al., 2012; Li et al., 2012). The RI software uses clinical measurements from the following four categories: nursing assessments, vital signs, laboratory results, and cardiac rhythms in an algorithm that translates to a RI score reflecting patient progress or lack of progress over time (Rothman et al., 2013). Bradley et al. (2013) concluded there was a strong relationship between the RI score at the time of discharge and unplanned readmissions within 30-days. They found cutoff points in the RI that helped the health care provider to identify patients at high risk for readmission which was considered to be the first step to reduce readmissions. Health care clinicians who use the latest RI score to individualize the patient's discharge plan may help to reduce the risk for 30-day readmissions (Yale-New Haven Hospital, 2013).
Design and Methodology: This was a retrospective study of information gathered from medical records of patients on a SNU during 2013. Variables were extracted from the medical records and sent to the principal investigator in the form of a Limited Data Set and analyzed with the statistical program SPSS Statistics Desktop, V22.0. Patients were classified into the following RI cutoff points related to their risk for 30-day readmission: high-risk (RI <70), medium risk (RI=70-79), low risk (RI=80-89), and lowest risk (RI = 90-100) (Bradley et al., 2013).
Discussion: Our SNU population had similar characteristics as populations identified in other studies, such as gender, race, education, and language. The analysis between our study group and the comparison group (Li et al., 2012) on the patient characteristics showed the following: our group of patients had a higher percentage in the <75 age group and a lower percentage in the>85 age group. Our group of patients showed a significant difference in percentage of married patients as compared to the comparison group. Our group of patients had a 29.3% of DNR orders as compared to 38.1% in the comparison group. Data analysis showed the following percentages by RI risk category for the 30-day patient readmission rate: RI high-risk group = 36.4%, RI medium risk group = 21.8%, RI low risk group = 28.6% and RI lowest risk group = 11.5%. This is comparable to the findings discussed in the Bradley et al. (2013) study.
Implication: Patient characteristics on our SNU in 2013 differed from some patient characteristics found in other studies. Prior to implementing evidence based interventions, our staff needs to look closely at how patient characteristics were applied in other studies. Nurses need to consider if a specific intervention could be used in our distinct patient population or if it needs to be modified to be effective within our population. Nurses need to identify any declining trend in the RI score and implement evidence based interventions to improve the overall patient condition as indicated by an increasing RI score. Our SNU needs to address the issue that 36.4% of our RI high-risk patients are readmitted within 30 days. An RI score in the high risk category (<70) at discharge should alert the nurse to implement interventions focused on individualized needs for health care and support services at home or an alternate health care facility. Nursing interventions should include education to promote health practices, to increase coping skills, and to ensure patient and family know when and how to contact health care providers to decrease potential 30-day readmissions.
References: Allen, L. A., Hernandez, A. F., Peterson, E. D., Curtis, L. H., Dai, D., Masoudi, F. A., Bhatt, D. L., Heidenreich, P. A., & Fonarow, G. C. (2011). Discharge to a skilled nursing facility and subsequent clinical outcomes among older patients hospitalized for heart failure. Circulation Heart Failure, 4, 293-300. Doi:10.1161/CIRCHEARTFAILURE.110.959171 Bradley, E. H., Yakusheva, O., Horsitz, L. I., Sipsma, H., & Fletcher, J. (2013). Identifying patients at increased risk of unplanned readmission. Medical Care, 51, 761-766. Hain, D. J., Tappen, R., Diaz, S., & Ouslander, J. G. (2012). Characteristics of older adults rehospitalized within 7-30 days of discharge: Implications for nursing practice. (2012). Journal of Gerontological Nursing. 38 : 32-44. Jacobs, B. (2011). Reducing heart failure hospital readmissions from skilled nursing facilities. Professional Case Management, 16, 18-24 .Li, Y., Cai, X., Yin, J., Clance, L. G., & Mukamel, D. B. (2012). Is higher volume of postacute care patients associated with a lower rehospitalization rate in skilled nursing facilities? Medical Care Research and Review, 69 , 103-118. Retrieved from http://mcr.sagepub.com/content/69/1/103 DOI: 10.1177/1077558711414274 Rothman, M., Rothman, S. & Beals, J. (2013). Development and Validation of a Continuous Measure of Patient Condition Using the Electronic Medical Record. J Biomed Inform: 46(5), 837-848. Wagner, L., & LaPorte, M. (December 2012). SNFs and hospitals team up to reduce readmissions. Provider: p. 11. Yale-New Haven Hospital. (2013). Rothman Index powerful tool for early detection of subtle patient changes. The Bulletin, 36 (7), 1-2.
Description
43rd Biennial Convention 2015 Theme: Serve Locally, Transform Regionally, Lead Globally.