Chantal Backman1, Saskia Vanderloo2, Kathy Momtahan3, Barb d'Entremont4, Lisa Freeman5, Lynn Kachuik6, Dianne Rossy7, Toba Mille8, Naghmeh Mojaverian9, Ginette Lemire-Rodger10, Alan Forster11. 1. Assistant Professor, School of Nursing, Faculty of Health Sciences, University of Ottawa Affiliate Investigator, Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON. 2. Research Coordinator, Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON. 3. Nursing Research Lead, The Ottawa Hospital and Associate Investigator, Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON. 4. Corporate Coordinator, Clinical Pathways, The Ottawa Hospital, Ottawa, ON. 5. Corporate Coordinator, Nursing Best Practices, The Ottawa Hospital, Ottawa, ON. 6. Advanced Practice Nurse Palliative Care, The Ottawa Hospital, Ottawa, ON. 7. Advanced Practice Nurse, Geriatrics, The Ottawa Hospital, Ottawa, ON. 8. Manager Wound and Ostomy Team, Advanced Practice Nurse, Wound, Ostomy and Rehabilitation, The Ottawa Hospital, Ottawa, ON. 9. Clinical Reviewer, Patient Safety Learning System, The Ottawa Hospital, Ottawa, ON. 10. Senior VP, Professional Practice, and Chief Nursing Executive, The Ottawa Hospital, Ottawa, ON. 11. Senior Scientist, Clinical Epidemiology Program, Ottawa Hospital Research Institute; Professor of Medicine, University of Ottawa, Ottawa, ON.
Abstract
BACKGROUND: Monitoring the quality of nursing care is essential to identify patients at risk, measure adherence to hospital policies and evaluate the effectiveness of best practice interventions. However, monitoring nursing-sensitive indicators (NSI) is a challenge. Prevalence surveys are one method used by some organizations to monitor NSI, which are patient outcomes that are directly affected by the quantity or quality of nursing care that the patient receives. OBJECTIVE: The aim of this paper is to describe the development of an innovative electronic data collection tool to monitor NSI. METHODS: In the preliminary development work, we designed a mobile computing application with pre-populated patient census information to collect the nursing quality data. In subsequent phases, we refined this process by designing an electronic trigger using The Ottawa Hospital's Patient Safety Learning System, which automatically generated a case report form for each inpatient based on the hospital's daily patient census on the day of the prevalence survey. OBSERVATIONS: Both of these electronic data collection tools were accessible on tablet computers, which substantially reduced data collection, analysis and reporting time compared to previous paper-based methods. The electronic trigger provided improved completeness of the data. CONCLUSION: This work leveraged the use of tablet computers combined with a web-based application for patient data collection at point of care. Overall, the electronic methods improved data completeness and timeliness compared to traditional paper-based methods. This initiative has resulted in the ability to collect and report on NSI organization-wide to advance decision-making support and identify quality improvement opportunities within the organization.
BACKGROUND: Monitoring the quality of nursing care is essential to identify patients at risk, measure adherence to hospital policies and evaluate the effectiveness of best practice interventions. However, monitoring nursing-sensitive indicators (NSI) is a challenge. Prevalence surveys are one method used by some organizations to monitor NSI, which are patient outcomes that are directly affected by the quantity or quality of nursing care that the patient receives. OBJECTIVE: The aim of this paper is to describe the development of an innovative electronic data collection tool to monitor NSI. METHODS: In the preliminary development work, we designed a mobile computing application with pre-populated patient census information to collect the nursing quality data. In subsequent phases, we refined this process by designing an electronic trigger using The Ottawa Hospital's Patient Safety Learning System, which automatically generated a case report form for each inpatient based on the hospital's daily patient census on the day of the prevalence survey. OBSERVATIONS: Both of these electronic data collection tools were accessible on tablet computers, which substantially reduced data collection, analysis and reporting time compared to previous paper-based methods. The electronic trigger provided improved completeness of the data. CONCLUSION: This work leveraged the use of tablet computers combined with a web-based application for patient data collection at point of care. Overall, the electronic methods improved data completeness and timeliness compared to traditional paper-based methods. This initiative has resulted in the ability to collect and report on NSI organization-wide to advance decision-making support and identify quality improvement opportunities within the organization.