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Update on the NNQR(C) pilot project

Using nursing-sensitive indicators to inform quality improvement

Mar 04, 2015, By: Susan VanDeVelde-Coke, RN, MBA, PhD, Diane Doran, RN, PhD, FCAHS, Lianne Jeffs, RN, PhD

An essential component of a sustainable health-care system is access to high-quality information that can be used to design, deliver and evaluate health-care services in the most effective and efficient way possible. In 2010, the Academy of Canadian Executive Nurses (ACEN) leadership/policy committee identified the need to make explicit the contribution of nursing to quality health outcomes; one method to achieve this was to create a national report card on nursing-sensitive indicators that could be used to formulate and drive future policy platforms. ACEN partnered with CNA and the Lawrence S. Bloomberg faculty of nursing at the University of Toronto and received funding from Canada Health Infoway to develop the Canadian National Nursing Quality Report (NNQR(C)) pilot project. The overall goal of the NNQR(C) is to create sustainable collection of a national set of indicators that examines the relationships between resources deployed in the delivery of nursing services and the outcomes achieved by those services, enabling nurse leaders to exercise accountability over quality of care issues (VanDeVelde-Coke et al., 2012).

Developing the set of initial NNQR(C) indicators involved a panel of experts consisting of leaders from health organizations (hospitals, long-term care and mental health) and professional associations. Participating in a modified Delphi survey, the panel identified indicators associated with nursing care that are known to be evidence-based, meaningful, feasible and actionable. The panel then selected standardized definitions of each of these indicators (see box) through a collaborative effort of NNQR(C), Canadian Health Outcomes for Better Informed Care (C-HOBIC), and the Registered Nurses’ Association of Ontario’s Nursing Quality Indicators for Reporting and Evaluation (NQuIRE) initiatives (VanDeVelde-Coke et al., 2012).

Ten health-care organizations, representing acute care, long-term care and inpatient mental health services from three provinces (Manitoba, Ontario and New Brunswick), were recruited to participate in the pilot project. These organizations selected from the NNQR(C) list of structure, process and outcome indicators and collected data from existing clinical and financial data sources including the C-HOBIC dataset, the Resident Assessment Instrument, the Discharge Abstract Database and the Management Information System. Site coordinators entered the data using Patient Safety Metrics, a web-based data submission and reporting system developed and maintained by the Canadian Patient Safety Institute. Dashboard reports on the indicators (e.g., falls risk assessment, falls rate, hand hygiene, use of restraints, incidence of pressure ulcers) were developed by the Patient Safety Metrics team and provided to the sites in a PDF format. These reports, along with trend graphs, were reviewed and discussed by site coordinators, nursing managers and other practice leaders in participating organizations. Monthly communities of practice took place, online whereby site coordinators met to discuss ongoing issues and strategies on how best to collect and use data within their organizations. Sites also had access to their own unit-level data and could produce charts from the Patient Safety Metrics system to compare data over time.

One site dropped out during the pilot due to difficulties collecting the data; another dropped out prior to the pilot due to restructuring. The remaining eight organizations participated in a mixed-method evaluation performed by the NNQR(C) project team, assessing (1) the feasibility of collecting and submitting NNQR(C) data, (2) the utility of data collection for organizational improvement efforts, and (3) the usefulness of the indicators for determining relationships between structure indicators (e.g., staffing resources), processes of care (e.g., falls risk assessment) and patient outcomes (e.g., falls rate). The project team analyzed trends in indicators over time and relationships among indicators, and interviewed key stakeholders at the pilot sites about their experiences associated with participating in the pilot project.


Pilot data revealed some observations of relationships among indicators, which provided direction for the organizations’ quality improvement efforts. While it is important to note that correlational data do not imply causation, the following were some of the correlation findings based on the overall results: (1) more nursing hours were associated with improved aggressive behaviour scores, lower use of restraints, and appropriate hand hygiene practices; (2) fewer nursing hours were associated with high falls rates; and (3) higher pain scores were associated with higher percentage of patients restrained.

Success Factors and Lessons Learned

Participating organizations faced challenges in accessing structure, process and outcome indicators and in submitting the data using common definitions. Once those challenges were overcome, they made progress toward the goal of providing internal dashboard and benchmarking reports and of engaging front-line clinicians and leaders to use data to guide quality improvement initiatives, as shown in these examples:

  • A coordinator at one site presented a dashboard report on falls to a regional quality and professionalism committee, which in turn identified the need to focus on falls as a priority quality improvement project. The focus of this project, launched in June 2014, is for nurses to conduct hourly rounding with patients on the units to ensure that patients are not at risk for falling and to decrease the falls rate.
  • At another site, pain results on one participating NNQR(C) unit were higher than on the other unit. Upon further exploration, differences in underlying processes of care were posited to be contributing factors. Data supported the need for ongoing efforts to monitor outcomes and implement the Registered Nurses’ Association of Ontario’s Assessment and Management of Pain best practice guideline.
  • At a third site, utilization, absenteeism and turnover of the RN staff were identified as areas for improvement, which motivated the leadership team to review their staff mix model. As part of the improvement efforts, there is a plan to increase the number of RNs.

Next Steps

The NNQR(C) project team is in the process of finalizing recruitment of sites for the second round of data collection, scheduled to begin this spring. The plan is to extend recruitment beyond the original pilot sites. We anticipate that continued monitoring using NNQR(C) indicators will provide organizations with high-quality standardized data to evaluate the results of their quality improvement efforts. The team continues to collaborate with groups working on other indicator projects to ensure the principle of one standard definition for each indicator. It is also working with national organizations, including the Canadian Institute for Health Information, to move toward having these indicators included as part of a national health-care database that can be used by all health-care providers.


The authors thank other members of the NNQR(C) team, including Lori Lamont (ACEN), Anne Sutherland Boal (CNA), and Laureen Hayes (University of Toronto), and the teams at the sites in the NNQR(C) pilot project and acknowledge the continued support of ACEN, CNA and Virginia Flintoft from the Patient Safety Metrics team.


VanDeVelde-Coke, S., Doran, D., Grinspun, D., Hayes, L., Sutherland Boal, A., Velji, K....Hannah, K. (2012). Measuring outcomes of nursing care, improving the health of Canadians: NNQR (C), C-HOBIC and NQuIRECanadian Journal of Nursing Leadership, 25(2), 26-37.

NNQR(C) Indicators

Structure Indicators

  • Percentage of Registered Nurse hours worked for inpatient care
  • Percentage of total nursing hours worked for direct inpatient care per patient day
  • Percentage of nursing care hours as paid absenteeism
  • Percentage of voluntary turnover among full- and permanent part-time staff
  • Total nursing hours worked per weighted inpatient day

Process Indicators

  • Percentage Completed Fall Risk Assessment on Admission
  • Percentage with pressure ulcer risk assessment completed on admission
  • Percent Appropriate Hand Hygiene Practice
  • Percentage of Patients with Restraints
  • Percentage of residents physically restrained daily on the most recent RAI assessment
  • Medication Reconciliation — Percentage of Patients Reconciled at Admission

Outcome Indicators

  • Percentage of patients with pain
  • Incidence of Pressure ulcers
  • Mean Therapeutic Self-Care score at discharge
  • Falls Rate per 1000 Patient/Resident Days
  • Percentage of Falls causing Injury
  • Percent of patients with improved Aggressive Behaviour Score (Mental Health)
  • Mean Self-Care Index Score on discharge or most recent assessment (Mental Health)

Susan VanDeVelde-Coke, RN, MBA, PhD, is Director of Health Policy Analysis‎ and Knowledge Transfer, Health and Social Service Utilization Research Unit, McMaster University, Hamilton, Ont.
Diane Doran, RN, PhD, FCAHS, is Professor Emeritus, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto.
Lianne Jeffs, RN, PhD, is Director, Nursing Research and a Scientist, Keenan Research Centre of the Li Ka Shing Knowledge Institute, St. Michael’s Hospital.


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