Measuring Nursing Outcomes, with a Focus on Inpatient Complications

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Patient Safety and Quality

Barbara Doyle
Clinical Staff, CareScience

Nurse sensitive indicators of the incidence of clinical complications of urinary tract infection, Upper GI bleed, thromboses, post-op infection, shock, cardiac arrest, and pneumonia are measured across different institutions, utilizing the Care Management SystemTM. Inpatient complications are investigated in more detail, identifying sub-populations most at risk to develop one or more after admission. Patient flow and resource utilization are analyzed, with a special focus on Core Measures indicators. The impact of flow and resource utilization on overall performance is studied, and areas where clinicians can intervene to decrease the overall incidence of inpatient complications are identified.

This presentation will discuss the capability of electronically measuring Nursing Outcomes for both internal Quality Improvement initiatives, as well as magnet status applications.

Hospitals struggle with how best to capture process and outcomes data related to nursing outcomes. This presentation will show that this information can be obtained electronically, and will demonstrate how that is done with an on-line outcomes management product (CareScience Quality Manager). Risk-adjustment methodologies will be discussed, as well as the clinical application of linking process data to outcomes to improve patient care.

Discussion of specific product features will be kept at a minimum - the product will be presented as one of many solutions available to clinicians to evaluate outcomes and care processes. The "take-away" message will be that clinical data is readily available, and that the clinicians who are interested in these outcomes should learn both who to ask for information and what clinical questions or hypotheses that they would like to answer.

The presentation will be in powerpoint format. Blinded data from hospitals across the USA will be displayed, and pros and cons of electronic data collection and analysis will be discussed.