Closing the Gap in Children's Quality Measures: A Collaborative Model

Abstract

The need for measures of the quality of healthcare provided to children and adolescents is well documented. However, children have been underrepresented in national healthcare quality measurement and reporting efforts. The Pediatric Data Quality Systems (Pedi-QS) Collaborative is addressing this gap. Two consensus measure sets and an assessment of nursing-sensitive indicators in pediatric care have been produced through the collaborative. The framework and measure set development process are described. Lessons learned from applying the process are summarized, and future directions are suggested. Voluntary collaborative efforts are vital for advancing children's measures, and national support and funding are also needed.

Parents' Perspectives on “Keeping Their Children Safe” in the Hospital

“…[1][2][3][4] Patientcenteredness refers to a partnership emphasizing open access to information, shared decision-making, and mutual respect. 1,5 Engagement of patients and families and promotion of self-efficacy in health care 6 are promoted as potential ways to improve safety.…”

Measuring patient safety culture in pediatric long-term care

“…Standardized outcome measurements do not exist for pLTC, making internal and external benchmarking impossible and hampering quality improvement efforts [20]. Indeed, children with medically complex chronic conditions have been identified as a priority population for improvement efforts [19,21].…”

National Testing of the Nursing-Kids Intensity of Care Survey for Pediatric Long-term Care

“…The pediatric population with CMC is a designated priority population for healthcare delivery improvements (Agrawal, 2015; Schwalenstocker et al, 2008). Despite prioritization, there is limited evidence of the most effective an efficient delivery of care models for this vulnerable population (Cohen, 2011).…”

“…Thus, beyond the research implications and in the context of the growing population in both numbers and intensity, along with increased focus on fiscal restraint and reimbursement, the potential importance of this measure to benchmark intensity internally or externally is notable. The lack of standardized measures makes these comparisons impossible and thus difficult to assess resource demand and utilization as well as strategize the best care delivery models (Schwalenstocker et al, 2008). Policy implications include use of the N-KICS tool internally to better manage resources as well as externally to add to process and staffing measures tied to public and private reimbursement for care.…”