Development and Implementation of an Inpatient CAMEO© Staffing Algorithm to Inform Nurse- Patient Assignments in a Pediatric Cardiac Inpatient Unit.

Michelle Hurtig, Stephanie Liseno, Mary C McLellan, Adam Homoki, Maeve Giangregorio, Jean Connor
Author Information
  1. Michelle Hurtig: Nursing Director of Cardiovascular - Inpatient/ICP, Procedural Programs, Boston Children's Hospital, MA, United States. Electronic address: michelle.hurtig@cardio.chboston.org.
  2. Stephanie Liseno: Staff Nurse II, Cardiac Inpatient Unit, Boston Children's Hospital, MA 02115, United States.
  3. Mary C McLellan: Cardiac Inpatient Unit, Boston Children's Hospital, MA, United States. Electronic address: Mary.McLellan@childrens.harvard.edu.
  4. Adam Homoki: Cardiac Inpatient Unit, Boston Children's Hospital, MA, United States. Electronic address: Adam.Homoki@childrens.harvard.edu.
  5. Maeve Giangregorio: Cardiac Inpatient Unit, Boston Children's Hospital, MA, United States. Electronic address: Maeve.Giangregorio@childrens.harvard.edu.
  6. Jean Connor: Cardiovascular & Critical Care Patient Care Operations, Boston Children's Hospital, Boston, Harvard Medical School, MA, United States. Electronic address: Jean.Connor@cardio.chboston.org.

Abstract

BACKGROUND: Nursing workload measurement systems are vital to determine nurse staffing for safe care. The Inpatient Complexity and Assessment and Monitoring to Ensure Optimal Outcomes (CAMEO©) acuity tool provides a standardized language to communicate the acuity and complexity of nursing care in the pediatric inpatient setting.
DESIGN AND METHODS: A process improvement project was implemented on a pediatric cardiac inpatient unit to utilize the Inpatient CAMEO© tool to inform nurse-patient assignments. Development of the Inpatient CAMEO© Staffing Algorithm utilized a modified Delphi methodology. Six Delphi rounds were performed for algorithm development, addressing potential implementation barriers, educating nursing staff, piloting feasibility, and final full implementation.
RESULTS: The cardiac inpatient unit's charge nurses' algorithm utilization was 86% (n = 12) during the feasibility pilot. The algorithm impacted and changed 28% (n = 4) of the shifts' assignments. One-year post algorithm implementation, CAMEO© documentation rates increased from 25 to 30% to >60%. A retrospective, two-week point-prevalence analysis one-year post-implementation described adherence to the Inpatient CAMEO© Staffing Algorithm for 87% (n = 375) of the nurses' patient assignments.
CONCLUSIONS: The Inpatient CAMEO© Staffing Algorithm was developed based upon the Inpatient CAMEO© tool and the Inpatient CAMEO© Complexity Classification System to inform nurse-patient assignments and allocate nursing resources. The Inpatient CAMEO© Staffing Algorithm was feasible and sustainable for over one year following implementation at a single center's pediatric cardiac inpatient unit.

Keywords

MeSH Term

Algorithms
Child
Humans
Inpatients
Nurse-Patient Relations
Nursing Staff, Hospital
Personnel Staffing and Scheduling
Retrospective Studies
Workforce
Workload

Word Cloud

Created with Highcharts 10.0.0InpatientCAMEO©assignmentsStaffingAlgorithminpatientalgorithmimplementationacuitytoolnursingpediatriccardiacn=PediatricNursingworkloadcareComplexityunitinformnurse-patientDevelopmentDelphifeasibilitynurses'BACKGROUND:measurementsystemsvitaldeterminenursestaffingsafeAssessmentMonitoringEnsureOptimalOutcomesprovidesstandardizedlanguagecommunicatecomplexitysettingDESIGNANDMETHODS:processimprovementprojectimplementedutilizeutilizedmodifiedmethodologySixroundsperformeddevelopmentaddressingpotentialbarrierseducatingstaffpilotingfinalfullRESULTS:unit'schargeutilization86%12pilotimpactedchanged28%4shifts'One-yearpostdocumentationratesincreased2530%>60%retrospectivetwo-weekpoint-prevalenceanalysisone-yearpost-implementationdescribedadherence87%375patientCONCLUSIONS:developedbaseduponClassificationSystemallocateresourcesfeasiblesustainableoneyearfollowingsinglecenter'sImplementationInformNurse-PatientAssignmentsCardiacUnitNurse-patientcardiology

Similar Articles

Cited By