Drive Operational Excellence Through AI-Enabled Proactive Staffing

INPATIENT


NURSE STAFFING


“In nursing, adding numbers isn’t always the answer. We want to be smarter and more efficient with our existing resources. Hospital IQ has given us the ability to be proactive about our staffing needs and helps us assign, or reassign, staff based on the actual demand.”

Shawna Gunn
Manager of Operations

50%

reduction in the utilization of premium pay-based shifts

80+

hours given back weekly to the staffing office for proactive staff planning

10+

hours given back weekly to each nursing leader to focus on patient care

Customer Overview

MercyOne

» MercyOne Des Moines Medical Center has over 650 inpatient beds

» Over 5,000 staff members

» Longest continually operating hospital in Des Moines

THEIR PROBLEM: INEFFICIENT MANUAL STAFFING PROCESSES

Managing in crisis mode daily due to staff shortages and manual staffing processes:

The manual staffing process was incredibly time intensive and laborious:

» Staffing office spent 2 hours, 3 times a day, rounding on units to understand staffing needs
» Unit leadership spent the majority of their day addressing staffing-related issues
» No consolidated view of all available nursing resources

Daily challenges with short staffing in nursing due to:

» Limited insight into patient demand and nursing staff availability
» Unit protection of staff, limiting collaboration across nursing units
» A regional nursing shortage and high rates of turnover

OUR SOLUTION: AI-DRIVEN HOSPITAL STAFF MANAGEMENT SYSTEM

With Hospital IQ’s Staffing solution, MercyOne Des Moines was able to:

Institute proactive staff planning based on the 7-day forecast, resulting in:

» Improved utilization of staff by reallocating nurses from low census days to high census days
» More strategic use of float staff and premium pay-based shifts
» Improved patient care and staff satisfaction

Automate manual staffing processes and reduce time required to allocate staff daily:

» Automated float staff assignment, reducing phone calls and interruptions
» Unit leadership can focus their time on patient care related activities and ensuring staff productivity
» Staffing Office rounding reduced to 15 minutes, 3 times daily, enabling proactive staff planning

Download Case Study

Reduce Length of Stay Through Proactive Management of Observation Patients

INPATIENT


CAPACITY MANAGEMENT


“Since making the decision to focus on length of stay for observation patients, we have reduced hours per patient by over 30%. This was achieved through the combination of process improvements and Hospital IQ’s platform.”

Diane Murphy
Market Director Performance Excellence, Logistics, and Virtual Care

33%

reduction in average observation length of stay

100

bed days gained per month

24 hrs

average observation LOS

Customer Overview

MercyOne

» Common Spirit Health System affiliate

» Main campus for the MercyOne Des Moines network with over 650 beds

» Over 5,000 staff members

» Longest continually operating hospital in Des Moines

THEIR PROBLEM: DIFFICULTY MANAGING HOSPITAL LENGTH OF STAY

Average length of stay for observation patients consistently exceeded their targets:

Limited visibility to the status and location of their observation population due to:

» High observation population of 10-15% of total patients spread across the hospital
» Lack of a dedicated observation unit or specific care team assigned to them
» Reviewing applicability for observation status was inconsistent

The difficulty in managing their observation patient population resulted in:

» Observation patients placed in inpatient units, receiving commensurate care
» Reduced reimbursement associated with misclassified patients
» Average LOS for observation patients exceeded 24 hr target (ranged from 35 to 42 hours)

OUR SOLUTION: REAL-TIME, DATA-DRIVEN PATIENT FLOW DASHBOARD

With the predictive and real-time capabilities in Hospital IQ’s Inpatient solution, MercyOne Des Moines was able to:

Support its governance, organizational, and process changes, enabling them to:

» Forecast and prepare for upcoming observation patient demand
» Create real-time visibility to the observation patient-related KPIs
» Accelerate initiatives that produced good results and adjust those that weren’t as effective

Implement intelligent process changes and best practices that led to:

» A 33% reduction in the average observation length of stay
» Gaining 100 bed days a month
» The creation of a short stay unit with staff trained to evaluate observation criteria

Download Case Study

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