Determining Nurse Aide Requirements to Provide Care Based on Resident Workload: A Discrete Event Simulation Model John F. Schnelle, PhD Professor of.

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Presentation transcript:

Determining Nurse Aide Requirements to Provide Care Based on Resident Workload: A Discrete Event Simulation Model John F. Schnelle, PhD Professor of Medicine Hamilton Chair, Division of Geriatric Medicine Director, Center for Quality Aging Veterans Affairs Geriatric Research, Education and Clinical Center (GRECC) Disclosures Funding for simulation analyses to ProModel Life Sciences Corporation by Marks, Balette, and Gissel

Article Citation and Link Schnelle JF, Schroyer LD, Saraf AA, Simmons SF. Determining Nurse Aide Staffing Requirements to Provide Care Based on Resident Workload: A Discrete Event Simulation Model. Journal of the American Medical Directors Association. 2016 Nov 1;17(11):970-7. doi: 10.1016/j.jamda.2016.08.006 Link: http://authors.elsevier.com/a/1TwP45QyCpsdVb

Use a validated method to plan and manage long term care staffing Vision Use a validated method to plan and manage long term care staffing

Background High variability in nurse aide staffing About 25% of nursing homes in the US < 2.1 HPRD No objective method to plan staff based on resident workload No effective method to experiment with management interventions to improve staff efficiency

Discrete Event Simulation Systems engineering approach that models realistic work environments Recommended by IOM as method to improve health care (2005)1 Widely used in and outside health care First used in NHs to determine staffing in 2001 CMS report on minimum staffing2 Source: 1. Dittus RS. Discrete-Event Simulation Modeling of the Content, Processes, and Structures of Health Care. In: Reid PP, Compton WD, Grossman JH, Fanjiang G, eds. Building a Better Delivery System: A New Engineering/Health Care Partnership. Washington (DC); 2005 2. US Centers for Medicare and Medicaid Services, Prepared by Abt Associates Inc. Appropriateness of Minimum Nurse Staffing Ratios in Nursing Homes. Report to Congress: Phase II Final. Volumes I-III. 2001 Baltimore, MD: CMS

Kindly refer to Table 2. of the article How will this work? Kindly refer to Table 2. of the article 1. Define Resident ADL Care Needs MDS identifies residents needing supervision to full assistance in each ADL care area Two-person assists can be considered 2. Define Schedule of Care E.g., Incontinence care every two hours for people who require toileting assistance Define time to provide episode of care Variability is key factor driving staffing needs (Table 2)

Kindly refer to Table 2. of the article How will this work? Kindly refer to Table 2. of the article 4. Define other work conditions Random events (e.g. call lights) Travel times Care windows (e.g. 2 hours for meals) 5. Describe time available to provide care Number of staff Productivity estimates All time available providing care minus meal breaks

Activities of Daily Living (ADL) Care Required RESIDENT WORKLOAD CATEGORIES (Prevalence) WORKLOAD DESCRIPTION Activities of Daily Living (ADL) CARE REQUIRED Incontinent Toileting Assistance Repositioning Assistance Eating Assistance AM/PM Dressing Hygiene Assistance Exercise or Range of Motion 1 (3.6%) Lightest NO YES 2 (3.6%) Light 3 (1%) Moderate 4 (21.2%) Heavy 5 (60.2%) Heaviest 6 (1.4%) 7 (7.9%) Heavy (Bedbound)

Time to provide care Exercise for people with independent mobility Triangular distribution 10, 15, 20 minutes 3 times per week: people with PT do not receive 8 hour care window expires at 10 pm

Define Work Scenario for Specific Home Resident workload categories Time to provide care (Table 2) Schedule of care and care window times (Table 2) # of aides (e.g. 2.4 HPRD) Productivity (e.g. No breaks, 7.5 hours providing care) No two person assists

Simulation – 100 replications over 3 week period Outcome – Omitted care time All care delivered divided by all care scheduled

Omitted Care: By Workload & Staffing Levels

Applications of this approach Consumer Information Quarterly omitted care time for each home based on quarterly staffing and MDS reports Other outcomes – waiting times for care in each ADL care, % of tasks completed in each ADL care area

Applications of this approach Develop Online Management Tool to test Different staffing levels Different staffing models (e.g. part-time staff) Different care schedules

Thank you! Questions? www.vanderbiltcqa.org