Hospital Patient Flow and NEST. Damian Miners, Principal Policy Analyst, SRF February 2013

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Transcription:

Hospital Patient Flow and NEST Damian Miners, Principal Policy Analyst, SRF February 2013

Patient Flow & NEST Many strategies to assist with the flow of patients through NSW Hospitals National Emergency Access Targets (NEAT) National Elective Surgery Targets (NEST) Patient Flow Systems and Patient Flow Portal Hospital in the Home Community packages ComPacks

Patient Flow & NEST What affects a Hospital s Patient Flow? Increasing presentations to ED s across NSW

ED Attendances across all NSW Hospitals 2600000 2500000 2400000 Long period of no real growth followed by a 24% increase from 2005 2300000 2200000 2100000 2000000 1900000 1800000 1700000 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2010-11 2011-12 Source = NSW Health Annual Report:: Total ED Attendances by Year 2002-03 to 2011-12

Patient Flow & NEST What affects a Hospital s Patient Flow? Increased ED admissions Planned & Unplanned surgery Winter sicker patient s

Patient Flow & NEST What affects a Hospital s Patient Flow? Ageing population Longer length s of admissions Discharge rates

Patient Flow & NEST Knock on effect Admissions & overcrowding in ED Ambulance delays Delaying Medical and Surgical admissions Surging open beds

Patient Flow & NEST Poor health outcomes for patients who stay longer than required in both Inpatient ward beds Emergency Department

Patient Flow & NEST Organisational Strategy Utilise Predictive Tool via Patient Flow Portal

Predictive Planning Patient Flow Portal Capacity Demand planning 14 days ahead Identifies bed capacity deficits Earlier escalation Earlier intervention

Predictive Planning The Data: We know there is actually little variation in: ED presentations ED admissions Discharges The predictive tool collates Patients coming into the hospital Patients exiting Capacity to fit demand Uses Historical data Current ED status Expected EDO, DOSA, Surgical and Medical booked Direct admissions Projected discharges / EDT Data is used to inform short and long term capacity planning: Calculate tipping points in the short and long term Analyse daily demand for each ward area deliver a plan for required discharges each day. Analyse demand over the long term (e.g. identifying frequent outliers does this service require extra capacity?) Mange predicted events medical term change / public holidays / events

Patient Flow Portal

Predictive Planning Actions Discuss predictive plan with Hospital execs Awareness and shape of the organisation over the next 14 days Review surgical bookings in advance Bed containment Surge capacity when needed Review future staffing requirements

Patient Flow & NEST How does Planned Surgery Influence patient flow?

Predictability of Emergency Trends Emergency Surgery is predictable emergency vs. non-emergency Surgical admissions Planned Surgery is not! emergency other Total separations for surgical procedures 7,000 6,000 5,000 4,000 3,000 2,000 1,000 0 12/31/2007 3/10/2008 5/19/2008 7/28/2008 10/06/2008 12/15/2008 2/23/2009 5/04/2009 7/13/2009 9/21/2009 11/30/2009 2/08/2010 4/19/2010 6/28/2010

Predictability of Emergency Trends ED emergency attendances by week of year - NSW 2008 2009 2010 Presentations are predictable Emergency attendances 50,000 45,000 40,000 35,000 30,000 25,000 1 4 7 10 13 16 19 22 25 28 31 34 37 ED emergency admissions by week of year 40 43 46 49 52 2008 2009 2010 9,500 Admissions are predictable 9,000 8,500 8,000 7,500 7,000 6,500 6,000 5,500 5,000 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 Emergency admissions

Booked Variation Is booked variation tipping the facility over the edge Variation in booked activity can be a driver for consistent capacity short falls Identification of trends Develop action plans to manage problematic variation

Patient Flow Portal

Predictive Planning Planned Surgery Allocate dates for surgery in PAS at least 2 to 4 weeks in advance. Be aware and understand your day to day variations in overnight bookings Reduce variation where possible

Variation Management Variation in practice affects LOS, errors, complaints, admission rates, readmission rates, off stretcher time, emergency access performance, diagnostic capacity, delays in consults, staff satisfaction. Questions to answer: What can we control? How differently do we have to do things? What time frames are we looking at? Flattening the variation within a coordinated system leads to better outcomes.

Predictive Planning Planned Surgery Gain access to the Patient Flow Portal - review the Predictive Tool be informed! Surgery Models of care: - Extended Day Only / 23 Hour - High Volume Short Stay Surgery (HVSSS) - Emergency Surgery Models

Patient Flow Patient Flow is everyone s responsibility

Patient Flow Questions?