NZ Hospital Performance (2001-09) Outputs, Inputs, and Productivity - - PowerPoint PPT Presentation
NZ Hospital Performance (2001-09) Outputs, Inputs, and Productivity Motivating questions Have NZ hospitals become more/less productive in the past 9 years (2001-09)? What is the evidence? What are the limitations in drawing inferences
What is the evidence? What are the limitations in drawing inferences from available data
What is the evidence? What factors explain differences? What are the limitations in drawing inferences from available data
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all facilities, all discharges
using relative resource use by DRG (WEIS) as weights
~25% (or more) of total hospital output
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700000 750000 800000 850000 900000 950000 1000000
2.8 2.9 3 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 2001 20022003200420052006200720082009
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23% increase 16% decline Year Year
Ave Length of Stay
2500 2700 2900 3100 3300 3500 3700 3900 4100
Mean discharges per month
2500 2700 2900 3100 3300 3500 3700 3900 4100
Mean WEIS-weighted discharges per month
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WIES weighted No. of Discharges
Time (2001 – 2009) Time (2001 – 2009)
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50 60 70 80 90 100 110 120 80 100 120 140 160 180 200
Year Year
Change in Average Length of Stay Change in Proportion of Day Stays Index (2001=100) Index (2001=100)
80 90 100 110 120 130 140 150 2001 2002 2003 2004 2005 2006 2007 2008 2009
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Year
Index (2001=100)
By month, disaggregated by type, with FTEs
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$3.5 $4.0 $4.5 $5.0 $5.5 $6.0 $ billions
Total DHB (real) expenditure
1.0000 1.0500 1.1000 1.1500 1.2000 1.2500 1.3000 1.3500 1.4000
DHB (real) expenditure per capita
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40% increase 26% increase Year Year
$thousands
Personnel 60% Outsource d Services 7% Clinical Supplies 14%
Infrastructu re & Nonclinical supplies 19%
Input Expenditure shares
Medical 25% Nursing 39% Allied Health 16% Support 3% Manageme nt 17%
Personnel Expenditure shares
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90 100 110 120 130 140 150 160 170 180 190
01 02 03 04 05 06 07 08 09
90 100 110 120 130 140 150 160 170 180 190
01 02 03 04 05 06 07 08 09
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Year Year
Index (2001=100) Index (2001=100)
NMDS Outputs = inpatient stays (case mix weighted)
incl. day stays counted as 0.5 days Excl. outpatient & ED visits
DHB provider expenditures in 2001 NZD(MoH)
Deflated by GDP deflator (StatsNZ)
12% decline between 2001 & 2009
BUT measure is based on inpatient stays so underestimates
productivity
IF share of outpatient and ED increased over time then decline is
Substantial variation across DHBs
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60 65 70 75 80 85 90 95 100 105 110 2001 2002 2003 2004 2005 2006 2007 2008 2009
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Year
Index (2001=100)
Data: Panel of monthly data on case-mix weighted hospital output
(partial) and DHB provider expenditure for 9 years
Super-population perspective for statistical inference Hospital productivity of DHB at time t is a function of …
time-varying DHB characteristics (eg. case mix, organization, resource allocation)
time-invariant DHB characteristics (eg. Population size and demographic composition, location)
time-varying DHB-invariant characteristics (policy directive)
Some characteristics observed, some not Dynamic (changing) relationships – with past characteristics (including
productivity itself)
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Specifications estimated (so far)
Pooled with robust standard errors for DHB clustering Random effects Fixed effects
Lagged dependent variables Endogenous regressors (input expenditures, acute admissions,
etc)
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0.005 0.01 0.015 0.02 0.025 Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Seasonal Variation (Base=Jan)
02 03 04 05 06 07 08
Annual Variation (Base=2001)
Monthly Data Yearly Data
Year Month
Percentage Change (Base=2001) Percentage Change (Base=Jan)
Monthly data
DHB fixed effects specification best Significant effects: Proportion Pacific (-ve), Proportion newborn (-ve),
proportion arranged admissions (+ve), and significant month & year variation (previous slide)
Annual data
DHB random effects specification best Only year dummies significant (previous slide)
Serial correlation in errors so dynamic model more efficient Significant effects:
Lagged productivity (+ve): higher past productivity -> higher current Economies of scale (+ve): larger admission volume -> higher productivity
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based on 11 (of 20) provider-level patient safety indicators (PSIs) developed by AHRQ
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Patient-level Logistic regressions for each PSI to derive predicted values of the outcomes of interest on full nine years of data in NMDS.
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Need to adjust indicator for reliability by isolating true variability of indicator.
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Need weighting system to combine indicators of different dimensions into a single composite index.
Equal Weights, Factor Analysis based weights, Expert opinion based weights
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80 90 100 110 120 130 140 150 2001 2002 2003 2004 2005 2006 2007 2008 2009
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Year
Index (2001=100)
Increase in index => decline in quality
Total DHB expenditures have little explanatory power
Source: Bowden-Desai paper presented at NZAE (2011) 20
Significant Effects Sign Time +ve Proportion Female +ve Proportion NZ European
Proportion Pacific
Clinical Severity +ve
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2.
3.
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