safe, patient-centered healthcare: checklists, data analytics … · checklists, data analytics and...
TRANSCRIPT
Safe, Patient-Centered Healthcare:
Checklists, Data Analytics and
Standardizing Operations
Kenneth K. Boyer
Academic Director, IMS
Patient Safety Medical Errors are prevalent – even in top tier hospitals
•In 1998, Institute of Medicine published a seminal report estimating that:
•As many as 1,000,000 patients a year in the U.S. are harmed and
•98,000 people die as a result of preventable errors
•Set goal of reducing this number by 50% in five years
Progress?
•Pronovost, Miller and Wachter (2006, JAMA)
provide commentary that outlines the many
challenges in first measuring, then acting to
prevent medical errors and ask the question “are
patients safer now” and answer by writing “The
inability to answer this question is doubly
surprising given the increase in publicly available
quality measures over the same period” (p. 696).
Recent Newsweek Article (Oct, 2010)
•Some progress, but still substantial room to improve
•80,000 central line infections per year, with 30,000
deaths and a cost of > $2 billion
•Pronovost – Michigan Central Line Study
•Estimated to save 2,000 lives and $200M per
year
What is clear is the culture of
medicine must change ...
Undoing a culture is hard,
especially one steeped in
hierarchy and intimidation
Bringing Operations to the
Operating Room
•Dr. Atul Gawande – Surgeon and Public Health Researcher,
Harvard University
•Dr. Peter Pronovost – Anesthesiologist and Public Health
Researcher, Johns Hopkins University
Some Success Stories
• Virginia Mason Hospital (Washington)
• ThedaCare (Wisconsin)
• Beth Israel Deaconess Hospital (Boston)
• UPMC
• OSU Medical Center
• mms://streaming1.osu.edu/mediaWWW2/osu
mc10/townhall/060810townhalloitstream.wmv
• Show 9:45 – 10:30
• Show 16:15 – 18:30
CMS Process of Care Measures
• Medicare mandates that hospitals collect
data on 4 common conditions (originally 3)
and ties reimbursement to performance
– Heart Attacks (AMI) – 8 measures
– Heart Failure (HF) – 4 measures
– Pneumonia Care (PN) – 7 measures
– Surgical Infection Prevention (INF) – 5
measures
CMS Process of Care Measures
What do you as patients, expect these percentages to be?
What do you think OSUMC’s numbers are?
CMS Core Measures: OSUMC
You can compare hospitals at:
http://www.hospitalcompare.hhs.gov
Improvement: 2005 to 2009
0.600
0.650
0.700
0.750
0.800
0.850
0.900
0.950
1.000
2005 2007 2009
Heart Failure (HF) Aggregate CMS Process of Care Median and Quartiles
Improvement: 2005 to 2009
0.600
0.650
0.700
0.750
0.800
0.850
0.900
0.950
1.000
2005 2007 2009
Pneumonia (PN) Aggregate CMS Process of Care Median and Quartiles
Variability in Hospital Performance
Best Hospitals
Middle Hospitals
Worst Hospitals
Quality Tools: Strong Impact on Patient Outcomes
Healthcare Research
• “Process Quality Improvement: An Examination of General vs. Outcome-Specific Climate and Practices in Hospitals”, forthcoming 2012, Journal of Operations Management, Kenneth K. Boyer, John Gardner, Sharon Schweikhart.
– Primary Findings:
• Quality Tools from private sector have strong impact on Patient Safety and Satisfaction
• Big hospitals benefit most from efforts to improve patient safety culture.
• Small hospitals benefit most from efforts to develop specialized safety tools – checklists, standard work etc.
• “Process Management Impact on Clinical and Experiential Quality: Managing Tensions between Safe and Patient-Centered Healthcare”, Aravind Chandrasekeran, Claire Senot, Kenneth K. Boyer, Manufacturing and Service Operations Management,forthcoming 2012.
Research Questions
Effect of CMS Process Management on Quality Outcomes
• Exploitation/Exploration dilemma (Benner & Tushman 2003, March 1991)
• Healthcare: Clinical and
Experiential quality (Donabedian 1980)
Effect of External and Internal Forces
• External (e.g. regulatory pressure):
focus on clinical quality (Westphal et
al. 1998)
• Internal (e.g. hospital leadership):
impacts outcomes (Guler et al. 2002)
RQ1: What is the effect of CMS process
management initiatives on both the clinical
and experiential quality of care in U.S
hospitals?
RQ2: How do regulatory forces influence
the effect of CMS process management
on clinical and experiential quality?
RQ3: How does hospital leadership
influence the relationship between CMS
process management and clinical and
experiential quality?
Research Design Overview
Sampling
Frame
284 acute care U.S. hospitals – 273 in final sample
Across 43 states
Average size: 268 beds
Method
Web Survey: Quality management practices in U.S.
hospitals
2 waves: Network hospitals (81), other (192)
Respondent Director of quality or chief nursing officer
Elements
measured
CMS Process Management
Hospital Leadership
Controls: CMS FTE, Training, Perceived Relative
Performance
Primary Data
Research Design Overview
Secondary Data
Construct Source Measurement
Clinical Quality CMS Process of care
measures
Experiential Quality CMS HCAHPS survey
State Legislation Timing APIC report 2009 - year of first
enacted HAI law
Controls: CMS FTE, Training, Perceived Relative Performance
P
PCQij
1ln
Q
QEQij
1ln
Evaluating State Leadership Timing
Sept 2009 March 2010
Tracking quality
performance
Administering survey
Jan 2003 Apr 2009 Dec 2008
Framework
Clinical
Quality
Experiential Quality
CMS Process Management
Hospital Leadership
State
Legislation Timing
Primary data
Secondary data
Data reported to CMS on patient
care processes – see Hospital
Compare for your local hospital
Patient Satisfaction survey data
reported to CMS on patient care
processes – see Hospital Compare
for your local hospital
Trade-off: A focus on Clinical Quality negatively impacts
Experiential Quality --- in the short run
Predictor Variables
Clinical Quality Experiential Quality
Model 1 Model 2 Model 5 Model 6
Constant 1.890** 1.962** 1.544**
1.532**
Teaching - 0.238+ - 0.292* 0.118+ 0.115+
Size 0.207** 0.188** - 0.076+ - 0.222**
Corporate Goals (for profit) 0.380* 0.364* - 0.166* - 0.168*
Ownership Structure (public) - 0.317** - 0.276** - 0.076+ - 0.078+
Training 0.024 - 0.055 0.041+ 0.069**
CMS FTE 0.014 0.022 0.010 0.012
Perceived Relative Performance 0.155** 0.120** 0.042
* 0.053*
CMS Process Management 0.231** - 0.066*
R-Square 26.34 32.87 23.79 26.17
ΔR-Square --- 6.53** ---- 2.38*
Chi-Square 77.85** 103.03** 118.91** 125.87**
Positive effect of
CMS process
management
H1a: Supported
Negative effect of
CMS process
management
H1b: Supported
Predictor Variables
Clinical
Quality
Experiential
Quality
Model 3 Model 7
Constant 1.903** 1.375**
Teaching - 0.343** 0.065
Size 0.187** - 0.184**
Corporate Goals (for profit) 0.462** - 0.165*
Ownership Structure (public) - 0.219* - 0.084+
Training - 0.033 0.053*
CMS FTE 0.029 0.005
Perceived Relative Performance 0.112* 0.063**
CMS Process Management 0.233** - 0.031
State Legislation Timing 0.017 - 0.034*
CMS Process Management * State Legislation Timing 0.044+ 0.023*
R-Square 34.14 28.85
ΔR-Square 1.27* 2.68*
Chi-Square 107.31** 142.66**
Positive effect of
CMS process
management *
State Legislation
Timing
H2a: Supported
Positive effect
of CMS process
management *
State Legislation
Timing
H2b: Supported
Results: Timing of State Legislation has strong impact on Quality
Interaction Plot: Effect of State Legislation Timing
Cli
nic
al Q
ua
lity
State Legislation Timing = Late
State Legislation Timing = Early
Low
High
CMS Process Management
Low High
Ex
perie
nti
al Q
ua
lity
State Legislation Timing = Late
State Legislation Timing = Early
Low
High
CMS Process Management
Low High
Conclusions
• Tradeoffs between Clinical and Patient
Experience Quality
• One Step Backward …. Two Steps
Forward
• Legislation does initiate progress on
Clinical Quality
• Leadership re Patient Experience helps
shape that outcome