Surveillance & Quality Improvement Is there Tension? Mary G. George MD, MSPH, FACS, FAHA Division for Heart Disease and Stroke Prevention, Centers for Disease Control and Prevention May 2010

I have no financial or other disclosures The findings in this presentation are those of the author and do not necessarily represent the views of the Centers for Disease Control and Prevention, or the Division for Heart Disease and Stroke Prevention. Disclosure Information Mary G. George MD MSPH FACS FAHA Surveillance & Quality Improvement – Is there tension?

Objectives Review definitions of surveillance and quality Review the core surveillance and QI functions of PCNASR Examples where the 2 functions may be in conflict and suggest ways to increase the QI efforts without compromising surveillance Review data on the representativeness of the PCNASR data

In a Nutshell...

Is there Tension between Surveillance & QI

Public Health Surveillance “The ongoing systematic collection, analysis, and interpretation of outcome-specific data for use in the planning, implementation, and evaluation of public health practice” Surveillance includes the dissemination of findings Public health surveillance identifies problems, who the problems affect, and where prevention priorities should be directed PHS must be data for decision makers – to be useful for policy makers Thacker, SB. Principles and Practice of Public Health Surveillance, 2 nd Ed. 2000

Surveillance cont. Assessing quality of care is a valid function of public health surveillance Surveillance Modes –Active –Passive –Sentinel –Census –Sampled

Quality – How is it Defined? “Almost all quality improvement comes via simplification of design, manufacturing...layout, processes, and procedures.” “Quality is not an act, it is a habit” “Quality means doing it right when no one is looking” “Professionalism means consistency of quality” Kaizen – a total life philosophy of incremental, gradual, continuous improvement

Which Road

PCNASR Activities Surveillance on quality of care Hospital sampling Data quality assurance (re-abstraction, data cleaning and feedback) Evaluate hospital stroke capacity Quality improvement Program evaluation (Connecting across the continuum – EMS)

Is there Tension? How Good is Good Enough? QI vs. QA QI vs. research (generalizability) Patient care vs. data collection Hospital sampling (representativeness of hospitals)

Where Tension Can Lead to Bias

Hospital Selection – biased? –Do you limit your surveillance to certain hospitals that fit your sampling frame? –What if sample selected hospitals don’t have the resources to participate or don’t want to participate? –What if state regulations encourage participation (sampling frame is irrelevant)? Case Selection – biased? –Convenience selection of cases –Convenience selection of case mix

Is PCNASR Representative? What is the appropriate comparison group? A convenience sample raises issues of generalizability Hawthorne effect vs. program effect Sources of selection bias

Hospital Characteristics No. of stroke discharges* 101– – Hospital type Academic60.49 Nonacademic39.51 GWTG † † Fonarow, GC. Circulation 2010 *George, MG. MMWR 2009

Demographics PCNASR*GWTG † † Fonarow, GC. Circulation 2010*George, MG. MMWR 2009

Risk Factors Atrial fib/flutter17.11 Stroke/TIA32.07 CAD/prior MI27.72 Carotid stenosis4.32 Diabetes mellitus30.32 PVD4.86 Hypertension77.91 Smoker18.99 Dyslipidemia38.59 GWTG † † Fonarow, GC. Circulation 2010*George, MG. MMWR 2009

Tension in QI Initiatives Is between clinically based guidelines of care, the development of a performance measure, and the availability of data that can accurately describe the measure Not unique to PCNASR

How to Reduce the Tension How much is due to the burden of data collection? How much is due to using the data? Would automatic data collection from EMRs reduce the tension? Would fewer measures of care reduce the tension?

How Flexible Should Our Systems Be?