Healthcare Data Goals, Audiences, Difficulties Timothy A. Denton, M.D., F.A.C.C. High Desert Heart Institute Victorville, CA California Medical Association 8 th Annual California Healthcare Leadership Academy

Datum [Pl. data] (L datum given, that which is given ) A thing given or granted; something known or assumed as fact, and made the basis of reasoning or calculation; an assumption or premiss from which inferences are drawn. OED

Data Collection Efforts Scientific research Epidemiology Financial Government reporting Public reporting

Data: The Good the Bad and the Ugly

Cardiac Surgery Reporting Northern New England (1987) New York (1989) STS (1992) Pennsylvania (1992) VA NSQIP (1994) mort dec 27% New Jersey (1994) California (2001)

“… to give consumers information they can use in making informed choices…” “…to encourage hospitals to take an in-depth look at their cardiac surgery programs, and make changes that can improve surgical outcomes…”

Cardiac Surgery Reporting Excess mortality Not believed, cases reviewed Excess mortality in high acuity patients MI<6 hrs, emergency changed management of MI, NOT CABG Dzubian et al. Ann Thorac Surg 1999;58:

Data: The Good the Bad and the Ugly

Cardiac Surgery Reporting Cardiac Surgeon survey 70% no change in practice Gaming of risk factors Refused high risk patients because of reporting “…denial of surgical treatment to high risk patients.” Burak et al. Ann Thorac Surg 1999;68:

Medical Data Reporting America’s Best Hospitals US News and World Report Guide to Hospitals Consumer Checkbook Hospital Report Cards Health Grades, Inc. JCAHO California CCMRP California (patient opinions) Maryland LOS, readmit, volume New Jersey CABG reporting New York CABG, PTCA Physician-specific Pennsylvania Volume, Mortality, LOS 75 diagnostic groups Texas Volume, Mortality 25 diagnostic groups Virginia Volume, Mortality 25 diagnostic groups South-Central Wisconsin Hip, Knee, cardiac Employer alliance

HCFA Mortality Data Mid to late 1980’s Administrative database Risk adjustment from same dataset Poor accuracy Rarely used by consumers 31% of hospitals used for internal purposes Ultimately discontinued JAMA. 1990;263: JAMA. 2000;283:

Volume-Outcome Relationship CCMRP 2001, Page 55

Central Limit Theorem – The more you measure, the less you learn Rare events – 2 % outcome characteristics are very difficult to stratify More Problems

Data: The Good the Bad and the Ugly

Center for Medical Consumers “Patient safety crisis in New York State” “Report refutes medical lobby’s claim of doctor shortage in New York” “ ’Crisis’ in malpractice insurance manufactured by organized medicine” “More is Better” (Surgical volumes)

Dear Dr. Denton, Our pharmacy records indicate that your patient, George Washington, has been placed on amiodarone and we don’t have evidence of a recent chest xray based on billing records. If you have not responded to this letter in two weeks, we will contact the patient directly to communicate our concerns to him. Sincerely, Your loving Health Insurance Company An example letter

1.Short-term amiodarone 2.No indication for CxR 3.Patient admitted to hospital in interval 4.You are not licensed to practice medicine in California 5.You are interfering in the MD-patient relationship 6.State Board of Medical Examiners An example response

A Different Ugly Patients want local care Patients believe in “their doctor” Patients don’t read the reports Patients can’t read the reports in 60% of CABG cases

Data: The Good the Bad and the Ugly The Solution

What are the goals of healthcare? Survival Quality of life Are the data important? Are the data accurate? Are the data interpretable? Are the data reasonably collectable? How will the data used? First Principles

1. Performing CABG surgery 2. Decreasing CABG mortality from 4.2% to 2.7% 3. Starting a statin on all CABG patients A Test Which is more important in overall mortality?

Who is the audience? Patients Physicians Government Administration Payors

Types of Data 1. Mortality 2. Morbidity / Quality of Life 3. Process variables 4. Decision-making variables

First Principles 1. Patient care comes first 2. Variables that change system behavior 3. Variables collected with minimal intrusion 4. Reported to the correct audience 5. Physicians must lead