Diabetes Data Dilemmas: Diabetes Prevention and Control

Transcription

1 Diabetes Data Dilemmas: Diabetes Prevention and Control Kansas Diabetes Quality of Care Project Seventh Annual Disease Management Colloquium Philadelphia, PA May 8, 2007 Marti Macchi, MEd, Director, Special Studies Kansas Department of Health and Environment Joe Brisson, Vice President Client Services Browsersoft

2 Outline Project Rationale Statewide Project Project Components First Year Outcomes Data Translated Into Practice Future Direction Open HRE Project

3 Project Rationale Data Decision Support

4 Burden of Diabetes in Kansas % Adult Kansans diagnosed with diabetes 7 th Leading cause of death (683 Kansans died of diabetes in 2004) Estimated direct and indirect costs of diabetes were nearly $1.3 billion a year 2004 Kansas Behavioral Risk Factor Surveillance System, KDHE. Center for Health & Environmental Statistics,Office of Vital Statistics KDHE, 2004 Lewin Group, Inc., American Diabetes Association,, 2002

5 Average Yearly Health Care Cost United States 2002 $14,000 $12,000 $10,000 $8,000 $6,000 $4,000 $2,000 $0 $13,243 $2,560 Person With Diabetes Person Without Diabetes Source: Hogan P etal. Economic Cost of Diabetes in the U.S.in American Diabetes Association. Diabetes Care. 26: , 2003.

6 Costs Associated with Poorly Controlled Versus Well Controlled Diabetes A1c Level 6% (normal) 7% (goal) 8% 9% 10% Adult with Diabetes $8,576 $8,954 $9,555 $10,424 $11,629 Adult with Diabetes, Hypertension & Heart Disease $38,726 $40,230 $42,467 $45,557 $49,673 Source: Gilmer, Todd P, et al. Diabetes Care 1997; Vol. 20, No. 12. Average Medical Care Over 3 Year Period

7 Kansas Diabetes Prevention & Control Program Objectives By 2008, increase the rate of: HbA1c test Annual foot exam Dilated eye exam Recommended annual pneumococcal immunization Recommended annual influenza immunization 69.1 % to 83.0 % 60.8% to 83.0% 67.5% to 83.0% 49.3% to 51.6% 60.7% to 63.5%

8 Statewide Project

9 Kansas Diabetes Quality of Care Project Sites Cheyenne Rawlins Decatur Norton Phillips Smith Jewell Sherman Thomas Sheridan Graham Rooks Osborne Mitchell Wallace Logan Gove Trego Ellis Russell Lincoln Republic Cloud Ottawa Saline Doniphan Brown Washington Marshall Nemaha Atchison Pottawatomie Leavenworth Riley Jackson Clay Jefferson Geary Shawnee Waubaunsee Dickinson Douglas Johnson Greeley Wichita Scott Lane Ness Hodgeman Hamilton Kearney Finney Stanton Grant Haskell Gray Ford Rush Pawnee Edwards Kiowa Barton Stafford Pratt Ellsworth Rice Reno Kingman McPherson Harvey Sedgwick Marion Butler Morris Chase Greenwood Elk Lyon Osage Coffey Woodson Wilson Franklin Anderson Allen Neosho Miami Linn Bourbon Crawford Morton Stevens Seward Meade Clark Comanche Barber Harper Sumner Cowley Chautauqua Montgomery Labette Cherokee

10 Project Organization Demographics 68 funded organizations 90 sites statewide 350 participating health professionals 50% of Kansas counties represented Diverse organizations participating Over 4,000 patients with Diabetes

11 Project Organization Demographics cont d Types of participating organizations: Local Health Departments Community Health Clinics Safety Net Clinics American Indian Health Clinic Home Health Agencies Hospital Affiliated Practices Private Practices Farmworker Program Promotora Program

12 Project Components First Year-----Process Chronic Care Model Training Chronic Disease Electronic Management System (CDEMS) Training Data Entry and Analysis Quarterly Reports Office Protocol Development Encouraged Diabetes Teams Encouraged Regular Team Meetings Encouraged Monthly Conference Calls Site Visits

13 Project Components Second Year-----Outcomes Advanced CDEMS Training Advanced Data Analysis Diabetes Teams Established Regular Team Meetings Documented Office Protocols Implemented Monthly Conference Calls Improved Quality of Care Measures

14 The Chronic Care Model

15 Chronic Care Model Components Health Care Organization Delivery System Design Decision Support Self-Management Support Community Resources Clinical Information System

16 CDEMS How does it work? Patient Data Entered Hard copy inserted into patient s chart % of Patients Receiving Vaccinations and Foot Exams Needs Improvement Dr. updates patient s chart

17 First Year Outcomes Health Care Organization Outcomes Quantifiable goals for quality of care provided to Patients 1st quarter 45% 4 th quarter 66% % change 46% Holding routine diabetes team meetings 42% 60% 42% Organizations Checking Yes on the Quarterly Office Self-Assessment Form

18 First Year Outcomes Cont d. Outcomes Routinely ask patients to remove socks and shoes before exam Non-physician staff allowed to do foot exam All patients scheduled for follow-up Non-physician staff empowered to order overdue labs Delivery System Design 1st quarter 39% 36% 60% 36% 4 th quarter 69% 39% 60% 54% % change 76% 8% - 50% Non-physician staff empowered to administer flu and pneumonia vaccinations 48% 57% 18% Organizations Checking Yes on the Quarterly Office Self-Assessment Form

19 First Year Outcomes Cont d. Outcomes CDEMS used to make decisions about needed care for patients Patients routinely know their targets for blood pressure, finger stick blood sugar, and HbA1 Provide resources for patients to allow them to be full partners in their care Decision Support 1st quarter 36% 4 th quarter 54% Self-management Support Outcomes 1st quarter 18% 42% 4 th quarter 54% 69% Organizations Checking Yes on the Quarterly Office Self-Assessment Form % change 50% % change 200% 64%

20 First Year Outcomes Cont d. Community Resources Outcomes 1st quarter 4 th quarter % change Develop partnerships in the community for referral 39% 51% 30% Clinical Information Systems Outcomes 1st quarter 4 th quarter % change Use CDEMS to record patients with eye exams, foot exams, HbA1c, flu and pneumonia vaccinations 45% 75% 66% Use CDEMS as a reminder system to prompt when a patient is due for labs or visit 27% 42% 55% Organizations Checking Yes on the Quarterly Office Self-Assessment Form

21 Patient Office Visits Percentage of Patients by Number of Visits Patiant Percentage to 2 3 to 5 6+ Number of Visits 1 st Year Results CDEMS Data, Office of Health Promotion (KDHE)

22 Age Demographics Percentage of Patients by Age Group Patient Percentage Age Group st Year Results CDEMS Data,Office of Health Promotion (KDHE)

23 Ethnicity Percentage of Patients by Ethnicity Patient Percentage White 4.7 African American 0.4 American Indian 0.3 Asian Hispanic Unspecifie d 1 st Year Results CDEMS Data, Office of Health Promotion (KDHE)

24 Insurance Percentage of Patients by Insurance Type Patient Percentage Medicaid Medicare Commercial Other None Type of Insurance 1 st Year Results CDEMS Data, Office of Health Promotion (KDHE)

25 Body Mass Index Percentage of Patients by Body Mass Index Patient Percentage <=24 Normal Overweight >=30 Obese Body Mass Index Range Body Mass Index is defined as weight in kilograms divided by height in meters squared (kg/m 2 ) 1 st Year Results CDEMS Data, Office of Health Promotion (KDHE)

26 Comorbidity/Complication Profile of Patients Comorbidity/Complication Hypertension Hyperlipidemia Heart Disease/Coronary Artery Disease Neuropathy Nephropathy Peripheral Vascular Disease Cerebrovascular Disease (stroke) Retinopathy Percentage (%) st Year Results CDEMS Data, Office of Health Promotion (KDHE)

27 Specialty Care Received Percentage of Patients Who Received Specialty Care Patient Percentage DM Edu. Nutrition Edu. Specialty Care Smoke cessation Self Mgt. Goal Set 1 st Year Results CDEMS Data, Office of Health Promotion (KDHE)

28 Preventive Care Practices Percentage of Patients by Preventive Care Practices Patient Percentage A1c Test Flu Vac Pneumo Vac Foot Check Retinal Exam Self Moniter BG 1 st Year Results CDEMS Data, Office of Health Promotion (KDHE)

29 HbA1c Levels Percentage of Patients by HbA1c Level 60 Patient Percentage < HbA1c Level (%) 1 st Year Results CDEMS Data, Office of Health Promotion (KDHE)

30 Data Translated Into Practice - at the clinic level New office protocols in all organizations Diabetes patient newsletters Patient certificates for improved A1c Pre-visit patient self-assessment programs CDEMS data used to guide team decisions Improved communication among providers Separate diabetes clinic days established Patients made full partners in care

31 Data Translated Into Practice - at the community level Pre-Diabetes Screening Programs Community health fairs Churches Cattle and hog processing plants New Community Partnerships YMCA Podiatrists Optometrists Dentists Community Diabetes Education Programs Targeting seniors Targeting overweight/obese

32 Project Direction Continue to add organizations Provide technical assistance to practices to further improvements in diabetes indicators Collaborate with other chronic disease programs (Hypertension quality of care project) Explore collecting primary prevention data Explore interfacing CDEMS with EHR OpenHRE expansion (Pilot to additional clinics)

33 OpenHRE Pilot Project Process Problem Method of data collection was not efficient (manual spreadsheets) Accuracy of information obtained was affected due to inconsistent data collection and submission Timeliness to aggregate data Reporting limited to MS Excel

34 About OpenHRE OpenHRE Community - is a consortium of communities and organizations working together to achieve secure and sustainable Health Record Exchanges. OpenHRE - toolkit consists of three configurable services that connect existing data sources for Health Information Exchange. The OpenHRE toolkit is available for download as free, open source software.

35 OpenHRE Pilot Project Pilot Deployment Collect data from 5 rural sites representing 13 clinics (1,408 patients) Remove directly identifiable patient data Create web-based Diabetes Summary Report Implement OLAP Reporting

36 Kansas Department of Health and Environment CDEMS - Pilot Browsersoft/OpenHRE

37 Kansas Department of Health and Environment CDEMS - Pilot Browsersoft/OpenHRE Plainville Tomcat Colby Mondrian Ellworth CDEMS Adapter Reporting Database JPivot Browser OLAP Application Salina Hiawatha KDHE Server running the OpenHRE application. Replicated site databases Diabetes Summary Report

38 Diabetes Summary Report Parameters Screen

39 Diabetes Summary Report Report Output

40 OLAP Reporting Tool Parameters Screen

41 OLAP Reporting Tool Sample Output

42 OLAP Reporting Tool Sample Graph Output

43 Problems Addressed Process Problems Method of data collection was not efficient (manual spreadsheets) Eliminated manual entry for participating clinics Accuracy of information obtained was affected due to inconsistent data collection and submission Automated collection occurs monthly or more frequently if desired Timeliness to aggregate data Nightly updates as new data arrives Reporting limited to MS Excel Parameter driven Diabetes Summary Report OLAP tool for Data Analysis Open source software provides a cost effective deployment Reusability Sustainable

44 Contact Information Marti Macchi, MEd Director of Special Studies Kansas Department of Health and Environment Joe Brisson Browsersoft, Inc. Vice President of Client Services