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Improving Office Care for Chest Pain Thomas D. Sequist, MD MPH Associate Professor of Medicine and Health Care Policy Brigham and Women ’ s Hospital, Division.

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Presentation on theme: "Improving Office Care for Chest Pain Thomas D. Sequist, MD MPH Associate Professor of Medicine and Health Care Policy Brigham and Women ’ s Hospital, Division."— Presentation transcript:

1 Improving Office Care for Chest Pain Thomas D. Sequist, MD MPH Associate Professor of Medicine and Health Care Policy Brigham and Women ’ s Hospital, Division of General Medicine Harvard Medical School, Department of Health Care Policy Harvard Vanguard Medical Associates

2 Why Chest Pain? Chest pain is a common symptom –Increasing burden in primary care Frequent missed diagnosis of acute MI Excess utilization of resources

3 Patient Care Model Primary care visit Home without further testing Home with further testing Emergency Department Discharged Chest Pain Unit Inpatient ICU

4 Patient Care Model Primary care visit Home without further testing Home with further testing Emergency Department Discharged Chest Pain Unit Inpatient ICU

5 Primary Care Challenges Low risk population –Limit excess resource utilization –Avoid missed diagnoses Time-limited care –Cannot usually observe over several hours No immediate cardiac stress testing No immediate cardiac enzymes

6 Can the Framingham Score Help? Main utility is to raise awareness FRS variables are generally available FRS compares favorably with exercise stress testing

7 Defining High Risk Patients FRS CutoffSensitivitySpecificity ≥ 5% ≥ 10% ≥ 20% Sequist et al. Arch Intern Med 2006.

8 Study Questions 1.Can risk score alerts within an EHR improve risk-appropriate care for patients with chest pain? 2.What are the additional opportunities to improve the efficiency of chest pain care?

9 Harvard Vanguard Medical Associates Multi-specialty group practice Integrated electronic health record 15 ambulatory health centers 175 primary care physicians 300,000 adult patients

10 Randomization Scheme 292 Primary Care Clinicians 7,083 patients (≥ 30 years old) Intervention Group 149 clinicians 3,634 patients Control Group 143 clinicians 3,449 patients High Risk 717 patients Low Risk 2917 patients High Risk 610 patients Low Risk 2839 patients

11 Intervention Design Identification of patients with chest pain –Medical assistant training Automated calculation of Framingham Risk Score Delivery of risk-appropriate recommendations via electronic alerts

12 Risk Appropriate Recommendations High risk patients (FRS ≥ 10%) –Electrocardiogram performance –Aspirin therapy Low risk patients (FRS < 10%) –Avoidance of cardiac stress testing

13 Entry of Chest Pain Complaint

14 High Risk Patient Alert

15 Low Risk Patient Alert

16 SmartLink (.frsdetail)

17 Baseline Patient Characteristics Intervention (n = 3,634) Control (n = 3,449) p value Mean age, years Female, % Insurance Commercial Medicare Medicaid Uninsured Framingham Risk Score < 10% ≥ 10%

18 Clinical Care and Outcomes High Risk (n=1327) Low Risk (n=5756) p value Evaluation and treatment Electrocardiogram Aspirin therapy Cardiac stress test Follow up care Home Hospitalized Diagnoses Acute myocardial infarction* < * Among 26 cases of AMI, 10 (36%) represented missed diagnoses

19 Impact of Electronic Alerts High Risk PatientsLow Risk Patients

20 Clinician Views on Intervention Is the Framingham Risk Score a valid tool for evaluating chest pain?

21 Clinician Views on Intervention Is a Risk Score Cutoff of 10% to identify high risk patients….

22 Conclusions Acute MI is uncommon among primary care patients with chest pain Missed diagnosis of acute MI is common, while many low risk patients undergo cardiac stress testing Electronic risk alerts do not change care patterns

23 Implications Failure to change care patterns –Is it lack of belief in the risk assessment tool? –Is it failure to deliver information effectively? –Do we need more comprehensive efforts? Electronic health records represent one piece of a multi-component program

24 Improving Efficiency of Chest Pain Care Map flow of patients from primary care Evaluate cost implications for varied evaluation and management strategies Analyze variation in care patterns

25 Patient Care Model Primary care visit Home without further testing Home with further testing Emergency Department Discharged Chest Pain Unit Inpatient ICU

26 Estimated Average Costs Per Patient Primary care visit Home without further testing $293 Home with further testing $442 Emergency Department Discharged $1,087 Chest Pain Unit $3,192 Inpatient $17,562 ICU $47,575 55% 40% 5% 37% 47% 13% 3%

27 Estimated Average Costs Per Patient Primary care visit Home without further testing $293 Home with further testing $442 Emergency Department Discharged $1,087 Chest Pain Unit $3,192 Inpatient $17,562 ICU $47,575 55% 40% 5% 37% 47% 13% 3%

28 Physician Level Clinical Variation Cardiac Stress Testing* Emergency Department Triage* % of patients referred for care within physician practices 3.8%26.7% 1.3%14.9% * p<0.01 for random effects of physician level variation. 0%50% 10.8% 4.7% Legend 95% Lower CI 95% Upper CI Average

29 How Can the EHR Improve Efficiency? Increasing awareness of pre-test probability –All variation is within low risk patients Focus on low value emergency department referrals Peer to peer education

30 Clinical Process Flow Primary care visit EKG Stress ECHO Stress Nuclear ETT Cardiology Home Triage Emergency Dept ICU Inpatient Chest Pain Unit Triage Home


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