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More Information, Less Work: EHRs and Public Health Surveillance CSTE 2013 Richard Platt, MD, MS Harvard Medical School and Harvard Pilgrim Health Care.

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Presentation on theme: "More Information, Less Work: EHRs and Public Health Surveillance CSTE 2013 Richard Platt, MD, MS Harvard Medical School and Harvard Pilgrim Health Care."— Presentation transcript:

1 More Information, Less Work: EHRs and Public Health Surveillance CSTE 2013 Richard Platt, MD, MS Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA For the ESPnet team, led by Michael Klompas, MD, MPH

2 Diseases reportable by providers “REPORT PROMPTLY (WITHIN 1-2 BUSINESS DAYS)”

3 Chlamydia case report form

4 Paper-based reporting Am J Prev Med 2001;20:108 BMC Public Health 2004;4:29 Am J Epidemiol 2002;155:866 Pertussis Salmonella Hepatitis A

5 Paper-based reporting Am J Prev Med 2001;20:108 BMC Public Health 2004;4:29 Am J Epidemiol 2002;155:866 Salmonella Pertussis Hepatitis A

6 Electronic Laboratory vs Paper Reporting Number of Reports Paper reports Electronic lab reports 4.4 Fold Increase in Total Number of Reports Time from Diagnosis to Report Paper reports Electronic lab reports 7.9 Day Decrease in Mean Time to Report Am J Public Health 2008;98:344

7 Electronic laboratory reports – MA 2011

8 from www.sciencewatch.com (November 12, 2010)

9 www.esphealth.org Development supported by CDC and ONC

10 ESPnet – EHR Support for Public Health Compatible with any EHR that can export data Compliant with national standards (ONC Query Health) Open source JAMIA 2009;16:18-24 MMWR 2008;57:372-375 Am J Pub Health 2012;102:S325–S332 Identify conditions of interest, create complete reports, and transmit them securely, all automatically

11 ESPnet Partners Massachusetts Dept of Public Health Dept of Population Medicine Harvard Medical School / Harvard Pilgrim Health Care Inst. Massachusetts eHealth Institute Atrius Health Cambridge Health Alliance Mass League of Community Health Centers MetroHealth

12 Current ESPnet installations Northern Berkshires, MA Health Info Exchange 14 sites 50,000 patients Atrius Health 27 Sites 700,000 pts © Google Maps Cambridge Health Alliance 20 sites 400,000 patients MetroHealth Cleveland, OH 250,000 patients Mass League of Community Health Centers 18 sites 300,000 patients

13

14 Practice EHR’s D P H Health Department HL7 electronic case reports or aggregate summaries Automated disease detection and reporting ESPnet Server diagnoses lab results meds demographics vital signs JAMIA 2009;16:18-24 Am J Pub Health 2012; 102:S325–S332

15 Implications Compatible with most EHRs (local codes translated to common nomenclature) Universal Offloads computing burden from EHR Unobtrusive Clinical practice controls access/use Secure Implications Compatible with most EHRs (local codes translated to common nomenclature) Universal Offloads computing burden from EHR Unobtrusive Implications Compatible with most EHRs (local codes translated to common nomenclature) Universal Decoupled architecture EHR ESPnet

16 ESP’s Data Model Etc. Lab Result Person ID Dates of order, collection & result Test type, immediacy & location Procedure code & type Abnormal result indicator Test result & unit Amount dispensed Dispensing Person ID Dispensing date Days supply National drug code (NDC) Etc. Visit Person ID Dates of service Type of encounter Provider seen Facility BP type & position Vital Signs Person ID Date & time of measurement Weight Height Diastolic & systolic BP Etc. Allergy Person ID Date Code Name Etc. Procedure Person ID Dates of service Procedure code & type Encounter type & provider Etc. Diagnosis Person ID Date Principal diagnosis flag Encounter type & provider Diagnosis code & type Address, Etc. Demographic Birth date Person ID Sex Race Diagnosis code Etc. Problem Person ID Date Etc. Social Person ID Date Tobacco Alcohol Amt Etc. Medication Person ID Date Name/NDC code Refillls Birthweight, Etc. Pregnancy Person ID Date Gravida / Para Gest age @ deliv Etc. Provider Person ID Date Code Name Etc. Immunization Person ID Date Vaccine/Mfr/Lot CPT code Diagnosis code, POA Etc. Problem (Hospital) Person ID Date PersonVisit

17 CASE IDENTIFICATION

18 ICD9’s meds orders lab results vital signs Chlamydia Acute Hepatitis B Acute tuberculosis ESPnet

19 Acute hepatitis B Strategy 1: ICD9 070.3 Viral hepatitis B without mention of hepatic coma – Review of 50 patients’ charts 0% (95% confidence interval, 0-6%) Positive Predictive Value PLoS ONE 2008:3:e2626 Atrius Health, 1990-2006

20 Acute hepatitis B Strategy 2: current lab tests – ALT or AST > 5x normal AND – Positive hepatitis B surface antigen 47% (95% confidence interval, 41-53%) Positive Predictive Value PLoS ONE 2008:3:e2626 Atrius Health, 1990-2006

21 Acute hepatitis B Strategy 3: current & past lab tests & ICD9 codes – ALT or AST > 5x normal AND – Positive hepatitis B surface antigen AND – No prior positive hepatitis B surface AND – No ICD9 code for chronic hepatitis B ever AND – Total bilirubin >1.5 97% (95% confidence interval, 94-100%) Sensitivity 99%Specificity 94% Positive Predictive Value PLoS ONE 2008:3:e2626 Atrius Health, 1990-2006

22 Hepatitis B Case Finding - ESP versus ELR 601 distinct patients 8 acute 593 chronic cases 2648 positive test results for hepatitis B E S P E L R

23 Case Definition: Active Tuberculosis Prescription for pyrazinamide or Prescription of 2 or more anti-tuberculous medications plus ICD9 code for TB within 60 days or Order for (AFB smear or AFB culture) plus ICD9 code for TB within 60 days Public Health Reports 2010:125:843 Strategy : drug prescribing & lab test orders & ICD9 codes Atrius Health, 2006-9

24 ESPnet Conditions Currently Being Reporting Condition Total Cases Chlamydia16,200 Gonorrhea3,422 Pelvic inflammatory disease186 Acute hepatitis A22 Acute hepatitis B69 Acute hepatitis C114 Tuberculosis256 Syphilis406

25 INFECTIOUS DISEASE CASE REPORTING

26 Report to Health Department – HL7 format Patient demographics Responsible clinician, site, contact info Basis for condition being detected Treatment given Symptoms (ICD9 code & temperature) Pregnancy status (if pertinent)

27 ESPnet vs manual reporting MMWR 2008;57:372-375 PLoS ONE 2008;e2626 Public Health Reports 2010;125:843 Atrius Health (variable time periods) 25/0758/54595/628/338/1414/13

28 Pregnancy status: Chlamydia & Gonorrhea MMWR 2008;57:372-375 Atrius Health, June 2006 - July 2007 22/445649/6495/44586/649

29 Pregnancy status: Chlamydia & Gonorrhea MMWR 2008;57:372-375 Atrius Health, June 2006 - July 2007 22/445649/6495/44586/649

30 Treatment reports: Chlamydia & Gonorrhea MMWR 2008;57:372-375 Atrius Health, June 2006 - July 2007 524/607873/873

31 Patient name error: Chlamydia & Gonorrhea *EHR spelling presumed as gold standard. Includes transposition of first and last name, incorrect first name, and spelling errors MMWR 2008;57:372-375 Atrius Health, June 2006 - July 2007 34/607

32 SYNDROMIC SURVEILLANCE

33 Influenza-Like Illness Atrius Health, 2009-2013

34 CHRONIC DISEASE SURVEILLANCE

35 Criteria for Frank Diabetes Laboratory tests – Hemoglobin A1C ≥ 6.5 – Fasting glucose ≥126 – Random glucose ≥200 on two or more occasions Diagnoses – ICD9 code 250.x (DM) on two or more occasions Prescribing – Insulin outside of pregnancy – Any of these oral agents: Glyburide, gliclazide, glipizide, glimeprimide Pioglitazone, rosiglitazone Repaglinide, nateglinide, meglitinide Sitagliptin Exenatide, pramlintide Diabetes Care 2013; 36:914-21

36 Type 1 versus Type 2 Diabetes Among patients with frank diabetes, label as type 1 if any of these: – C-peptide negative – DM auto-antibodies positive – Prescription for urine acetone test strips – Ratio of type 1 : type 2 diabetes ICD9s > 0.5 and NOT on oral hypoglycemics – Ratio of type 1 : type 2 diabetes ICD9s > 0.5 and Rx for glucagon If not type 1 then type 2 Diabetes Care 2013; 36:914-21

37 Practice EHR’s D P H Health Department ESPnet: Scheduled reporting Notifiable diseases Influenza-like Illness Chronic diseases Notifiable diseases Influenza-like Illness Chronic diseases

38 SENDING QUERIES TO AN EHR

39 Practice EHR’s D P H Health Department ESPnet: ad hoc queries Ectopic pregnancy Blood pressure Infertility Asthma ALS Chlamydia screening rates

40 Practice #1 ESPnet server MA Dept Public Health User ESPnet Secure Network Portal 1 52 ESP tables Review & Run Query 3 Review & Return Results 4 6 ESP tables Review & Run Query 3 Review & Return Results 4 1- User creates and submits query (a computer program) 2- Data partners retrieve query 3- Data partners review and run query against their local data 4- Data partners review results 5- Data partners return results via secure network 6 Results are aggregated Practice #n ESPnet server

41 Development supported by CDC and ONC The RiskScape www.esphealth.org

42 Summarizing and sharing data: The RiskScape Web-based interface to display data from EHRs Helps users visualize and manipulate data Uses the strengths of the data – Electronic and analysis ready – Timely (updated daily) – Clinically rich – includes clinician-measured demographics, vitals (height, weight, blood pressure), lab tests, medications, vaccines, and outcomes

43 Select an Outcome: Example Type 2 Diabetes

44 Type 2 Diabetes in Eastern Massachusetts

45 Obesity (BMI >30)

46 High blood pressure

47 Stratify by age, sex, race, BMI, BP, etc. Type 2 diabetes under age 40 is most prevalent among those with BMI > 30 Type 2 diabetes under age 40 is most prevalent in Blacks.

48 Drill Down on ZIP Codes

49 Hypertension more prevalent for all races in Greater Boston vs Central Mass Compare locations Hypertension more prevalent for all ages in Greater Boston vs Central Mass

50 Evaluate whether patients meet clinical targets 57% of people with type 2 diabetes have high blood pressure 51% of people with type 2 diabetes have hemoglobin A1C above 6.5

51 In progress Vaccine adverse event detection and reporting to CDC VAERS Send messages to clinician’s inbox to elicit additional information – via link to secure external site Ability to insert reports in EHR

52 Data from EHR Practice EMR’s Eliciting clinician input and reporting in EHR diagnoses lab results meds vaccines allergies ESPnet Server 2 Request for info

53 Dear Dr. JONES Your patient BOB WIGGINS may have suffered an adverse effect from a recent vaccine. BOB WIGGINS was diagnosed with MENINGITIS on AUGUST 12, 7 days after receiving MEASLES VACCINE. If you think the MENINGITIS might have been due to the vaccine, we can automatically submit an electronic report to CDC / FDA’s Vaccine Adverse Event Reporting System on your behalf. Please provide any additional clinical details on this event that you think might be helpful to CDC and FDA vaccine safety investigators: SUBMITDECLINE Clinician inbox message

54 Data from EHR Practice EMR’s Eliciting clinician input and reporting in EHR diagnoses lab results meds vaccines allergies ESPnet Server HL7 electronic VAERS report 2 Request for info 3 Clinician response 4 Report to EHR

55 On the horizon Meaningful use stage 2 certification for ELR reporting Monitoring response to community-focused obesity prevention program

56 Just over the horizon Notification about overdue follow up (STD test of cure, gestational diabetes post-partum glucose tolerance test…) Meaningful use stage 3 certification Research support, e.g., comparative effectiveness, clinical trials

57 “No health department, State or local, can effectively prevent or control disease without knowledge of when, where, and under what conditions cases are occurring” Introductory statement printed each week in Public Health Reports, 1913-1951

58 Source code and documentation available free of charge from esphealth.org www.esphealth.org

59 ESPnet Team Harvard Dept of Population Medicine Michael Klompas Ross Lazarus Emma Eggleston Julie Lankiewicz Michael Murphy Meghan Baker Richard Platt Massachusetts Dept of Public Health Alfred DeMaria Gillian Haney Kathy Hsu Sita Smith Josh Vogel Paul Oppedisano Ohio Department of Health Lilith Tatham Massachusetts eHealth Institute Keely Benson Laurance Stuntz MetroHealth, OH David Kaelber Guptha Baskaran Atrius Health Ben Kruskal Mike Lee Cambridge Health Alliance Michelle Weiss Brian Herrick Jim LaPlante Northern Berkshires eHealth Collaborative Don LeBreux Massachusetts League of Community Health Centers Ellen Hafer Mark Josephson Commonwealth Informatics LincolnPeak Partners

60 Thank you!

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