Benefits of nationwide, interoperable electronic health records

Benefits of nationwide, interoperable electronic health records for doctors and patients Ilkka Kunnamo, MD The Finnish Medical Society Duodecim ilkka.kunnamo@duodecim.fi Data must be available at the point they are needed - if not, they are useless Data must be available at the point they are needed - if not, they are useless Relevant context should be included (time, place, action, other data) Electronic patient records in Finland: aims • Every health professional will have all patient data (recorded anywhere) accessible in electronic format (if authorized by patient) • Citizens have access to their own data via citizen-friendly user interface National standards in use by 2008 • Structured key data from all patient records available in HL7 CDA (Clinical Document Architecture) Release 2 format • Certification of EPR systems to follow national standards – Data exchange – Data security, autenthication, archiving • Extensive support for coding and knowledge – National Code server – Knowledge databases, including decision support – Data mining and benchmarking National health records archive • A national health records archive is planned – Every citizen will have one personal health record • Data stored in HL7 CDA R2 (XML) format • Accessible by all patient record systems and clinical applications (by strong authentication) – Several options for user interface • Access by patient’s on-site or prospective permission To code or not to code? • Coding has advantages if – the computer assists the clinician in data processing and decision-making • Coding is unnecessary if – only the clinician (and not the computer) interprets the data To code or not to code? • Coding has advantages if – the computer assists the clinician in data processing and decision-making • Coding is unnecessary if – only the clinician (and not the computer) interprets the data • Unstructured free text contains valuable information and supports the human side of medicine Structured (coded) information in the EPR (key data set) • Patient ID, name, address etc. • Diagnoses (list) • Medication (list) – Allergies and adverse drug reactions • Results of investigations – BP, lab, x-ray • Surgery, procedures, implants • Structured treatment plan – includes targets for treatment Uses of medical record information • • • • To manage my patients To audit and improve my service To support my research To feed another information system Wyatt JC, Sullivan F. What is health information? BMJ 2005;331:566-568 Uses of medical record information • To manage my patients – – – – Shared care by general practitioner and specialist Patient’s user interface Problem-specific views on the data Decision support • To audit and improve my service – Benchmarking – Virtual health check • To support my research – Multicentre studies • To feed another information system – Hospital and health centre systems – Disease-specific systems – Clinical databanks Smith John 12.10.2002 HbA1c Type 2 diabetes 9.4 020248-139Y 10/2003 08/2004 4-6 05/2003 3.0 140/90 Search Dg 7.5 55.1 y New i i i i i i R R R R R R Medication 25.03.2003 Insulin H Protaphan Metformin 500 mg Aspirin 100 mg Simvastatin 20 mg Enalapril 20 mg Amlodipine 5 mg 21.01.2003 Karstula 01.11.2002 KSKS 32 yks. ilt. 2x2 1x1 1x1 1x1 1x1 I. Kunnamo J. Saltevo High BP 12.10.2001 fB-Gluc 9.8 Rheumatoid arthritis 01.12.2001 LDL-chol 2.9 Osteoporosis 12.10.2002 BP 136/88 Visits 20.8.2004/I Kunnamo Yes Smoking Swelling in right knee for 2 weeks. Considerable hydrops. No other joints active. 25 ml of fluid was CV risk 14 % Data aspirated, and steroid injected. entry BP in home measurements 145 – 158/92-98. Not successful in reducing weight. Willing to start antihypertensive medication. Drug orders: The colour indicates national Enalapril (Renitec) 20 mg x 1 (new) Methyl prednisolone (Solomet) 40 mg i.a. treatment target (guideline) Certificate for drug remuneration 20.04.2003 Reminders Determine S-K and S-Creatinine (enalapril started 20.10.2002) Search Treatment of type 2 diabetes • Diagnosis and treatment of rheumatoid arthritis Lifestyle counseling in type 2 diabetes Insulin pathway for type 2 diabetes in C-Finland • Care treatment of type 2 diabetes Smoking cessation • Osteoporosis (patient information leaflet) Care pathway/type 2 diabetes, Central Finland Lab Diagnoses Care plan Forms Knowledge Smith John 12.10.2002 HbA1c Type 2 diabetes 9.4 020248-139Y 10/2003 08/2004 4-6 05/2003 7.5 55.1 y New i i i i i i R R R R R R Medication 25.03.2003 Insulin H Protaphan Metformin 500 mg Aspirin 100 mg Simvastatin 20 mg Enalapril 20 mg Amlodipin 5 mg 21.01.2003 Karstula 01.11.2002 KSKS 32 yks. ilt. 2x2 1x1 1x1 1x1 1x1 I. Kunnamo J. Saltevo High BP 12.10.2001 fB-Gluc 9.8 Rheumatoid arthritis 01.12.2001 LDL-chol 2.9 3.0 Repeat prescription Osteoporosis 12.10.2002 BP 136/88 140/90 Medication Dg Search started by another doctor Visits 20.8.2004/I Kunnamo Yes Smoking Swelling in right knee for 2 weeks. Considerable hydrops. No other joints active. 25 ml of fluid was CV risk 14 % Data aspirated, and steroid injected. entry BP in home measurements 145 – 158/92-98. Not successful in reducing weight. Willing to start antihypertensive medication. Drug orders: The colour indicates x 1 (new) Enalapril (Renitec) 20 mgnational Methyl prednisolone (Solomet) 40 mg i.a. treatment target (guideline) Certificate for drug remuneration 20.04.2003 Reminders Determine S-K and S-Creatinine (enalapril started 20.10.2002) Search Treatment of type 2 diabetes • Diagnosis and treatment of rheumatoid arthritis Lifestyle counseling in type 2 diabetes Insulin pathway for type 2 diabetes in C-Finland • Care treatment of type 2 diabetes Smoking cessation • Osteoporosis (patient information leaflet) Care pathway/type 2 diabetes, Central Finland Lab Diagnoses Care plan Forms Knowledge Medication 15.6.2005 Insulin H Protaphan Metformin 500 mg Aspirin 100 mg Simvastatin 20 mg Enalapril 20 mg Amlodipine 5 mg 32 U. 2x2 1x1 1x1 1x1 1x1 New i i i i i i R R R R R R Always visible view Detailed view Continuous medication 05.07.2003 Long-acting insulin 23.6.2001 Metformin 500 mg 12.11.2004 Aspirin 100 mg 20.06.2004 Simvastatin 20 mg 04.12.1999 Enalapril 20 mg 26.05.2005 Amlodipine 5 mg Insulin H Protaphan Diformin retard Disperin Simvastatin Ratiopharm Enalapril Generics Norvasc 32 U. 2x2 1x1 1x1 1x1 1x1 M. Valli/KSKS I. Kunnamo S. Miettinen I. Kunnamo I Kunnamo K.Virta/KSKS Type 2 diabetes Type 2 diabetes Antiplatelet drug Hyperlipidaemia Hypertension Hypertension i i i i i i R R R R R R Medication used during previous month 23.6.2001 Amoksisilliini 750 mg Amoxin 1x2 I. Kunnamo Acute maxillary sinusitis Medications withdrawn 21.02.1998 Hydroklorothiazide 25 mg Diurex mite 1x1 K.Virta/KSKS Hypertension + amiloridechloride 5 mg Withdrawn 15.3.1998. Cause: Rash I Kunnamo Medication 15.6.2005 Insulin H Protaphan Metformin 500 mg Aspirin 100 mg Simvastatin 20 mg Enalapril 20 mg Amlodipine 5 mg 32 U. 2x2 1x1 1x1 1x1 1x1 Uusi i i i i i i R R R R R R Always visible view Detailed view Continuous medication 05.07.2003 Long-acting insulin 23.6.2001 Metformin 500 mg 12.11.2004 Aspirin 100 mg 20.06.2004 Simvastatin 20 mg 04.12.1999 Enalapril 20 mg 26.05.2005 Amlodipine 5 mg Insulin H Protaphan Diformin retard Disperin Simvastatin Ratiopharm Enalapril Generics Norvasc 32 U. 2x2 1x1 1x1 1x1 1x1 M. Valli/KSKS I. Kunnamo S. Miettinen I. Kunnamo I Kunnamo K.Virta/KSKS Type 2 diabetes Type 2 diabetes Antiplatelet drug Hyperlipidaemia Hypertension Hypertension i i i i i i R R R R R R Medication used during previous month 23.6.2001 Amoksisilliini 750 mg Amoxin Actively approved by personal doctor 1x2 I. Kunnamo Acute maxillary sinusitis Medications withdrawn 21.02.1998 Hydroklorothiazide 25 mg Diurex mite 1x1 K.Virta/KSKS Hypertension + amiloridechloride 5 mg Withdrawn 15.3.1998. Cause: Rash I Kunnamo Patient’s user interface • Coded data is translated into lay language by means of a metathesaurus • The terms are linked to definitions and explanations, ”The Patient’s Handbook”, and local sources of patient information Diagnoses Lactose intolerance (poor absorption of ) What is lactose intolerance Diet advice Laboratory results Haemoglobin 124 Normal range What does Hb tell Cholesterol 5.9 Normal range LDL cholesterol 3.8 Normal range Lipid measurements (”evil cholesterol”) Cardiovascular risk (10 yrs) 3.2 % Miten vaikutan riskitekijöihini Hoitosuunnitelma Computer-generated letter Dear Mrs. Smith, The laboratory tests taken on June 1st were as follows: Haemoglobin was 134, which is excellent. The kidney test (creatinine 86) and the liver test (ALT 32) were normal. You can continue your medication. The next tests are due in October. The laboratory referral is attached. Faithfully yours, Dr. Jones Uses of medical record information • To manage my patients – – – – Shared care by general practitioner and specialist Patient’s user interface Problem-specific views on the data Decision support • To audit and improve my service – Benchmarking – Virtual health check • To support my research – Multicentre studies • To feed another information system – Hospital and health centre systems – Disease-specific systems – Clinical databanks Smith John 12.10.2002 HbA1c Type 2 diabetes 9.4 020248-139Y 10/2003 08/2004 4-6 05/2003 3.0 140/90 Search Dg 7.5 55.1 y New i i i i i i R R R R R R Medication 25.03.2003 Insulin H Protaphan Metformin 500 mg Aspirin 100 mg Simvastatin 20 mg Enalapril 20 mg Amlodipin 5 mg 21.01.2003 Karstula 01.11.2002 KSKS 32 yks. ilt. 2x2 1x1 1x1 1x1 1x1 I. Kunnamo J. Saltevo High BP 12.10.2001 fB-Gluc 9.8 Rheumatoid arthritis 01.12.2001 LDL-chol 2.9 Osteoporosis 12.10.2002 BP 136/88 Visits Smoking Select problemknee forYes Swelling in right 2 weeks. Considerable from list No other joints active. 25 ml of fluid was hydrops. Data aspirated, and steroid injected. entry BP in home measurements 145 – 158/92-98. Not successful in reducing weight. Willing to start antihypertensive medication. Drug orders: The colour indicates x 1 (new) Enalapril (Renitec) 20 mgnational Methyl prednisolone (Solomet) 40 mg i.a. treatment target (guideline) CV risk 14 % 20.8.2004/I Kunnamo Certificate for drug remuneration 20.04.2003 Reminders Determine S-K and S-Creatinine (enalapril started 20.10.2002) Search Treatment of type 2 diabetes • Diagnosis and treatment of rheumatoid arthritis Lifestyle counseling in type 2 diabetes Insulin pathway for type 2 diabetes in C-Finland • Care treatment of type 2 diabetes Smoking cessation • Osteoporosis (patient information leaflet) Care pathway/type 2 diabetes, Central Finland Lab Diagnoses Care plan Forms Knowledge Smith John 12.10.2002 HbA1c 9.4 020248-139Y 7.5 4-6 3.0 140/90 102 kg 95 kg 55.1 y DM II 5/1991 New i i i i i R R R R R Medication 25.03.2003 Insulin H Protaphan Metformin 500 mg Aspirin 100 mg Simvastatin 20 mg Enalapril 20 mg Amlodipin 5 mg 21.01.2003 Karstula 01.11.2002 KSKS 32 yks. ilt. 2x2 1x1 1x1 1x1 1x1 I. Kunnamo J. Saltevo 12.10.2001 fB-Gluc 9.8 01.12.2001 LDL-chol 2.9 12.10.2002 BP 21.01.2003 BMI 136/88 32.2 Formulary and prescriptions Visits 01.12.2001 Smoking Yes 01.12.2001 CV risk 14 % Red colour shows need for update or control Data entry Certificate for drug remuneration 20.04.2003 Reminders Determine S-K and S-Creatinine (enalapril started 20.10.2002) Search Treatment of type 2 diabetes Lifestyle counseling in type 2 diabetes Insulin treatment of type 2 diabetes Smoking cessation Care pathway/type 2 diabetes, Central Finland The colour indicates national treatment target (guideline) Problem list Individual treatment target Lab Diagnoses Care plan Forms Knowledge Indexing guidelines by diagnostic codes • EPR system that makes the link from ICPC code used by EPR in assessment of the patient’s problem • 946 topics in “EBM guidelines” indexed by ICPC: to which question is this guideline an answer? - Guidelines accessible by ICPC instead of search terms Indexing result Number of guidelines in Number of ICPC-2 search result codes used as main indexing terms 1 2 3 4-6 7-10 More than 10 188 83 40 35 12 14 Indexing result • 372 ICPC codes used as main indexing terms • 50% of ICPC codes retrieve only one guideline • 93% of the ICPC codes retrieve not more than 6 guidelines Guidelines in Finland in 2005 • EBM Guidelines (Primary care) • Current Care guidelines (national guideline programme) • Local guidelines – Linked to EBM Guidelines and national guidelines 1230 58 527 • Evidence summaries – Linked Cochrane reviews 4760 1100 • Pictures 1527 All guidelines are available in one search engine to 97 % of Finnish physicians as a part of Physician’s Database with 36000 documents Smith John 12.10.2002 HbA1c 9.4 020248-139Y 7.5 4-6 3.0 140/90 102 kg 95 kg 55.1 y DM II 5/1991 New i i i i i R R R R R Medication 25.03.2003 Insulin H Protaphan Metformin 500 mg Aspirin 100 mg Simvastatin 20 mg Enalapril 20 mg Amlodipin 5 mg 21.01.2003 Karstula 01.11.2002 KSKS 32 yks. ilt. 2x2 1x1 1x1 1x1 1x1 I. Kunnamo J. Saltevo 12.10.2001 fB-Gluc 9.8 01.12.2001 LDL-chol 2.9 12.10.2002 BP 21.01.2003 BMI 136/88 32.2 Visits 01.12.2001 Smoking Yes 01.12.2001 CV risk 14 % Certificate for drug remuneration 20.04.2003 Reminders Determine S-K and S-Creatinine (enalapril started 20.10.2002) Search National guidelines Treatment of type 2 diabetes Lifestyle counseling in type 2 diabetes Insulin treatment of type 2 diabetes Smoking cessation Care pathway/type 2 diabetes, Central Finland Local guidelines Lab Diagnoses Care plan Forms Knowledge Decision support database: script descriptions Example 2: Recommending metformin for obese patients with type 2 diabetes • Input – – – – Diagnoses Latest laboratory test results List of drugs (present and discontinued) Body weight and height (for calculation of body mass index) • Output – – – – – If the patient has type 2 diabetes and If BMI > 23 and If HbA1c > 7 % and If he/she is not on metformin and If metformin has not been discontinued because of adverse effects, => a prescription of metformin is recommended. Triggers / events firing off calls to the decision support engine • • • • • Calling up a patient on screen Entering a new drug for a drug prescription Picking / entering a diagnosis Ordering further examinations & tests Launching decision support manually by a clinician • Batch run for a group of selected patients (virtual health check) Systematic review on the effectiveness of clinical decision support systems • 100 controlled trials • In 64 % of the trials performance of clinicians improved by 50 % or more – Suggestions for diagnosis 40 % – Preventive interventions (reminders) 76 % – Suggestions for medication & doses 66 % Garg AX et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes. JAMA 2005;293:1223-1238 Factors and elements predicting the success of a clinical DS system • Automatic provision of reminders as part of clinician workflow • Providing clear recommendations as opposed to providing only assessment about the situation / patient’s condition • Providing decision support at the time and location of decision making • Using a computer to generate decision support • Of systems possessing all 4 features, 30 out of 32 (94%) improved the quality of patient care Kawamoto K ym. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ 2005;330:765-768 What does a decision support system do? • Displays guidelines at the right moment • Displays reminders to clinicians (prevents forgettings) • Warns about drug interactions, drug allergies, adverse effects • Calculates patient risks (UKPDS, SCORE) • Lists possible diagnoses based on patient’s data and checks criteria for diagnoses • Suggests additional examinations, validates indications for treatment • Could pre-fill screens or forms automatically Uses of medical record information • To manage my patients – – – – Shared care by general practitioner and specialist Patient’s user interface Problem-specific views on the data Decision support • To audit and improve my service – Benchmarking – Virtual health check • To support my research – Multicentre studies • To feed another information system – Hospital and health centre systems – Disease-specific systems – Clinical databanks Quality assessment and audit • Key data retrieved anonymously from a representative sample of all records (or even all records) – for assessing whether quality targets have been met – for comparison between units (benchmarking) – for identifying factors that explain quality Type 2 diabetes at Karstula Primary Care Practice HbA1c < 6 % HbA1c < 7 % Aspirin in use Visit during previous year 18 % 61 % 82 % 71 % ”Virtual health check” • Based on guidelines-driven clinical decision support scripts • Utilises all patient data needed for clinical decision support • Virtual health check executed on a selected population or region; produces a status report of the condition of the selected target population • Could file suggestions on individual patients´ treatment plans Structured treatment plan • Key element for coordinated care • Updated for all patients at every encounter • Reminders produced by the decision support system can be stored as suggestions in the treatment plan – ”Virtual health check” • List of banned scripts/reminders is a part of the treatment plan Problems and solutions • Decision support formalism is difficult for clinicians – Let clinicians describe decision support functions in plain English • Decision support functions are modelled in languages that require special training – Use general programming language (e.g. JavaScript or Java -> platform independent + availability of programmers + local tailoring possible) • Clinicians’ input for the development of decision support systems is minimal – Use a comprehensive set of guidelines (EBM Guidelines with evidence summaries) as a starting point Uses of medical record information • To manage my patients – – – – Shared care by general practitioner and specialist Patient’s user interface Problem-specific views on the data Decision support • To audit and improve my service – Benchmarking – Virtual health check • To support my research – Multicentre studies • To feed another information system – Hospital and health centre systems – Disease-specific systems – Clinical databanks APR-tallennustyökalu A national web tool for recording data for clinical research Multicentre studies in primary health care - Web-based data recording form is activated if patient meets inclusion criteria - Informed consent form is printed for the patient - Part of the data are transferred automatically from the records - An interactive form facilitates data entry - Data are stored in a web server for analysis Surveillance of drug safety • The patient’s list of medications contains history of drug withdrawal because of adverse effects • Cause of withdrawal is coded by controlled vocabulary – The MedDRA vocabulary is used by all major drug regulation authorities • A database of all drug withdrawals is collected from all patient records • Types, frequency and clustering of causes of withdrawal are analyzed Uses of medical record information • To manage my patients – – – – Shared care by general practitioner and specialist Patient’s user interface Problem-specific views on the data Decision support • To audit and improve my service – Benchmarking – Virtual health check • To support my research – Multicentre studies • To feed another information system – Hospital and health centre systems – Disease-specific systems – Clinical databanks The next step: Prognosis and benefit from treatment is estimated by methods resembling weather forecasting: a large history database of previous patients is searched for a group of matched cases whose prognosis is known. Selection of treatment in the future KNOWLEDGE Patient data Probably Decision Guidelines Genome map beneficial support Graded evidence therapy Databases: drugs, laboratory, genome Patient’s values Images and videos for Doctor’s and choices training skills interpretation Ethical summaries and experience Patient information Simulation Individualized prediction of the effects of treatment Selection of treatment Database of ”all” previous patients