The use of patient data for research purposes.

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A lecture for the MSc in Health Informatics at the UCL Centre for Health Informatics & Multiprofessional Education (CHIME).

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The use of patient data for research purposes.

  1. 1. The secondary use of patient data forresearch. Dr. Spiros Denaxas Clinical Epidemiology Epidemiology and Public Health UCL Medical School s.denaxas@ucl.ac.uk
  2. 2. Structure Epidemiological studies Patient data enhancing existing epidemiological studies Patient data for performing in vitro epidemiological studies The future of large-scale epidemiological studies
  3. 3. Learning outcomes Epidemiology defined Timeline of cohort studies Challenges using clinical data for research EHR linking Value of linking different data repositories
  4. 4. Clinical epidemiology“The application of epidemiological knowledge, reasoning, and methods to study clinicalissues and improve clinical care. Research often addresses aetiological, diagnostic,therapeutic, and prognostic medical issues, is conducted in clinical settings led byclinicians and had patients as the subjects of the study.” J. M. Last, A Dictionary of Epidemiology
  5. 5. Coronary Heart Disease (CHD) Coronary Heart Disease (CHD) is the leading cause of death in the UK  ~180.000 CHD deaths in the UK p.a. Collective term for diseases which occur due to atheroma building up in artery walls. Prevalence: ~2.7M Risk factors: smoking, diabetes, obesity, diet, physical activity, SES, mental health
  6. 6. Stable angina Early manifestation: angina (chest pain) Symptoms: chest pain, feeling of heartburn, palpitations, shortness of breath Triggered by: − Exercise − Cold weather − Stress
  7. 7. Myocardial Infarction (MI) Myocardial Infarction: Necrosis of the myocardial tissue due to ischaemia due to a thrombus Symptoms: gripping chest pain, dizziness, overwhelming anxiety, shortness of breath ~124.000 MI’s in the UK per year (BHF, Statistics 2010)
  8. 8. (BHF, Statistics 2010)
  9. 9. Wisdom “It is only by collecting data and using them that you get sense” William Osler, Aequanimitas, 1928
  10. 10. Timeline of disease
  11. 11. Start with a healthy population
  12. 12. Some people drop out
  13. 13. Wait
  14. 14. Some people get diagnosed
  15. 15. Some people get events (and some die)
  16. 16. Gathering as much as possible Medical screening clinics − Anthropomorphic measurements − Blood / urine samples − Other measurements Repeat questionnaires − Life style − SES − Activity
  17. 17. Smoking
  18. 18. Only one problem "The problem with quotes on the Internet is that it is hard to verify their authenticity" - Abraham Lincoln
  19. 19. Self-reporting data People forget − or chose to forget Temporality Subjective by definition Different people -> different thresholds Ascertainment
  20. 20. Periodontal disease Seven cohorts, multiple papers Relative risk 1.24 (95% CI 1.01-1.51) to 1.34 (95% CI 1.10 – 1.63) Humphrey LL, Fu R, Buckley DI, Freeman M, Helfand M. Periodontal disease and coronary heart disease incidence: a systematic review and meta-analysis. J Gen Intern Med. 2008.
  21. 21. Primary care data First line of care in the UK: the GP Centered around consultations Diagnostic information, prescriptions, referrals, additional measurements Information is recorded using a standard clinical terminology system (Read)
  22. 22. Sample primary care data
  23. 23. Advantages Majority of people registered with GP Data collected at large scale Data recorded at regular intervals Greater data granularity High data completeness on comorbidities Introduction of QoF
  24. 24. Problems: conflicting information
  25. 25. Problems Lack of streamlined approach to obtain data  How? Conflicts Measurement error (BP,HR) Information error (aspirin)
  26. 26. Pathway of disease
  27. 27. Secondary care data Hospital Episode Statistics (HES) Data warehouse of all admissions to NHS hospitals Information is recorded using the International Classification of Diseases ontology 10th revision (ICD10)
  28. 28. Sample secondary care data
  29. 29. Secondary care data: advantages Extremely high data completeness Complete picture of admissions and re- admissions to secondary care Provide information where not possible to collect (admission for severe depression episode)
  30. 30. Secondary care data: disadvantages Data collected for administrative purposes Coding of individual entries is not done exclusively by doctors Coding standards change over time − ICD9 to ICD10 − ICD10-CM − SNOMED-CT
  31. 31. Pathway of disease
  32. 32. Registries “The collection of information for its own sake is of doubtful value unless it is acted upon. Community registers should not become the equivalent of village war memorials.” Hugh Tunstall Pedoe 1978
  33. 33. Myocardial Ischaemia National Audit Project(MINAP) Established in 2000 All hospitals in England and Wales submit data ~600.000 records ~120 fields on medical history, medication, admission and discharge Initially setup for auditing purposes
  34. 34. Myocardial Ischaemia National Audit Project(MINAP): advantages Coronary phenotype information not available elsewhere  ST elevation MI (STEMI)  Non ST elevation MI (nSTEMI) Added flexibility (markers, ECG etc)
  35. 35. Myocardial Ischaemia National Audit Project(MINAP): disadvantages Data collected and recorded on a voluntary basis Less severe cases (nSTEMI) are not always submitted due to lack of resources (MINAP Public Report 2011) On its own, provides little information on pre-event pathway
  36. 36. Registries International (Sweden RIKS-HIA) In registry randomization Harmonization between types
  37. 37. Pathway of disease
  38. 38. Office for National Statistics (ONS) MortalityData Medical Research Information Service (MRIS) Current status service − Date and place of death − Causes of death (underlying and primary) − Occupation Cause of death certified by medical practitioner
  39. 39. Office for National Statistics (ONS) MortalityData
  40. 40. Mortality data: advantages Enable (cheap) long term follow up and establish cause of death. Provide information where not ethical to collect (cause of death inquiry from spouse)
  41. 41. Pathway of disease
  42. 42. Rare disease? CHD  Prevalence of 2.7M (BHF) Creutzfeldt–Jakob disease (CJD)  1 case per million per year (CDC) Other?
  43. 43. Novel electronic health record linkages:CALIBER Cardiovascular disease research using linking bespoke studies and electronic health records. Bring everything together by linking multiple sources
  44. 44. CALIBER
  45. 45. CALIBER - validation Two distinct steps Identify patients  Demographics and timing Identify events  Timing and consistency  Severity
  46. 46. Problems with EHR linking - governance Multiple stakeholders Different methods of access  Primary care Attitude towards linking
  47. 47. Problems with EHR linking - data Unequal granularity between sources  Coding Timing issues  Resurrections Conflicting information Shifting patterns
  48. 48. Not just for CHD Bespoke cohorts can be enhanced through linking − Ascertainment − Validation Similar approaches work for other diseases − Cancer registries − HIV registries − Infection / HPA
  49. 49. So much more…! Plethora of information enclosed within hospital EPR systems − ECG data − Imaging, sound − Routine blood results − A&E records − Ambulance records
  50. 50. So much more…! Plethora of information contained in disparate information systems − Pension records − Criminal records − National Treatment Agency − Port Health Screening datasets
  51. 51. Conclusions Routinely collected data facilitates research which might have previously been impossible to perform Data is not perfect, must be treated with caution The future is in linking multiple disparate sources … and amalgamating different disciplines together
  52. 52. Thank you.

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