1. Medical informatics Linking diseases, drugs, and adverse reactions Lars Juhl Jensen

2. structured data

3. Jensen et al., Nature Reviews Genetics, 2012

4. unstructured data

6. central registries

7. hospital EHR systems

9. opt-out

10. opt-in

11. registry data

12. civil registration system

13. established in 1968

14. CPR number

15. Jensen et al., Nature Reviews Genetics, 2012

16. national discharge registry

17. 14 years

18. 6.2 million patients

19. 45 million admissions

20. 68 million records

21. 119 million diagnosis

22. ICD-10

23. Jensen et al., Nature Reviews Genetics, 2012

24. not research

25. reimbursement

26. diagnosis trajectories

27. comorbidity

28. contingency table

29. Jensen et al., Nature Reviews Genetics, 2012

30. confounding factors

31. “known knowns”

32. gender

33. age

34. type of hospital encounter

35. Jensen et al., Nature Communications, 2014

36. “known unknowns”

37. smoking

38. diet

39. “unknown unknowns”

40. reporting biases

41. matched controls

42. proxy diagnoses

43. temporal correlations

44. diagnosis trajectories

45. Jensen et al., Nature Communications, 2014

46. trajectory networks

47. Jensen et al., Nature Communications, 2014

48. key diagnoses

49. Jensen et al., Nature Communications, 2014

50. direct medical implications

51. clinical text

52. unstructured data

54. free text

55. Danish

56. complex terminology

57. busy doctors

58. abbreviations

59. misspellings

60. a lot of it

61. computer

62. as smart as a dog

63. teach it specific tricks

66. named entity recognition

67. comprehensive dictionary

68. diseases

69. drugs

70. adverse drug reactions

71. synonyms

72. orthographic variation

73. flexible matching

74. hyphens and spaces

75. expansion rules

76. spelling variants

77. Clozapine

78. clozapin clossapin klozapin e chlosapi n chlosapin e chlozapin chlozapin e klossapi n closapin e klozapi n klosapin

79. “black list”

80. pest eller kolera

81. pharmacovigilance

82. clinical trials

83. spontaneous reports

85. underreporting

86. text/data mining

87. medication

88. Jensen et al., Nature Reviews Genetics, 2012

89. adverse events

91. hand-crafted rules

92. Eriksson et al., Drug Safety, 2014

96. recall known ADRs

97. estimate ADR frequencies

98. Eriksson et al., Drug Safety, 2014

99. discover new ADRs

100. Drug substanceADEp-value ChlordiazepoxideNystagmus4.0e-8 SimvastatinPersonality changes8.4e-8 DipyridamoleVisual impairment4.4e-4 CitalopramPsychosis8.8e-4 BendroflumethiazideApoplexy8.5e-3 Eriksson et al., Drug Safety, 2014

101. Acknowledgments Disease trajectories Anders Bøck Jensen Tudor Oprea Pope Moseley Søren Brunak Adverse drug reactions Robert Eriksson Thomas Werge Søren Brunak EHR text mining Peter Bjødstrup Jensen Robert Eriksson Henriette Schmock Francisco S. Roque Anders Juul Marlene Dalgaard Massimo Andreatta Sune Frankild Eva Roitmann Thomas Hansen Karen Søeby Søren Bredkjær Thomas Werge Søren Brunak