System, method, and apparatus for storing, retrieving, and integrating clinical, diagnostic, genomic, and therapeutic data

• US 20030046114A1
• Filed: 10/23/2001
• Published: 03/06/2003
• Est. Priority Date: 08/28/2001
• Status: Active Grant

• Current Assignee: MD Datacor Incorporated
• Original Assignee: MD Datacor Incorporated
• Inventors: Davies, Richard J., Batye, Rick
• Granted Patent: US 7,529,685 B2
• Time in Patent Office: Days
• US Class Current: 705/3
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access

Abstract

A method, system, and computer program product for storing and retrieving patient data in a database connected to a network is disclosed. The method, system, and computer program product comprises storing clinical data in the database, extracting data from the clinical data, querying the database using a taxonomy that includes inclusive or exclusive search criterion, and receiving a result set. The method, system, and computer program product comprises creating a taxonomy that includes at least one search criterion, sending a query to the database, the query including said at least one search criteria, receiving the result set in response to the query, the result set including at least one result record, and displaying said at least one result record. The method, system, and computer program product can further include a user such as a clinical researcher, a treating physician, or a consulting physician analyzing the result set.

Claims

1. A method of retrieving a result set from a database that includes data, comprising:

creating a taxonomy that includes at least one search rule comprising at least one search characteristic, said at least one search rule including an exclusion rule to define at least one exclusion search characteristic, wherein running the exclusion rule against the database generates at least one exclusion result record, each exclusion result record excluding said at least one exclusion search characteristic;

querying the database, the query including said at least one search rule;

receiving the result set in response to the query, the result set including at least one result record; and

displaying said at least one result record.

2. The method of claim 1, wherein the data is diagnostic data.

3. The method of claim 1, wherein the data includes past diagnosis and treatment data, medical history data, biochemical data, physiologic data, proteonomic data, family history data, dietary data, exercise data, demographic data, or drug response history data.

4. The method of claim 3, wherein the data further includes genotype data or haplotype data.

5. The method of claim 4, wherein the genotype data or the haplotype data includes a chromosome structure, a DNA sequence, a length of a specific gene or region, a gene expression, or at least one single nucleotide polymorphism (SNP).

6. The method of claim 1, wherein the data is related to a genetic-based disease.

7. The method of claim 6, wherein the genetic-based disease includes oncology data, urology data, cardiology data, gastroenterology data, orthopedic data, immunology data, rheumatology data, neurology data, pulmonology data, internal medicine data, family practice medicine data, and demographic data.

8. The method of claim 1, wherein the database is a data warehouse.

9. The method of claim 1, wherein the creating of the taxonomy further comprises:

storing the taxonomy; and

validating the taxonomy.

10. The method of claim 9, wherein said at least one search rule further includes an inclusion search rule to define at least one inclusion search characteristic, and wherein running the inclusion rule against the database generates at least one inclusion result record, each inclusion result record including said at least one inclusion search characteristic.

11. The method of claim 9, wherein said at least one search characteristic includes an illness, a drug prescription, a medical coverage plan, family history data, demographic data for the patient, a specialty for a physician, or a clinical diagnosis phrase.

12. The method of claim 11, wherein the demographic data for the patient includes a geographic location, a gender, or an age.

13. The method of claim 11, wherein the clinical diagnosis phrase includes a myocardial infarction, an LDL, a heart attack, or a bundle branch block.

14. The method of claim 9, wherein the storing of the taxonomy further comprises:

storing the taxonomy in the database.

15. The method of claim 9, wherein the validating of the taxonomy further comprises:

running the taxonomy against the database;

receiving the result set; and

displaying the result set.

16. The method of claim 15, wherein the running of the taxonomy further comprises:

notifying the database to run the taxonomy.

17. The method of claim 15, wherein the receiving of the result set further comprises:

receiving an inclusion result set, wherein said at least one search rule includes an inclusion rule and running the inclusion rule against the database generates the inclusion result set, each record in the inclusion result set including at least one inclusion search characteristic.

18. The method of claim 15, wherein the receiving of the result set further comprises:

receiving an exclusion result set, wherein said at least one search rule includes an exclusion rule and running the exclusion rule against the database generates the exclusion result set, each record in the exclusion result set including at least one exclusion search characteristic.

19. The method of claim 15, wherein the receiving of the result set further comprises:

receiving an inclusion result set, wherein said at least one search rule includes an inclusion rule and running the inclusion rule against the database generates the inclusion result set, each record in the inclusion result set including at least one inclusion search characteristic; and

receiving an exclusion result set, wherein said at least one search rule includes an exclusion rule and running the exclusion rule against the database generates the exclusion result set, each record in the exclusion result set including at least one exclusion search characteristic;

wherein each record in the exclusion result set is flagged.

20. The method of claim 15, further comprising:

analyzing the result set; and

updating the taxonomy based on the analyzing of the result set.

21. The method of claim 20, wherein the updating of the taxonomy further comprises:

unflagging an excluded record.

22. The method of claim 20, wherein the updating of the taxonomy further comprises:

flagging an included record.

23. The method of claim 1, further comprising:

analyzing the result set.

24. The method of claim 23, wherein a user analyzes the result set.

25. The method of claim 24, wherein the user includes a clinical researcher, a treating physician, or a consulting physician.

26. The method of claim 23, wherein the analyzing of the result set determines a disease risk or susceptibility type for at least one patient.

27. The method of claim 26, wherein genetic testing of said at least one patient can detect the disease.

28. The method of claim 27, wherein the genetic testing includes germ-line testing.

29. The method of claim 27, wherein the genetic testing identifies at least one modifier gene.

30. The method of claim 26, wherein somatic testing of a sample can detect the disease.

31. The method of claim 30, wherein the somatic testing yields prognostic information about the disease or a propensity for the disease.

32. The method of claim 30, wherein the sample is a tissue sample.

33. The method of claim 30, wherein the sample is a tumor sample.

34. The method of claim 26, wherein somatic testing of a sample can predict a drug response.

35. The method of claim 26, wherein proteonomic testing of said at least one patient can detect the disease.

36. The method of claim 35, wherein the proteonomic testing yields prognostic information about the disease or a propensity for the disease.

37. The method of claim 26, wherein the disease is cancer.

38. The method of claim 23, wherein the analyzing of the result set identifies at least one patient including a characteristic.

39. The method of claim 38, wherein the characteristic is a drug reaction polymorphism.

40. The method of claim 39, wherein the drug reaction polymorphism is a hypertension drug response polymorphism.

41. The method of claim 38, wherein the characteristic is necessary for said at least one patient to be eligible for a clinical trial.

42. The method of claim 23, wherein the analyzing of the result set generates a treatment suggestion for at least one patient.

43. The method of claim 23, wherein the result set identifies at least one clinical trial for which said at least one patient is eligible.

44. The method of claim 23, wherein the analyzing of the result set models a virtual clinical trial protocol.

45. The method of claim 23, wherein the analyzing of the result set generates market research data or market services data.

46. A system for retrieving a result set from a database that includes data, comprising:

a memory device; and

a processor disposed in communication with the memory device, the processor configured to;

create a taxonomy that includes at least one search rule comprising at least one search characteristic, said at least one search rule including an exclusion rule to define at least one exclusion search characteristic, wherein running the exclusion rule against the database generates at least one exclusion result record, each exclusion result record excluding said at least one exclusion search characteristic;

querying the database, the query including said at least one search rule;

receive the result set in response to the query, the result set including at least one result record; and

display said at least one result record.

47. The system of claim 46, wherein the data is diagnostic data.

48. The system of claim 46, wherein the data includes past diagnosis and treatment data, medical history data, biochemical data, physiologic data, proteonomic data, family history data, dietary data, exercise data, demographic data, or drug response history data.

49. The system of claim 48, wherein the data further includes genotype data or haplotype data.

50. The system of claim 49, wherein the genotype data or the haplotype data includes a chromosome structure, a DNA sequence, a length of a specific gene or region, a gene expression, or at least one single nucleotide polymorphism (SNP).

51. The system of claim 46, wherein the data is related to a genetic-based disease.

52. The system of claim 51, wherein the genetic-based disease includes oncology data, urology data, cardiology data, gastroenterology data, orthopedic data, immunology data, rheumatology data, neurology data, pulmonology data, internal medicine data, family practice medicine data, and demographic data.

53. The system of claim 46, wherein the database is a data warehouse.

54. The system of claim 46, wherein to create the taxonomy, the processor is further configured to:

store the taxonomy; and

validate the taxonomy.

55. The system of claim 54, wherein said at least one search rule further includes an inclusion search rule to define at least one inclusion search characteristic, and wherein running the inclusion rule against the database generates at least one inclusion result record, each inclusion result record including said at least one inclusion search characteristic.

56. The system of claim 54, wherein said at least one search characteristic includes an illness, a drug prescription, a medical coverage plan, family history data, demographic data for the patient, a specialty for a physician, or a clinical diagnosis phrase.

57. The system of claim 56, wherein the demographic data for the patient includes a geographic location, a gender, or an age.

58. The system of claim 56, wherein the clinical diagnosis phrase includes a myocardial infarction, an LDL, a heart attack, or a bundle branch block.

59. The system of claim 54, wherein to store the taxonomy, the processor is further configured to:

store the taxonomy in the database.

60. The system of claim 54, wherein to validate the taxonomy, the processor is further configured to:

run the taxonomy against the database;

receive the result set; and

display the result set.

61. The system of claim 60, wherein to run the taxonomy, the processor is further configured to:

notify the database to run the taxonomy.

62. The system of claim 60, wherein to receive the result set, the processor is further configured to:

receive an inclusion result set, wherein said at least one search rule includes an inclusion rule and running the inclusion rule against the database generates the inclusion result set, each record in the inclusion result set including at least one inclusion search characteristic.

63. The system of claim 60, wherein to receive the result set, the processor is further configured to:

receive an exclusion result set, wherein said at least one search rule includes an exclusion rule and running the exclusion rule against the database generates the exclusion result set, each record in the exclusion result set inluding at least one exclusion search characteristic.

64. The system of claim 60, wherein to receive the result set, the processor is further configured to:

receive an inclusion result set, wherein said at least one search rule includes an inclusion rule and running the inclusion rule against the database generates the inclusion result set, each record in the inclusion result set including at least one inclusion search characteristic; and

receive an exclusion result set, wherein said at least one search rule includes an exclusion rule and running the exclusion rule against the database generates the exclusion result set, each record in the exclusion result set including at least one exclusion search characteristic;

wherein each record in the exclusion result set is flagged.

65. The system of claim 60, wherein the processor is further configured to:

analyze the result set; and

update the taxonomy based on the analyzing of the result set.

66. The system of claim 65, wherein to update the taxonomy, the processor is further configured to:

unflag an excluded record.

67. The system of claim 65, wherein to update the taxonomy, the processor is further configured to:

flag an included record.

68. The system of claim 46, wherein the processor is further configured to:

analyze the result set.

69. The system of claim 68, wherein a user analyzes the result set.

70. The system of claim 69, wherein the user includes a clinical researcher, a treating physician, or a consulting physician.

71. The system of claim 68, wherein the analyzing of the result set determines a disease risk or susceptibility type for at least one patient.

72. The system of claim 71, wherein genetic testing of said at least one patient can detect the disease.

73. The system of claim 72, wherein the genetic testing includes germ-line testing.

74. The system of claim 72, wherein the genetic testing identifies at least one modifier gene.

75. The system of claim 71, wherein somatic testing of a sample can detect the disease.

76. The system of claim 75, wherein the somatic testing yields prognostic information about the disease or a propensity for the disease.

77. The system of claim 75, wherein the sample is a tissue sample.

78. The system of claim 75, wherein the sample is a tumor sample.

79. The system of claim 71, wherein somatic testing of a sample can predict a drug response.

80. The system of claim 71, wherein proteonomic testing of said at least one patient can detect the disease.

81. The system of claim 80, wherein the proteonomic testing yields prognostic information about the disease or a propensity for the disease.

82. The system of claim 71, wherein the disease is cancer.

83. The system of claim 68, wherein the analyzing of the result set identifies at least one patient including a characteristic.

84. The system of claim 83, wherein the characteristic is a drug reaction polymorphism.

85. The system of claim 84, wherein the drug reaction polymorphism is a hypertension drug response polymorphism.

86. The system of claim 83, wherein the characteristic is necessary for said at least one patient to be eligible for a clinical trial.

87. The system of claim 68, wherein the analyzing of the result set generates a treatment suggestion for at least one patient.

88. The system of claim 68, wherein the result set identifies at least one clinical trial for which said at least one patient is eligible.

89. The system of claim 68, wherein the analyzing of the result set models a virtual clinical trial protocol.

90. The system of claim 68, wherein the analyzing of the result set generates market research data or market services data.

91. A computer program product for retrieving a result set from a database that includes data, comprising:

a computer readable medium;

program code in said computer readable medium for creating a taxonomy that includes at least one search rule comprising at least one search characteristic, said at least one search rule including an exclusion rule to define at least one exclusion search characteristic, wherein running the exclusion rule against the database generates at least one exclusion result record, each exclusion result record excluding said at least one exclusion search characteristic;

program code in said computer readable medium for sending a query to the database, the query including said at least one search rule;

program code in said computer readable medium for receiving the result set in response to the query, the result set including at least one result record; and

program code in said computer readable medium for displaying said at least one result record.

92. The computer program product of claim 91, wherein the data is diagnostic data.

93. The computer program product of claim 91, wherein the data includes past diagnosis and treatment data, medical history data, biochemical data, physiologic data, proteonomic data, family history data, dietary data, exercise data, demographic data, or drug response history data.

94. The computer program product of claim 93, wherein the data further includes genotype data or haplotype data.

95. The computer program product of claim 94, wherein the genotype data or the haplotype data includes a chromosome structure, a DNA sequence, a length of a specific gene or region, a gene expression, or at least one single nucleotide polymorphism (SNP).

96. The computer program product of claim 91, wherein the data is related to a genetic-based disease.

97. The computer program product of claim 96, wherein the genetic-based disease includes oncology data, urology data, cardiology data, gastroenterology data, orthopedic data, immunology data, rheumatology data, neurology data, pulmonology data, internal medicine data, family practice medicine data, and demographic data.

98. The computer program product of claim 91, wherein the database is a data warehouse.

99. The computer program product of claim 91, wherein the program code in said computer readable medium for the creating of the taxonomy further comprises:

program code in said computer readable medium for storing the taxonomy; and

program code in said computer readable medium for validating the taxonomy.

100. The computer program product of claim 99, wherein said at least one search rule further includes an inclusion search rule to define at least one inclusion search characteristic, and wherein running the inclusion rule against the database generates at least one inclusion result record, each inclusion result record including said at least one inclusion search characteristic.

101. The computer program product of claim 99, wherein said at least one search characteristic includes an illness, a drug prescription, a medical coverage plan, family history data, demographic data for the patient, a specialty for a physician, or a clinical diagnosis phrase.

102. The computer program product of claim 101, wherein the demographic data for the patient includes a geographic location, a gender, or an age.

103. The computer program product of claim 101, wherein the clinical diagnosis phrase includes a myocardial infarction, an LDL, a heart attack, or a bundle branch block.

104. The computer program product of claim 99, wherein the program code in said computer readable medium for the storing of the taxonomy further comprises:

storing the taxonomy in the database.

105. The computer program product of claim 99, wherein the program code in said computer readable medium for the validating of the taxonomy further comprises:

program code in said computer readable medium for running the taxonomy against the database;

program code in said computer readable medium for receiving the result set; and

program code in said computer readable medium for displaying the result set.

106. The computer program product of claim 105, wherein the program code in said computer readable medium for the running of the taxonomy further comprises:

program code in said computer readable medium for notifying the database to run the taxonomy.

107. The computer program product of claim 105, wherein the program code in said computer readable medium for the receiving of the result set further comprises:

program code in said computer readable medium for receiving an inclusion result set, wherein said at least one search rule includes an inclusion rule and running the inclusion rule against the database generates the inclusion result set, each record in the inclusion result set including at least one inclusion search characteristic.

108. The computer program product of claim 105, wherein the program code in said computer readable medium for the receiving of the result set further comprises:

program code in said computer readable medium for receiving an exclusion result set, wherein said at least one search rule includes an exclusion rule and running the exclusion rule against the database generates the exclusion result set, each record in the exclusion result set including at least one exclusion search characteristic.

109. The computer program product of claim 105, wherein the program code in said computer readable medium for the receiving of the result set further comprises:

program code in said computer readable medium for receiving an inclusion result set, wherein said at least one search rule includes an inclusion rule and running the inclusion rule against the database generates the inclusion result set, each record in the inclusion result set including at least one inclusion search characteristic; and

program code in said computer readable medium for receiving an exclusion result set, wherein said at least one search rule includes an exclusion rule and running the exclusion rule against the database generates the exclusion result set, each record in the exclusion result set including at least one exclusion search characteristic;

wherein each record in the exclusion result set is flagged.

110. The computer program product of claim 105, further comprising:

program code in said computer readable medium for analyzing the result set; and

program code in said computer readable medium for updating the taxonomy based on the analyzing of the result set.

111. The computer program product of claim 110, wherein the program code in said computer readable medium for the updating of the taxonomy further comprises:

program code in said computer readable medium for unflagging an excluded record.

112. The computer program product of claim 110, wherein the program code in said computer readable medium for the updating of the taxonomy further comprises:

program code in said computer readable medium for flagging an included record.

113. The computer program product of claim 91, further comprising:

program code in said computer readable medium for analyzing the result set.

114. The computer program product of claim 113, wherein a user analyzes the result set.

115. The computer program product of claim 114, wherein the user includes a clinical researcher, a treating physician, or a consulting physician.

116. The computer program product of claim 113, wherein the analyzing of the result set determines a disease risk or susceptibility type for at least one patient.

117. The computer program product of claim 116, wherein genetic testing of said at least one patient can detect the disease.

118. The computer program product of claim 117, wherein the genetic testing includes germ-line testing.

119. The computer program product of claim 117, wherein the genetic testing identifies at least one modifier gene.

120. The computer program product of claim 116, wherein somatic testing of a sample can detect the disease.

121. The computer program product of claim 120, wherein the somatic testing yields prognostic information about the disease or a propensity for the disease.

122. The computer program product of claim 120, wherein the sample is a tissue sample.

123. The computer program product of claim 120, wherein the sample is a tumor sample.

124. The computer program product of claim 116, wherein somatic testing of a sample can predict a drug response.

125. The computer program product of claim 116, wherein proteonomic testing of said at least one patient can detect the disease.

126. The computer program product of claim 125, wherein the proteonomic testing yields prognostic information about the disease or a propensity for the disease.

127. The computer program product of claim 116, wherein the disease is cancer.

128. The computer program product of claim 113, wherein the analyzing of the result set identifies at least one patient including a characteristic.

129. The computer program product of claim 128, wherein the characteristic is a drug reaction polymorphism.

130. The computer program product of claim 129, wherein the drug reaction polymorphism is a hypertension drug response polymorphism.

131. The computer program product of claim 128, wherein the characteristic is necessary for said at least one patient to be eligible for a clinical trial.

132. The computer program product of claim 113, wherein the analyzing of the result set generates a treatment suggestion for at least one patient.

133. The computer program product of claim 113, wherein the result set identifies at least one clinical trial for which said at least one patient is eligible.

134. The computer program product of claim 113, wherein the analyzing of the result set models a virtual clinical trial protocol.

135. The computer program product of claim 113, wherein the analyzing of the result set generates market research data or market services data.

136. A method of storing data for a patient in a database connected to a network, comprising:

receiving clinical data for the patient;

storing the clinical data in an archive database connected to the network;

extracting data from the clinical data; and

storing the data in the database.

137. The method of claim 136, wherein the data is diagnostic data.

138. The method of claim 136, wherein the data includes past diagnosis and treatment data, medical history data, biochemical data, physiologic data, proteonomic data, family history data, dietary data, exercise data, demographic data, or drug response history data.

139. The method of claim 138, wherein the data further includes genotype data or haplotype data.

140. The method of claim 139, wherein the genotype data or the haplotype data includes a chromosome structure, a DNA sequence, a length of a specific gene or region, a gene expression, or at least one single nucleotide polymorphism (SNP).

141. The method of claim 136, wherein the clinical data is an electronic medical record including a clinical note dictated by a physician, a laboratory report, or a laboratory result.

142. The method of claim 136, wherein the data is related to a genetic-based disease.

143. The method of claim 142, wherein the genetic-based disease includes oncology data, urology data, cardiology data, gastroenterology data, orthopedic data, immunology data, rheumatology data, neurology data, pulmonology data, internal medicine data, family practice medicine data, and demographic data.

144. The method of claim 136, wherein the database is a data warehouse.

145. The method of claim 144, wherein the data warehouse includes the archive database.

146. The method of claim 136, wherein the receiving of the clinical data further comprises:

establishing a network connection to a server computer that includes the clinical data; and

requesting the clinical data from the server computer.

147. The method of claim 146, further comprising:

destroying the network connection to the server computer after successfully receiving the clinical data.

148. The method of claim 136, wherein the extracting of the data further comprises:

creating a structured file;

parsing the clinical data; and

copying the clinical data into the structured file;

wherein the clinical data includes at least one data segment; and

wherein the structured file includes a tag for each data segment in said at least one data segment.

149. The method of claim 148, wherein the parsing of the clinical data further comprises:

locating at least one data segment in the clinical data.

150. The method of claim 149, further comprising:

converting the data in said at least one data segment to another data format to improve the performance of the database when performing a search, a record addition, or a record deletion.

151. The method of claim 149, further comprising:

linking the data in said at least one data segment to related clinical data for another patient.

152. The method of claim 149, further comprising:

recognizing a known error in the clinical data, wherein the parsing of the clinical data corrects the known error prior to the copying of the clinical data.

153. The method of claim 149, further comprising:

storing an unknown error in an error database.

154. The method of claim 148, wherein the tag is an extensible markup language tag, a hypertext markup language tag, a simple generalized markup language tag, or a health level seven tag.

155. The method of claim 136, further comprising:

storing the structured file in the database.

156. The method of claim 136, wherein the storing of the data further comprises:

creating a record in the database for the patient; and

populating the record with the data.

157. A system for storing data for a patient in a database connected to a network, comprising:

a memory device; and

a processor disposed in communication with the memory device, the processor configured to;

receive clinical data for the patient;

store the clinical data in an archive database connected to the network;

extract data from the clinical data; and

store the data in the database.

158. The system of claim 157, wherein the data is diagnostic data.

159. The system of claim 157, wherein the data includes past diagnosis and treatment data, medical history data, biochemical data, physiologic data, proteonomic data, family history data, dietary data, exercise data, demographic data, or drug response history data.

160. The system of claim 159, wherein the data further includes genotype data or haplotype data.

161. The system of claim 160, wherein the genotype data or the haplotype data includes a chromosome structure, a DNA sequence, a length of a specific gene or region, a gene expression, or at least one single nucleotide polymorphism (SNP).

162. The system of claim 157, wherein the clinical data is an electronic medical record including a clinical note dictated by a physician, a laboratory report, or a laboratory result.

163. The system of claim 157, wherein the data is related to a genetic-based disease.

164. The system of claim 163, wherein the genetic-based disease includes oncology data, urology data, cardiology data, gastroenterology data, orthopedic data, immunology data, rheumatology data, neurology data, pulmonology data, internal medicine data, family practice medicine data, and demographic data.

165. The system of claim 157, wherein the database is a data warehouse.

166. The system of claim 165, wherein the data warehouse includes the archive database.

167. The system of claim 157, wherein to receive the clinical data, the processor is further configured to:

establish a network connection to a server computer that includes the clinical data; and

request the clinical data from the server computer.

168. The system of claim 167, wherein the processor is further configured to:

destroy the network connection to the server computer after successfully receiving the clinical data.

169. The system of claim 157, wherein extract the data, the processor is further configured to:

create a structured file;

parse the clinical data; and

copy the clinical data into the structured file;

wherein the clinical data includes at least one data segment; and

wherein the structured file includes a tag for each data segment in said at least one data segment.

170. The system of claim 169, wherein to parse the clinical data, the processor is further configured to:

locate at least one data segment in the clinical data.

171. The system of claim 170, wherein the processor is further configured to:

convert the data in said at least one data segment to another data format to improve the performance of the database when performing a search, a record addition, or a record deletion.

172. The system of claim 170, wherein the processor is further configured to:

link the data in said at least one data segment to related clinical data for another patient.

173. The system of claim 170, wherein the processor is further configured to:

recognize a known error in the clinical data, wherein the parsing of the clinical data corrects the known error prior to the copying of the clinical data.

174. The system of claim 170, wherein the processor is further configured to:

store an unknown error in an error database.

175. The system of claim 169, wherein the tag is an extensible markup language tag, a hypertext markup language tag, a simple generalized markup language tag, or a health level seven tag.

176. The system of claim 157, wherein the processor is further configured to:

store the structured file in the database.

177. The system of claim 157, wherein to store the data, the processor is further configured to:

create a record in the database for the patient; and

populate the record with the data.

178. A computer program product for storing data for a patient in a database connected to a network, comprising:

a computer readable medium;

program code in said computer readable medium for receiving clinical data for the patient;

program code in said computer readable medium for storing the clinical data in an archive database connected to the network;

program code in said computer readable medium for extracting data from the clinical data; and

program code in said computer readable medium for storing the data in the database.

179. The computer program product of claim 178, wherein the data is diagnostic data.

180. The computer program product of claim 178, wherein the data includes past diagnosis and treatment data, medical history data, biochemical data, physiologic data, proteonomic data, family history data, dietary data, exercise data, demographic data, or drug response history data.

181. The computer program product of claim 180, wherein the data further includes genotype data or haplotype data.

182. The computer program product of claim 181, wherein the genotype data or the haplotype data includes a chromosome structure, a DNA sequence, a length of a specific gene or region, a gene expression, or at least one single nucleotide polymorphism (SNP).

183. The computer program product of claim 178, wherein the clinical data is an electronic medical record including a clinical note dictated by a physician, a laboratory report, or a laboratory result.

184. The computer program product of claim 178, wherein the data is related to a genetic-based disease.

185. The computer program product of claim 184, wherein the genetic-based disease includes oncology data, urology data, cardiology data, gastroenterology data, orthopedic data, immunology data, rheumatology data, neurology data, pulmonology data, internal medicine data, family practice medicine data, and demographic data.

186. The computer program product of claim 178, wherein the database is a data warehouse.

187. The computer program product of claim 186, wherein the data warehouse includes the archive database.

188. The computer program product of claim 178, wherein the program code in said computer readable medium for the receiving of the clinical data further comprises:

program code in said computer readable medium for establishing a network connection to a server computer that includes the clinical data; and

program code in said computer readable medium for requesting the clinical data from the server computer.

189. The computer program product of claim 188, further comprising:

program code in said computer readable medium for destroying the network connection to the server computer after successfully receiving the clinical data.

190. The computer program product of claim 178, wherein the program code in said computer readable medium for the extracting of the data further comprises:

program code in said computer readable medium for creating a structured file;

program code in said computer readable medium for parsing the clinical data; and

program code in said computer readable medium for copying the clinical data into the structured file;

wherein the clinical data includes at least one data segment; and

wherein the structured file includes a tag for each data segment in said at least one data segment.

191. The computer program product of claim 190, wherein the program code in said computer readable medium for the parsing of the clinical data further comprises:

program code in said computer readable medium for locating at least one data segment in the clinical data.

192. The computer program product of claim 191, further comprising:

program code in said computer readable medium for converting the data in said at least one data segment to another data format to improve the performance of the database when performing a search, a record addition, or a record deletion.

193. The computer program product of claim 191, further comprising:

program code in said computer readable medium for linking the data in said at least one data segment to related clinical data for another patient.

194. The computer program product of claim 191, further comprising:

program code in said computer readable medium for recognizing a known error in the clinical data, wherein the parsing of the clinical data corrects the known error prior to the copying of the clinical data.

195. The computer program product of claim 191, further comprising:

program code in said computer readable medium for storing an unknown error in an error database.

196. The computer program product of claim 190, wherein the tag is an extensible markup language tag, a hypertext markup language tag, a simple generalized markup language tag, or a health level seven tag.

197. The computer program product of claim 178, further comprising:

program code in said computer readable medium for storing the structured file in the database.

198. The computer program product of claim 178, wherein the program code in said computer readable medium for the storing of the data further comprises:

program code in said computer readable medium for creating a record in the database for the patient; and

program code in said computer readable medium for populating the record with the data.

199. A system for determining a disease risk or susceptibility type for a patient, comprising:

a memory device; and

a processor disposed in communication with the memory device, the processor configured to;

store at least one clinical information record for the patient, said at least one clinical information record retrieved from a data warehouse and including medical history data, biochemical data, physiologic data, proteonomic data, family history data, dietary data, exercise data, demographic data, and drug response history data.

200. The system of claim 199, wherein said at least one clinical information record further includes genotype data or haplotype data.

201. The system of claim 200, wherein the genotype data or the haplotype data comprises genetic makeup data.

202. The system of claim 201, wherein the genetic makeup data includes a chromosome structure, a DNA sequence, a length of a specific gene or region, a gene expression, or identification of one or more single nucleotide polymorphisms.

203. The system of claim 202, wherein the gene expression comprises mRNA or transcription levels.

204. A method of using a computer device to determine a disease risk or susceptibility type for a patient, comprising:

extracting clinical information from the physician'"'"'s dictated notes, laboratory reports, laboratory results, EKG results, or other clinical data, including attribute and/or demographic information to create a patient record;

correlating the patient'"'"'s clinical information with information either (a) from a data warehouse or (b) accessed from one or more public or private domain databases, the correlation based on clinical information for the patient comprising phenotype, medical history, biochemical, physiologic, proteonomic, family history, diet, exercise, demographic, or drug response history;

characterizing the patient and identifying a predisposition to a disease or susceptibility type; and

generating a result set that includes a suggestion for genetic testing, proteonomic testing, and/or other diagnostic testing.

205. The method of claim 204, wherein the correlating of the patient'"'"'s clinical information queries the data warehouse for at least one other patient record that contains the clinical information for the patient.

206. The method of claim 204, wherein the correlating of the patient'"'"'s clinical information queries the data warehouse for at least one other patient record that does not contain the clinical information for the patient.

207. The method of claim 204, further comprising:

displaying the identified correlation.

208. The method of claim 204, further comprising:

calculating the statistical significance of the identified correlation.

209. The method of claim 204, further comprising:

inputting the patient'"'"'s test results into the system.

210. The method of claim 209, wherein the system generates a suggestion for treatment.

211. The method of claim 204, wherein the patient'"'"'s record is updated by entering subsequent or additional clinical information.

212. A method of using a computer device to identify a patient with a drug reaction polymorphism, comprising:

extracting clinical information from the physician'"'"'s dictated notes, laboratory reports, laboratory results, EKG results, or other clinical data, including idiosyncratic drug reaction information to create a patient record;

correlating the patient'"'"'s clinical information with information either (a) from a data warehouse or (b) accessed from one or more public or private domain databases relating to single nucleotide polymorphisms (SNPs), the correlation based on clinical information for the patient comprising phenotype, medical history, biochemical, physiologic, proteonomic, family history, diet, exercise, demographic, or drug response history;

characterizing the patient as potentially having one or more SNPs; and

generating a result set that includes a suggestion for genetic testing, proteonomic testing, and/or other diagnostic testing.

213. The method of claim 212, wherein the correlating of the patient'"'"'s clinical information queries the data warehouse for at least one other patient record that contains the clinical information for the patient.

214. The method of claim 212, wherein the correlating of the patient'"'"'s clinical information queries the data warehouse for at least one other patient record that does not contain the clinical information for the patient.

215. The method of claim 212, further comprising:

displaying the identified correlation.

216. The method of claim 212, further comprising:

calculating the statistical significance of the identified correlation.

217. The method of claim 212, further comprising:

inputting the patient'"'"'s test results into the system.

218. The method of claim 217, where in the system generates a suggestion for alternative drug therapy.

219. A method of using a computer device to identify a subject for a clinical trial, comprising:

extracting clinical information from the physician'"'"'s dictated notes, laboratory reports, laboratory results, EKG results, or other clinical data, including attribute and/or demographic information to create a patient record;

correlating the patient'"'"'s clinical information with other patient records in a data warehouse, the correlation based on clinical information comprising phenotype, medical history, biochemical, physiologic, proteonomic, family history, diet, exercise, demographic, or drug response history;

identifying a population or sub-population of patients having similar phenotypes or clinical characteristics; and

generating a result set that includes a suggestion for clinical trials which would be appropriate for the patient'"'"'s participation.

220. The method of claim 219, wherein the correlating of the patient'"'"'s clinical information queries the data warehouse for at least one other patient record that contains the clinical information for the patient.

221. The method of claim 219, wherein the correlating of the patient'"'"'s clinical information queries the data warehouse for at least one other patient record that does not contain the clinical information for the patient.

222. The method of claim 219, further comprising:

displaying the identified correlation.

223. The method of claim 219, further comprising:

calculating the statistical significance of the identified correlation.

224. A method of using a computer device to determine a cancer risk or susceptibility type for a patient, comprising:

extracting clinical information from the physician'"'"'s dictated notes, laboratory reports, laboratory results, EKG results, or other clinical data, including attribute and/or demographic information to create a patient record;

correlating the patient'"'"'s clinical information either (a) from a data warehouse or (b) accessed from one or more public or private domain databases, the correlation based on clinical information comprising phenotype, medical history, biochemical, physiologic, proteonomic, family history, diet, exercise, demographic, or drug response history;

characterizing the patient and identifying a predisposition to a disease or susceptibility type; and

generating a result set that includes a suggestion for genetic testing, proteonomic testing, or other diagnostic testing.

225. The method of claim 224, wherein the correlating of the patient'"'"'s clinical information queries the data warehouse for at least one other patient record that contains the clinical information for the patient.

226. The method of claim 224, wherein the correlating of the patient'"'"'s clinical information queries the data warehouse for at least one other patient record that does not contain the clinical information for the patient.

227. The method of claim 224, further comprising:

displaying the identified correlation.

228. The method of claim 224, further comprising:

calculating the statistical significance of the identified correlation.

229. The method of claim 224, further comprising:

entering the patient'"'"'s test results into the system.

230. The method of claim 224, wherein the system generates a suggestion for treatment.

231. The method of claim 224, wherein the patient'"'"'s record is updated by entering subsequent or additional clinical information.

232. A method for identifying a patient with a hypertension drug response polymorphism, comprising:

creating a patient record by extracting the patient'"'"'s clinical information including drug reaction in a data warehouse including at least one record containing clinical information for the patient comprising phenotype, medical history, biochemical, physiologic, proteonomic, family history, diet, exercise, demographic, and drug response history;

correlating the patient'"'"'s clinical information with information either (a) from a data warehouse or (b) accessed from one or more public or private domain databases relating to single polynucleotide polymorphisms (SNPs);

generating a recommendation for genetic testing of the patient'"'"'s CYP2D6 gene identified to be correlated with the hypertension drug response.

233. The method of claim 232, further comprising:

entering the result of the genetic test; and

generating a recommendation for an alternative drug therapy.

234. The method of claim 233, further comprising:

displaying the alternative drug therapy recommendation.

235. A system for determining a disease risk or susceptibility type for a patient, comprising:

a memory device; and

a processor disposed in communication with the memory device, the processor configured to;

receive an electronic medical record for the patient from at transcription service;

convert the electronic medical record to a structured electronic medical record; and

storing the structured electronic medical record in a data warehouse.

236. The system of claim 235, wherein the electronic medical record includes medical history data, biochemical data, physiologic data, proteonomic data, family history data, dietary data, exercise data, demographic data, and drug response history data.

237. The system of claim 235, wherein the structured electronic medical record includes at least one segment of the electronic medical record and a field tag associated with said at least one segment.

238. The system of claim 237, wherein the field tag is an extensible markup language (XML) tag.

239. A method of using a computer device to perform market research, comprising:

importing and aggregating archived and prospective electronic medical records containing patient clinical information;

correlating the patient'"'"'s clinical information contained in the electronic medical record with other patient records in a data warehouse, the correlation based on clinical information for the patient comprising phenotype, medical history, biochemical, physiologic, proteonomic, family history, diet, exercise, demographic, drug response history, and referring physician;

identifying a population or sub-population of patients having similar phenotypes or clinical characteristics;

displaying the information for utilization in market research and targeting treatment plans or products to the patient population.

240. The method of claim 239, wherein the correlating of the patient'"'"'s clinical information queries the data warehouse for at least one other patient record that contains the clinical information for the patient.

241. The method of claim 239, wherein the correlating of the patient'"'"'s clinical information queries the data warehouse for at least one other patient record that does not contain the clinical information for the patient.