ライフサイエンスコーパス: electronic medical record

1 a a patient scoring tool integrated into the electronic medical record.

2 l centers were entered prospectively into an electronic medical record.

3 on and retrospective analysis as part of the electronic medical record.

4 ns, compared to the data available within an electronic medical record.

5 data are presented to the provider within an electronic medical record.

6 edical data contained within a comprehensive electronic medical record.

7 a valid archive of vital sign data within an electronic medical record.

8 rfaces currently available within a standard electronic medical record.

9 Clinical data were extracted from the electronic medical record.

10 e team to make treatment recommendations via electronic medical record.

11 emergency department visits recorded in the electronic medical record.

12 high when measures were structured into our electronic medical record.

13 d an appropriate diagnosis documented in the electronic medical record.

14 y to be facilitated by the transition to the electronic medical record.

15 tension or prehypertension documented in the electronic medical record.

16 or elevated blood pressure documented in the electronic medical record.

17 All used the same electronic medical record.

18 and pharmacy data were extracted from the VA electronic medical record.

19 ations to primary care providers through the electronic medical record.

20 care was obtained from documentation in the electronic medical record.

21 telet count variables were obtained from the electronic medical record.

22 Clinical data were collected from electronic medical records.

23 time to onset of cirrhotic decompensation in electronic medical records.

24 period that ended in 2011 and verified using electronic medical records.

25 ineligibility was assessed through review of electronic medical records.

26 iovascular risk factors were identified from electronic medical records.

27 d using information extracted from patients' electronic medical records.

28 and clinical covariates were determined from electronic medical records.

29 s to register a diagnosis of HD in patients' electronic medical records.

30 readily transferable to modern comprehensive electronic medical records.

31 e registries, administrative claims data and electronic medical records.

32 nts in a DNA biobank linked to comprehensive electronic medical records.

33 tomated reporting from laboratory panels and electronic medical records.

34 Data were abstracted from electronic medical records.

35 a validated machine learning tool applied to electronic medical records.

36 ortant clinical variables were obtained from electronic medical records.

37 linking diseases and symptoms directly from electronic medical records.

38 l consequent biopsies were obtained from the electronic medical records.

39 Data on end-of-life care were collected from electronic medical records.

40 cal information was extracted from subjects' electronic medical records.

41 in 6 months before CT were obtained from the electronic medical records.

42 nd echocardiographic data were reviewed from electronic medical records.

43 row CT were retrospectively identified from electronic medical records.

44 OPMRs permitted data transfer from physician electronic medical records.

45 includes all security measures required for electronic medical records.

46 l Leuven were identified via a search of the electronic medical records.

47 Clinical data were extracted from electronic medical records.

48 topathologic outcomes were obtained from the electronic medical records.

49 s trapped in the free-text narratives within electronic medical records.

50 and March 31, 2011, were identified from the electronic medical records.

51 g documented HCV infection was obtained from electronic medical records.

52 % vs 22.0%, P = .03) and a fully implemented electronic medical record (12.6% vs 17.8%, P = .03).

53 l of 726 (70.3%) had a weight entered in the electronic medical record 7 or more years after surgery

54 iduals without cardiac disease selected from electronic medical record algorithms at 5 sites in the E

55 The increasing adoption of electronic medical records allows large amounts of patie

56 dy of patient data from United Kingdom-based electronic medical records; analysis included 9035 patie

57 ny CD import attempt were extracted from the electronic medical record and compared between two patie

58 apy was set to discontinue after 48 h in the electronic medical record and the duration of therapy fo

59 and clinician information were obtained from electronic medical records and administrative data.

60 Electronic medical records and all available imaging stu

61 Electronic medical records and all available imaging stu

62 ALI development were identified by review of electronic medical records and analyzed in univariate an

63 ta from Wake Forest Baptist Medical Center's electronic medical records and annotated with BioCarta s

64 Data were obtained from electronic medical records and chart abstraction of surg

65 We used Intermountain Healthcare's electronic medical records and data warehouse to identif

66 A review of the electronic medical records and dictated reports identifi

67 atients of European or African ancestry with electronic medical records and exome chip data to compar

68 e Research Institute (NHGRI) established the Electronic MEdical Records and GEnomics (eMERGE) Consort

69 ploratory Research (CSER) Consortium and the Electronic Medical Records and Genomics (eMERGE) Network

70 medical record algorithms at 5 sites in the Electronic Medical Records and Genomics (eMERGE) network

71 de association study of 7607 patients in the Electronic Medical Records and Genomics (eMERGE) network

72 viduals from 11 US healthcare systems in the Electronic Medical Records and Genomics (eMERGE) Network

73 ober 5, 2012, to September 30, 2013, for the Electronic Medical Records and Genomics Network Pharmaco

74 xisting genotypes in DNA biobanks across the Electronic Medical Records and Genomics network to perfo

75 zed Medicine Research Project, a site in the electronic Medical Records and Genomics Network, we appl

76 es with asthma and control subjects from the Electronic Medical Records and Genomics network.

77 ith monocyte count in 11 014 subjects in the electronic Medical Records and Genomics Network.

78 modulated diseases from the eMERGE network (Electronic Medical Records and Genomics; n=12 978).

79 The authors reviewed the electronic medical records and imaging reports for all p

80 d postdelivery infant feeding practices from electronic medical records and in-person surveys.

81 Electronic medical records and patient interviews were r

82 Primary care practices that use electronic medical records and receive regular performan

83 ta were collected from the Parkland Hospital electronic medical records and the US census, constituti

84 Patient data were collected from electronic medical records and traditional chart reviews

85 ocol development and implementation into the electronic medical record, and (5) ongoing review of dat

86 Patient characteristics were obtained from electronic medical records, and ASCVD events were ascert

87 Surgery-related data were collected via electronic medical records, and complications were calcu

88 ofiling, proteomic and metabolomic analyses, electronic medical records, and patient-reported health

89 nal use of privacy protection, leveraging of electronic medical records, and recruitment of a larger

90 otic prescribing frequency, especially where electronic medical records are not available.

91 estimates, derived from large collections of electronic medical records, are useful for interpreting

92 but there is a need for more research on the electronic medical record as it relates to the practicin

93 nt confidentiality include ease of access to electronic medical records as well as patient (and/or pa

94 Electronic medical records at the Cleveland Clinic were

95 n-dialysis-dependent CKD population using an electronic medical record-based CKD registry in a large

96 left ventricular ejection fraction, a simple electronic medical record-based intervention directed to

97 h care among patients with public insurance, electronic medical records, billing among pediatric resi

98 However, the electronic medical record can reliably be used to identi

99 Information overload in electronic medical records can impede providers' ability

100 utilization, the widespread availability of electronic medical records capable of supporting clinici

101 Barriers may be overcome with: electronic medical records, changes in reporting require

102 The Boston Electronic Medical Record Collaborative is working to de

103 National electronic medical records compiled by the Veterans Heal

104 The standard electronic medical record contained a much larger data v

105 The electronic medical record contains an abundance of unuse

106 e data codes; however, free-text searches of electronic medical records could represent an additional

107 We benefit from data in electronic medical records covering all hospital encount

108 All transmitted data are transferred to the electronic medical record daily.

109 We used electronic medical record data (1997 to 2005) to identif

110 measurements from a single blood sample with electronic medical record data (EMR) for the identificat

111 We measured implementation metrics based on electronic medical record data and evaluated the impact

112 The utility of automated claims and electronic medical record data for this purpose was asse

113 We analyzed electronic medical record data from a 4-site retrospecti

114 a text-processing method was used to analyze electronic medical record data from an academic medical

115 Retrospective analysis of nationwide electronic medical record data from the US Veterans Heal

116 lemented text-processing pipeline to analyze electronic medical record data in a retrospective cohort

117 Electronic medical record data included gestational week

118 ates the utility of novel methods to analyze electronic medical record data to generate practice-base

119 Electronic medical record data were used to divide into

120 in our study intensive care unit (ICU) using electronic medical record data.

121 We examined electronic medical-record data for outpatient care recei

122 f patients with EoE within our hospital-wide electronic medical record database and our EoE research

123 discovery approach with analysis of a large electronic medical record database method to predict and

124 study determined by an initial search of the electronic medical record database of Kaiser Permanente

125 , Titusville, NJ) were identified through an electronic medical record database.

126 tering Cancer Center were identified from an electronic medical record database.

127 om The Health Improvement Network (THIN), an electronic medical records database broadly representati

128 A population-based, electronic medical records database from the Hong Kong C

129 e drawn from the General Electric Centricity electronic medical records database.

130 inistrative, clinical, laboratory, drug, and electronic medical record databases using encoded person

131 ricular tachycardia (VT)-were ascertained by electronic medical records, defibrillator interrogation,

132 ciation studies performed with the use of an electronic medical records-derived cohort, supporting th

133 mic data linked to health information in the electronic medical record (EMR) and explores the issues

134 1) free text, and 2) structured data from an electronic medical record (EMR) could complement each ot

135 Electronic medical record (EMR) data from patients 10 ye

136 The electronic medical record (EMR) has huge potential for f

137 ate documentation of patient symptoms in the electronic medical record (EMR) is important for high-qu

138 Retrospective analysis of electronic medical record (EMR) notes (OpenEyes) and pap

139 ters in the United Kingdom that use the same electronic medical record (EMR) system (Medisoft Ophthal

140 ively collected clinical data using a single electronic medical record (EMR) system, with automatic e

141 ngdom centers to a central database using an electronic medical record (EMR) system.

142 search that combine DNA biorepositories with electronic medical record (EMR) systems for large-scale,

143 Electronic medical record (EMR) systems have become wide

144 Large-scale DNA databanks linked to electronic medical record (EMR) systems have been propos

145 nformation system (LIS) can be linked to the electronic medical record (EMR) to enable adaptive alert

146 , patient-level administration data from the electronic medical record (EMR), and patient-level admin

147 agnosis by combining these measurements with electronic medical record (EMR).

148 ientific use of increasing digital data from electronic medical records (EMR) and diagnostic devices.

149 inistrative claims, physician databases, and electronic medical records (EMR) from 1455 patients (50-

150 The advent of Electronic Medical Records (EMR) with large electronic i

151 g methods that combine chart data, including electronic medical records (EMR), with PRO symptoms may

152 alleles and with clinical diagnoses from the electronic medical records (EMRs) among RA cases and non

153 Retrospective review of electronic medical records (EMRs) in an integrated healt

154 medication prescribing patterns by analyzing Electronic Medical Records (EMRs) including the narrativ

155 Phenotype data from electronic medical records (EMRs) may provide a resource

156 ence of genetic data coupled to longitudinal electronic medical records (EMRs) offers the possibility

157 nt referral system included (1) implementing electronic medical records (EMRs), (2) receiving better

158 lore integrating NGS with clinical data from electronic medical records (EMRs), immune profiling data

159 With the increased adoption and evolution of electronic medical records (EMRs), there is a need to as

160 ia to enable an automated chart review using electronic medical records (EMRs).

161 to the topics of government policy regarding electronic medical records (EMRs); data definitions and

162 53 controls of European ancestry within five electronic medical records (EMRs); the algorithms' posit

163 As electronic medical records enable increasingly ambitious

164 lopmental Cohort is a genotyped sample, with electronic medical records, enrolled in the study of bra

165 veitis was determined through a query of the electronic medical record followed by individual medical

166 s-sectional analysis of routine primary care electronic medical records for 1 424 378 adults in the U

167 Electronic medical records for 223,502 US deliveries wer

168 All electronic medical records for enrollees in Kaiser Perma

169 opulation-based genealogy resource linked to electronic medical records for health care systems acros

170 With the increased use of data from electronic medical records for research, it is important

171 data were abstracted from individual patient electronic medical records for the 24 hours before the r

172 aset of >10 million individuals derived from electronic medical records from 1995 through 2013 in the

173 y using nationwide pharmacy claims linked to electronic medical records from a nationwide data wareho

174 l signatures extracted from over 13 years of electronic medical records from a tertiary hospital, inc

175 ntional radiology database and of individual electronic medical records from an academic tertiary med

176 Electronic medical records from colonoscopies performed

177 r Infirmary Ocular Inflammation Database and electronic medical records from March 1, 2008, to Decemb

178 2009 were identified using linked anonymized electronic medical records from the Myocardial Ischaemia

179 cal and demographic data were extracted from electronic medical records from the University of Califo

180 ents, and results were made available in the electronic medical record; however, medications were not

181 ultisite, observational study (2002-2008) of electronic medical records in the United States.

182 e clinical factors (>200) extracted from the electronic medical record included medications, comorbid

183 y was ascertained via resurvey or linkage to electronic medical records (including hospital admission

184 and unconventional structured data from the electronic medical record, including need for medical in

185 ation strategies (repeated-mailing outreach, electronic medical record-integrated provider best pract

186 ological approach to quality improvement and electronic medical record integration has potential to s

187 3) for the novel user interface and standard electronic medical record interface, respectively (p = .

188 Access to an electronic medical record is essential for personalized

189 can be demonstrated in cohorts derived from electronic medical records is unknown.

190 core 3, using only data available within the electronic medical record (Kaiser Permanente HealthConne

191 Vanderbilt University's electronic medical record linked to a DNA biorepository

192 ealth Administration's integrated, national, electronic medical record linked to Organ Procurement an

193 (BioVU; n = 786), the Vanderbilt University electronic medical record-linked DNA biobank.

194 HumanExome BeadChip v.1.0 in the Vanderbilt electronic medical record-linked DNA repository, BioVU.

195 and their skin check partners drawn from an electronic medical record melanoma registry and advertis

196 2006, and May 30, 2012, were identified from electronic medical records (n = 830).

197 We conclude that DNA biobanks coupled to electronic medical records not only provide a platform f

198 Electronic medical records, nowadays routinely collected

199 eriod determined by an initial search of the electronic medical record of Kaiser Permanente Hawaii an

200 nuary 1, 2006, and December 31, 2007, in the electronic medical record of Kaiser Permanente Hawaii we

201 , based on secondary data extracted from the electronic medical record of the Hospital Italiano of Bu

202 The electronic medical record of the patients with C-RADS E3

203 Electronic medical records of 2003 patients who underwen

204 Authors reviewed the electronic medical records of 3 treatment-naive HCV geno

205 A prospectively maintained registry and the electronic medical records of 400 consecutive thoracic e

206 Potential subjects were screened using electronic medical records of a regional Veterans Affair

207 graft survival by retrospective analysis of electronic medical records of a single-center cohort of

208 roved study, we retrospectively reviewed the electronic medical records of all patients (N=91) who ha

209 We carried out a retrospective review of the electronic medical records of all patients undergoing GM

210 nset were collected retrospectively from the electronic medical records of ALS patients.

211 ction of detailed phenotype information from electronic medical records of cancer patients.

212 Electronic medical records of consecutive patients who r

213 were determined using standard criteria with electronic medical records of laboratory, diagnosis, and

214 The electronic medical records of patients aged 21 years or

215 This was a retrospective review of the electronic medical records of patients who had CSFP meas

216 this retrospective, single-center study, the electronic medical records of patients who were primaril

217 We retrospectively analyzed electronic medical records of patients with Ehlers-Danlo

218 PATIENTS AND METHODS Electronic medical records of patients with metastatic b

219 All data were obtained by a review of electronic medical records of patients.

220 d identification of domestic violence in the electronic medical records of the general practice.

221 ded in Kaiser Permanente Northern California electronic medical records on at least 2 occasions any t

222 jects randomly assigned to either a standard electronic medical record or a novel user interface, wer

223 uted changes, such as the introduction of an electronic medical record or comparative effectiveness s

224 characteristics, identified full adoption of electronic medical records (OR 4.74), home health progra

225 ersonal digital assistant, on the hospital's electronic medical record, or on a distant site on the W

226 A retrospective review and analysis of electronic medical records over a 12-week period examine

227 el user interface compared with the standard electronic medical record (p < .001).

228 istration (VHA) has introduced an integrated electronic medical record, performance measurement, and

229 were obtained from full review of paper and electronic medical records, prescriptions, and investiga

230 with the length of stay ascertained via the electronic medical record (r=0.53; P=0.03).

231 n review of the insulin/glucose chart in the electronic medical record, recommendations for insulin c

232 Electronic medical record review for International Class

233 gh questionnaires with confirmation using an electronic medical record review.

234 le pathologic analyses were assessed through electronic medical record review.

235 compared to information availability in the electronic medical record (secondary outcome).

236 the original examination and report and the electronic medical record served as the reference standa

237 order to extract meaningful information from electronic medical records, such as signs and symptoms,

238 Electronic medical record surveillance of mechanically v

239 extracted from 14 UK centers using the same electronic medical record system (EMR).

240 ing the development and implementation of an electronic medical record system and a new league-wide i

241 2005 Medicare initiative will provide the VA electronic medical record system as a free benefit to al

242 Follow-up electronic medical record system data were available for

243 1 physician organization linked by a common electronic medical record system in Eastern Massachusett

244 rovider decision-making support tools in the electronic medical record system may potentially improve

245 tients' care preferences and progress via an electronic medical record system under the direction of

246 Using the Minneapolis Veterans Affairs electronic medical record system, we identified a cohort

247 ively collected clinical data using a single electronic medical record system, with automatic extract

248 ea primary care practices linked by a common electronic medical record system.Patients A total of 191

249 , OPCRIT+, that is being introduced into the electronic medical records system of the South London an

250 reoretinal surgery were recorded on the same electronic medical records system.

251 sease pairs that are overrepresented in both electronic medical record systems and in VARIMED come fr

252 EF differs from regular electronic medical record systems because frontline prov

253 routinely collected, anonymized data within electronic medical record systems were extracted remotel

254 After review of the electronic medical record, the prevalence of clinically

255 medical record tool was implemented into the electronic medical record to aid preoperative clinic pro

256 We used electronic medical records to ascertain data for antibio

257 the time to utilize information recorded in electronic medical records to develop innovative disease

258 also the time to use information recorded in electronic medical records to develop innovative disease

259 We used electronic medical records to identify all office visits

260 We used electronic medical records to identify patients beginnin

261 ers, natural language processing analysis of electronic medical records to identify postoperative com

262 frequently used clinical concepts within the electronic medical record, to improve the efficiency of

263 ticenter cohort with genotype data linked to electronic medical records, to estimate the diagnostic r

264 A clinically based electronic medical record tool was implemented into the

265 rt, recent stressor exposures, and, from the electronic medical record, treatment history, and Charls

266 ecause the largest source of clinical data - Electronic Medical Records - typically contains noisy, s

267 t, a computerized handoff tool linked to the electronic medical record was introduced.

268 er 25% of the clinical data available in the electronic medical record was never used, and only 33% w

269 The electronic medical record was reviewed for each patient

270 The electronic medical record was searched to obtain clinica

271 A phenotyping algorithm mining electronic medical records was developed and validated t

272 h at least 12 months follow-up and available electronic medical records was used to identify 37 T2D p

273 Electronic medical records were also reviewed.

274 Electronic medical records were examined for a history o

275 Serial prenatal electronic medical records were obtained from women who

276 Electronic medical records were reviewed and data were a

277 Electronic medical records were reviewed for 102 patient

278 Electronic medical records were reviewed for a 5-year pe

279 Electronic medical records were reviewed for demographic

280 Electronic medical records were reviewed for demographic

281 Electronic medical records were reviewed for follow-up i

282 Electronic medical records were reviewed for OTRs diagno

283 Electronic medical records were reviewed for patients wi

284 an indication of "diarrhea." These patient's electronic medical records were reviewed to determine pa

285 Electronic medical records were reviewed to determine th

286 Electronic medical records were reviewed, and radiology

287 The electronic medical records were searched for all contras

288 Electronic medical records were searched to identify mya

289 Limitations of our study include the use of electronic medical records, which could have resulted in

290 zation of health care is best exemplified by electronic medical records, which have been far from fav

291 ylococcus aureus (MRSA) were reported in the electronic medical record without additional interventio