145 related articles for article (PubMed ID: 37650032)
21. DEVELOPMENT AND PERFORMANCE OF TEXT-MINING ALGORITHMS TO EXTRACT SOCIOECONOMIC STATUS FROM DE-IDENTIFIED ELECTRONIC HEALTH RECORDS.
Hollister BM; Restrepo NA; Farber-Eger E; Crawford DC; Aldrich MC; Non A
Pac Symp Biocomput; 2017; 22():230-241. PubMed ID: 27896978
[TBL] [Abstract][Full Text] [Related]
22. Dynamic ElecTronic hEalth reCord deTection (DETECT) of individuals at risk of a first episode of psychosis: a case-control development and validation study.
Raket LL; Jaskolowski J; Kinon BJ; Brasen JC; Jönsson L; Wehnert A; Fusar-Poli P
Lancet Digit Health; 2020 May; 2(5):e229-e239. PubMed ID: 33328055
[TBL] [Abstract][Full Text] [Related]
23. Systematic review of electronic health records to manage chronic conditions among displaced populations.
Buford A; Ashworth HC; Ezzeddine FL; Dada S; Nguyen E; Ebrahim S; Zhang A; Lebovic J; Hamvas L; Prokop LJ; Midani S; Chilazi M; Alahdab F
BMJ Open; 2022 Sep; 12(9):e056987. PubMed ID: 36285578
[TBL] [Abstract][Full Text] [Related]
24. An audit of the reliability of influenza vaccination and medical information extracted from eHealth records in general practice.
Regan AK; Gibbs RA; Effler PV
Vaccine; 2018 May; 36(23):3195-3198. PubMed ID: 29716772
[TBL] [Abstract][Full Text] [Related]
25. Data extraction from electronic health records (EHRs) for quality measurement of the physical therapy process: comparison between EHR data and survey data.
Scholte M; van Dulmen SA; Neeleman-Van der Steen CW; van der Wees PJ; Nijhuis-van der Sanden MW; Braspenning J
BMC Med Inform Decis Mak; 2016 Nov; 16(1):141. PubMed ID: 27825333
[TBL] [Abstract][Full Text] [Related]
26. Do GPs know their patients with cancer? Assessing the quality of cancer registration in Dutch primary care: a cross-sectional validation study.
Sollie A; Roskam J; Sijmons RH; Numans ME; Helsper CW
BMJ Open; 2016 Sep; 6(9):e012669. PubMed ID: 27633642
[TBL] [Abstract][Full Text] [Related]
27. Identifying lupus patients in electronic health records: Development and validation of machine learning algorithms and application of rule-based algorithms.
Jorge A; Castro VM; Barnado A; Gainer V; Hong C; Cai T; Cai T; Carroll R; Denny JC; Crofford L; Costenbader KH; Liao KP; Karlson EW; Feldman CH
Semin Arthritis Rheum; 2019 Aug; 49(1):84-90. PubMed ID: 30665626
[TBL] [Abstract][Full Text] [Related]
28. Compliance with pathology testing guidelines in Australian general practice: protocol for a secondary analysis of electronic health record data.
Sezgin G; Georgiou A; Hardie RA; Li L; Pont LG; Badrick T; Franco GS; Westbrook JI; Rinehart N; McLeod A; Pearce C; Shearer M; Whyte R; Deveny E
BMJ Open; 2018 Nov; 8(11):e024223. PubMed ID: 30429148
[TBL] [Abstract][Full Text] [Related]
29. Completeness and accuracy of morbidity and repeat prescribing records held on general practice computers in Scotland.
Whitelaw FG; Nevin SL; Milne RM; Taylor RJ; Taylor MW; Watt AH
Br J Gen Pract; 1996 Mar; 46(404):181-6. PubMed ID: 8731627
[TBL] [Abstract][Full Text] [Related]
30. Combining information from a clinical data warehouse and a pharmaceutical database to generate a framework to detect comorbidities in electronic health records.
Sylvestre E; Bouzillé G; Chazard E; His-Mahier C; Riou C; Cuggia M
BMC Med Inform Decis Mak; 2018 Jan; 18(1):9. PubMed ID: 29368609
[TBL] [Abstract][Full Text] [Related]
31. The opportunities and challenges of pragmatic point-of-care randomised trials using routinely collected electronic records: evaluations of two exemplar trials.
van Staa TP; Dyson L; McCann G; Padmanabhan S; Belatri R; Goldacre B; Cassell J; Pirmohamed M; Torgerson D; Ronaldson S; Adamson J; Taweel A; Delaney B; Mahmood S; Baracaia S; Round T; Fox R; Hunter T; Gulliford M; Smeeth L
Health Technol Assess; 2014 Jul; 18(43):1-146. PubMed ID: 25011568
[TBL] [Abstract][Full Text] [Related]
32. Blood pressure control in Australian general practice: analysis using general practice records of 1.2 million patients from the MedicineInsight database.
Roseleur J; Gonzalez-Chica DA; Bernardo CO; Geisler BP; Karnon J; Stocks NP
J Hypertens; 2021 Jun; 39(6):1134-1142. PubMed ID: 33967217
[TBL] [Abstract][Full Text] [Related]
33. Diabetes Mellitus Diagnosis and Screening in Australian General Practice: A National Study.
Zheng M; Bernardo CO; Stocks N; Gonzalez-Chica D
J Diabetes Res; 2022; 2022():1566408. PubMed ID: 35372584
[TBL] [Abstract][Full Text] [Related]
34. Evaluation of an Algorithm for Identifying Ocular Conditions in Electronic Health Record Data.
Stein JD; Rahman M; Andrews C; Ehrlich JR; Kamat S; Shah M; Boese EA; Woodward MA; Cowall J; Trager EH; Narayanaswamy P; Hanauer DA
JAMA Ophthalmol; 2019 May; 137(5):491-497. PubMed ID: 30789656
[TBL] [Abstract][Full Text] [Related]
35. Exploring the physical health of patients with severe or long-term mental illness using routinely collected general practice data from MedicineInsight.
Belcher J; Myton R; Yoo J; Boville C; Chidwick K
Aust J Gen Pract; 2021 Dec; 50(12):944-949. PubMed ID: 34845468
[TBL] [Abstract][Full Text] [Related]
36. Trends in long-term opioid prescriptions for musculoskeletal conditions in Australian general practice: a national longitudinal study using MedicineInsight, 2012-2018.
Black-Tiong S; Gonzalez-Chica D; Stocks N
BMJ Open; 2021 Apr; 11(4):e045418. PubMed ID: 33827841
[TBL] [Abstract][Full Text] [Related]
37. Automatic identification of type 2 diabetes, hypertension, ischaemic heart disease, heart failure and their levels of severity from Italian General Practitioners' electronic medical records: a validation study.
Gini R; Schuemie MJ; Mazzaglia G; Lapi F; Francesconi P; Pasqua A; Bianchini E; Montalbano C; Roberto G; Barletta V; Cricelli I; Cricelli C; Dal Co G; Bellentani M; Sturkenboom M; Klazinga N
BMJ Open; 2016 Dec; 6(12):e012413. PubMed ID: 27940627
[TBL] [Abstract][Full Text] [Related]
38. Real-world data in primary care: validation of diagnosis of atrial fibrillation in primary care electronic medical records and estimated prevalence among consulting patients'.
de Burgos-Lunar C; Del Cura-González I; Cárdenas-Valladolid J; Gómez-Campelo P; Abánades-Herranz JC; López-de Andrés A; Sotos-Prieto M; Iriarte-Campo V; Salinero-Fort MA
BMC Prim Care; 2023 Jan; 24(1):4. PubMed ID: 36600196
[TBL] [Abstract][Full Text] [Related]
39. Diagnostic accuracy of the International Classification of Diseases, Tenth Revision, codes of heart failure in an administrative database.
Bosco-Lévy P; Duret S; Picard F; Dos Santos P; Puymirat E; Gilleron V; Blin P; Chatellier G; Looten V; Moore N
Pharmacoepidemiol Drug Saf; 2019 Feb; 28(2):194-200. PubMed ID: 30395375
[TBL] [Abstract][Full Text] [Related]
40. Handwork vs machine: a comparison of rheumatoid arthritis patient populations as identified from EHR free-text by diagnosis extraction through machine-learning or traditional criteria-based chart review.
Maarseveen TD; Maurits MP; Niemantsverdriet E; van der Helm-van Mil AHM; Huizinga TWJ; Knevel R
Arthritis Res Ther; 2021 Jun; 23(1):174. PubMed ID: 34158089
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]