Formalization and computation of quality measures based on electronic medical records

Journal of the American Medical Informatics Association

Volumn 21, Issue 2, 2014, Pages 285-291

  Dentler, Kathrin ^a,b   Numans, Mattijs E ^c,d   ten Teije, Annette ^a   Cornet, Ronald ^b,e   de Keizer, Nicolette F ^b  

^a VU UNIVERSITY AMSTERDAM   (Netherlands)

^b UNIVERSITY OF AMSTERDAM   (Netherlands)

^c UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

^d VU UNIVERSITY MEDICAL CENTER   (Netherlands)

^e LINKÖPING UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTRONIC MEDICAL RECORD; EMR-DRIVEN PHENOTYPING; IDENTIFICATION OF PATIENT COHORTS; QUALITY INDICATORS; QUALITY MEASURES; SECONDARY USE OF PATIENT DATA;

ELECTRONIC HEALTH RECORDS; GENERAL PRACTICE; HUMANS; NATURAL LANGUAGE PROCESSING; NETHERLANDS; PRACTICE GUIDELINES AS TOPIC; PROGRAMMING LANGUAGES; QUALITY INDICATORS, HEALTH CARE;

EID: 84894082866     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1136/amiajnl-2013-001921     Document Type: Article

References (15)

1. Dentler K, ten Teije A, Cornet R, et al. Towards the automated calculation of clinical quality measures. Knowledge Represent Health Care 2012;LNCS 6924: 51-64.
2. Dentler K, Cornet R, ten Teije A, et al. The reproducibility of CLIF, a method for clinical quality measure formalisation. In: J Mantas et al, editor. Stud Health Technol Inform 2012;180:113-17.
3. Dentler K, ten Teije A, Cornet R, et al. Semantic integration of patient data and quality measures based on openEHR archetypes. ProHealth 2012/KR4HC 2012 2013;LNAI 7738:85-97.
4. Medlock S, Opondo D, Eslami S, et al. LERM (Logical Elements Rule Method): a method for assessing and formalizing clinical rules for decision support. Int J Med Inform 2011;80:286-95.
5. Stegers R, ten Teije A, van Harmelen F. Managing Knowledge in a World of Networks, Lecture Notes in Computer Science. EKAW'06 2006;4248:51-8.
6. Blumenthal D, Tavenner M. The "meaningful use" regulation for electronic health records. N Engl J Med 2010;363:501-4.
7. Donabedian A. Evaluating the quality of medical care. Milbank Q 2005;83: 691-729.
8. Grobbee DE, Hoes AW, Verheij TJM, et al. The Utrecht Health Project: optimization of routine healthcare data for research. Eur J Epidemiol 2005;20:285-7.
9. Cornet R, de Keizer N. Forty years of SNOMED: a literature review. BMC Med Inform Decis Mak 2008;8(Suppl 1):S2.
10. Ross J, Tu MSS, Carini MSS, et al. Analysis of eligibility criteria complexity in clinical trials. AMIA Summits Transl Sci Proc 2010;2010:46-50.
11. Conway M, Berg RL, Carrell D, et al. Analyzing the heterogeneity and complexity of Electronic Health Record oriented phenotyping algorithms. AMIA Symp 2011;2011:274-83.
12. Weng C, Wu X, Luo Z, et al. EliXR: an approach to eligibility criteria extraction and representation. J Am Med Inform Assoc 2011;18(Suppl 1):i116-24.
13. Tu SW, Peleg M, Carini S, et al. A practical method for transforming free-text eligibility criteria into computable criteria. J Biomed Inform 2011;44:239-50.
14. Milian K, Bucur A, Ten Teije A. Formalization of clinical trial eligibility criteria: evaluation of a pattern-based approach. 2012 IEEE International Conference on Bioinformatics and Biomedicine; 2012:1-4.
15. Thompson WK, Rasmussen LV, Pacheco JA, et al. An evaluation of the NQF Quality Data Model for representing Electronic Health Record driven phenotyping algorithms. AMIA Annu Symp Proc 2012;2012:911-20.