Identifying priorities in methodological research using ICD-9-ICM and ICD-10 administrative data: report from an international consortium

被引:122
作者
De Coster, Carolyn [1 ]
Quan, Hude
Finlayson, Alan
Gao, Min
Halfon, Patricia
Humphries, Karin H.
Johansen, Helen
Lix, Lisa M.
Luthi, Jean-Christophe
Ma, Jin
Romano, Patrick S.
Roos, Leslie
Sundararajan, Vijaya
Tu, Jack V.
Webster, Greg
Ghali, William A.
机构
[1] Univ Calgary, Dept Community Hlth Sci, Calgary, AB, Canada
[2] Univ Calgary, Ctr Hlth & Policy Studies, Calgary, AB, Canada
[3] Healthcare Informat Grp, Informat Serv, Edinburgh, Midlothian, Scotland
[4] British Columbia Cardiac Registry, Vancouver, BC, Canada
[5] Univ Lausanne, Inst Univ Med Sociale & Prevent, CH-1015 Lausanne, Switzerland
[6] Univ British Columbia, Ctr Hlth Evaluat & Outcome Sci, Vancouver, BC V5Z 1M9, Canada
[7] Statistics Canada, Hlth Div, Ottawa, ON, Canada
[8] Univ Manitoba, Manitoba Ctr Hlth Policy, Dept Community Hlth Sci, Winnipeg, MB, Canada
[9] Second Shanghai Med Univ, Coll Publ Hlth, Shanghai, Peoples R China
[10] Univ Calif Davis, Sch Med, Davis, CA 95616 USA
[11] Dept Human Serv, Melbourne, Vic, Australia
[12] Univ Toronto, Inst Clin Evaluat Sci, Sunnybrook Hlth Sci Ctr, Toronto, ON, Canada
[13] Canadian Inst Hlth Informat, Toronto, ON, Canada
[14] Univ Calgary, Dept Med, Calgary, AB, Canada
关键词
D O I
10.1186/1472-6963-6-77
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: Health administrative data are frequently used for health services and population health research. Comparative research using these data has been facilitated by the use of a standard system for coding diagnoses, the International Classification of Diseases (ICD). Research using the data must deal with data quality and validity limitations which arise because the data are not created for research purposes. This paper presents a list of high-priority methodological areas for researchers using health administrative data. Methods: A group of researchers and users of health administrative data from Canada, the United States, Switzerland, Australia, China and the United Kingdom came together in June 2005 in Banff, Canada to discuss and identify high-priority methodological research areas. The generation of ideas for research focussed not only on matters relating to the use of administrative data in health services and population health research, but also on the challenges created in transitioning from ICD-9 to ICD-10. After the brain-storming session, voting took place to rank-order the suggested projects. Participants were asked to rate the importance of each project from 1 ( low priority) to 10 ( high priority). Average ranks were computed to prioritise the projects. Results: Thirteen potential areas of research were identified, some of which represented preparatory work rather than research per se. The three most highly ranked priorities were the documentation of data fields in each country's hospital administrative data ( average score 8.4), the translation of patient safety indicators from ICD-9 to ICD-10 ( average score 8.0), and the development and validation of algorithms to verify the logic and internal consistency of coding in hospital abstract data ( average score 7.0). Conclusion: The group discussions resulted in a list of expert views on critical international priorities for future methodological research relating to health administrative data. The consortium's members welcome contacts from investigators involved in research using health administrative data, especially in cross-jurisdictional collaborative studies or in studies that illustrate the application of ICD-10.
引用
收藏
页数:6
相关论文
共 20 条
[1]   Measuring underuse of necessary care among elderly Medicare beneficiaries using inpatient and outpatient claims [J].
Asch, SM ;
Sloss, EEM ;
Hogan, C ;
Brook, RH ;
Kravitz, RL .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2000, 284 (18) :2325-2333
[2]  
Bernstein CN, 1999, AM J EPIDEMIOL, V149, P916, DOI 10.1093/oxfordjournals.aje.a009735
[3]  
Brouch K, 2000, J AHIMA, V71, P52
[4]  
DELUSIGNAN S, 2001, MEDINFO, V10, P86
[5]  
DEYO RA, 1994, SPINE, V19, pS2083
[6]   Comparison of 2 methods for calculating adjusted survival curves from proportional hazards models [J].
Ghali, WA ;
Quan, HD ;
Brant, R ;
van Melle, G ;
Norris, CM ;
Faris, PD ;
Galbraith, PD ;
Knudtson, ML .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2001, 286 (12) :1494-1497
[7]   Congestive heart failure in the United States -: Is there more than meets the I(CD code)?: The Corpus Christi Heart Project [J].
Goff, DC ;
Pandey, DK ;
Chan, FA ;
Ortiz, C ;
Nichaman, MZ .
ARCHIVES OF INTERNAL MEDICINE, 2000, 160 (02) :197-202
[8]  
Hamilton WT, 2003, BRIT J GEN PRACT, V53, P929
[9]   Diabetes in Ontario - Determination of prevalence and incidence using a validated administrative data algorithm [J].
Hux, JE ;
Flintoft, V ;
Ivis, F ;
Bica, A .
DIABETES CARE, 2002, 25 (03) :512-516
[10]  
Joffres MR, 1997, AM J HYPERTENS, V10, P1097