The importance of defining periods of complete mortality reporting for research using automated data from primary care

被引:252
作者
Maguire, Andrew [1 ,2 ]
Blak, Betina T. [1 ]
Thompson, Mary [2 ]
机构
[1] EPIC, London NW1 0QG, England
[2] London Sch Hyg & Trop Med, Dept Epidemiol & Populat Hlth, London WC1, England
关键词
mortality; data quality; primary care; ROUTINE GENERAL-PRACTICE; INSULIN GLARGINE; UK; VALIDATION; DETEMIR; PEOPLE; TYPE-1;
D O I
10.1002/pds.1688
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Purpose To define periods of acceptable mortality reporting in primary care and to demonstrate through examples the implication for research using automated medical data. Methods Annual death counts were obtained for each primary care practice participating in The Health Improvement Network "THIN" (UK). Expected counts were calculated from national death rates, accounting for the practice's age/sex structure. The standardized mortality ratio (SMR) was calculated with 95% confidence intervals (CI). A visual review process was undertaken to assign the year from which the practice had acceptable mortality reporting (AMR). The process involved reviewer pairs who were blinded to each other's decisions. Patterns of death reporting were checked. The AMR year was applied as a filter to THIN data to assess its impact on the SMR. Results For most practices the SMR was relatively stable and the AMR year was easily identified with 86% agreement between the blinded reviewer pairs. Applying the AMR to THIN removed under-reporting of death. However, the total computerized follow-up reduced from 37 to 32 million patient-years. Problematic death recording patterns included some practices keeping only live patient records when converting their software systems thereby creating 'immortal periods' prior to this moment, and peaks occurring when practices updated the vital status of their patients' records. Conclusions This is the first time that an external standard has been used to assess completeness of mortality in automated primary care data. The resulting AMR year provides a natural filter for research and avoids biases associated with 'immortal periods', record updating and under-reporting. Copyright (C) 2008 John Wiley & Sons, Ltd.
引用
收藏
页码:76 / 83
页数:8
相关论文
共 17 条
[1]  
ADAMS J, 2003, J PUBLIC HLTH, V27, P101
[2]  
[Anonymous], 1987, STAT METHODS CANC RE
[3]   Data quality improvement in general practice [J].
Brouwer, H. J. ;
Bindels, P. J. E. ;
Van Weert, H. C. .
FAMILY PRACTICE, 2006, 23 (05) :529-536
[4]   Is an internal comparison better than using national data when estimating mortality in longitudinal studies? [J].
Card, T. R. ;
Solaymani-Dodaran, M. ;
Hubbard, R. ;
Logan, R. F. A. ;
West, J. .
JOURNAL OF EPIDEMIOLOGY AND COMMUNITY HEALTH, 2006, 60 (09) :819-821
[5]   The outcome of care in people with type 1 and type 2 diabetes following switching to treatment with either insulin glargine or insulin detemir in routine general practice in the UK: a retrospective database analysis [J].
Currie, Craig J. ;
Poole, Chris D. ;
Tetlow, Tony ;
Holmes, Paul ;
McEwan, Phil .
CURRENT MEDICAL RESEARCH AND OPINION, 2007, 23 :S33-S39
[6]   Primary care, core values - Developing primary care: gatekeeping, commissioning, and managed care [J].
Dixon, J ;
Holland, P ;
Mays, N .
BRITISH MEDICAL JOURNAL, 1998, 317 (7151) :125-128
[7]  
*GEN REG OFF SCOTL, 2007, INF SCOTL PEOPL STAT
[8]  
HALL GC, 1998, PHARM MED, V2, P345
[9]   Performance of the QRISK cardiovascular risk prediction algorithm in an independent UK sample of patients from general practice: a validation study [J].
Hippisley-Cox, J. ;
Coupland, C. ;
Vinogradova, Y. ;
Robson, J. ;
Brindle, P. .
HEART, 2008, 94 (01) :34-39
[10]   Accuracy of data in computer-based patient records [J].
Hogan, WR ;
Wagner, MM .
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 1997, 4 (05) :342-355