1997
DOI: 10.1136/jamia.1997.0040233
|View full text |Cite
|
Sign up to set email alerts
|

Use of Commercial Record Linkage Software and Vital Statistics to Identify Patient Deaths

Abstract: We evaluate the ability of a microcomputer program (Automatch) to link patient records in our hospital's database (N = 253,836) with mortality files from California (N = 1,312,779) and the U.S. Social Security Administration (N = 13,341,581). We linked 96.5% of 3,448 in-hospital deaths, 99.3% for patients with social security numbers. None of 14,073 patients known to be alive (because they were subsequently admitted) was linked with California deaths, and only 6 (0.1%) of 6,444 were falsely identified as dead … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

3
102
0

Year Published

2000
2000
2014
2014

Publication Types

Select...
9

Relationship

0
9

Authors

Journals

citations
Cited by 189 publications
(105 citation statements)
references
References 1 publication
3
102
0
Order By: Relevance
“…This was close to the odds ratio for ANLL reported by Altmann et al 12 (odds ratio of 11.1). Narod et al 8 also reported a higher-than-expected rate of congenital abnormalities in children with cancer.…”
Section: Discussionsupporting
confidence: 73%
See 1 more Smart Citation
“…This was close to the odds ratio for ANLL reported by Altmann et al 12 (odds ratio of 11.1). Narod et al 8 also reported a higher-than-expected rate of congenital abnormalities in children with cancer.…”
Section: Discussionsupporting
confidence: 73%
“…11 It has been reported previously that hospital data can be accurately linked with state and national vital statistics using this record linkage software. 12 …”
Section: Linkagesmentioning
confidence: 99%
“…Death was identified from health plan administrative data (including proxy reporting), California death certificate data, and Social Security Administrative vital status files. 35,36 The primary outcome of interest was occurrence of incident renal cancer during the study period identified from the Kaiser Permanente Cancer Registry. Renal cancer histology codes used in our dataset were in compliance with the World Health Organization International Classification of Diseases for Oncology international standard for primary site and histology (December 2009; www.seer.cancer.gov/ icd-o-3/index.html).…”
Section: Follow-up and Outcomesmentioning
confidence: 99%
“…This index has been shown to be highly specific and unbiased (21,22). Follow-up was for a mean of 3 years for nondiabetic as well as diabetic patients.…”
Section: End Pointsmentioning
confidence: 99%