Literature DB >> 15893348

Quality and variability of osteoporosis data in general practice computer records: implications for disease registers.

S de Lusignan1, T Chan, O Wood, N Hague, T Valentin, J Van Vlymen.   

Abstract

OBJECTIVE: To determine the extent to which routinely collected general practitioner computer data could be used to create disease registers of patients with osteoporosis, and to report any improvement in data quality since previous studies. STUDY
DESIGN: Audit using anonymized data extracted from general practice computer records from across England.
METHODS: Morbidity Query Information and Export Syntax (MIQUEST) software was used to extract structured data from the 78 volunteer practices that participated in the study. The data were aggregated and analysed.
RESULTS: There were 100-fold differences in the rates of recording of relevant data. Many patients receiving treatment had no diagnostic codes. Data about secondary causes of osteoporosis and fractures were more consistently recorded than data relating to falls. There were no data to indicate whether fractures were low impact. T-scores, the gold-standard measure of bone density, were very infrequently recorded.
CONCLUSIONS: Sufficient data about secondary causes of osteoporosis exist, and these could be searched to identify patients at risk. Meanwhile, fracture recoding could be improved, including likely fragility fractures, and T-scores could be added to computer records. A systematic approach is needed to raise the computer records to a standard where they can be used as valid and reliable disease registers.

Entities:  

Mesh:

Year:  2005        PMID: 15893348     DOI: 10.1016/j.puhe.2004.10.018

Source DB:  PubMed          Journal:  Public Health        ISSN: 0033-3506            Impact factor:   2.427


  7 in total

1.  Temporal and within practice variability in the health improvement network.

Authors:  Kevin Haynes; Warren B Bilker; Tom R Tenhave; Brian L Strom; James D Lewis
Journal:  Pharmacoepidemiol Drug Saf       Date:  2011-07-13       Impact factor: 2.890

2.  Using computers to identify non-compliant people at increased risk of osteoporotic fractures in general practice: a cross-sectional study.

Authors:  S de Lusignan; J van Vlymen; N Hague; N Dhoul
Journal:  Osteoporos Int       Date:  2006-08-24       Impact factor: 4.507

3.  Clinical risk factors for fracture among postmenopausal patients at risk for fracture: a historical cohort study using electronic medical record data.

Authors:  Joanne LaFleur; Carrie McAdam-Marx; Stephen S Alder; Xiaoming Sheng; Carl V Asche; Jonathan Nebeker; Diana I Brixner; Stuart L Silverman
Journal:  J Bone Miner Metab       Date:  2010-08-06       Impact factor: 2.626

4.  Capture of osteoporosis and fracture information in an electronic medical record database from primary care.

Authors:  Sonya Allin; Sarah Munce; Susan Jaglal; Debra Butt; Jacqueline Young; Karen Tu
Journal:  AMIA Annu Symp Proc       Date:  2014-11-14

Review 5.  Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research.

Authors:  Nicole Gray Weiskopf; Chunhua Weng
Journal:  J Am Med Inform Assoc       Date:  2012-06-25       Impact factor: 4.497

6.  Improving Osteoporosis Management in Primary Care: An Audit of the Impact of a Community Based Fracture Liaison Nurse.

Authors:  Tom Chan; Simon de Lusignan; Alun Cooper; Mary Elliott
Journal:  PLoS One       Date:  2015-08-27       Impact factor: 3.240

7.  Can the Use of Bayesian Analysis Methods Correct for Incompleteness in Electronic Health Records Diagnosis Data? Development of a Novel Method Using Simulated and Real-Life Clinical Data.

Authors:  Elizabeth Ford; Philip Rooney; Peter Hurley; Seb Oliver; Stephen Bremner; Jackie Cassell
Journal:  Front Public Health       Date:  2020-03-05
  7 in total

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