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      A comparison of the recording of comorbidity in primary and secondary care by using the Charlson Index to predict short-term and long-term survival in a routine linked data cohort

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          Abstract

          Objective

          Hospital admission records provide snapshots of clinical histories for a subset of the population admitted to hospital. In contrast, primary care records provide continuous clinical histories for complete populations, but might lack detail about inpatient stays. Therefore, combining primary and secondary care records should improve the ability of comorbidity scores to predict survival in population-based studies, and provide better adjustment for case-mix differences when assessing mortality outcomes.

          Design

          Cohort study.

          Setting

          English primary and secondary care 1 January 2005 to 1 January 2010.

          Participants

          All patients 20 years and older registered to a primary care practice contributing to the linked Clinical Practice Research Datalink from England.

          Outcome

          The performance of the Charlson index with mortality was compared when derived from either primary or secondary care data or both. This was assessed in relation to short-term and long-term survival, age, consultation rate, and specific acute and chronic diseases.

          Results

          657 264 people were followed up from 1 January 2005. Although primary care recorded more comorbidity than secondary care, the resulting C statistics for the Charlson index remained similar: 0.86 and 0.87, respectively. Higher consultation rates and restricted age bands reduced the performance of the Charlson index, but the index's excellent performance persisted over longer follow-up; the C statistic was 0.87 over 1 year, and 0.85 over all 5 years of follow-up. The Charlson index derived from secondary care comorbidity had a greater effect than primary care comorbidity in reducing the association of upper gastrointestinal bleeding with mortality. However, they had a similar effect in reducing the association of diabetes with mortality.

          Conclusions

          These findings support the use of the Charlson index from linked data and show that secondary care comorbidity coding performed at least as well as that derived from primary care in predicting survival.

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          Most cited references18

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          Validity of diagnostic coding within the General Practice Research Database: a systematic review.

          The UK-based General Practice Research Database (GPRD) is a valuable source of longitudinal primary care records and is increasingly used for epidemiological research. To conduct a systematic review of the literature on accuracy and completeness of diagnostic coding in the GPRD. Systematic review. Six electronic databases were searched using search terms relating to the GPRD, in association with terms synonymous with validity, accuracy, concordance, and recording. A positive predictive value was calculated for each diagnosis that considered a comparison with a gold standard. Studies were also considered that compared the GPRD with other databases and national statistics. A total of 49 papers are included in this review. Forty papers conducted validation of a clinical diagnosis in the GPRD. When assessed against a gold standard (validation using GP questionnaire, primary care medical records, or hospital correspondence), most of the diagnoses were accurately recorded in the patient electronic record. Acute conditions were not as well recorded, with positive predictive values lower than 50%. Twelve papers compared prevalence or consultation rates in the GPRD against other primary care databases or national statistics. Generally, there was good agreement between disease prevalence and consultation rates between the GPRD and other datasets; however, rates of diabetes and musculoskeletal conditions were underestimated in the GPRD. Most of the diagnoses coded in the GPRD are well recorded. Researchers using the GPRD may want to consider how well the disease of interest is recorded before planning research, and consider how to optimise the identification of clinical events.
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            Risk assessment after acute upper gastrointestinal haemorrhage.

            The aim of this study was to establish the relative importance of risk factors for mortality after acute upper gastrointestinal haemorrhage, and to formulate a simple numerical scoring system that categorizes patients by risk. A prospective, unselected, multicentre, population based study was undertaken using standardised questionnaires in two phases one year apart. A total of 4185 cases of acute upper gastrointestinal haemorrhage over the age of 16 identified over a four month period in 1993 and 1625 cases identified subsequently over a three month period in 1994 were included in the study. It was found that age, shock, comorbidity, diagnosis, major stigmata of recent haemorrhage, and rebleeding are all independent predictors of mortality when assessed using multiple logistic regression. A numerical score using these parameters has been developed that closely follows the predictions generated by logistical regression equations. Haemoglobin, sex, presentation (other than shock), and drug therapy (non-steroidal anti-inflammatory drugs and anticoagulants) are not represented in the final model. When tested for general applicability in a second population, the scoring system was found to reproducibly predict mortality in each risk category. In conclusion, a simple numerical score can be used to categorize patients presenting with acute upper gastrointestinal haemorrhage by risk of death. This score can be used to determine case mix when comparing outcomes in audit and research and to calculate risk standardised mortality. In addition, this risk score can identify 15% of all cases with acute upper gastrointestinal haemorrhage at the time of presentation and 26% of cases after endoscopy who are at low risk of rebleeding and negligible risk of death and who might therefore be considered for early discharge or outpatient treatment with consequent resource savings.
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              Validation of information recorded on general practitioner based computerised data resource in the United Kingdom.

              To determine the extent of agreement between clinical information recorded on surgery computers of selected general practitioners and similar information in manual records of letters received from hospital consultants and kept in the general practitioners' files. Hospital consultants' letters in the manual records of selected general practitioners were photocopied and the consultants' clinical diagnoses were compared with diagnoses recorded on computer. General practices in the United Kingdom using computers provided by VAMP Health for recording clinical information. 2491 patients who received one of three non-steroidal anti-inflammatory drugs and who attended 58 practices whose computer recorded data were considered after a preliminary review to be of satisfactory quality. Among 1191 patients for whom consultants' letters were forwarded a clinical diagnosis reflecting the diagnosis noted on a consultant letter was present on the computer record for 1038 (87%). Clinical information available on the computer records of the general practitioners who participated in this study is satisfactory for many clinical studies.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2015
                5 June 2015
                : 5
                : 6
                : e007974
                Affiliations
                Division of Epidemiology and Public Health, Nottingham City Hospital, University of Nottingham , Nottingham, Nottinghamshire, UK
                Author notes
                [Correspondence to ] Dr CJ Crooks; colincrooks@ 123456doctors.org.uk
                Author information
                http://orcid.org/0000-0002-1135-9356
                Article
                bmjopen-2015-007974
                10.1136/bmjopen-2015-007974
                4458584
                26048212
                2d61bbd2-ed63-408f-8128-f8bc8dfc99d2
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions

                This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

                History
                : 14 February 2015
                : 28 April 2015
                : 20 May 2015
                Categories
                Epidemiology
                Research
                1506
                1692
                1696
                1704
                1730

                Medicine
                epidemiology,gastroenterology,general medicine (see internal medicine),primary care,statistics & research methods

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