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

Maguire, Andrew; Blak, Betina; Thompson, Mary Ann

doi:10.1002/pds.1688

Cited by 274 publications

(257 citation statements)

References 9 publications

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“…Only data recorded after each practice's Acceptable Mortality Reporting (AMR) year were analysed, 6 except for death rates which were also analysed without applying the AMR year, i.e. all years were included.…”

Section: Methodsmentioning

confidence: 99%

Generalisability of The Health Improvement Network (THIN) database: demographics, chronic disease prevalence and mortality rates

Blak

Thompson²,

Dattani³

et al. 2011

Journal of Innovation in Health Informatics

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525

692

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Introduction The degree of generalisability of patient databases to the general population is important for interpreting database research. This report describes the representativeness of The Health Improvement Network (THIN), a UK primary care database, of the UK population. Methods Demographics, deprivation (Townsend), Quality and Outcomes Framework (QOF) condition prevalence and deaths from THIN were compared with national statistical and QOF 2006/ 2007 data. Results Demographics were similar although THIN contained fewer people aged under 25 years. Condition prevalence was comparable, e.g. 3.5% diabetes prevalence in THIN, 3.7% nationally. More

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Section: Methodsmentioning

confidence: 99%

Generalisability of The Health Improvement Network (THIN) database: demographics, chronic disease prevalence and mortality rates

Blak

Thompson²,

Dattani³

et al. 2011

Journal of Innovation in Health Informatics

Self Cite

525

692

View full text Add to dashboard Cite

show abstract

“…It was, however, in the mid-1990s that an increasing number of general practices became fully computerised 29 and in this study we utilised data from 1 January 1995, or when general practices met data quality standards. [28][29][30] Pregnancy cohort and mother-child cohorts…”

Section: The Health Improvement Network Primary Care Database and Thementioning

confidence: 99%

Risks and benefits of psychotropic medication in pregnancy: cohort studies based on UK electronic primary care health records

Petersen

McCrea

Sammon

et al. 2016

Health Technol Assess

133

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BackgroundAlthough many women treated with psychotropic medication become pregnant, no psychotropic medication has been licensed for use in pregnancy. This leaves women and their health-care professionals in a treatment dilemma, as they need to balance the health of the woman with that of the unborn child. The aim of this project was to investigate the risks and benefits of psychotropic medication in women treated for psychosis who become pregnant.Objective(s)(1) To provide a descriptive account of psychotropic medication prescribed before pregnancy, during pregnancy and up to 15 months after delivery in UK primary care from 1995 to 2012; (2) to identify risk factors predictive of discontinuation and restarting of lithium (multiple manufacturers), anticonvulsant mood stabilisers and antipsychotic medication; (3) to examine the extent to which pregnancy is a determinant for discontinuation of psychotropic medication; (4) to examine prevalence of records suggestive of adverse mental health, deterioration or relapse 18 months before and during pregnancy, and up to 15 months after delivery; and (5) to estimate absolute and relative risks of adverse maternal and child outcomes of psychotropic treatment in pregnancy.DesignRetrospective cohort studies.SettingPrimary care.ParticipantsWomen treated for psychosis who became pregnant, and their children.InterventionsTreatment with antipsychotics, lithium or anticonvulsant mood stabilisers.Main outcome measuresDiscontinuation and restarting of treatment; worsening of mental health; acute pre-eclampsia/gestational hypertension; gestational diabetes; caesarean section; perinatal death; major congenital malformations; poor birth outcome (low birthweight, preterm birth, small for gestational age, low Apgar score); transient poor birth outcomes (tremor, agitation, breathing and muscle tone problems); and neurodevelopmental and behavioural disorders.Data sourcesClinical Practice Research Datalink database and The Health Improvement Network primary care database.ResultsPrescribing of psychotropic medication was relatively constant before pregnancy, decreased sharply in early pregnancy and peaked after delivery. Antipsychotic and anticonvulsant treatment increased over the study period. The recording of markers of worsening mental health peaked after delivery. Pregnancy was a strong determinant for discontinuation of psychotropic medication. However, between 40% and 76% of women who discontinued psychotropic medication before or in early pregnancy restarted treatment by 15 months after delivery. The risk of major congenital malformations, and neurodevelopmental and behavioural outcomes in valproate (multiple manufacturers) users was twice that in users of other anticonvulsants. The risks of adverse maternal and child outcomes in women who continued antipsychotic use in pregnancy were not greater than in those who discontinued treatment before pregnancy.LimitationsA few women would have received parts of their care outside primary care, which may not be captured in this analysis. Likewise, the analyses were based on prescribing data, which may differ from usage.ConclusionsPsychotropic medication is prescribed before, during and after pregnancy. Many women discontinue treatment before or during early pregnancy and then restart again in late pregnancy or after delivery. Our results support previous associations between valproate and adverse child outcomes but we found no evidence of such an association for antipsychotics.Future workFuture research should focus on (1) curtailing the use of sodium valproate; (2) estimating the benefits of psychotropic drug use in pregnancy; and (3) investigating the risks associated with lifestyle choices that are more prevalent among women using psychotropic drugs.Funding detailsThe National Institute for Health Research Health Technology Assessment programme.

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“…The THIN database presently contains records for .8 million patients, of whom ;4 million are actively registered and can be followed prospectively (12). Available data include patient demographics, medical history (including diagnoses and health contacts), biochemistry and microbiology test results, and pharmaceutical prescriptions.…”

Section: Data Sourcementioning

confidence: 99%

The impact of treatment non-compliance on mortality in people with type 1 diabetes

Currie

Peyrot

Morgan³

et al. 2013

Journal of Diabetes and its Complications

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OBJECTIVEdTo assess the association of compliance with treatment (medication and clinic appointments) and all-cause mortality in people with insulin-treated type 2 diabetes.RESEARCH DESIGN AND METHODSdData were extracted from U.K. general practice records and included patients (N = 15,984) who had diagnostic codes indicative of type 2 diabetes or who had received a prescription for an oral antidiabetic agent and were treated with insulin. Records in the 30 months before the index date were inspected for clinical codes (recorded at consultation) indicating medication noncompliance or medical appointment nonattendance. Noncompliance was defined as missing more than one scheduled visit or having at least one provider code for not taking medications as prescribed. Relative survival postindex date was compared by determining progression to all-cause mortality using Cox proportional hazards models.RESULTSdThose identified as clinic nonattenders were more likely to be smokers, younger, have higher HbA 1c , and have more prior primary care contacts and greater morbidity (P , 0.001). Those identified as medication noncompliers were more likely to be women (P = 0.001), smokers (P = 0.014), and have higher HbA 1c , more prior primary care contacts, and greater morbidity (all P , 0.001). After adjustment for confounding factors, medication noncompliance (hazard ratio 1.579 [95% CI 1.167-2.135]), clinic nonattendance of one or two missed appointments (1.163 [1.042-1.299]), and clinic nonattendance of greater than two missed appointments (1.605 [1.356-1.900]) were independent risk factors for all-cause mortality.CONCLUSIONSdMedication noncompliance and clinic nonattendance, assessed during routine care by primary care physicians or their staff, were independently associated with increased all-cause mortality in patients with type 2 diabetes receiving insulin.

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

Abstract: 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.

Cited by 274 publications

References 9 publications

Generalisability of The Health Improvement Network (THIN) database: demographics, chronic disease prevalence and mortality rates

Generalisability of The Health Improvement Network (THIN) database: demographics, chronic disease prevalence and mortality rates

Risks and benefits of psychotropic medication in pregnancy: cohort studies based on UK electronic primary care health records

The impact of treatment non-compliance on mortality in people with type 1 diabetes

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