scholarly journals Identifying all persons in Wales with type 1 diabetes mellitus using routinely collected linked data

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
James Rafferty ◽  
Ashley Akbari ◽  
Mark D Atkinson ◽  
Stephen Bain ◽  
Stephen Luzio ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Primary Care ◽  
False Positive ◽  
Secondary Care ◽  
Population Level ◽  
International Classification Of Disease ◽  
Primary Care Data ◽  
Diagnosis Codes ◽  
Diabetes Status ◽  
Autoimmune Condition

IntroductionType 1 diabetes mellitus (T1DM) is an autoimmune condition characterised by hyperglycaemia, caused by the destruction of insulin producing β-cells in the pancreas. Previous epidemiological population level studies of T1DM and its complications have typically used recorded T1DM diagnoses to determine diabetes status and define cohorts. Objectives and ApproachThe objective was to identify all persons with T1DM in Wales from Primary (~70\% population coverage) and Secondary Care (100% coverage) data held in the Secure Anonymised Information Linkage (SAIL) databank. People with a coded T1DM diagnosis (using Read codes in Primary Care data and International Classification of Disease (ICD10) codes in Secondary Care data), plus either insulin prescribed shortly after diagnosis or a hospital admission for diabetic ketoacidosis were identified as having T1DM. A sub-group of this SAIL e-cohort were validated using a register of persons diagnosed with T1DM in Wales under 15 years old (Brecon cohort). Results18,285 people had a T1DM diagnosis and 10,539 had more T1DM than type 2 diabetes mellitus (T2DM) diagnoses. 6,375 persons were identified with T1DM in Primary Care data using our criteria, with a median diagnosis age of 19.2 years (interquartile range 11.0, 35.5). 47.5\% were diagnosed under 18 years of age. 39.6% of people with a T1DM diagnosis did not have T1DM using our criteria. False positive and negative rates of 4.8% and 4.5% respectively were achieved by comparing persons in the SAIL e-cohort against the Brecon cohort. Clinician estimated false positive and negative rates were 1.4% and 3.9% respectively. The prevalence of T1DM in Wales in 2016 was 0.37% or 11,049 people. Conclusion/ImplicationsOur criteria for identifying people with T1DM was more reliable than using diagnosis codes alone, allowing for a more accurate, efficient and reproducible means of identifying individuals with T1DM for researchers utilising the SAIL databank, and other national health repositories.

scholarly journals Primary care risk stratification in COPD using routinely collected data: a secondary data analysis

2019 ◽  
Vol 29 (1) ◽  
Author(s):  
Matthew Johnson ◽  
Lucy Rigge ◽  
David Culliford ◽  
Lynn Josephs ◽  
Mike Thomas ◽  
...  
Keyword(s):  
Primary Care ◽  
Risk Stratification ◽  
Data Quality ◽  
Risk Score ◽  
Secondary Care ◽  
Risk Scores ◽  
Average Risk ◽  
Primary Care Data ◽  
Copd Patients ◽  
Dose Index

AbstractMost clinical contacts with chronic obstructive pulmonary disease (COPD) patients take place in primary care, presenting opportunity for proactive clinical management. Electronic health records could be used to risk stratify diagnosed patients in this setting, but may be limited by poor data quality or completeness. We developed a risk stratification database algorithm using the DOSE index (Dyspnoea, Obstruction, Smoking and Exacerbation) with routinely collected primary care data, aiming to calculate up to three repeated risk scores per patient over five years, each separated by at least one year. Among 10,393 patients with diagnosed COPD, sufficient primary care data were present to calculate at least one risk score for 77.4%, and the maximum of three risk scores for 50.6%. Linked secondary care data revealed primary care under-recording of hospital exacerbations, which translated to a slight, non-significant cohort average risk score reduction, and an understated risk group allocation for less than 1% of patients. Algorithmic calculation of the DOSE index is possible using primary care data, and appears robust to the absence of linked secondary care data, if unavailable. The DOSE index appears a simple and practical means of incorporating risk stratification into the routine primary care of COPD patients, but further research is needed to evaluate its clinical utility in this setting. Although secondary analysis of routinely collected primary care data could benefit clinicians, patients and the health system, standardised data collection and improved data quality and completeness are also needed.

scholarly journals Exploring the Effect of Nice Guidelines on Prescribing for Childhood Atopic Eczema in Primary Care with An Interrupted Time Series

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
LIW Schreuders ◽  
SJ Ersser ◽  
C Thompson
Keyword(s):  
Primary Care ◽  
Atopic Eczema ◽  
Best Practice ◽  
Secondary Analysis ◽  
Clinical Excellence ◽  
Population Level ◽  
Prescribing Practices ◽  
Nice Guideline ◽  
Primary Care Data ◽  
First Time

IntroductionAtopic eczema (AE) is a chronic inflammatory skin condition affecting 20-32% of UK children, typically diagnosed and treated in primary care. National Institute of Health and Clinical Excellence (NICE, 2007) guidelines recommend all children presenting with AE in primary care are prescribed emollient; topical corticosteroids (TCS) are co-prescribed if indicated by severity. The proportion of children receiving recommended treatment and NICE guideline impact on prescribing practices is unknown. This study was the first to access population-level UK-wide primary care dermatology data from SystmOne. Objectives and ApproachWe explored treatment patterns for childhood AE documented in primary care data from SystmOne. Secondary analysis of retrospective, longitudinal primary care data for childhood (<12yo) AE-related consultations from 2002 to 2013. Four treatment scenarios were compared: 1) emollient and TCS co-prescribed (NICE-recommended for moderate-high severity presentation), 2) emollient only (NICE-recommended for mild severity presentation), 3) TCS only (not recommended), or 4) no topical treatment prescribed (not recommended). ARIMA used to examine step and trend-change in prescribing following guideline release. ResultsNICE-recommended treatments were more common following guideline release: emollient+TCS increased 8% (95%CI 7.7,8.7%); emollient alone increased 8% (95%CI 7.8,8.8%); TCS alone decreased 5% (95%CI -4.2,-5.1%); and no treatment decreased 11% (95%CI -11.3,-12.3%). Longitudinal analysis indicated increased NICE-recommended prescribing was due to pre-existing trends not significantly altered by the guideline release. By December 2013, ~334 children per month were still not receiving recommended AE treatment (37% of ~900 first-time consultations/month). Conclusion / ImplicationsAdherence to best practice guidelines for treatment and management of childhood atopic eczema is currently sub-optimal. Significant barriers to optimal use of this data could be achieved by improving design of data input interfaces with secondary use for research in mind. As well as study findings, this presentation will share challenges associated with utilising routinely collected SystmOne data for research purposes for the first time in the UK.

scholarly journals Determinants of referral of women with urinary incontinence to specialist services: a national cohort study using primary care data from the UK

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Ipek Gurol-Urganci ◽  
Rebecca S. Geary ◽  
Jil B. Mamza ◽  
Masao Iwagami ◽  
Dina El-Hamamsy ◽  
...  
Keyword(s):  
Primary Care ◽  
Urinary Incontinence ◽  
Cohort Study ◽  
Secondary Care ◽  
Referral Rates ◽  
Primary Care Data ◽  
Specialist Services ◽  
One Year ◽  
The Impact ◽  
Minority Ethnic

Abstract Background Female urinary incontinence is underdiagnosed and undertreated in primary care. There is little evidence on factors that determine whether women with urinary incontinence are referred to specialist services. This study aimed to investigate characteristics associated with referrals from primary to specialist secondary care for urinary incontinence. Methods We carried out a cohort study, using primary care data from over 600 general practices contributing to the Clinical Practice Research Datalink (CPRD) in the United Kingdom. We used multi-level logistic regression to estimate adjusted odds ratios (aOR) that reflect the impact of patient and GP practice-level characteristics on referrals to specialist services in secondary care within 30 days of a urinary incontinence diagnosis. All women aged ≥18 years newly diagnosed with urinary incontinence between 1 April 2004 and 31 March 2013 were included. One-year referral was estimated with death as competing event. Results Of the 104,466 included women (median age: 58 years), 28,476 (27.3%) were referred within 30 days. Referral rates decreased with age (aOR 0.34, 95% CI 0.31–0.37, comparing women aged ≥80 with those aged 40–49 years) and was lower among women who were severely obese (aOR 0.84, 95% CI 0.78–0.90), smokers (aOR 0.94, 95% CI 0.90–0.98), women from a minority-ethnic backgrounds (aOR 0.76, 95% CI 0.65–0.89 comparing Asian with white women), women with pelvic organ prolapse (aOR 0.77, 95% CI 0.68–0.87), and women in Scotland (aOR 0.60, 95% CI 0.46–0.78, comparing women in Scotland and England). One-year referral rate was 34.0% and the pattern of associations with patient characteristics was almost the same as for 30-day referrals. Conclusions About one in four women with urinary incontinence were referred to specialist secondary care services within one month after a UI diagnosis and one in three within one year. Referral rates decreased with age which confirms concerns that older women with UI are less likely to receive care according to existing clinical guidelines. Referral rates were also lower in women from minority-ethnic backgrounds. These finding may reflect clinicians’ beliefs about the appropriateness of referral, differences in women’s preferences for treatment, or other factors leading to inequities in referral for urinary incontinence.

More severe mental illness is more concentrated in deprived areas

1999 ◽  
Vol 175 (6) ◽  
pp. 544-548 ◽  
Author(s):  
Gyles R. Glover ◽  
Morven Leese ◽  
Paul McCrone
Keyword(s):  
Mental Health ◽  
Primary Care ◽  
Mental Illness ◽  
Secondary Care ◽  
Mental Health Problems ◽  
Population Level ◽  
Mentally Disordered Offenders ◽  
Health Care Need ◽  
Mentally Disordered ◽  
The Uk

BackgroundThe greater frequency of mental illness in deprived and inner-city populations is well recognised; allocation of funds in the UK health service makes some allowance for this. However, it is not clear whether the differences are similar for all levels of mental health care need.AimsTo study the range in prevalence of mental health problems and care at primary care, general secondary care and forensic care levels.MethodWe used mainly descriptive statistics to study evidence available from existing sources – some based on indicators of likely need, some on observed prevalance of treatment.ResultsAmong English health authority areas, the most morbid have about twice the prevalence of primary care level mental illness of the least morbid. For secondary care the ratio is between 2.5 and 4 to 1, while for services for mentally disordered offenders it is in excess of 20:1.ConclusionsWhere needs indices are used for resource allocation, responsible authorities should ensure that they produce ranges reflecting the full compass of services funded. For forensic services the range of morbidity levels may be so great that funding needs to rest at a larger population level than that of health authorities.

‘Diagnostic downshift’: clinical and system consequences of extrapolating secondary care testing tactics to primary care

2021 ◽  
pp. bmjebm-2020-111629
Author(s):  
Imran Mohammed Sajid ◽  
Kathleen Frost ◽  
Ash K Paul
Keyword(s):  
Primary Care ◽  
False Positive ◽  
Secondary Care ◽  
Market Failure ◽  
Unintended Consequences ◽  
Service Utilisation ◽  
Economic Returns ◽  
Patient Anxiety ◽  
Predictive Values ◽  
Multiplier Effects

Numerous drivers push specialist diagnostic approaches down to primary care (‘diagnostic downshift’), intuitively welcomed by clinicians and patients. However, primary care’s different population and processes result in under-recognised, unintended consequences. Testing performs poorer in primary care, with indication creep due to earlier, more undifferentiated presentation and reduced accuracy due to spectrum bias and the ‘false-positive paradox’. In low-prevalence settings, tests without near-100% specificity have their useful yield eclipsed by greater incidental or false-positive findings. Ensuing cascades and multiplier effects can generate clinician workload, patient anxiety, further low-value tests, referrals, treatments and a potentially nocebic population ‘disease’ burden of unclear benefit. Increased diagnostics earlier in pathways can burden patients and stretch general practice (GP) workloads, inducing downstream service utilisation and unintended ‘market failure’ effects. Evidence is tenuous for reducing secondary care referrals, providing patient reassurance or meaningfully improving clinical outcomes. Subsequently, inflated investment in per capita testing, at a lower level in a healthcare system, may deliver diminishing or even negative economic returns. Test cost poorly represents ‘value’, neglecting under-recognised downstream consequences, which must be balanced against therapeutic yield. With lower positive predictive values, more tests are required per true diagnosis and cost-effectiveness is rarely robust. With fixed secondary care capacity, novel primary care testing is an added cost pressure, rarely reducing hospital activity. GP testing strategies require real-world evaluation, in primary care populations, of all downstream consequences. Test formularies should be scrutinised in view of the setting of care, with interventions to focus rational testing towards those with higher pretest probabilities, while improving interpretation and communication of results.

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