Data quality in primary care, Scotland.

BACKGROUND AND AIMS: This project explores primary care data quality (DQ) across Scotland. METHODS AND RESULTS: A survey was sent to primary care staff in winter 2019. National data regarding Quality and Outcomes Framework (QOF) performance indicators and the GP software system used was obtained, analysed with T-tests and Chi-squared tests. Overall QOF performance with non-financial incentives from 918 practices was 77%. There was no significant difference with overall QOF performance against GP system (p = 0.46) or if the practice had a coder (p = 0.06). From the survey, search systems that make it hard to search for particular codes was the most important barrier to DQ; 61% of respondents (n = 491) felt there was particular information GPs should code, 16% of respondents stated that hospital discharge letters generally include corresponding codes and 9% for outpatient correspondence; 43% stated their practice had undertaken steps to improve DQ, training was the most common initiative, followed by workflow optimisation, dedicated coder(s), audit, guidelines and using code lists; 80% (n = 475) of respondents had received training in using their GP system, an average of eight years ago. CONCLUSION: Obtaining improved GP systems, training, agreeing what GPs should code and improving transfer of data should be explored.

Impact of medicines regulatory risk communications in the UK on prescribing and clinical outcomes: Systematic review, time series analysis and meta-analysis.

AIMS: Regulatory risk communications are important to ensure medication safety, but their impact is poorly understood. The aim was to quantify the impact of UK risk communications on medication use and other outcomes. METHODS: We conducted a systematic review of studies reporting prescribing/health outcome data relevant to UK regulatory risk communication. Data were reanalysed using interrupted time series regression 12 months after each regulatory intervention. Mean changes were pooled using random-effects generic inverse variance examining the following subgroups: drug withdrawals; restrictions/changes in indications; be aware messages without specific recommendations for action; communication via direct healthcare practitioner communications; communication via drug bulletins. RESULTS: Of 11 466 articles screened, 40 studies examining 25 UK regulatory risk communications were included. Product withdrawals, restriction in indications and be aware communications were associated with relative mean changes of -78% (95% confidence interval [CI] -60 to -96%), -34% (95% confidence interval [CI] -12 to -55%) and -11% (95%CI -8 to -15%) in targeted drug prescribing respectively. Direct healthcare professional communications were associated with relative mean changes of -47% (95%CI -27 to -68%) compared to -13% (95%CI -6 to -20%) for drug bulletins. Of 7 studies examining unique health outcomes related to the safety concern, risk communications were associated with a mean -10% (95%CI -3 to -16%) decrease in intended and a 7% (95%CI 4 to 10%) increase in unintended health outcomes. DISCUSSION: UK regulatory risk communications were associated with significant changes in targeted prescribing and potential changes in clinical outcomes. Further research is needed to systematically study the impact of regulatory interventions.

Intelligent liver function testing (iLFT): A trial of automated diagnosis and staging of liver disease in primary care.

BACKGROUND & AIMS: Liver function tests (LFTs) are frequently requested blood tests which may indicate liver disease. LFTs are commonly abnormal, the causes of which can be complex and are frequently under investigated. This can lead to missed opportunities to diagnose and treat liver disease at an early stage. We developed an automated investigation algorithm, intelligent liver function testing (iLFT), with the aim of increasing the early diagnosis of liver disease in a cost-effective manner. METHODS: We developed an automated system that further investigated abnormal LFTs on initial testing samples to generate a probable diagnosis and management plan. We integrated this automated investigation algorithm into the laboratory management system, based on minimal diagnostic criteria, liver fibrosis estimation, and reflex testing for causes of liver disease. This algorithm then generated a diagnosis and/or management plan. A stepped-wedged trial design was utilised to compare LFT outcomes in general practices in the 6 months before and after introduction of the iLFT system. Diagnostic outcomes were collated and compared. RESULTS: Of eligible patients with abnormal LFTs, 490 were recruited to the control group and 64 were recruited to the intervention group. The primary diagnostic outcome was based on the general practitioner diagnosis, which agreed with the iLFT diagnosis in 67% of cases. In the iLFT group, the diagnosis of liver disease was increased by 43%. Additionally, there were significant increases in the rates of GP visits after diagnosis and the number of referrals to secondary care in the iLFT group. iLFT was cost-effective with a low initial incremental cost-effectiveness ratio of £284 per correct diagnosis, and a saving to the NHS of £3,216 per patient lifetime. CONCLUSIONS: iLFT increases liver disease diagnoses, improves quality of care, and is highly cost-effective. This can be achieved with minor changes to working practices and exploitation of functionality existing within modern laboratory diagnostics systems. LAY SUMMARY: There is a growing epidemic of advanced liver disease, this could be offset by early detection and management. Checking liver blood tests (LFTs) should be an opportunity to diagnose liver problems, but abnormal results are often incompletely investigated. In this study we were able to substantially increase the diagnostic yield of the abnormal LFTs using the automated intelligent LFT system. With the addition of referral recommendations and management plans, this strategy provides optimum investigation and management of LFTs and is cost saving to the NHS.

Benzodiazepines and non-benzodiazepine hypnotics - impact of a cluster adopted protocol on primary care prescribing.

BACKGROUND AND AIMS: Reduction of benzodiazepines and non-benzodiazepine hypnotics (BZDs and Z-drugs) prescribing is a priority. Dundee, Scotland, has a total of 25 general practices, split into four clusters. The cluster with the highest recorded prescribing of BZDs and Z-drugs adopted a prescribing protocol that aimed to reduce such prescribing. This paper evaluates the impact of this protocol. METHODS: Quarterly prescribing data were obtained from Information Service Division, NHS Scotland from Q1 2015/16 to Q4 2017/18. Data were split into four clusters and standardised to Defined Daily Dose (DDDs) per 1000 registered patients. Interrupted time series (ITS) analysis was performed to assess prescribing one year after this protocol was introduced. RESULTS: There was a crude reduction in prescribing of BZDs and Z-drugs across all GP practice clusters, but this related to an ongoing downward trend in prescribing. Allowing for this, in the cluster that adopted the protocol, ITS revealed there was no significant reduction attributable to the intervention in prescribing of DDD equivalent doses (-0.4%, 95% CI: -7.2 to 7.6). CONCLUSIONS: Introduction of a cluster-wide prescribing protocol did not provide significant reduction of prescribing. Although crude figures might suggest an improvement, ITS analysis revealed this not to be the case.

Recording COVID-19 consultations: review of symptoms, risk factors, and proposed SNOMED CT terms.

BACKGROUND: There is an urgent need for epidemiological research in primary care to develop risk assessment processes for patients presenting with COVID-19, but lack of a standardised approach to data collection is a significant barrier to implementation. AIM: To collate a list of relevant symptoms, assessment items, demographics, and lifestyle and health conditions associated with COVID-19, and match these data items with corresponding SNOMED CT clinical terms to support the development and implementation of consultation templates. DESIGN & SETTING: Published and preprint literature for systematic reviews, meta-analyses, and clinical guidelines describing the symptoms, assessment items, demographics, and/or lifestyle and health conditions associated with COVID-19 and its complications were reviewed. Corresponding clinical concepts from SNOMED CT, a widely used structured clinical vocabulary for electronic primary care health records, were identified. METHOD: Guidelines and published and unpublished reviews (N = 61) were utilised to collate a list of relevant data items for COVID-19 consultations. The NHS Digital SNOMED CT Browser was used to identify concept and descriptive identifiers. Key implementation challenges were conceptualised through a Normalisation Process Theory (NPT) lens. RESULTS: In total, 32 symptoms, eight demographic and lifestyle features, 25 health conditions, and 20 assessment items relevant to COVID-19 were identified, with proposed corresponding SNOMED CT concepts. These data items can be adapted into a consultation template for COVID-19. Key implementation challenges include: 1) engaging with key stakeholders to achieve 'buy in'; and 2) ensuring any template is usable within practice settings. CONCLUSION: Consultation templates for COVID-19 are needed to standardise data collection, facilitate research and learning, and potentially improve quality of care for COVID-19.

Physical and mental health comorbidities of epilepsy: Population-based cross-sectional analysis of 1.5 million people in Scotland.

PURPOSE: To measure the prevalence of physical and mental health comorbidities in people with epilepsy in a large population cohort, and to examine the prevalence of depression accounting for other physical comorbidity. METHODS: Population-based, cross-sectional descriptive epidemiology analysis of primary care electronic records for 1,510,742 people aged 14+ years, examining the prevalence of 39 comorbidities. RESULTS: 12,720 people with epilepsy were identified (prevalence 8.4/1000 population, 95% CI 8.3-8.5). Physical and mental health comorbidity was more common with epilepsy (mean of an additional 1.02 physical conditions difference, 95% CI 0.99-1.06). 69.9% of people with epilepsy had one or more comorbid health conditions and 18.6% had four or more, compared to 46.9% and 9.0% of people without epilepsy. Depression was present in 16.3% of people with epilepsy compared to 9.5% of those without (adjusted OR 1.57, 95% CI 1.49-1.65). The prevalence of comorbid depression in epilepsy increased as the number of physical comorbidities increased (OR 5.82, 95% CI 4.90-6.91 for 4+ physical comorbidities vs none) and with increasing deprivation, similar to the patterns observed in other common physical conditions. CONCLUSION: People with epilepsy have higher rates of both physical and mental health comorbidity than people without even after adjustment for age, gender and levels of deprivation. Depression is more common than in the general population but the prevalence is similar to other physical health conditions, and is strongly associated with the total burden of physical conditions. This study highlights the complexity in caring for people with epilepsy.

General Practice Locum Improvement Tool.

An improvement culture is required in the NHS. Staff members who move from one place of work to another are often best placed to see alternative methods of working that at times are more efficient - locum general practitioners (GPs) tend to be in this category. A tool was developed specifically to obtain quality improvement suggestions to the general practice from the locum GP and vice versa in a time efficient manner. A pilot study was performed in one general practice in Tayside (Grove Health Centre) in December 2013 to assess if this was possible. During this month a general practice partner provided feedback to the locum GP by completing a drop down tick box survey while reviewing three cases dealt with by the locum. The locum GP was emailed after their session with a one question survey enquiring about improvement suggestions for that practice. Five different locum GPs provided clinical cover during the month studied - of these, one opted out from the study. The other four locums performed their clinical session and completed the survey. Feedback from the practice to locums included specific clinical guidance, suggestions for improving documentation, and ways to optimise referrals; of note, unique feedback was given to each locum and this was generated using this tool. Themes from the locum suggestions to the practice included more physical resources (such as cameras in each room), different ways of handling prescriptions, and a suggestion about identifying complex patients. As a direct result of this pilot a locum box has been implemented in this practice and plans are to rerun this tool periodically. The authors would recommend utilising this tool periodically in other general practices as it has the potential to identify improvement suggestions unique for that particular practice.