OpenSAFELY: impact of national guidance on switching anticoagulant therapy during COVID-19 pandemic.

BACKGROUND: Early in the COVID-19 pandemic, the National Health Service (NHS) recommended that appropriate patients anticoagulated with warfarin should be switched to direct-acting oral anticoagulants (DOACs), requiring less frequent blood testing. Subsequently, a national safety alert was issued regarding patients being inappropriately coprescribed two anticoagulants following a medication change and associated monitoring. OBJECTIVE: To describe which people were switched from warfarin to DOACs; identify potentially unsafe coprescribing of anticoagulants; and assess whether abnormal clotting results have become more frequent during the pandemic. METHODS: With the approval of NHS England, we conducted a cohort study using routine clinical data from 24 million NHS patients in England. RESULTS: 20 000 of 164 000 warfarin patients (12.2%) switched to DOACs between March and May 2020, most commonly to edoxaban and apixaban. Factors associated with switching included: older age, recent renal function test, higher number of recent INR tests recorded, atrial fibrillation diagnosis and care home residency. There was a sharp rise in coprescribing of warfarin and DOACs from typically 50-100 per month to 246 in April 2020, 0.06% of all people receiving a DOAC or warfarin. International normalised ratio (INR) testing fell by 14% to 506.8 patients tested per 1000 warfarin patients each month. We observed a very small increase in elevated INRs (n=470) during April compared with January (n=420). CONCLUSIONS: Increased switching of anticoagulants from warfarin to DOACs was observed at the outset of the COVID-19 pandemic in England following national guidance. There was a small but substantial number of people coprescribed warfarin and DOACs during this period. Despite a national safety alert on the issue, a widespread rise in elevated INR test results was not found. Primary care has responded rapidly to changes in patient care during the COVID-19 pandemic.

Evaluating the impact of a very low-cost intervention to increase practices' engagement with data and change prescribing behaviour: a randomized trial in English primary care.

BACKGROUND: Unsolicited feedback can solicit changes in prescribing. OBJECTIVES: Determine whether a low-cost intervention increases clinicians' engagement with data, and changes prescribing; with or without behavioural science techniques. METHODS: Randomized trial (ISRCTN86418238). The highest prescribing practices in England for broad-spectrum antibiotics were allocated to: feedback with behavioural impact optimization; plain feedback; or no intervention. Feedback was sent monthly for 3 months by letter, fax and email. Each included a link to a prescribing dashboard. The primary outcomes were dashboard usage and change in prescribing. RESULTS: A total of 1401 practices were randomized: 356 behavioural optimization, 347 plain feedback, and 698 control. For the primary engagement outcome, more intervention practices had their dashboards viewed compared with controls [65.7% versus 55.9%; RD 9.8%, 95% confidence intervals (CIs): 4.76% to 14.9%, P < 0.001]. More plain feedback practices had their dashboard viewed than behavioural feedback practices (69.1% versus 62.4%); but not meeting the P < 0.05 threshold (6.8%, 95% CI: -0.19% to 13.8%, P = 0.069). For the primary prescribing outcome, intervention practices possibly reduced broad-spectrum prescribing to a greater extent than controls (1.42% versus 1.12%); but again not meeting the P < 0.05 threshold (coefficient -0.31%, CI: -0.7% to 0.1%, P = 0.104). The behavioural impact group reduced broad-spectrum prescribing to a greater extent than plain feedback practices (1.63% versus 1.20%; coefficient 0.41%, CI: 0.007% to 0.8%, P = 0.046). No harms were detected. CONCLUSIONS: Unsolicited feedback increased practices' engagement with data, with possible slightly reduced antibiotic prescribing (P = 0.104). Behavioural science techniques gave greater prescribing effects. The modest effects on prescribing may reflect saturation from similar initiatives on antibiotic prescribing. CLINICAL TRIAL REGISTRATION: ISRCTN86418238.

Use of non-steroidal anti-inflammatory drugs and risk of death from COVID-19: an OpenSAFELY cohort analysis based on two cohorts.

OBJECTIVES: To assess the association between routinely prescribed non-steroidal anti-inflammatory drugs (NSAIDs) and deaths from COVID-19 using OpenSAFELY, a secure analytical platform. METHODS: We conducted two cohort studies from 1 March to 14 June 2020. Working on behalf of National Health Service England, we used routine clinical data in England linked to death data. In study 1, we identified people with an NSAID prescription in the last 3 years from the general population. In study 2, we identified people with rheumatoid arthritis/osteoarthritis. We defined exposure as current NSAID prescription within the 4 months before 1 March 2020. We used Cox regression to estimate HRs for COVID-19 related death in people currently prescribed NSAIDs, compared with those not currently prescribed NSAIDs, accounting for age, sex, comorbidities, other medications and geographical region. RESULTS: In study 1, we included 536 423 current NSAID users and 1 927 284 non-users in the general population. We observed no evidence of difference in risk of COVID-19 related death associated with current use (HR 0.96, 95% CI 0.80 to 1.14) in the multivariable-adjusted model. In study 2, we included 1 708 781 people with rheumatoid arthritis/osteoarthritis, of whom 175 495 (10%) were current NSAID users. In the multivariable-adjusted model, we observed a lower risk of COVID-19 related death (HR 0.78, 95% CI 0.64 to 0.94) associated with current use of NSAID versus non-use. CONCLUSIONS: We found no evidence of a harmful effect of routinely prescribed NSAIDs on COVID-19 related deaths. Risks of COVID-19 do not need to influence decisions about the routine therapeutic use of NSAIDs.

A comprehensive high cost drugs dataset from the NHS in England - An OpenSAFELY-TPP Short Data Report.

Background: At the outset of the COVID-19 pandemic, there was no routine comprehensive hospital medicines data from the UK available to researchers. These records can be important for many analyses including the effect of certain medicines on the risk of severe COVID-19 outcomes. With the approval of NHS England, we set out to obtain data on one specific group of medicines, "high-cost drugs" (HCD) which are typically specialist medicines for the management of long-term conditions, prescribed by hospitals to patients. Additionally, we aimed to make these data available to all approved researchers in OpenSAFELY-TPP. This report is intended to support all studies carried out in OpenSAFELY-TPP, and those elsewhere, working with this dataset or similar data. Methods: Working with the North East Commissioning Support Unit and NHS Digital, we arranged for collation of a single national HCD dataset to help inform responses to the COVID-19 pandemic. The dataset was developed from payment submissions from hospitals to commissioners. Results: In the financial year (FY) 2018/19 there were 2.8 million submissions for 1.1 million unique patient IDs recorded in the HCD. The average number of submissions per patient over the year was 2.6. In FY 2019/20 there were 4.0 million submissions for 1.3 million unique patient IDs. The average number of submissions per patient over the year was 3.1. Of the 21 variables in the dataset, three are now available for analysis in OpenSafely-TPP: Financial year and month of drug being dispensed; drug name; and a description of the drug dispensed. Conclusions: We have described the process for sourcing a national HCD dataset, making these data available for COVID-19-related analysis through OpenSAFELY-TPP and provided information on the variables included in the dataset, data coverage and an initial descriptive analysis.

Suboptimal prescribing behaviour associated with clinical software design features: a retrospective cohort study in English NHS primary care.

BACKGROUND: Electronic health record (EHR) systems are used by clinicians to record patients' medical information, and support clinical activities such as prescribing. In England, healthcare professionals are advised to 'prescribe generically' because generic drugs are usually cheaper than branded alternatives, and have fixed reimbursement costs. 'Ghost-branded generics' are a new category of medicines savings, caused by prescribers specifying a manufacturer for a generic product, often resulting in a higher reimbursement price compared with the true generic. AIM: To describe time trends and practice factors associated with excess medication costs from ghost-branded generic prescribing. DESIGN AND SETTING: Retrospective cohort study of English GP prescribing data and EHR deployment data. METHOD: A retrospective cohort study was conducted, based on data from the OpenPrescribing.net database from May 2013 to May 2019. Total spending on ghost-branded generics across England was calculated, and excess spend on ghost-branded generics calculated as a percentage of all spending on generics for every CCG and general practice in England, for every month in the study period. RESULTS: There were 31.8 million ghost-branded generic items and £9.5 million excess cost in 2018, compared with 7.45 million ghost-branded generic items and £1.3 million excess cost in 2014. Most excess costs were associated with one EHR, SystmOne, and it was identified that SystmOne offered ghost-branded generic options as the default. After informing the vendor, the authors monitored for subsequent change in costs, and report a rapid decrease in ghost-branded generic expenditure. CONCLUSION: A design choice in a commonly used EHR has led to £9.5 million in avoidable excess prescribing costs for the NHS in 1 year. Notifying the vendor led to a change in user interface and a rapid, substantial spend reduction. This finding illustrates that EHR user interface design has a substantial impact on the quality, safety, and cost-effectiveness of clinical practice; this should be a priority for quantitative research.

Do doctors in dispensing practices with a financial conflict of interest prescribe more expensive drugs? A cross-sectional analysis of English primary care prescribing data.

OBJECTIVES: Approximately one in eight practices in primary care in England are 'dispensing practices' with an in-house dispensary providing medication directly to patients. These practices can generate additional income by negotiating lower prices on higher cost drugs, while being reimbursed at a standard rate. They, therefore, have a potential financial conflict of interest around prescribing choices. We aimed to determine whether dispensing practices are more likely to prescribe high-cost options for four commonly prescribed classes of drug where there is no evidence of superiority for high-cost options. DESIGN: A list was generated of drugs with high acquisition costs that were no more clinically effective than those with the lowest acquisition costs, for all four classes of drug examined. Data were obtained prescribing of statins, proton pump inhibitors (PPIs), angiotensin receptor blockers (ARBs) and ACE inhibitors (ACEis). Logistic regression was used to calculate ORs for prescribing high-cost options in dispensing practices, adjusting for Index of Multiple Deprivation score, practice list size and the number of doctors at each practice. SETTING: English primary care. PARTICIPANTS: All general practices in England. MAIN OUTCOME MEASURES: Mean cost per dose was calculated separately for dispensing and non-dispensing practices. Dispensing practices can vary in the number of patients they dispense to; we, therefore, additionally compared practices with no dispensing patients, low, medium and high proportions of dispensing patients. Total cost savings were modelled by applying the mean cost per dose from non-dispensing practices to the number of doses prescribed in dispensing practices. RESULTS: Dispensing practices were more likely to prescribe high-cost drugs across all classes: statins adjusted OR 1.51 (95% CI 1.49 to 1.53, p<0.0001), PPIs OR 1.11 (95% CI 1.09 to 1.13, p<0.0001), ACEi OR 2.58 (95% CI 2.46 to 2.70, p<0.0001), ARB OR 5.11 (95% CI 5.02 to 5.20, p<0.0001). Mean cost per dose in pence was higher in dispensing practices (statins 7.44 vs 6.27, PPIs 5.57 vs 5.46, ACEi 4.30 vs 4.24, ARB 11.09 vs 8.19). For all drug classes, the more dispensing patients a practice had, the more likely it was to issue a prescription for a high-cost option. Total cost savings in England available from all four classes are £628 875 per month or £7 546 502 per year. CONCLUSIONS: Doctors in dispensing practices are more likely to prescribe higher cost drugs. This is the largest study ever conducted on dispensing practices, and the first contemporary research suggesting some UK doctors respond to a financial conflict of interest in treatment decisions. The reimbursement system for dispensing practices may generate unintended consequences. Robust routine audit of practices prescribing higher volumes of unnecessarily expensive drugs may help reduce costs.

Measuring the Impact of an Open Web-Based Prescribing Data Analysis Service on Clinical Practice: Cohort Study on NHS England Data.

BACKGROUND: OpenPrescribing is a freely accessible service that enables any user to view and analyze the National Health Service (NHS) primary care prescribing data at the level of individual practices. This tool is intended to improve the quality, safety, and cost-effectiveness of prescribing. OBJECTIVE: We aimed to measure the impact of OpenPrescribing being viewed on subsequent prescribing. METHODS: Having preregistered our protocol and code, we measured three different metrics of prescribing quality (mean percentile across 34 existing OpenPrescribing quality measures, available "price-per-unit" savings, and total "low-priority prescribing" spend) to see whether they changed after the viewing of Clinical Commissioning Group (CCG) and practice pages. We also measured whether practices whose data were viewed on OpenPrescribing differed in prescribing, prior to viewing, compared with those who were not. We used fixed-effects and between-effects linear panel regression to isolate change over time and differences between practices, respectively. We adjusted for the month of prescribing in the fixed-effects model to remove underlying trends in outcome measures. RESULTS: We found a reduction in available price-per-unit savings for both practices and CCGs after their pages were viewed. The saving was greater at practice level (-£40.42 per thousand patients per month; 95% CI -54.04 to -26.81) than at CCG level (-£14.70 per thousand patients per month; 95% CI -25.56 to -3.84). We estimate a total saving since launch of £243 thosand at practice level and £1.47 million at CCG level between the feature launch and end of follow-up (August to November 2017) among practices viewed. If the observed savings from practices viewed were extrapolated to all practices, this would generate £26.8 million in annual savings for the NHS, approximately 20% of the total possible savings from this method. The other two measures were not different after CCGs or practices were viewed. Practices that were viewed had worse prescribing quality scores overall prior to viewing. CONCLUSIONS: We found a positive impact from the use of OpenPrescribing, specifically for the class of savings opportunities that can only be identified by using this tool. Furthermore, we show that it is possible to conduct a robust analysis of the impact of such a Web-based service on clinical practice.

Why did some practices not implement new antibiotic prescribing guidelines on urinary tract infection? A cohort study and survey in NHS England primary care.

OBJECTIVES: To describe trends and geographical variation in prescribing of trimethoprim and nitrofurantoin to treat urinary tract infections, to describe variation in implementing guideline change and to compare actions taken to reduce trimethoprim use in high- and low-using Clinical Commissioning Groups (CCGs). METHODS: A retrospective cohort study and interrupted time series analysis of English NHS primary care prescribing data, complemented by information obtained through Freedom of Information Act requests to CCGs. The main outcome measures were variation in practice and CCG prescribing ratios geographically and over time, including an interrupted time series, and responses to Freedom of Information requests. RESULTS: The amount of trimethoprim prescribed, as a proportion of nitrofurantoin and trimethoprim combined, remained stable and high until 2014, then fell gradually to <50% in 2017; this reduction was more rapid following the introduction of the 'Quality Premium'. There was substantial variation in the speed of change between CCGs. As of April 2017, for the 10 CCGs with the lowest trimethoprim ratios, 9 had reported at least one of: formulary change, work plan or incentive scheme to change prescribing behaviour. None of the 10 highest-ratio CCGs did so. CONCLUSIONS: Many CCGs failed to implement an important change in antibiotic prescribing guidance, and there is strong evidence suggesting that CCGs with minimal prescribing change did little to implement the new guidance. We recommend: (i) a national programme of training and accreditation for medicines optimization pharmacists; and (ii) remedial action for CCGs that fail to implement guidance-with all materials and data shared publicly for both such activities.

The clinician impact and financial cost to the NHS of litigation over pregabalin: a cohort study in English primary care.

OBJECTIVES: Following litigation over pregabalin's second-use medical patent for neuropathic pain, National Health Service (NHS) England was required by the court to instruct general practitioners (GPs) to prescribe the branded form (Lyrica) for pain. Pfizer's patent was found invalid in 2015, a ruling subject to ongoing appeals. If the Supreme Court appeal in February 2018, whose judgement is awaited, is unsuccessful, the NHS can seek to reclaim excess prescribing costs. We set out to describe the variation in prescribing of pregabalin as branded Lyrica, geographically and over time; to determine how clinicians responded to the NHS England instruction to GPs; and to model excess costs to the NHS attributable to the legal judgements. SETTING: English primary care. PARTICIPANTS: English general practices. PRIMARY AND SECONDARY OUTCOME MEASURES: Variation in prescribing of branded Lyrica across the country before and after the NHS England instruction, by practice and by Clinical Commissioning Group; excess prescribing costs. RESULTS: The proportion of pregabalin prescribed as Lyrica increased from 0.3% over 6 months before the NHS England instruction (September 2014 to February 2015) to 25.7% afterwards (April to September 2015). Although 70% of pregabalin is estimated to be for pain, including neuropathic pain, only 11.6% of practices prescribed Lyrica at this level; the median proportion prescribed as Lyrica was 8.8% (IQR 1.1%-41.9%). If pregabalin had come entirely off patent in September 2015, and Pfizer had not appealed, we estimate the NHS would have spent £502 million less on pregabalin to July 2017. CONCLUSION: NHS England instructions to GPs regarding branded prescription of pregabalin were widely ignored and have created much debate around clinical independence in prescribing. Protecting revenue from 'skinny labels' will pose a challenge. If Pfizer's final appeal on the patent is unsuccessful, the NHS can seek reimbursement of excess pregabalin prescribing costs, potentially £502 million.

Trends and variation in prescribing of low-priority treatments identified by NHS England: a cross-sectional study and interactive data tool in English primary care.

Objectives NHS England recently announced a consultation seeking to discourage the use of treatments it considers to be low-value. We set out to produce an interactive data resource to show savings in each NHS general practice and to assess the current use of these treatments, their change in use over time, and the extent and reasons for variation in such prescribing. Design Cross-sectional analysis. Setting English primary care. Participants English general practices. Main outcome measures We determined the cost per 1000 patients for prescribing of each of 18 treatments identified by NHS England for each month from July 2012 to June 2017, and also aggregated over the most recent year to assess total cost and variation among practices. We used mixed effects linear regression to determine factors associated with cost of prescribing. Results Spend on low-value treatments was £153.5 m in the last year, across 5.8 m prescriptions (mean, £26 per prescription). Among individual treatments, liothyronine had the highest prescribing cost at £29.6 m, followed by trimipramine (£20.2 m). Over time, the overall total number of low-value prescriptions decreased, but the cost increased, although this varied greatly between treatments. Three treatment areas increased in cost and two increased in volume, all others reduced in cost and volume. Annual practice level spending varied widely (median, £2262 per thousand patients; interquartile range £1439 to £3298). Proportion of patients over 65 was strongly associated with low-value prescribing, as was Clinical Commissioning Group. Our interactive data tool was deployed to OpenPrescribing.net where monthly updated figures and graphs can be viewed. Conclusions Prescribing of low-value treatments is extensive but varies widely by treatment, geographic area and individual practice. Despite a fall in prescription numbers, the overall cost of prescribing for low-value items has risen. Prescribing behaviour is clustered by Clinical Commissioning Group, which may represent variation in the optimisation efficiency of medicines, or in some cases access inequality.

Is use of homeopathy associated with poor prescribing in English primary care? A cross-sectional study.

Objectives Prescribing of homeopathy still occurs in a small minority of English general practices. We hypothesised that practices that prescribe any homeopathic preparations might differ in their prescribing of other drugs. Design Cross-sectional analysis. Setting English primary care. Participants English general practices. Main outcome measures We identified practices that made any homeopathy prescriptions over six months of data. We measured associations with four prescribing and two practice quality indicators using multivariable logistic regression. Results Only 8.5% of practices (644) prescribed homeopathy between December 2016 and May 2017. Practices in the worst-scoring quartile for a composite measure of prescribing quality (>51.4 mean percentile) were 2.1 times more likely to prescribe homeopathy than those in the best category (<40.3) (95% confidence interval: 1.6-2.8). Aggregate savings from the subset of these measures where a cost saving could be calculated were also strongly associated (highest vs. lowest quartile multivariable odds ratio: 2.9, confidence interval: 2.1-4.1). Of practices spending the most on medicines identified as 'low value' by NHS England, 12.8% prescribed homeopathy, compared to 3.9% for lowest spenders (multivariable odds ratio: 2.6, confidence interval: 1.9-3.6). Of practices in the worst category for aggregated price-per-unit cost savings, 12.7% prescribed homeopathy, compared to 3.5% in the best category (multivariable odds ratio: 2.7, confidence interval: 1.9-3.9). Practice quality outcomes framework scores and patient recommendation rates were not associated with prescribing homeopathy (odds ratio range: 0.9-1.2). Conclusions Even infrequent homeopathy prescribing is strongly associated with poor performance on a range of prescribing quality measures, but not with overall patient recommendation or quality outcomes framework score. The association is unlikely to be a direct causal relationship, but may reflect underlying practice features, such as the extent of respect for evidence-based practice, or poorer stewardship of the prescribing budget.

New mechanism to identify cost savings in English NHS prescribing: minimising 'price per unit', a cross-sectional study.

BACKGROUND: Minimising prescription costs while maintaining quality is a core element of delivering high-value healthcare. There are various strategies to achieve savings, but almost no research to date on determining the most effective approach. We describe a new method of identifying potential savings due to large national variations in drug cost, including variation in generic drug cost, and compare these with potential savings from an established method (generic prescribing). METHODS: We used English National Health Service (NHS) Digital prescribing data, from October 2015 to September 2016. Potential cost savings were calculated by determining the price per unit (eg, pill, millilitre) for each drug and dose within each general practice. This was compared against the same cost for the practice at the lowest cost decile to determine achievable savings. We compared these price-per-unit savings to the savings possible from generic switching and determined the chemicals with the highest savings nationally. A senior pharmacist manually assessed whether a random sample of savings were practically achievable. RESULTS: We identified a theoretical maximum of £410 million of savings over 12 months. £273 million of these savings were for individual prescribing changes worth over £50 per practice per month (mean annual saving £33 433 per practice); this compares favourably with generic switching, where only £35 million of achievable savings were identified. The biggest savings nationally were on glucose blood testing reagents (£12 million), fluticasone propionate (£9 million) and venlafaxine (£8 million). Approximately half of all savings were deemed practically achievable. DISCUSSION: We have developed a new method to identify and enable large potential cost savings within NHS community prescribing. Given the current pressures on the NHS, it is vital that these potential savings are realised. Our tool enabling doctors to achieve these savings is now launched in pilot form at OpenPrescribing.net. However, savings could potentially be achieved more simply through national policy change.