Variation in responsiveness to warranted behaviour change among NHS clinicians: novel implementation of change detection methods in longitudinal prescribing data

Investigating innovations in outpatient services: a mixed-methods rapid evaluation

Background

Within outpatient services, a broad range of innovations are being pursued to better manage care and reduce unnecessary appointments. One of the least-studied innovations is Patient-Initiated Follow-Up, which allows patients to book appointments if and when they need them, rather than follow a standard schedule.

Objectives

To use routine national hospital data to identify innovations in outpatient services implemented, in recent years, within the National Health Service in England. To carry out a rapid mixed-methods evaluation of the implementation and impact of Patient-Initiated Follow-Up.

Methods

The project was carried out in four sequential workstreams: (1) a rapid scoping review of outpatient innovations; (2) the application of indicator saturation methodology for scanning national patient-level data to identify potentially successful local interventions; (3) interviews with hospitals identified in workstream 2; and (4) a rapid mixed-methods evaluation of Patient-Initiated Follow-Up. The evaluation of Patient-Initiated Follow-Up comprised an evidence review, interviews with 36 clinical and operational staff at 5 National Health Service acute trusts, a workshop with staff from 13 National Health Service acute trusts, interviews with four patients, analysis of national and local data, and development of an evaluation guide.

Results

Using indicator saturation, we identified nine services with notable changes in follow-up to first attendance ratios. Of three sites interviewed, two queried the data findings and one attributed the change to a clinical assessment service. Models of Patient-Initiated Follow-Up varied widely between hospital and clinical specialty, with a significant degree of variation in the approach to patient selection, patient monitoring and discharge. The success of implementation was dependent on several factors, for example, clinical condition, staff capacity and information technology systems. From the analysis of national data, we found evidence of an association between greater use of Patient-Initiated Follow-Up and a lower frequency of outpatient attendance within 15 out of 29 specialties and higher frequency of outpatient attendance within 7 specialties. Four specialties had less frequent emergency department visits associated with increasing Patient-Initiated Follow-Up rates. Patient-Initiated Follow-Up was viewed by staff and the few patients we interviewed as a positive intervention, although there was varied impact on individual staff roles and workload. It is important that sites and services undertake their own evaluations of Patient-Initiated Follow-Up. To this end we have developed an evaluation guide to support trusts with data collection and methods.

Limitations

The Patient-Initiated Follow-Up evaluation was affected by a lack of patient-level data showing who is on a Patient-Initiated Follow-Up pathway. Engagement with local services was also challenging, given the pressures facing sites and staff. Patient recruitment was low, which affected the ability to understand experiences of patients directly.

Conclusions

The study provides useful insights into the evolving national outpatient transformation policy and for local practice. Patient-Initiated Follow-Up is often perceived as a positive intervention for staff and patients, but the impact on individual outcomes, health inequalities, wider patient experience, workload and capacity is still uncertain.

Future research

Further research should include patient-level analysis to determine clinical outcomes for individual patients on Patient-Initiated Follow-Up and health inequalities, and more extensive investigation of patient experiences.

Study registration

This study is registered with the Research Registry (UIN: researchregistry8864).

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 16/138/17) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 38. See the NIHR Funding and Awards website for further award information.

Data-Driven Identification of Potentially Successful Intervention Implementations Using 5 Years of Opioid Prescribing Data: Retrospective Database Study

BACKGROUND

We have previously demonstrated that opioid prescribing increased by 127% between 1998 and 2016. New policies aimed at tackling this increasing trend have been recommended by public health bodies, and there is some evidence that progress is being made.

OBJECTIVE

We sought to extend our previous work and develop a data-driven approach to identify general practices and clinical commissioning groups (CCGs) whose prescribing data suggest that interventions to reduce the prescribing of opioids may have been successfully implemented.

METHODS

We analyzed 5 years of prescribing data (December 2014 to November 2019) for 3 opioid prescribing measures-total opioid prescribing as oral morphine equivalent per 1000 registered population, the number of high-dose opioids prescribed per 1000 registered population, and the number of high-dose opioids as a percentage of total opioids prescribed. Using a data-driven approach, we applied a modified version of our change detection Python library to identify reductions in these measures over time, which may be consistent with the successful implementation of an intervention to reduce opioid prescribing. This analysis was carried out for general practices and CCGs, and organizations were ranked according to the change in prescribing rate.

RESULTS

We identified a reduction in total opioid prescribing in 94 (49.2%) out of 191 CCGs, with a median reduction of 15.1 (IQR 11.8-18.7; range 9.0-32.8) in total oral morphine equivalence per 1000 patients. We present data for the 3 CCGs and practices demonstrating the biggest reduction in opioid prescribing for each of the 3 opioid prescribing measures. We observed a 40% proportional drop (8.9% absolute reduction) in the regular prescribing of high-dose opioids (measured as a percentage of regular opioids) in the highest-ranked CCG (North Tyneside); a 99% drop in this same measure was found in several practices (44%-95% absolute reduction). Decile plots demonstrate that CCGs exhibiting large reductions in opioid prescribing do so via slow and gradual reductions over a long period of time (typically over a period of 2 years); in contrast, practices exhibiting large reductions do so rapidly over a much shorter period of time.

CONCLUSIONS

By applying 1 of our existing analysis tools to a national data set, we were able to identify rapid and maintained changes in opioid prescribing within practices and CCGs and rank organizations by the magnitude of reduction. Highly ranked organizations are candidates for further qualitative research into intervention design and implementation.

Changes in medication safety indicators in England throughout the covid-19 pandemic using OpenSAFELY: population based, retrospective cohort study of 57 million patients using federated analytics

Objective

To implement complex, PINCER (pharmacist led information technology intervention) prescribing indicators, on a national scale with general practice data to describe the impact of the covid-19 pandemic on safe prescribing.

Design

Population based, retrospective cohort study using federated analytics.

Setting

Electronic general practice health record data from 56.8 million NHS patients by use of the OpenSAFELY platform, with the approval of the National Health Service (NHS) England.

Participants

NHS patients (aged 18-120 years) who were alive and registered at a general practice that used TPP or EMIS computer systems and were recorded as at risk of at least one potentially hazardous PINCER indicator.

Main outcome measure

Between 1 September 2019 and 1 September 2021, monthly trends and between practice variation for compliance with 13 PINCER indicators, as calculated on the first of every month, were reported. Prescriptions that do not adhere to these indicators are potentially hazardous and can cause gastrointestinal bleeds; are cautioned against in specific conditions (specifically heart failure, asthma, and chronic renal failure); or require blood test monitoring. The percentage for each indicator is formed of a numerator of patients deemed to be at risk of a potentially hazardous prescribing event and the denominator is of patients for which assessment of the indicator is clinically meaningful. Higher indicator percentages represent potentially poorer performance on medication safety.

Results

The PINCER indicators were successfully implemented across general practice data for 56.8 million patient records from 6367 practices in OpenSAFELY. Hazardous prescribing remained largely unchanged during the covid-19 pandemic, with no evidence of increases in indicators of harm as captured by the PINCER indicators. The percentage of patients at risk of potentially hazardous prescribing, as defined by each PINCER indicator, at mean quarter 1 (Q1) 2020 (representing before the pandemic) ranged from 1.11% (age ≥65 years and non-steroidal anti-inflammatory drugs) to 36.20% (amiodarone and no thyroid function test), while Q1 2021 (representing after the pandemic) percentages ranged from 0.75% (age ≥65 years and non-steroidal anti-inflammatory drugs) to 39.23% (amiodarone and no thyroid function test). Transient delays occurred in blood test monitoring for some medications, particularly angiotensin-converting enzyme inhibitors (where blood monitoring worsened from a mean of 5.16% in Q1 2020 to 12.14% in Q1 2021, and began to recover in June 2021). All indicators substantially recovered by September 2021. We identified 1 813 058 patients (3.1%) at risk of at least one potentially hazardous prescribing event.

Conclusion

NHS data from general practices can be analysed at national scale to generate insights into service delivery. Potentially hazardous prescribing was largely unaffected by the covid-19 pandemic in primary care health records in England.

Local variation in low carbon footprint inhalers in pre-COVID pandemic primary care prescribing guidelines for adult asthma in England and its potential impact

AIMS

Pressurised metered-dose inhalers (MDIs) have a much higher carbon footprint than dry powder inhalers (DPIs). We aimed to describe variations of inhaler options in local adult asthma prescribing guidance.

METHODS

We reviewed local clinical commissioning group (CCG) adult asthma prescribing guidance for primary care in England in 2019 and recorded DPI and MDI inclusion. The relationship to prescribing data from OpenPrescribing.net was examined.

RESULTS

In total, 58 unique guidance documents were analysed covering 144 out of 191 CCGs in England. Only 3% of CCG guidelines expressed an overall preference for DPIs, while 12% explicitly preferred MDIs. The inclusion of DPIs first-line was 77% for short-acting β-agonists, 78% for low-dose inhaled corticosteroid (ICS) inhalers and 90-96% for combination long-acting β-agonist/ICS inhalers. MDIs were included first-line in 98-100% of these classes. In 26% of CCGs, there was no first-line DPI option for at least 1 asthma management step. Ten percent of CCGs had no DPI included first-line for any of the 5 classes examined. Many CCGs recommended higher carbon footprint options; Ventolin MDI (25.6%), inhalers containing HFA227ea (57.9%) and ICS regimes recommending 2 puffs of a lower dose over 1 puff of higher dose (94.2%). MDIs were prescribed more in CCGs that recommended them.

CONCLUSION

Before the COVID pandemic, there was substantial variation between CCGs in adult asthma prescribing guidance regarding higher and lower carbon footprint options. There may still be scope to amend local guidance to improve clinical and environmental outcomes. This study provides a method and baseline for further investigation of this.

Short-term forecasting of the coronavirus pandemic

We have been publishing real-time forecasts of confirmed cases and deaths from coronavirus disease 2019 (COVID-19) since mid-March 2020 (published at www.doornik.com/COVID-19). These forecasts are short-term statistical extrapolations of past and current data. They assume that the underlying trend is informative regarding short-term developments but without requiring other assumptions about how the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is spreading, or whether preventative policies are effective. Thus, they are complementary to the forecasts obtained from epidemiological models. The forecasts are based on extracting trends from windows of data using machine learning and then computing the forecasts by applying some constraints to the flexible extracted trend. These methods have been applied previously to various other time series data and they performed well. They have also proved effective in the COVID-19 setting where they provided better forecasts than some epidemiological models in the earlier stages of the pandemic.

Short-term forecasting of the coronavirus pandemic

We have been publishing real-time forecasts of confirmed cases and deaths from coronavirus disease 2019 (COVID-19) since mid-March 2020 (published at www.doornik.com/COVID-19). These forecasts are short-term statistical extrapolations of past and current data. They assume that the underlying trend is informative regarding short-term developments but without requiring other assumptions about how the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is spreading, or whether preventative policies are effective. Thus, they are complementary to the forecasts obtained from epidemiological models. The forecasts are based on extracting trends from windows of data using machine learning and then computing the forecasts by applying some constraints to the flexible extracted trend. These methods have been applied previously to various other time series data and they performed well. They have also proved effective in the COVID-19 setting where they provided better forecasts than some epidemiological models in the earlier stages of the pandemic.

Dental extractions in primary care for patients at risk of MRONJ

Aims This study aims to understand the experiences of general dental practitioners (GDPs) performing dental extractions for patients at risk of developing medication-related osteonecrosis of the jaw (MRONJ) and to identify the key features of the patients who are referred to secondary care for their extractions.Materials and methods A mixed-method study consisting of quantitative analysis of anonymised electronic referrals and thematic analysis of in-depth telephone interviews with GDPs.Results In total, 122 electronic referrals for patients at risk of MRONJ were identified. The majority of the referrals contained insufficient information to categorise the patient's risk of developing MRONJ. In-depth telephone interviews with six GDPs were analysed and the themes identified were consequences, difficult decisions, patient awareness and bridging the gap.Conclusion Our results show that fewer than half of the referrals to secondary care investigated in this study showed a clear indication for secondary care involvement and the quality of the patient information provided was often insufficient to determine the patients' risk of developing MRONJ. Improved local guidance for the management of these patients and a dedicated pathway for their post-operative complications may encourage GDPs to perform more of these dental extractions in practice.

Price versus clinical guidelines in primary care statin prescribing: a retrospective cohort study and cost simulation model

OBJECTIVE

To investigate the relative impact of generic entry and National Institute for Health and Care Excellence clinical guidelines on prescribing using statins as an exemplar.

DESIGN

Retrospective analysis of statin prescribing in primary care and cost simulation model.

SETTING

Royal College of General Practitioners Research and Surveillance Centre (RCGP R&SC) database and Prescription Cost Analysis (PCA) database.

PARTICIPANTS

New patients prescribed statins for the first time between July 2003 and September 2018.

RESULTS

General trends of statin' prescriptions were largely driven by a decrease in acquisition costs triggered by patent expiration, preceding NICE guidelines which themselves did not seem to affect prescription trends. Significant heterogeneity is observed in the prescription of the most cost-effective statin across GPs. A cost simulation shows that, between 2004 and 2018, the NHS could have saved £2.8bn (around 40% of the £6.3bn spent on statins during this time) if all GP practices had prescribed only the most cost-effective treatment.

CONCLUSIONS

There is potential for large savings for the NHS if new and, whenever possible, ongoing patients are promptly switched to the first medicine that becomes available as generic within a therapeutic class as long as it has similar efficacy to still-patented medicines.

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.

General practice responses to opioid prescribing feedback: a qualitative process evaluation

BACKGROUND

The rise in opioid prescribing in primary care represents a significant public health challenge, associated with increased psychosocial problems, hospitalisations, and mortality. An evidence-based bimonthly feedback intervention to reduce opioid prescribing was developed and implemented, targeting 316 general practices in West Yorkshire over 1 year.

AIM

To understand how general practice staff received and responded to the feedback intervention.

DESIGN AND SETTING

Qualitative process evaluation involving semi-structured interviews, guided by Normalisation Process Theory (NPT), of primary care healthcare professionals targeted by feedback.

METHOD

Participants were purposively recruited according to baseline opioid prescribing levels and degree of change following feedback. Interview data were coded to NPT constructs, and thematically analysed.

RESULTS

Interviews were conducted with 21 staff from 20 practices. Reducing opioid prescribing was recognised as a priority. While high achievers had clear structures for quality improvement, feedback encouraged some less structured practices to embed changes. The non-prescriptive nature of the feedback reports allowed practices to develop strategies consistent with their own ways of working and existing resources. Practice concerns were allayed by the credibility of the reports and positive experiences of reducing opioid prescribing. The scale, frequency, and duration of feedback may have ensured a good overall level of practice population reach.

CONCLUSION

The intervention engaged general practice staff in change by targeting an issue of emerging concern, and allowing adaption to different ways of working. Practice efforts to reduce opioid prescribing were reinforced by regular feedback, credible comparative data showing progress, and shared experiences of patient benefit.

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.

How many medications do doctors in primary care use? An observational study of the DU90% indicator in primary care in England

AIM

To apply the drug utilisation 90% (DU90%) indicator (the number of unique drugs which makes up 90% of a doctor's prescribing) to general practitioner (GP) practices prescribing in England to examine time trends, practice-level variation, and relationships with practice characteristics, prescribing costs and low-value prescribing.

STUDY DESIGN

Retrospective cohort study.

SETTING

Primary care in England, using publicly available prescribing data available from the National Health Service (NHS) digital platform for 2013-2017.

PARTICIPANTS

All general practices in England (n=7620).

PRIMARY AND SECONDARY OUTCOME MEASURES

The DU90% was calculated on an annual basis for each practice based on medication British National Formulary codes. Low-value prescribing was defined using NHS 2017 guidance (including lidocaine plasters, liothyronine, omega-3 supplements). Descriptive statistics were generated per year on time trends and practice-level variation in the DU90%. Multilevel linear regression was used to examine the practice characteristics (relating to staff, patients and deprivation of the practice area).

RESULTS

Among 7620 practices, mean DU90% ranged from 130.0 to 131.0 across study years, and regarding variation between practices, there was a 1.4-fold difference between the lowest and highest 5% of practices. A range of medications were included in the DU90% of virtually all practices, including atorvastatin, levothyroxine, omeprazole, ramipril, amlodipine, simvastatin and aspirin. A higher volume of prescribing was associated with a lower DU90%, while having more patients, higher proportions of patients who are women or aged ≥45 years, higher number of GPs working in the practice and being in a more deprived area were associated with a higher DU90%. Practices in higher quintiles of DU90% had higher levels of low-priority prescribing and prescribing costs.

CONCLUSION

GP practices typically use 130 different medications in the bulk of their prescribing. Higher DU90% was associated with higher levels of low-priority prescribing and prescribing costs. Increasing use of personal formularies may enhance prescribing quality and reduce costs.

Projected spending for brand-name drugs in English primary care given US prices: a cross-sectional study

Objectives

To estimate additional spending if NHS England paid the same prices as US Medicare Part D for the 50 single-source brand-name drugs with the highest expenditure in English primary care in 2018.

Design

Retrospective analysis of 2018 drug prescribing and spending in the NHS England prescribing data and the Medicare Part D Drug Spending Dashboard and Data. We examined the 50 costliest drugs in English primary care available as brand-name-only in the US and England. We performed cost projections of NHS England spending with US Medicare Part D prices. We estimated average 2018 US rebates as 1 minus the quotient of net divided by gross Medicare Part D spending.

Setting

England and US

Participants

NHS England and US Medicare systems

Main outcome measures

Total spending, prescriptions and claims in NHS England and Medicare Part D. All spending and cost measures were reported in 2018 British pounds.

Results

NHS England spent £1.39 billion on drugs in the cohort. All drugs were more expensive under US Medicare Part D than NHS England. The US–England price ratios ranged from 1.3 to 9.9 (mean ratio 4.8). Accounting for prescribing volume, if NHS England had paid US Medicare Part D prices after adjusting for estimated US rebates, it would have spent 4.6 times as much in 2018 on drugs in the cohort (£6.42 billion).

Conclusions

Spending by NHS England would be substantially higher if it paid US Medicare Part D prices. This could result in decreased access to medicines and other health services.

Prescription of suboptimal statin treatment regimens: a retrospective cohort study of trends and variation in English primary care

BACKGROUND

Since 2014 English national guidance recommends 'high-intensity' statins, reducing low-density lipoprotein (LDL) cholesterol by ≥40%.

AIM

To describe trends and variation in low-/medium-intensity statin prescribing and assess the feasibility of rapid prescribing behaviour change.

DESIGN AND SETTING

A retrospective cohort study using OpenPrescribing data from all 8142 standard NHS general practices in England from August 2010 to March 2019.

METHOD

Statins were categorised as high- or low-/medium-intensity using two different thresholds, and the proportion prescribed below these thresholds was calculated. The authors plotted trends and geographical variation, carried out mixed-effects logistic regression to identify practice characteristics associated with breaching of guidance, and used indicator saturation to identify sudden prescribing changes.

RESULTS

The proportion of statins prescribed below the recommended 40% LDL-lowering threshold has decreased gradually from 80% in 2011/2012 to 45% in 2019; the proportion below a pragmatic 37% threshold decreased from 30% to 18% in 2019. Guidance from 2014 had minimal impact on trends. Wide variation was found between practices (interdecile ranges 20% to 85% and 10% to 30% respectively in 2018). Regression identified no strong associations with breaching of guidance. Indicator saturation identified several practices exhibiting sudden changes towards greater guideline compliance.

CONCLUSION

Breaches of guidance on choice of statin remain common, with substantial variation between practices. Some have implemented rapid change, indicating the feasibility of rapid prescribing behaviour change. This article discusses the potential for a national strategic approach, using data and evidence to optimise care, including targeted education alongside audit and feedback to outliers through services such as OpenPrescribing.