scholarly journals Evaluation of a complex intervention to improve primary care prescribing: a phase IV segmented regression interrupted time series analysis

2017 ◽  
Vol 67 (658) ◽  
pp. e352-e360 ◽  
Author(s):  
Sean MacBride-Stewart ◽  
Charis Marwick ◽  
Neil Houston ◽  
Iain Watt ◽  
Andrea Patton ◽  
...  
Keyword(s):  
Primary Care ◽  
Time Series ◽  
High Risk ◽  
Older People ◽  
Secondary Analysis ◽  
Interrupted Time Series ◽  
Segmented Regression ◽  
Intervention Period ◽  
Interrupted Time Series Analysis ◽  
Primary Analysis

BackgroundIt is uncertain whether improvements in primary care high-risk prescribing seen in research trials can be realised in the real-world setting.AimTo evaluate the impact of a 1-year system-wide phase IV prescribing safety improvement initiative, which included education, feedback, support to identify patients to review, and small financial incentives.Design and settingAn interrupted time series analysis of targeted high-risk prescribing in all 56 general practices in NHS Forth Valley, Scotland, was performed. In 2013–2014, this focused on high-risk non-steroidal anti-inflammatory drugs (NSAIDs) in older people and NSAIDs with oral anticoagulants; in 2014–2015, it focused on antipsychotics in older people.MethodThe primary analysis used segmented regression analysis to estimate impact at the end of the intervention, and 12 months later. The secondary analysis used difference-in-difference methods to compare Forth Valley changes with those in NHS Greater Glasgow and Clyde (GGC).ResultsIn the primary analysis, downward trends for all three NSAID measures that were existent before the intervention statistically significantly steepened following implementation of the intervention. At the end of the intervention period, 1221 fewer patients than expected were prescribed a high-risk NSAID. In contrast, antipsychotic prescribing in older people increased slowly over time, with no intervention-associated change. In the secondary analysis, reductions at the end of the intervention period in all three NSAID measures were statistically significantly greater in NHS Forth Valley than in NHS GGC, but only significantly greater for two of these measures 12 months after the intervention finished.ConclusionThere were substantial and sustained reductions in the high-risk prescribing of NSAIDs, although with some waning of effect 12 months after the intervention ceased. The same intervention had no effect on antipsychotic prescribing in older people.

scholarly journals LB-16. Association Between Universal Face Shield in a Quaternary Care Center and Reduction of SARS-COV2 Infections Among Healthcare Personnel and Hospitalized Patients

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S851-S851
Author(s):  
Vagesh Hemmige ◽  
Becky Winterer ◽  
Todd Lasco ◽  
Bradley Lembcke
Keyword(s):  
Time Series ◽  
Care Center ◽  
Interrupted Time Series ◽  
Hospitalized Patients ◽  
Healthcare Personnel ◽  
Segmented Regression ◽  
Intervention Period ◽  
Interrupted Time Series Analysis ◽  
Post Intervention ◽  
The Impact

Abstract Background SARS-COV2 transmission to healthcare personnel (HCP) and hospitalized patients is a significant challenge. Our hospital is a quaternary healthcare system with more than 500 beds and 8,000 HCP. Between April 1 and April 17, 2020, we instituted several infection prevention strategies to limit transmission of SARS-COV2 including universal masking of HCP and patients, surveillance testing every two weeks for high-risk HCP and every week for cluster units, and surveillance testing for all patients on admission and prior to invasive procedures. On July 6, 2020, we implemented universal face shield for all healthcare personnel upon entry to facility. The aim of this study is to assess the impact of face shield policy on SARS-COV2 infection among HCP and hospitalized patients. Figure 1- Interrupted time series Methods The preintervention period (April 17, 2020-July 5, 2020) included implementation of universal face masks and surveillance testing of HCP and patients. The intervention period (July 6, 2020-July 26, 2020) included the addition of face shield to all HCP (for patient encounters and staff-to-staff encounters). We used interrupted time series analysis with segmented regression to examine the effect of our intervention on the difference in proportion of HCP positive for SARS-COV2 (using logistic regression) and HAI (using Poisson regression). We defined significance as p values < 0.05. Results Of 4731 HCP tested, 192 tested positive for SARS-COV2 (4.1%). In the preintervention period, the weekly positivity rate among HCP increased from 0% to 12.9%. During the intervention period, the weekly positivity rate among HCP decreased to 2.3%, with segmented regression showing a change in predicted proportion positive in week 13 (18.0% to 3.7%, p< 0.001) and change in the post-intervention slope on the log odds scale (p< 0.001). A total of 14 HAI cases were identified. In the preintervention period, HAI cases increased from 0 to 5. During the intervention period, HAI cases decreased to 0. There was a change between pre-intervention and post-intervention slope on the log scale was significant (p< 0.01). Conclusion Our study showed that the universal use of face shield was associated with significant reduction in SARS-COV2 infection among HCP and hospitalized patients. Disclosures All Authors: No reported disclosures

scholarly journals The effects of an evidence- and theory-informed feedback intervention on opioid prescribing for non-cancer pain in primary care: A controlled interrupted time series analysis

PLoS Medicine ◽  
2021 ◽  
Vol 18 (10) ◽  
pp. e1003796
Author(s):  
Sarah L. Alderson ◽  
Tracey M. Farragher ◽  
Thomas A. Willis ◽  
Paul Carder ◽  
Stella Johnson ◽  
...  
Keyword(s):  
Primary Care ◽  
Time Series ◽  
High Risk ◽  
High Risk Patient ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Opioid Prescribing ◽  
Patient Groups ◽  
Comparative Feedback ◽  
Strong Opioids

Background The rise in opioid prescribing in primary care represents a significant international public health challenge, associated with increased psychosocial problems, hospitalisations, and mortality. We evaluated the effects of a comparative feedback intervention with persuasive messaging and action planning on opioid prescribing in primary care. Methods and findings A quasi-experimental controlled interrupted time series analysis used anonymised, aggregated practice data from electronic health records and prescribing data from publicly available sources. The study included 316 intervention and 130 control primary care practices in the Yorkshire and Humber region, UK, serving 2.2 million and 1 million residents, respectively. We observed the number of adult patients prescribed opioid medication by practice between July 2013 and December 2017. We excluded adults with coded cancer or drug dependency. The intervention, the Campaign to Reduce Opioid Prescribing (CROP), entailed bimonthly, comparative, and practice-individualised feedback reports to practices, with persuasive messaging and suggested actions over 1 year. Outcomes comprised the number of adults per 1,000 adults per month prescribed any opioid (main outcome), prescribed strong opioids, prescribed opioids in high-risk groups, prescribed other analgesics, and referred to musculoskeletal services. The number of adults prescribed any opioid rose pre-intervention in both intervention and control practices, by 0.18 (95% CI 0.11, 0.25) and 0.36 (95% CI 0.27, 0.46) per 1,000 adults per month, respectively. During the intervention period, prescribing per 1,000 adults fell in intervention practices (change −0.11; 95% CI −0.30, −0.08) and continued rising in control practices (change 0.54; 95% CI 0.29, 0.78), with a difference of −0.65 per 1,000 patients (95% CI −0.96, −0.34), corresponding to 15,000 fewer patients prescribed opioids. These trends continued post-intervention, although at slower rates. Prescribing of strong opioids, total opioid prescriptions, and prescribing in high-risk patient groups also generally fell. Prescribing of other analgesics fell whilst musculoskeletal referrals did not rise. Effects were attenuated after feedback ceased. Study limitations include being limited to 1 region in the UK, possible coding errors in routine data, being unable to fully account for concurrent interventions, and uncertainties over how general practices actually used the feedback reports and whether reductions in prescribing were always clinically appropriate. Conclusions Repeated comparative feedback offers a promising and relatively efficient population-level approach to reduce opioid prescribing in primary care, including prescribing of strong opioids and prescribing in high-risk patient groups. Such feedback may also prompt clinicians to reconsider prescribing other medicines associated with chronic pain, without causing a rise in referrals to musculoskeletal clinics. Feedback may need to be sustained for maximum effect.

Has the SARS-CoV-2 outbreak had an impact on uptake of digital cessation support in UK smokers? An interrupted time series analysis (Preprint)

2020 ◽  
Author(s):  
Olga Perski ◽  
Aleksandra Herbec ◽  
Lion Shahab ◽  
Jamie Brown
Keyword(s):  
Time Series ◽  
Smoking Cessation ◽  
Secondary Analysis ◽  
Interrupted Time Series ◽  
Step Change ◽  
Outcome Variable ◽  
Primary Analysis ◽  
Increasing Trend ◽  
The Uk ◽  
Temporary Closure

BACKGROUND The SARS-CoV-2 outbreak may motivate smokers to attempt to stop in greater numbers. However, given the temporary closure of UK stop smoking services and vape shops, smokers attempting to quit may instead seek out digital support, such as websites and smartphone apps. OBJECTIVE We examined, using an interrupted time series approach, whether the SARS-CoV-2 outbreak has been associated with a step change or increasing trend in UK downloads of an otherwise popular smoking cessation app, Smoke Free. METHODS Data were from daily and non-daily adult smokers in the UK who had downloaded the Smoke Free app between 1 January 2020 and 31 March 2020 (primary analysis) and 1 January 2019 and 31 March 2020 (secondary analysis). The outcome variable was the number of downloads aggregated at the 12-hourly (primary analysis) or daily level (secondary analysis). The explanatory variable was the start of the SARS-CoV-2 outbreak, operationalised as 1 March 2020 (primary analysis) and 15 January 2020 (secondary analysis). Generalised Additive Mixed Models adjusted for relevant covariates were fitted. RESULTS Data were collected on 45,105 (primary analysis) and 119,881 (secondary analysis) users. In both analyses, there was no evidence for a step change or increasing trend in downloads attributable to the start of the SARS-CoV-2 outbreak. CONCLUSIONS In the UK, between 1 January 2020 and 31 March 2020, and between 1 January 2019 and 31 March 2020, there was no evidence that the SARS-CoV-2 outbreak has been associated with a surge in downloads of a popular smoking cessation app. CLINICALTRIAL osf.io/zan2s

The Impact of a National Antimicrobial Stewardship Program on Antibiotic Prescribing in Primary Care: An Interrupted Time Series Analysis

2018 ◽  
Vol 69 (2) ◽  
pp. 227-232 ◽  
Author(s):  
Violeta Balinskaite ◽  
Alan P Johnson ◽  
Alison Holmes ◽  
Paul Aylin
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Broad Spectrum ◽  
Interrupted Time Series ◽  
Series Data ◽  
Antibiotic Prescribing ◽  
Segmented Regression ◽  
Broad Spectrum Antibiotic ◽  
Stewardship Program ◽  
The Impact

Abstract Background The Quality Premium was introduced in 2015 to financially reward local commissioners of healthcare in England for targeted reductions in antibiotic prescribing in primary care. Methods We used a national antibiotic prescribing dataset from April 2013 until February 2017 to examine the number of antibiotic items prescribed, the total number of antibiotic items prescribed per STAR-PU (specific therapeutic group age/sex-related prescribing units), the number of broad-spectrum antibiotic items prescribed, and broad-spectrum antibiotic items prescribed, expressed as a percentage of the total number of antibiotic items. To evaluate the impact of the Quality Premium on antibiotic prescribing, we used a segmented regression analysis of interrupted time series data. Results During the study period, over 140 million antibiotic items were prescribed in primary care. Following the introduction of the Quality Premium, antibiotic items prescribed decreased by 8.2%, representing 5933563 fewer antibiotic items prescribed during the 23 post-intervention months, as compared with the expected numbers based on the trend in the pre-intervention period. After adjusting for the age and sex distribution in the population, the segmented regression model also showed a significant relative decrease in antibiotic items prescribed per STAR-PU. A similar effect was found for broad-spectrum antibiotics (comprising 10.1% of total antibiotic prescribing), with an 18.9% reduction in prescribing. Conclusions This study shows that the introduction of financial incentives for local commissioners of healthcare to improve the quality of prescribing was associated with a significant reduction in both total and broad-spectrum antibiotic prescribing in primary care in England.

scholarly journals Digital cognitive behavioural therapy for insomnia and primary care costs in England: an interrupted time series analysis

BJGP Open ◽  
2021 ◽  
pp. BJGPO.2021.0146
Author(s):  
Chris Sampson ◽  
Eleanor Bell ◽  
Amanda Cole ◽  
Christopher B Miller ◽  
Tracey Marriott ◽  
...  
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Cognitive Behavioural Therapy ◽  
Interrupted Time Series ◽  
Behavioural Therapy ◽  
Interrupted Time Series Analysis ◽  
Cognitive Behavioural ◽  
Before And After ◽  
Quasi Experimental ◽  
Care Costs

BackgroundSleepio is an automated digital programme that delivers cognitive behavioural therapy for insomnia (dCBT-I). Sleepio has been proven effective in improving sleep difficulties. However, evidence for the possible impact of Sleepio use on health care costs in the United Kingdom has not previously been developed.AimWe sought to identify the effect of a population-wide rollout of Sleepio in terms of primary care costs in the National Health Service (NHS) in England.Design & settingThe study was conducted in the Thames Valley region of England, where access to Sleepio was made freely available to all residents between October 2018 and January 2020. The study relies on a quasi-experimental design, using an interrupted time series to compare the trend in primary care costs before and after the rollout of Sleepio.MethodWe use primary care data for people with relevant characteristics from nine general practices in Buckinghamshire. Primary care costs include general practice contacts and prescriptions. Segmented regression analysis was used to estimate primary and secondary outcomes.ResultsFor the 10,704 patients included in our sample, the total saving over the 65-week follow-up period was £71,027. This corresponds to £6.64 per person in our sample or around £70.44 per Sleepio user. Secondary analyses suggest that savings may be driven primarily by reductions in prescribing.ConclusionSleepio rollout reduced primary care costs. National adoption of Sleepio may reduce primary care costs by £20 million in the first year. The expected impact on primary care costs in any particular setting will depend on the uptake of Sleepio.

scholarly journals Community-based testing of migrants for infectious diseases (COMBAT-ID): impact, acceptability and cost-effectiveness of identifying infectious diseases among migrants in primary care: protocol for an interrupted time-series, qualitative and health economic analysis

BMJ Open ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. e029188 ◽  
Author(s):  
Manish Pareek ◽  
Helen C Eborall ◽  
Fatimah Wobi ◽  
Kate S Ellis ◽  
Evangelos Kontopantelis ◽  
...  
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Cost Effectiveness ◽  
Hepatitis C ◽  
Hepatitis B ◽  
Infectious Diseases ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Series Analysis

BackgroundMigration is a major global driver of population change. Certain migrants may be at increased risk of infectious diseases, including tuberculosis (TB), HIV, hepatitis B and hepatitis C, and have poorer outcomes. Early diagnosis and management of these infections can reduce morbidity, mortality and onward transmission and is supported by national guidelines. To date, screening initiatives have been sporadic and focused on individual diseases; systematic routine testing of migrant groups for multiple infections is rarely undertaken and its impact is unknown. We describe the protocol for the evaluation of acceptability, effectiveness and cost-effectiveness of an integrated approach to screening migrants for a range of infectious diseases in primary care.Methods and analysisWe will conduct a mixed-methods study which includes an observational cohort with interrupted time-series analysis before and after the introduction of routine screening of migrants for infectious diseases (latent TB, HIV, hepatitis B and hepatitis C) when first registering with primary care within Leicester, UK. We will assess trends in the monthly number and rate of testing and diagnosis for latent TB, HIV, hepatitis B and hepatitis C to determine the effect of the policy change using segmented regression analyses at monthly time-points. Concurrently, we will undertake an integrated qualitative sub-study to understand the views of migrants and healthcare professionals to the new testing policy in primary care. Finally, we will evaluate the cost-effectiveness of combined infection testing for migrants in primary care.Ethics and disseminationThe study has received HRA and NHS approvals for both the interrupted time-series analysis (16/SC/0127) and the qualitative sub-study (16/EM/0159). For the interrupted time-series analysis we will only use fully anonymised data. For the qualitative sub-study, we will gain written, informed, consent. Dissemination of the results will be through local and national meetings/conferences as well as publications in peer-reviewed journals.

scholarly journals Successful improvement of antibiotic prescribing at Primary Care in Andalusia following the implementation of an antimicrobial guide through multifaceted interventions: An interrupted time-series analysis

PLoS ONE ◽  
2020 ◽  
Vol 15 (5) ◽  
pp. e0233062
Author(s):  
Rocío Fernández-Urrusuno ◽  
Carmen Marina Meseguer Barros ◽  
Regina Sandra Benavente Cantalejo ◽  
Elena Hevia ◽  
Carmen Serrano Martino ◽  
...  
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
Antibiotic Prescribing ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Multifaceted Interventions
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