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

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.

The Effects of Diverse Feedback Dynamics on Performance Improvement: A Typology of Performance Feedback Signals

This article illustrates managerial responses to different performance feedback signals in decision-making processes for improving performance. First, we conceptualize and illuminate distinctive dimensions of feedback signals—internal feedback, external feedback, and comparative feedback signals. Then, we test how these different feedback signals improve performance of public-sector programs based on a 10-year panel data set from the Korean Performance Assessment Rating Tool (K-PART). We find that performance signals from sources internal to individual programs and from external reference points of problem identification (social performance comparison) affect program performance. This suggests an association between internal management and social comparison mechanisms relative to performance improvement. The novel contribution of this research lies in promoting scholarship on performance management by identifying three unique sources of performance feedback signaling.

Unsolicited Patient Complaints among Otolaryngologists

Objectives To analyze unsolicited patient complaints (UPCs) among otolaryngologists, identify risk factors for UPCs, and determine the impact of physician feedback on subsequent UPCs. Methods This retrospective study reviewed UPCs associated with US otolaryngologists from 140 medical practices from 2014 to 2017. A subset of otolaryngologists with high UPCs received peer-comparative feedback and was monitored for changes. Results The study included 29,778 physicians, of whom 548 were otolaryngologists. UPCs described concerns with treatment (45%), communication (19%), accessibility (18%), concern for patients and families (10%), and billing (8%). Twenty-nine (5.3%) otolaryngologists were associated with 848 of 3659 (23.2%) total UPCs. Male sex and graduation from a US medical school were statistically significantly associated with an increased number of UPCs ( P = .0070 and P = .0036, respectively). Twenty-nine otolaryngologists with UPCs at or above the 95th percentile received peer-comparative feedback. The intervention led to an overall decrease in the number of UPCs following intervention ( P = .049). Twenty otolaryngologists (69%) categorized as “responders” reduced the number of complaints an average of 45% in the first 2 years following intervention. Discussion Physician demographic data can be used to identify otolaryngologists with a greater number of UPCs. Most commonly, UPCs expressed concern regarding treatment. Peer-delivered, comparative feedback can be effective in reducing UPCs in high-risk otolaryngologists. Implications for Practice Systematic monitoring and respectful sharing of peer-comparative patient complaint data offers an intervention associated with UPCs and concomitant malpractice risk reduction. Collegial feedback over time increases the response rate, but a small proportion of physicians will require directive interventions.

Design and Development of the Brain Training System for the Digital “Maintain Your Brain” Dementia Prevention Trial (Preprint)

BACKGROUND Dementia is the leading cause of disability worldwide, and interventions aimed at reducing the prevalence and burden of the disease are urgently needed. Maintain Your Brain (MYB) is a randomized controlled trial of a multimodal digital health intervention targeting modifiable dementia risk factors to combat cognitive decline and potentially prevent dementia. In addition to behavioral modules targeting mood, nutrition, and physical exercise, a new Brain Training System (BTS) will deliver computerized cognitive training (CCT) throughout the trial to provide systematic, challenging, and personally adaptive cognitive activity. OBJECTIVE This paper aimed to describe the design and development of BTS. METHODS BTS has been designed with a central focus on the end user. Raw training content is provided by our partner NeuroNation and delivered in several innovative ways. A baseline cognitive profile directs selection and sequencing of exercises within and between sessions and is updated during the 10-week 30-session module. Online trainers are available to provide supervision at different levels of engagement, including face-to-face share-screen coaching, a key implementation resource that is triaged by a “red flag” system for automatic tracking of user adherence and engagement, or through user-initiated help requests. Individualized and comparative feedback is provided to aid motivation and, for the first time, establish a social support network for the user based on their real-world circle of friends and family. RESULTS The MYB pilot was performed from November 2017 to March 2018. We are currently analyzing data from this pilot trial (n=100), which will make up a separate research paper. The main trial was launched in June 2018. Process and implementation data from the first training module (September to November 2018) are expected to be reported in 2019 and final trial outcomes are anticipated in 2022. CONCLUSIONS The BTS implemented in MYB is focused on maximizing adherence and engagement with CCT over the short and long term in the setting of a fully digital trial, which, if successful, could be delivered economically at scale. CLINICALTRIAL Australian New Zealand Clinical Trials Registry ACTRN12618000851268; https://www.anzctr.org.au /Trial/Registration/TrialReview.aspx?id=370631&isReview=true

Adding Psychological Factor in the Model of Electricity Consumption in Office Building

Researches indicate that energy behaviour is the key to energy conservation and suggest that comparative feedback on energy usage can generate savings in residential and organizational settings. In implementing comparative feedback in workplace, there are two different ways to disaggregate collective energy consumption and apportion it to building users; individual or group level. This research uses agent-based modelling and simulation to examine the impact of applying different approaches of energy data apportionment to change staff behaviour toward energy consumption reduction. A simulation model of energy consumption in workplace as a base model is a re-implementation and simplification from former research. Several psychological factors and decision-making mechanism are then being added as an extension. The model divides staffs into four energy awareness stereotypes based on motivation level. Sensitivity analysis suggests that motivation is an important factor in changing user‟s behaviour and the experiment results indicates greater potential for energy saving when energy usage is apportioned to group level. The significant difference of energy consumption level makes user with low and medium motivation should become the target of energy reduction campaign.