Strategies to guide the successful implementation of deprescribing in community practice: Lessons learned from the front line

Background

Sustainable implementation of new professional services into clinical practice can be difficult. In 2019, a population-wide initiative called SaferMedsNL was implemented across the province of Newfoundland and Labrador (NL), to promote appropriate medication use. Two evidence-based interventions were adapted to the context of NL to promote deprescribing of proton pump inhibitors and sedatives. The objective of this study was to identify and prioritize which actions supported the implementation of deprescribing in community practice for pharmacists, physicians and nurse practitioners across the province.

Methods

Community pharmacists, physicians and nurse practitioners were invited to participate in virtual focus groups. Nominal Group Technique was used to elicit responses to the question: "What actions support the implementation of deprescribing into the daily workflow of your practice?" Participants prioritized actions within each group while thematic analysis permitted comparison across groups.

Results

Five focus groups were held in fall 2020 involving pharmacists (n = 11), physicians (n = 7) and nurse practitioners (n = 4). Participants worked in rural (n = 10) and urban (n = 12) settings. The different groups agreed on what the top 5 actions were, with the top 5 receiving 68% of the scores: (1) providing patient education, (2) allocating time and resources, (3) building interprofessional collaboration and communication, (4) fostering patient relationships and (5) aligning with public awareness strategies.

Conclusion

Pharmacists, physicians and nurse practitioners identified similar actions that supported implementing evidence-based deprescribing into routine clinical practice. Sharing these strategies may help others embed deprescribing into daily practice and assist the uptake of medication appropriateness initiatives by front-line providers. Can Pharm J (Ott) 2024;157:xx-xx.

Comparison of individual and pooled sampling methods for estimation of Vairimorpha (Nosema) spp. levels in experimentally infected honey bee colonies

The microsporidian pathogens Vairimorpha apis and V. ceranae are known to cause intestinal infection in honey bees and are associated with decreased colony productivity and colony loss. The widely accepted method for determining Vairimorpha colony infection level for risk assessment and antibiotic treatment is based on spore counts of 60 pooled worker bees using light microscopy. Given that honey bee colonies consist of as many as 1,000 times more individuals, the number of bees collected for Vairimorpha detection may significantly impact the estimated colony infection level, especially in the case of uneven distribution of high- and low-infected individuals within a hive. Hence, we compared the frequency and severity of Vairimorpha infection in individual bees to pooled samples of 60, 120, and 180 bees, as well as compared the Vairimorpha spp. prevalence in pooled samples of 60 and 180 bees. Overall, we did not find significant differences in spore counts in pooled samples containing incremental numbers of bees, although we observed that, in less-infected colonies, a low frequency of highly infected individuals influenced the estimated colony infection level. Moreover, Vairimorpha spp. prevalence did not differ significantly among the pooled bee samples tested. Increasing the number of pooled bees from the recommended 60 bees to 180 bees did not yield a more accurate representation of colony infection level for highly infected colonies, but the clinical importance of a low frequency of highly infected individuals in less-infected colonies needs to be addressed in future studies.

The state of lead scoring models and their impact on sales performance

Although lead scoring is an essential component of lead management, there is a lack of a comprehensive literature review and a classification framework dedicated to it. Lead scoring is an effective and efficient way of measuring the quality of leads. In addition, as a critical Information Technology tool, a proper lead scoring model acts as an alleviator to weaken the conflicts between sales and marketing functions. Yet, little is known regarding lead scoring models and their impact on sales performance. Lead scoring models are commonly categorized into two classes: traditional and predictive. While the former primarily relies on the experience and knowledge of salespeople and marketers, the latter utilizes data mining models and machine learning algorithms to support the scoring process. This study aims to review and analyze the existing literature on lead scoring models and their impact on sales performance. A systematic literature review was conducted to examine lead scoring models. A total of 44 studies have met the criteria and were included for analysis. Fourteen metrics were identified to measure the impact of lead scoring models on sales performance. With the increased use of data mining and machine learning techniques in the fourth industrial revolution, predictive lead scoring models are expected to replace traditional lead scoring models as they positively impact sales performance. Despite the relative cost of implementing and maintaining predictive lead scoring models, it is still beneficial to supersede traditional lead scoring models, given the higher effectiveness and efficiency of predictive lead scoring models. This study reveals that classification is the most popular data mining model, while decision tree and logistic regression are the most applied algorithms among all the predictive lead scoring models. This study contributes by systematizing and recommending which machine learning method (i.e., supervised and/or unsupervised) shall be used to build predictive lead scoring models based on the integrity of different types of data sources. Additionally, this study offers both theoretical and practical research directions in the lead scoring field.

Measuring re-identification risk using a synthetic estimator to enable data sharing

Background

One common way to share health data for secondary analysis while meeting increasingly strict privacy regulations is to de-identify it. To demonstrate that the risk of re-identification is acceptably low, re-identification risk metrics are used. There is a dearth of good risk estimators modeling the attack scenario where an adversary selects a record from the microdata sample and attempts to match it with individuals in the population.

Objectives

Develop an accurate risk estimator for the sample-to-population attack.

Methods

A type of estimator based on creating a synthetic variant of a population dataset was developed to estimate the re-identification risk for an adversary performing a sample-to-population attack. The accuracy of the estimator was evaluated through a simulation on four different datasets in terms of estimation error. Two estimators were considered, a Gaussian copula and a d-vine copula. They were compared against three other estimators proposed in the literature.

Results

Taking the average of the two copula estimates consistently had a median error below 0.05 across all sampling fractions and true risk values. This was significantly more accurate than existing methods. A sensitivity analysis of the estimator accuracy based on variation in input parameter accuracy provides further application guidance. The estimator was then used to assess re-identification risk and de-identify a large Ontario COVID-19 behavioral survey dataset.

Conclusions

The average of two copula estimators consistently provides the most accurate re-identification risk estimate and can serve as a good basis for managing privacy risks when data are de-identified and shared.

Enhanced protection face masks do not adversely impact thermophysiological comfort

The World Health Organization has advocated mandatory face mask usage to combat the spread of COVID-19, with multilayer masks recommended for enhanced protection. However, this recommendation has not been widely adopted, with noncompliant persons citing discomfort during prolonged usage of face masks. And yet, a scientific understanding on how face mask fabrics/garment systems affect thermophysiological comfort remains lacking. We aimed to investigate how fabric/garment properties alter the thermal and evaporative resistances responsible for thermophysiological strain. We constructed 12 different layered facemasks (D1-D5, T1-T6, Q1) with various filters using commercially available fabrics. Three approaches were employed: (1) the evaporative and thermal resistances were measured in all the test face masks using the medium size to determine the effect of fabric properties; (2) the effect of face mask size by testing close-fitted (small), fitted (medium) and loose fitted (large) face mask T-6; (3) the effect of face mask fit by donning a large size face mask T-6, both loose and tightened using thermal manikin, Newton. ANOVA test revealed that the additional N95 middle layer filter has no significant effect on the thermal resistances of all the face masks, and evaporative resistances except for face masks T-2 and T-3 (P-values<0.05) whereas size significantly affected thermal and evaporative resistances (P-values<0.05). The correlation coefficient between the air gap size and the thermal and evaporative resistance of face masks T-6 were R² = 0.96 and 0.98, respectively. The tight fit large face mask had superior performance in the dissipation of heat and moisture from the skin (P-values <0.05). Three-layer masks incorporating filters and water-resistant and antimicrobial/antiviral finishes did not increase discomfort. Interestingly, using face masks with fitters improved user comfort, decreasing thermal and evaporative resistances in direct opposition to the preconceived notion that safer masks decrease comfort.

Management of veterinary anaesthesia and analgesia in small animals: A survey of English-speaking practitioners in Canada

OBJECTIVE

To describe how small animal anaesthesia and analgesia is performed in English-speaking Canada, document any variation among practices especially in relation to practice type and veterinarian's experience and compare results to published guidelines.

DESIGN

Observational study, electronic survey.

SAMPLE

126 respondents.

PROCEDURE

A questionnaire was designed to assess current small animal anaesthesia and analgesia practices in English-speaking Canadian provinces, mainly in Ontario, Alberta and British Columbia. The questionnaire was available through SurveyMonkey® and included four parts: demographic information about the veterinarians surveyed, evaluation and management of anaesthetic risk, anaesthesia procedure, monitoring and safety. Year of graduation and type of practice were evaluated as potential risk factors. Exact chi-square tests were used to study the association between risk factors and the association between risk factors and survey responses. For ordinal data, the Mantel-Haenszel test was used instead.

RESULTS

Response rate over a period of 3 months was 12.4% (126 respondents out of 1 016 invitations). Current anaesthesia and analgesia management failed to meet international guidelines for a sizable number of participants, notably regarding patient evaluation and preparation, safety and monitoring. Nearly one third of the participants still consider analgesia as optional for routine surgeries. Referral centres tend to follow guidelines more accurately and are better equipped than general practices.

CONCLUSIONS AND CLINICAL RELEVANCE

A proportion of surveyed Canadian English-speaking general practitioners do not follow current small animal anaesthesia and analgesia guidelines, but practitioners working in referral centres are closer to meet these recommendations.

Sex and age bias viral burden and interferon responses during SARS-CoV-2 infection in ferrets

SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) hospitalizations and deaths disportionally affect males and older ages. Here we investigated the impact of male sex and age comparing sex-matched or age-matched ferrets infected with SARS-CoV-2. Differences in temperature regulation was identified for male ferrets which was accompanied by prolonged viral replication in the upper respiratory tract after infection. Gene expression analysis of the nasal turbinates indicated that 1-year-old female ferrets had significant increases in interferon response genes post infection which were delayed in males. These results provide insight into COVID-19 and suggests that older males may play a role in viral transmission due to decreased antiviral responses.

Salivary Heme Oxygenase-1: A Potential Biomarker for Central Neurodegeneration

BACKGROUND

Parkinson disease (PD) is the second most common neurodegenerative disease, affecting 2% of the population over 65 years of age. PD diagnosis is based on clinical examination and can only be confirmed during autopsy. In 2018, we reported that heme oxygenase-1 (HO-1), an inducible stress response protein important for heme catabolism and implicated in PD pathology, was higher in PD saliva relative to healthy controls, suggesting that salivary HO-1 may serve as a potential biomarker of PD.

OBJECTIVES

To ascertain whether HO-1 protein levels are elevated in PD saliva relative to degenerative neurological, non-degenerative neurological and healthy controls.

METHODOLOGY

The study included 307 participants comprising 75 participants with idiopathic PD and 3 control groups: 162 non-neurological, 37 non-PD degenerative neurological, and 33 non-degenerative neurological participants. Salivary HO-1 and total protein concentrations were measured using ELISA and BCA assay, respectively. Receiver operating characteristic (ROC) curves were used to estimate model discrimination. Analyses were adjusted by age, sex, total protein, and relevant comorbidities.

RESULTS

Elevated HO-1 concentrations were observed in the PD group and other neurodegenerative conditions compared to subjects with no neurological or non-degenerative neurological conditions. ROC curves using HO-1 levels and covariates yielded areas under the curve above 85% in models for PD or neurodegenerative conditions versus controls.

CONCLUSIONS

Salivary HO-1 concentrations in combination with covariates may provide a biomarker signature that distinguishes patients with neurodegenerative conditions from persons without.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that salivary HO-1 multivariable models can distinguish neurodegenerative conditions.