The goal of this study is to determine whether an 'eco' version of the Electronic Asthma Management System (eAMS) can reduce inhaler carbon emissions in primary care, in patients with asthma. The existing eAMS uses patient-specific criteria (asthma control, asthma flare-up risk, and current medications) to provide guideline-based computerized clinical decision support to clinicians, to improve the delivery of asthma care. The eAMS-Eco includes embedded cues and messaging on the environmental impact of inhaler medications and links to a patient-friendly conversation aid that facilitates shared decision-making and climate-conscious prescribing. The study will evaluate the implementation of the eAMS-Eco in two primary care clinics that have been using the existing eAMS, using an interrupted time-series analysis (one year pre- and post-launch of the eAMS-Eco). The investigators will assess system uptake and user feedback on the eAMS-Eco, as well as changes in inhaler prescriptions (including resulting changes in carbon emissions and costs) and changes in asthma control, in the implementation period (eAMS-Eco) compared to the baseline period (eAMS).
Climate change poses a significant threat to human health and yet healthcare itself contributes substantially to climate change. Reducing the carbon emissions from healthcare is one actionable step to combat the climate crisis. In regards to asthma care, reductions in carbon emissions could be achieved by addressing the unnecessary of metered-dose inhalers (MDIs), the propellants in which contain potent greenhouse gases. This could be achieved by preferentially prescribing inhaler devices such as dry powder inhalers (DPIs) and soft mist inhalers (SMIs), which do not use propellants and have much lower carbon footprints than MDIs. These devices are almost always available in the same medication classes as MDIs (sometimes with the same active ingredient) and demonstrate comparable clinical efficacy and patient acceptability. Yet MDIs still account for the majority of prescribed inhalers. The investigators will leverage the existing Electronic Asthma Management System (eAMS), a computerized decision support system (CDSS) that recommends guideline-based medication changes based on assessment of the patients' asthma control and exacerbation risk, to promote climate-conscious prescribing at the point-of-care. When tested in real-world settings, the eAMS improved the quality of asthma care, with a significant increase in the provision of asthma action plans, assessment of asthma control, use of guideline-based inhaler medications, including escalation of controller therapy when indicated. Subsequently, the tool has been used widely in primary care sites in Ontario. To address the issue of inhaler GHG emissions, our team has now created an enhanced version of the existing eAMS, called the 'eAMS-Eco'. The eAMS-Eco has embedded cues and messaging that indicate the relative carbon footprint of each medication recommended by the eAMS, to provide clinicians with the knowledge needed to enact climate-conscious prescribing. A an orange or red leaf appears next to the recommended medication with hover text indicating that the device has a moderate or high carbon footprint, respectively. The medication name and hover text are clickable links which take the clinician to an inhaler conversation aid, which serves to promote shared decision-making by presenting the carbon footprint (as the equivalent to kilometers driven in a gas powered car) and cost of each inhaler in the corresponding medication class, along with usage details (dosing, number of inhalations per dose, number of doses per device). The conversation aids also include information on inhaler contents (active ingredients) and include a safety warning that emphasizes the importance of considering patient-level factors, such as adequate technique, age, disease severity, and the impact on adherence, when selecting an inhaler device. Ultimately, the eco-features added to the eAMS are designed to promote climate-conscious prescribing of inhalers while considering the preference and ability of each individual patient. Our study will evaluate the implementation of the eAMS-Eco in two primary care clinics which are already using the eAMS, with an overall goal of reducing inhaler emissions in the primary care of patients with asthma.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Enrollment
95
An 'eco' version of a computerized clinical decision support system that provides information on the carbon footprint of inhalers when making guideline-based treatment recommendations for patients with asthma
Taddle Creek Family Health Team (Bay Street)
Toronto, Ontario, Canada
Taddle Creek Family Health Team (Bloor Street)
Toronto, Ontario, Canada
Prescribed inhaler carbon emissions
Among patients entering on at least one metered dose inhaler, system analytics, chart review and existing data on inhaler carbon emissions will be used to assess the average and total difference in the change (exit versus entry medications) in estimated annual carbon emissions from inhalers per patient between the baseline and implementation periods
Time frame: 24 months, cumulative and broken into individual time periods
Proportion of low carbon footprint inhalers to moderate/high carbon footprint inhalers prescribed
For all new inhaler prescriptions, system analytics and chart review data will be used to compare the difference in the average proportion of low to moderate/high carbon footprint inhalers across all patients, between the baseline and implementation periods
Time frame: 24 months, cumulative and broken into individual time periods
Cost of prescribed inhalers
Among patients entering on at least one metered dose inhaler, system analytics, chart review and data from Ontario's provincial drug formulary will be used to assess the difference in the change (exit versus entry medications) in the estimated annual cost of prescribed inhalers, per patient, between the baseline and implementation periods
Time frame: 24 months, cumulative and broken into individual time periods
System usage: conversation aid access
Using system analytics from the implementation period, investigators will determine the proportion of visits in which the conversation aid was accessed when it was available and assess trends in access over time
Time frame: 12 months, cumulative and broken into individual time periods
System usage: decision-support access
Using system analytics, investigators will assess compare use of the decision support (access, medication changes, and asthma action plans created) between the baseline and implementation period
Time frame: 24 months, cumulative and broken into individual time periods
Quantitative patient Likert-Scale questionnaire
Exclusively throughout the implementation period, the investigators will identify clinic visits where the conversation aid was available and invite patients to complete an online feedback questionnaire to assess perceptions on the conversation aid's utility, content, and impact (using a 5-point likert scale from strongly disagree to strongly agree), overall impressions (rating from 1: worst to 10: best) and impact of switching (or not switching) to a lower carbon device on inhaler adherence, feelings of guilt, and contribution to climate action.
Time frame: 12 months
Patient feedback: 4-item Shared Decision-Making Process Scale
Exclusively throughout the implementation period, the investigators will identify clinic visits where the conversation aid was available and invite patients to complete the 4-item Shared Decision-Making (SDM) Process Scale (Version 2.0) which measures the amount of SDM that occurs around inhaler selection to assess the quality of shared decision-making during their recent clinic visit. Higher scores (range 0 to 4) reflect higher quality of SDM.
Time frame: 12 months
Qualitative patient free-text feedback questionnaire
Exclusively throughout the implementation period, the investigators will identify clinic visits in which the conversation aid was available and invite patients to provide feedback on their experience during their recent clinic visit
Time frame: 12 months
Quantitative provider Likert-Scale questionnaire
At the end of the implementation period, all providers who accessed the eAMS-Eco and had at least one visit with the Eco features triggered, will be invited to complete an online questionnaire to assess their perceptions of the eAMS-Eco and the conversation aid's utility, content and impact (using a 5-point likert scale from strongly disagree to strongly agree).
Time frame: 12 months
Provider feedback: 10-item System Usability Scale
At the end of the implementation period, all providers who accessed the eAMS-Eco and had at least one visit with the Eco features triggered, will be invited to complete the 10-item System Usability Scale (SUS) to assess feedback on system usability (using a 5-point likert scale from strongly disagree to strongly agree). Higher scores (range 0 to 100) reflect higher overall usability.
Time frame: 12 months
Qualitative provider free-text feedback questionnaire
At the end of the implementation period, all providers who accessed the eAMS-Eco and had at least one visit with the Eco features triggered, will be invited to provide feedback on their experience using the eAMS-Eco
Time frame: 12 months
Asthma Control
Among all patients who had at least one visit during the baseline and/or implementation period, the investigators will assess change in asthma control, exclusively using data from the pre-visit eAMS questionnaire (among patients with multiple visits during the baseline and/or implementation period) or by inviting patients to complete the pre-visit questionnaire at the end of the baseline and/or implementation period (among patients with a single visit during either period). Asthma control is scored as acceptable or suboptimal according to Canadian guidelines based on frequency of daytime symptoms, rescue medication use; nighttime awakenings; impact on school/work attendance; impact on exercise; and exacerbations.
Time frame: 24 months, cumulative and broken into individual time periods
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