Integrating digital inhalers into clinical care of patients with asthma and chronic obstructive pulmonary disease.

Modernizing inhaled medications through digital technology can help address persistent problems of non-adherence and poor inhaler technique in patients with obstructive lung diseases. With a growing body of supportive clinical studies, advances in digital inhaler sensors and platforms, greater support from payers and healthcare organizations, significant growth with these technologies is expected. While all digital (smart) inhalers record adherence, these are distinguished by their compatibility with commercial inhalers, capabilities to guide inhaler technique, use of patient-reported outcomes, and user-friendliness for both the healthcare professional (HCP) and patient. Due to the complexity and novelty of employing digital inhalers, collaboration with multiple entities within health systems is necessary and a well-planned integration is needed. For HCPs and patients, cybersecurity and privacy are critical, it will require review by each healthcare organization. In the US, some payers reimburse for remote monitoring using digital inhalers, but reimbursement is currently unavailable in other countries. There are several models for remote patient care, as employing an active, ongoing digital interface between the HCP and patient or they may choose to only review data at clinical encounters. Personalization of therapies and feedback are key to success. While digital inhaler malfunction uncommonly occurs, patient attrition over a year is significant. Some patients will be challenged to use digital platforms or have the necessary technology. Additional research is needed to address cost-effectiveness, in vivo accuracy of inspiratory measurement capable devices, ability to teach inhaler technique, their application for monitoring lung function, and lastly real-world adoption and implementation in routine clinical practice.

Lipid levels and major adverse cardiovascular events in patients initiated on statins for primary prevention: an international population-based cohort study protocol.

BACKGROUND: Clinical guidelines recommend specific targets for low-density lipoprotein cholesterol (LDL-C) and non-high-density lipoprotein cholesterol (non-HDL-C) for primary prevention of cardiovascular disease (CVD). Furthermore, individual variability in lipid response to statin therapy requires assessment of the association in diverse populations. AIM: To assess whether lower concentrations of LDL-C and non-HDL-C are associated with a reduced risk of major adverse cardiovascular events (MACE) in primary prevention of CVD. DESIGN & SETTING: An international, new-user, cohort study will be undertaken. It will use data from three electronic health record databases from three global regions: Clinical Practice Research Datalink, UK; PREDICT-CVD, New Zealand (NZ); and the Clinical Data and Analysis Reporting System, Hong Kong (HK). METHOD: New statin users without a history of atherosclerotic CVD, heart failure, or chronic kidney disease, with baseline and follow-up lipid levels will be eligible for inclusion. Patients will be classified according to LDL-C (<1.4, 1.4-1.7, 1.8-2.5, and ≥2.6 mmol/l) and non-HDL-C (<2.2, 2.2-2.5, 2.6-3.3, and ≥3.4 mmol/l) concentrations 24 months after initiating statin therapy. The primary outcome of interest is MACE, defined as the first occurrence of coronary heart disease, stroke, or cardiovascular death. Secondary outcomes include all-cause mortality and the individual components of MACE. Sensitivity analyses will be conducted using lipid levels at 3 and 12 months after starting statin therapy. CONCLUSION: Results will inform clinicians about the benefits of achieving guideline recommended concentrations of LDL-C for primary prevention of CVD.