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The Electronic Asthma Management System (eAMS) improves primary care asthma management.

ABSTRACT: A high prevalence of suboptimal asthma control is attributable to known evidence-practice gaps. We developed a computerised clinical decision support system (the Electronic Asthma Management System (eAMS)) to address major care gaps and sought to measure its impact on care in adults with asthma.This was a 2-year interrupted time-series study of usual care (year 1) versus eAMS (year 2) at three Canadian primary care sites. We included asthma patients aged ≥16 years receiving an asthma medication within the last 12 months. The eAMS consisted of a touch tablet patient questionnaire completed in the waiting room, with real-time data processing producing electronic medical record-integrated clinician decision support.Action plan delivery (primary outcome) improved from zero out of 412 (0%) to 79 out of 443 (17.8%) eligible patients (absolute increase 0.18 (95% CI 0.14-0.22)). Time-series analysis indicated a 30.5% increase in physician visits with action plan delivery with the intervention (p<0.0001). Assessment of asthma control level increased from 173 out of 3497 (4.9%) to 849 out of 3062 (27.7%) eligible visits (adjusted OR 8.62 (95% CI 5.14-12.45)). Clinicians escalated controller therapy in 108 out of 3422 (3.2%) baseline visits versus 126 out of 3240 (3.9%) intervention visits (p=0.12). At baseline, a short-acting β-agonist alone was added in 62 visits and a controller added in 54 visits; with the intervention, this occurred in 33 and 229 visits, respectively (p<0.001).The eAMS improved asthma quality of care in real-world primary care settings. Strategies to further increase clinician uptake and a randomised controlled trial to assess impact on patient outcomes are now required.

SUBMITTER: Gupta S

PROVIDER: S-EPMC6482383 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:OBJECTIVES:Care gaps in asthma may be highly prevalent but are poorly characterised. We sought to prospectively measure adherence to key evidence-based adult asthma practices in primary care, and predictors of these behaviours. DESIGN:One-year prospective cohort study employing an electronic chart audit. SETTING:Three family health teams (two academic, one community-based) in Ontario, Canada. PARTICIPANTS:884 patients (72.1% female; 46.0±17.5 years old) (4199 total visits; 4.8±4.8 visits/patient) assigned to 23 physicians (65% female; practising for 10.0±8.6 years). MAIN OUTCOME MEASURES:The primary outcome was the proportion of visits during which practitioners assessed asthma control according to symptom-based criteria. Secondary outcomes included the proportion of: patients who had asthma control assessed at least once; visits during which a controller medication was initiated or escalated; and patients who received a written asthma action plan. Behavioural predictors were established a priori and tested in a multivariable model. RESULTS:Primary outcome: Providers assessed asthma control in 4.9% of visits and 15.4% of patients. Factors influencing assessment included clinic site (p=0.019) and presenting symptom, with providers assessing control more often during visits for asthma symptoms (35.0%) or any respiratory symptoms (18.8%) relative to other visits (1.6%) (p<0.01). SECONDARY OUTCOMES:Providers escalated controller therapy in 3.3% of visits and 15.4% of patients. Factors influencing escalation included clinic site, presenting symptom and prior objective asthma diagnosis. Escalation occurred more frequently during visits for asthma symptoms (21.0%) or any respiratory symptoms (11.9%) relative to other visits (1.5%) (p<0.01) and in patients without a prior objective asthma diagnosis (3.5%) relative to those with (1.3%) (p=0.025). No asthma action plans were delivered. CONCLUSIONS:Major gaps in evidence-based asthma practice exist in primary care. Targeted knowledge translation interventions are required to address these gaps, and can be tailored by leveraging the identified behavioural predictors. TRIAL REGISTRATION NUMBER:NCT01070095; Pre-results.

Project description:BackgroundmHealth tablet-based interventions are increasingly being studied and deployed in various health care settings, yet little knowledge exists regarding patient uptake and acceptance or how patient demographics influence these important implementation metrics.ObjectiveTo determine which factors influence the uptake and successful completion of an mHealth tablet questionnaire by analyzing its implementation in a primary care setting.MethodsWe prospectively studied a patient-facing electronic touch-tablet asthma questionnaire deployed as part of the Electronic Asthma Management System. We describe tablet uptake and completion rates and corresponding predictor models for these behaviors.ResultsThe tablet was offered to and accepted by patients in 891/1715 (52.0%) visits. Patients refused the tablet in 33.0% (439/1330) visits in which it was successfully offered. Patients aged older than 65 years of age (odds ratio [OR] 2.30, 95% CI 1.33-3.95) and with concurrent chronic obstructive pulmonary disease (OR 2.22, 95% CI 1.05-4.67) were more likely to refuse the tablet, and those on an asthma medication (OR 0.55, 95% CI 0.30-0.99) were less likely to refuse it. Once accepted, the questionnaire was completed in 784/891 (88.0%) instances, with those on an asthma medication (OR 0.53, 95% CI 0.32-0.88) being less likely to leave it incomplete.ConclusionsOlder age predicted initial tablet refusal but not tablet questionnaire completion, suggesting that perceptions of mHealth among older adults may negatively impact uptake, independent of usability. The influence of being on an asthma medication suggests that disease severity may also mediate mHealth acceptance. Although use of mHealth questionnaires is growing rapidly across health care settings and diseases, few studies describe their real-world acceptance and its predictors. Our results should be complemented by qualitative methods to identify barriers and enablers to uptake and may inform technological and implementation strategies to drive successful usage.

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The Electronic Asthma Management System (eAMS) improves primary care asthma management.

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