To assess the effects of an electronic health record (EHR) intervention that prompts the clinician to prescribe nicotine replacement therapy (NRT) at hospital admission and discharge in a large integrated health system.

Retrospective cohort study using interrupted time series (ITS) analysis leveraging EHR data generated before and after implementation of the 2015 EHR-based intervention.

Kaiser Permanente Northern California, a large integrated health system with 4.2 million members.

Current smokers aged ≥18 hospitalised for any reason.

EHR-based clinical decision supports that prompted the clinician to order NRT on hospital admission (implemented February 2015) and discharge (implemented September 2015).

Primary outcomes included the monthly percentage of admitted smokers with NRT orders during admission and at discharge. A secondary outcome assessed patient quit rates within 30 days of hospital discharge as reported during discharge follow-up outpatient visits.

The percentage of admissions with NRT orders increased from 29.9% in the year preceding the intervention to 78.1% in the year following (41.8% change, 95% CI 38.6% to 44.9%) after implementation of the admission hard-stop intervention compared with the baseline trend (ITS estimate). The percentage of discharges with NRT orders increased acutely at the time of both interventions (admission intervention ITS estimate 15.5%, 95% CI 11% to 20%; discharge intervention ITS estimate 13.4%, 95% CI 9.1% to 17.7%). Following the implementation of the discharge intervention, there was a small increase in patient-reported quit rates (ITS estimate 5.0%, 95% CI 2.2% to 7.8%).

An EHR-based clinical decision-making support embedded into admission and discharge documentation was associated with an increase in NRT prescriptions and improvement in quit rates. Similar systemic EHR interventions can help improve smoking cessation efforts after hospitalisation.

To (1) pilot a study of behavioural characterisation based on risk and time preferences in clinically well-characterised individuals, (2) assess the distribution of preferences in this population and (3) explore differences in preferences between individuals with ‘lifestyle-related’ (LS) and ‘non-lifestyle-related’ (NLS) cardiovascular diseases.

Cross-sectional study with an economic online experiment to collect risk and time preferences, a detailed clinical characterisation and a sociodemographic and lifestyle survey. A definition of LS and NLS groups was developed.

Specialist outpatient clinics of the clinic for cardiology and pneumology of the University Hospital Düsseldorf and patients from a cardiology practice in Düsseldorf.

A total of 74 individuals with cardiovascular diseases.

Risk and time preferences.

The implementation of the study process, including participant recruitment and data collection, ran smoothly. The medical checklist, the survey and the time preference instrument were well received. However, the conceptual understanding of the risk preference instrument resulted in inconsistent choices for many participants (47%). The remaining individuals were more risk averse (27%) than risk seeking (16%) and risk neutral (10%). Individuals in our sample were also more impatient (49%) than patient (42%). The participant classification showed that 65% belonged to the LS group, 19% to the NLS group and 16% could not be assigned (unclear allocation to lifestyle (ULS) group). Excluding the ULS group, we show that individuals in the LS group were more risk seeking, and unexpectedly, more patient than those in the NLS group.

The process of the pilot study and its results can be used as a basis for the design of the main study. The differences in risk and time preferences between the LS and NLS groups provide us with a novel hypothesis for unhealthy behaviours: individuals never give up a bad habit, they simply postpone the latter, which can be tested alongside other additional research questions.