Pharmacological Risk Assessment Among Older Patients with Polypharmacy Using the Clinical Decision Support System Janusmed Risk Profile: A Cross-Sectional Register Study.

BACKGROUND: Polypharmacy in older people is steadily increasing and a combination of many medicines may result in adverse effects, especially if the medicines interact pharmacodynamically. Examples are additive or synergistic effects increasing the risk of falls, haemorrhage, serotonin syndrome and torsade de pointes. The clinical decision support system Janusmed Risk Profile has been developed to find such risks based on a patients' medication list. OBJECTIVES: The main aim of this retrospective register-based study was to study what pharmacodynamic risks older patients (aged 65 years or older) on polypharmacy (defined as using five or more medicines) are exposed to. Second, we studied if the introduction of the Janusmed Risk Profile in the main electronic health record system in Region Stockholm influenced the proportion of patients prescribed combinations that increase the risk for the nine adverse-effect categories defined (anticholinergic effects, haemorrhage, constipation, orthostatism, QT prolongation, renal toxicity, sedation, seizures and serotonin syndrome). METHODS: Data on all prescription medicines to individuals aged 65 years or older, and with at least five concomitant medicines were retrieved and analysed for the risk categories in the Janusmed Risk Profile. The proportions of patients with a high/moderate risk during a 4-month period before (period 1) and after (period 2) the introduction were compared. RESULTS: A total of 127,719 patients in period 1 (November 2016-February 2017), and 131,458 patients in period 2 (November 2017-February 2018) were included in the study. The proportion of patients with a high or moderate risk for each of the nine properties (anticholinergic effects, haemorrhage, constipation, orthostatism, QT prolongation, renal toxicity, sedation, seizures and serotonergic effects) were 10.9, 34.7, 32.8, 33.6, 17.2, 0.7, 15.4, 0.5 and 2.4%, respectively, in period 1 and 10.4, 35.5, 32.8, 33.3, 10.8, 0.71, 14.9, 0.5 and 2.3% in period 2. The changes for sedation and QT prolongation were statistically significant, with the most pronounced decrease for QT prolongation from 17.2 to 10.8% (p < 0.001). When analysing patients at a high risk, the decrease was significant for haemorrhage, orthostatism, QT prolongation and sedation. CONCLUSIONS: Older people are exposed to combinations of medications that increase the risk for potentially severe adverse effects. Prescribers seem to respond especially to warnings for QT prolongation, presented in the Janusmed Risk Profile implemented in the electronic health record system.

[Janusmed Renal Function, an appreciated CDSS to support prescription of drugs and appropriate dosing in patients with renal impairment]. / ¼Janusmed njurfunktion« ­ stöd för anpassning av läkemedelsdos.

Janusmed Renal Function is a clinical decision support system (CDSS) that provides evidence-based dosage recommendations for adult patients with renal impairment. Dosage recommendations are presented for each drug/active substance in relation to four stages of chronic kidney disease (CKD). In addition, substances that are nephrotoxic are labelled with a warning. The web version is available with free access for all caregivers in Sweden, and there is also a version available for integration in electronic health record (EHR) systems. A questionnaire distributed among users who already use a health record integrated version of the CDSS showed that physicians have good support from the system and perceive it as useful.

dfgcompare: a library to support process variant analysis through Markov models.

BACKGROUND: Data-driven process analysis is an important area that relies on software support. Process variant analysis is a sort of analysis technique in which analysts compare executed process variants, a.k.a. process cohorts. This comparison can help to identify insights for improving processes. There are a few software supports to enable process cohort comparison based on the frequencies of process activities and performance metrics. These metrics are effective in cohort analysis, but they cannot support cohort comparison based on the probability of transitions among states, which is an important enabler for cohort analysis in healthcare. RESULTS: This paper defines an approach to compare process cohorts using Markov models. The approach is formalized, and it is implemented as an open-source python library, named dfgcompare. This library can be used by other researchers to compare process cohorts. The implementation is also used to compare caregivers' behavior when prescribing drugs in the Stockholm Region. The result shows that the approach enables the comparison of process cohorts in practice. CONCLUSIONS: We conclude that dfgcompare supports identifying differences among process cohorts.

Patients' Use and Perceptions of a Drug-Drug Interaction Database: A Survey of Janusmed Interactions.

Janusmed interactions is a drug-drug interactions (DDI) database available online for healthcare professionals (HCP) at all levels of the healthcare system including pharmacies. The database is aimed at HCP but is also open to the public for free, for those individuals who register for a personal account. The aim of this study was to investigate why and how patients use the database Janusmed interactions, how they perceive content and usability, and how they would react if they found an interaction. A web-based questionnaire was sent by email to all users who had registered for Janusmed interactions as a "patient" (n = 3219). A total of 406 patients completed the survey (response rate 12.6%). The study shows that there is an interest among patients to use a DDI database to check their own or a relative's medication. The respondents found the database easy to use and perceive they understand the information aimed at HCP. Most patients stated they would talk to their HCP if they found an interaction and not adjust their treatment by themselves. However, the respondents in this study are actively searching for information and seem to have high health literacy. Thus, the findings are not generalizable for the general population.

Evaluating a Clinical Decision Support System for Drug-Drug Interactions.

Janusmed is a clinical decision support system, developed by the Stockholm County Council that supports physicians in identifying drug-drug interactions. To determine how Janusmed is used in and affects the clinical practice, an evaluation study is currently being carried out that analyzes multiple data sources through descriptive statistics. The study focuses on how Janusmed affects the behavior of the physicians, in particular, to what extent physicians reconsider their prescription decisions based on warnings from Janusmed.