Effect of a smart temperature logger on correctly storing biological disease-modifying antirheumatic drugs at home: a pre-post study.

OBJECTIVES: Biological disease-modifying antirheumatic drugs (bDMARDs) require specific storage temperatures, but are frequently stored outside the recommended range of 2-8°C. As incorrect storage may affect therapy effectiveness and consequently lead to higher disease activity, compliance with recommended storage temperatures should be improved. eHealth interventions can provide insight into storage temperatures and alerts in case of deviations from recommended temperatures. Therefore, this study aims to assess the effect of a smart temperature logger on correctly storing bDMARDs at home by patients with rheumatic diseases. METHODS: A pre-post study was performed in a hospital in the Netherlands. The baseline period consisted of 12 weeks of storage temperature measurement with a passive temperature logger, and the intervention period consisted of 12 weeks of storage temperature measurement with a smart temperature logger. This smart logger included a smartphone application which provided insight into storage temperatures and real-time alerts when exceeding recommended temperatures. The main outcome measure was the difference in the number of patients who stored their bDMARDs correctly between baseline and intervention. Secondary outcomes were the difference in the proportion of measurement time within 2-8°C between baseline and intervention, the distribution of measurement time among temperature categories, and the patient's acceptance measured using a questionnaire based on the Technology Acceptance Model. RESULTS: In total, 48 participants (median age 55 years (IQR 47-64), 53% male) were analysed. The proportion of participants correctly storing bDMARDs increased from 18.8% (n=9) during baseline to 39.6% (n=19) during intervention (p=0.004). The median proportion of measurement time between 2-8°C improved by 6% (IQR 0-34%) (p<0.0001). Technology acceptance was scored as moderate. CONCLUSIONS: Temperature monitoring and real-time feedback with a smart temperature logger shows potential to improve at-home storage of bDMARDs, provided that continuous connection is realised to ensure real-time alerts and data collection.

Preferences of Patients With Musculoskeletal Disorders Regarding the Timing and Channel of eHealth and Factors Influencing Its Use: Mixed Methods Study.

BACKGROUND: Implementation of eHealth is progressing slowly. In-depth insight into patients' preferences and needs regarding eHealth might improve its use. OBJECTIVE: This study aimed to describe when patients want to use eHealth, how patients want to communicate and receive information digitally, and what factors influence the use of eHealth in clinical practice. METHODS: A multimethod study was conducted. Two meetings of ~5.5 hours with plenary information sessions and focus groups were held with 22 patients from the rheumatology, orthopedics, and rehabilitation departments of a Dutch hospital specialized in musculoskeletal disorders. Assignments were performed during the focus groups in which qualitative (eg, semistructured interview questions) and quantitative (ie, voting and ranking factors) data were collected. RESULTS: The way patients want to use eHealth varies between patients and moments of a patient's care pathway. Patients' digital channel preferences depended on the need for interaction with a health care provider (HCP). The interaction need is in turn influenced by the degree to which information or communication is specific to an individual patient and leads to consequences for the patient. The 5 most important factors influencing the use of eHealth were access to medical information (eg, electronic health records), perceived control over disease management, correctness and completeness of information, data security, and access to information or an HCP at any time. The 5 least important factors influencing eHealth use were help with using digital devices, having internet or equipment, digital skills, attitude or emotions toward eHealth, and societal benefits. CONCLUSIONS: Patients identified opportunities for using eHealth during all moments of their care pathway. However, preferences for eHealth varied between patients and phases in the care pathway. As a consequence, eHealth should be tailored to fit individual patients' preferences but also the need for interaction regarding different topics by offering a variety of digital channels with a gradient of interaction possibilities. Furthermore, digital skills and access to the internet might become less important to focus on in the future. Improving eHealth use by patients may be achieved by providing patients access to correct and safe (medical) information and more control over their care.

Factors Influencing Preferences of Patients With Rheumatic Diseases Regarding Telehealth Channels for Support With Medication Use: Qualitative Study.

BACKGROUND: Patients with rheumatic diseases are known to experience drug-related problems at various times during their treatment. As these problems can negatively influence patients' health, they should be prevented or resolved as soon as possible, for which patients might benefit from additional support. Telehealth has the potential to continuously provide information and offers the possibility to easily contact a health care provider in order to support patients with medication use. Knowledge of factors influencing the patient's preference for telehealth channels can improve the actual use of telehealth channels. OBJECTIVE: This study aims to identify factors that influence the preferences of patients with rheumatic diseases regarding telehealth channels for support with medication use. METHODS: A qualitative study with face-to-face interviews was performed among patients with an inflammatory rheumatic disease in the Netherlands. A total of 4 telehealth channels were used: a frequently asked questions page, a digital human, an app for SMS text messaging with health care providers, and an app for video-calling with health care providers. Using a semistructured interview guide based on domains of the Capability, Opportunity, Motivation, and Behavior (COM-B) model, participants were questioned about (1) their general opinion on the 4 telehealth channels, (2) factors influencing preference for individual telehealth channels, and (3) factors influencing preference for individual telehealth channels in relation to the other available channels. Interviews were recorded, transcribed, and categorically analyzed. RESULTS: A total of 15 patients were interviewed (female: n=8, 53%; male: n=7, 47%; mean age 55, SD 16.8 years; median treatment duration of 41, IQR 12-106 months). The following 3 categories of factors influencing patient preference regarding telehealth channels were identified: (1) problem-related factors included problems needing a visual check, problems specifically related to the patient, and urgency of the problem; (2) patient-related factors included personal communication preference and patient characteristics; and (3) channel-related factors included familiarity with the telehealth channel, direct communication with a health care provider, methods of searching, and conversation history. CONCLUSIONS: Preference for telehealth channels is influenced by factors related to the problem experienced, the patient experiencing the problem, and telehealth channel characteristics. As the preference for telehealth channels varies between these categories, multiple telehealth channels should be offered to enable patients to tailor the support with their medication use to their needs.

Drug-related problems reported by patients with rheumatic diseases: an observational study.

BACKGROUND: Drug-related problems can negatively influence treatment outcome and well-being for patients with rheumatic diseases. Thus, it is important to support patients in preventing or resolving drug-related problems as quickly as possible. To effectively develop interventions for this purpose, knowledge on the frequency and character of drug-related problems is needed. Therefore, this study aims to quantify and characterize drug-related problems reported by patients with inflammatory rheumatic diseases along their treatment process. METHODS: A prospective observational study was conducted in a Dutch outpatient pharmacy. Adult patients with rheumatic diseases that were prescribed medication by a rheumatologist were questioned about experienced DRPs by telephone 4 times in 8 weeks using a structured interview-guide. Patient-reported DRPs were scored on uniqueness (i.e., if a specific DRP was reported in multiple interviews by one individual, this was counted as one unique DRP) and were categorized using a classification for patient-reported DRPs and analysed descriptively. RESULTS: In total, 52 participants (median age 68 years (interquartile range (IQR) 62-74), 52% male) completed 192 interviews with 45 (87%) participants completing all 4 interviews. The majority of patients (65%) were diagnosed with rheumatoid arthritis. Patients reported a median number of 3 (IQR 2-5) unique DRPs during interview 1. In subsequent interviews, patients reported median numbers of 1 (IQR 0-2), 1 (IQR 0-2) and 0 (IQR 0-1) unique DRPs for interviews 2-4 respectively. Participants reported a median number of 5 (IQR 3-9) unique DRPs over all completed interviews. Unique patient-reported DRPs were most frequently categorized into (suspected) side effects (28%), medication management (e.g., medication administering or adherence) (26%), medication concerns (e.g., concerns regarding long-term side-effects or effectiveness) (19%) and medication effectiveness (17%). CONCLUSIONS: Patients with rheumatic diseases report various unique DRPs with intervals as short as two weeks. These patients might therefore benefit from more continuous support in-between contact moments with their healthcare provider.