Interdisciplinary Mobile Health Model to Improve Clinical Care After Heart Transplantation: Implementation Strategy Study.

BACKGROUND: Solid organ transplantation could be the only life-saving treatment for end-stage heart failure. Nevertheless, multimorbidity and polypharmacy remain major problems after heart transplant. A technology-based behavioral intervention model was established to improve clinical practice in a heart transplant outpatient setting. To support the new strategy, the mHeart app, a mobile health (mHealth) tool, was developed for use by patients and providers. OBJECTIVE: The primary objective of this study was to describe the implementation of the mHeart model and to outline the main facilitators identified when conceiving an mHealth approach. The secondary objectives were to evaluate the barriers, benefits, and willingness to use mHealth services reported by heart transplant recipients and cardiology providers. METHODS: This was an implementation strategy study directed by a multidisciplinary cardiology team conducted in four stages: design of the model and the software, development of the mHeart tool, interoperability among systems, and quality and security requirements. A mixed methods study design was applied combining a literature review, several surveys, interviews, and focus groups. The approach involved merging engineering and behavioral theory science. Participants were chronic-stage heart transplant recipients, patient associations, health providers, stakeholders, and diverse experts from the legal, data protection, and interoperability fields. RESULTS: An interdisciplinary and patient-centered process was applied to obtain a comprehensive care model. The heart transplant recipients (N=135) included in the study confirmed they had access to smartphones (132/135, 97.7%) and were willing to use the mHeart system (132/135, 97.7%). Based on stakeholder agreement (>75%, N=26), the major priorities identified of the mHealth approach were to improve therapy management, patient empowerment, and patient-provider interactions. Stakeholder agreement on the barriers to implementing the system was weak (<75%). Establishing the new model posed several challenges to the multidisciplinary team in charge. The main factors that needed to be overcome were ensuring data confidentiality, reducing workload, minimizing the digital divide, and increasing interoperability. Experts from various fields, scientific societies, and patient associations were essential to meet the quality requirements and the model scalability. CONCLUSIONS: The mHeart model will be applicable in distinct clinical and research contexts, and may inspire other cardiology health providers to create innovative ways to deal with therapeutic complexity and multimorbidity through health care systems. Professionals and patients are willing to use such innovative mHealth programs. The facilitators and key strategies described were needed for success in the implementation of the new holistic theory-based mHealth strategy.

A Mobile App (mHeart) to Detect Medication Nonadherence in the Heart Transplant Population: Validation Study.

BACKGROUND: Medication nonadherence in heart transplant recipients (HTxR) is related to graft loss and death. mHeart is a mobile app that uses electronic patient-reported outcome measures (ePROMs) to identify and manage medication nonadherence in the outpatient heart transplant (HTx) population. OBJECTIVE: The study primarily aimed to validate mHeart to measure medication nonadherence in early stage HTxR by assessing the psychometric properties of ePROMs. The secondary aims were to (1) measure patient satisfaction with the mHeart tool and its usability and (2) explore the impact of a theory-based treatment on medication nonadherence rates to determine its scalability to larger research. METHODS: A prospective study was conducted in the outpatient clinic of a tertiary hospital. All consecutive early stage HTxR (<1.5 years from HTx) were included. The ePROM psychometric properties assessed were validity, reliability, responsiveness, interpretability, and burden. ePROMs comprised the 4-item Morisky-Green-Levine questionnaire and an adapted version of the Haynes-Sackett questionnaire. The Simplified Medication Adherence Questionnaire (SMAQ) was also applied on-site. Three consecutive medication nonadherence assessments were performed by a transplant pharmacist. To improve medication nonadherence, theory-based interventions were delivered in a 1-month period. Patient satisfaction was assessed by a semiquantitative Web-based survey at the end of the study. RESULTS: We included 31 early stage HTxR (age: mean 54 years, SD 12 years), and 71% (22/31) of them were men. The HTxR were taking a mean 13 (SD 4; range 7-18) drugs per day. A total of 42% (13/31) of patients were unaware of the consequences of medication nonadherence, and 39% (12/31) of patients were nonadherent to immunosuppressive treatment. The content validity measure showed excellent levels of expert panel agreement for the Haynes-Sacket (14/14, 100%) and Morisky-Green-Levine (13/14, 93%) questionnaires. SMAQ and Morisky-Green-Levine ePROMs showed similar measurement domains (convergent validity, phi=0.6, P<.001), which, as expected, differed from Haynes-Sackett ePROMs (divergent validity, phi=0.3, P=.12). Reliability assessment revealed a very strong association between ePROM and on-site PROMs (phi>0.7, P<.001). Reproducibility was moderate (Haynes-Sackett κ=0.6, P<.002) or poor (Morisky-Green-Levine κ=0.3, P=.11) because of unexpected improved medication adherence rates during the test-retest period. According to responsiveness, the theory-based multifaceted intervention program improved medication nonadherence by 16% to 26% (P<.05). A burden analysis showed that ePROMs could potentially overcome traditional on-site limitations (eg, automatic recording of ePROM responses in the hospital information system). The mean score for overall patient satisfaction with the mHeart approach was 9 (SD 2; score range: 0-10). All 100% (29/29) of patients surveyed reported that they would recommend the mHeart platform to other HTxR. CONCLUSIONS: ePROMs adhered to the quality standards and successfully identified medication nonadherence in the HTx population, supporting their widespread use. The theory-based intervention program showed a promising improvement in medication adherence rates and produced excellent patient satisfaction and usability scores in HTxR.

Prevalence and clinical impact of recreational drug consumption in people living with HIV on treatment: a cross-sectional study.

OBJECTIVES: Drug interactions, poor adherence to medication and high-risk sexual behaviour may occur in individuals with HIV using recreational drugs. Thus, we aimed to assess the prevalence of recreational drugs use and to explore its clinical impact in HIV patients on treatment. METHODS: Observational, cross sectional, study conducted in a 700 bed university hospital, Barcelona, Spain. A total of 208 adults living with HIV on treatment were included. A questionnaire was administered by clinical pharmacists, including evaluation of sociodemographic variables, past 12-month drug consumption, adherence to antiretrovirals (Simplified Medication Adherence Questionnaire) and high-risk sexual behaviour (condomless sex/multiple partners). Additional data were obtained from clinical records. Recreational drug-antiretroviral interactions were checked in reference databases. Prevalence was calculated for 5% precision and 95% CI. Crude and adjusted binary logistic regressions were performed to identify associations between recreational drug use and adherence problems, and between recreational drug use and high-risk sexual behaviour. RESULTS: From the overall sample, 92 participants (44.2%) consumed recreational drugs over the past 1 year. Of these, 44 (48.8%) had used different types of recreational drugs in this period. We detected 11 recreational substances, including sildenafil and nitrites. The most consumed drugs were: cannabis (68.5%), cocaine (45.5%), nitrites (31.5%), sildenafil (28.3) and ecstasy (19.6%). Relevant interactions occurred in 46 (50%) of the individuals consuming drugs. Recreational drug consumption was found to be related to adherence problems with antiretrovirals (OR: 2.51 (95% CI 1.32 to 4.77) p=0.005) and high-risk sexual behaviour (OR: 2.81 (95% CI 1.47 to 5.39) p=0.002). CONCLUSIONS: Recreational drugs are frequently used by HIV patients on treatment. Classical drugs and new substances consumed in sexual context are usual. Recreational drug consumption interferes with several clinical outcomes, including potentially relevant interactions between drugs and antiretrovirals, adherence problems and high-risk sexual behaviour. Thus, there is the urgent need of implementing patient-centred care involving recreational drug consumption.

Negative clinical outcomes associated with drug-related problems in heart failure (HF) outpatients: impact of a pharmacist in a multidisciplinary HF clinic.

BACKGROUND: Drug-related negative outcomes (DNOs) are health problems that patients experience due to drug use or nonuse. Heart failure (HF) patients are at high risk of experiencing DNOs owing to polypharmacy, comorbidities, and age. METHODS AND RESULTS: Ninety-seven consecutive HF patients were enrolled and followed for 6 months. A pharmacist, integrated within a multidisciplinary HF team, reviewed the medication of each patient to detect, resolve, and/or prevent possible DNOs, risks of developing a DNO (rDNOs) and the drug-related problems (DRPs) that are associated with them. We detected 147 DNOs/rDNOs with a mean of 1.5 ± 1.4 per patient. Among DNOs, 45% were due to a lack of a pharmacologic treatment (need for a drug) and 24% were treatments with an insufficient drug dose (quantitative ineffectiveness). Among rDNOs, 33% were due to use of an unsafe drug (nonquantitative lack of safety) and 30% to quantitative ineffectiveness. Ninety-four percent of DNOs/rDNOs were preventable, and, importantly, 5.5% were classified as clinically serious. During follow-up, pharmacist interventions solved or prevented the health problem in 83% of cases. The most frequently identified DRPs were "insufficiently treated health problem" (31%), "inadequate dose, regimen, or duration of a drug" (22%), "probability of adverse effects" (16%), and "nonadherence" (14%). A significant relationship between the number of DNOs/rDNOs and the number of drugs was found (P < .013). CONCLUSIONS: Chronic HF outpatients have a high incidence of preventable DNOs. The inclusion of a pharmacist in multidisciplinary HF teams should be considered, because it is clinically beneficial for patients and it increases HF specialists' awareness of DNOs, especially those beyond HF.