Computerized Clinical Records, which are incorporated in primary health care practice, have great potential for research. In order to use this information, data quality and reliability must be assessed to prevent compromising the validity of the results.

Background: Caregiver burden is related to personal factors and patient characteristics and is greater when neuropsychiatric symptoms (NPSs) are present. Objective: Estimate the prevalence of burden among caregivers of dementia patients and its association with NPSs and identify NPSs causing greater caregiver distress according to dementia stage. Methods: A cross-sectional observational study in caregivers of noninstitutionalized dementia patients was conducted. Caregiver variables were sociodemographic, time of care, NPS-associated distress based on the Neuropsychiatric Inventory Caregiver Distress Scale (NPI-D) and burden based on the Zarit Burden Interview (ZBI). Patient variables were time since disease onset, Global Deterioration Scale (GDS) disease stage, functional assessment and NPS presence and intensity according to the Neuropsychiatric Inventory (NPI). The mean ZBI score, prevalence of burden and NPI-D score with 95% CIs at each dementia stage were estimated. Factors associated with burden were identified by multivariate analysis. Results: Of the 125 caregivers included, 77.6% were women, with a mean age of 60.7 (± 14.3) years; 78.4% (95%CI: 71.0; 86.0) experienced burden. The mean ZBI score was 12.3 (95%CI: 11.6; 12.9) and increased according to NPS number (p = 0.042). The NPSs causing the most burden were disinhibition (93.5%), irritability (87.3%) and agitation (86.1%). Agitation, apathy, and sleep disorders were the NPSs generating the greatest overall caregiver distress; depression (max NPI-D 1.9), hyperactivity (max NPI-D 2.1), and psychosis symptoms (max NPI-D 1.6) generated the greatest distress at stage GDS 3, stages GDS 4–5, and stages GDS 6–7, respectively. The NPI score (OR = 1.0, 95%CI 1.0; 1.1), intensity of irritability (OR = 1.2, 95%CI 1.0; 1.6), disinhibition (OR = 2.6, 95%CI 1.1; 5.8) and hyperactivity subsyndrome (OR = 1.1, 95%CI 1.0; 1.2) were associated with caregiver burden. Other associated factors were female gender (OR = 6.0, 95%CI 1.6; 22.8), ≥ 8 h daily care (OR = 5.6, 95%CI 1.4; 22.8), working outside the home (OR = 7.6, 95%CI 1.8; 31.8), living with the patient (OR = 4.5, 95%CI 1.1; 19.6), kinship (OR = 5.4, 95%CI 1.0; 28.2) and lower patient education (OR = 8.3, 95%CI 2.3; 30.3). Conclusions: The burden on caregivers of dementia patients is high and associated with NPS presence and intensity. Disinhibition and irritability caused the highest burden. Depression, hyperactivity and psychosis produce more distress in mild, mild-moderate and severe dementia, respectively.

Multimorbidity is a global health challenge that is associated with polypharmacy, increasing the risk of potentially inappropriate prescribing (PIP). There are tools to improve prescription, such as implicit and explicit criteria. To estimate the prevalence of PIP in a population aged 65 to 74 years with multimorbidity and polypharmacy, according to American Geriatrics Society Beers Criteria^® (2015, 2019), the Screening Tool of Older Person’s Prescription -STOPP- criteria (2008, 2014), and the Medication Appropriateness Index -MAI- criteria in primary care. This was an observational, descriptive, cross-sectional study. The sample included 593 community-dwelling elderly aged 65 to 74 years, with multimorbidity and polypharmacy, who participated in the MULTIPAP trial. Socio-demographic, clinical, professional, and pharmacological-treatment variables were recorded. Potentially inappropriate prescribing was detected by computerized prescription assistance system, and family doctors evaluated the MAI. The MAI-associated factors were analysed using a logistic regression model. A total of 4,386 prescriptions were evaluated. The mean number of drugs was 7.4 (2.4 SD). A total of 94.1% of the patients in the study had at least one criterion for drug inappropriateness according to the MAI. Potentially inappropriate prescribing was detected in 57.7%, 43.6%, 68.8% and 71% of 50 patients according to the explicit criteria STOPP 2014, STOPP 2008, Beers 2019 and Beers 2015 respectively. For every new drug taken by a patient, the MAI score increased by 2.41 (95% CI 1.46; 3.35) points. Diabetes, ischaemic heart disease and asthma were independently associated with lower summated MAI scores. The prevalence of potentially inappropriate prescribing detected in the sample was high and in agreement with previous literature for populations with multimorbidity and polypharmacy. The MAI criteria detected greater inappropriateness than did the explicit criteria, but their application was more complex and difficult to automate.

Our aim is to conduct an exploratory study to provide an in-depth characterization of a neighborhood’s social and physical environment in relation to cardiovascular health. A mixed-methods approach was used to better understand the food, alcohol, tobacco and physical activity domains of the urban environment. We conducted this study in an area of 16,000 residents in Madrid (Spain). We obtained cardiovascular health and risk factors data from all residents aged 45 and above using Electronic Health Records from the Madrid Primary Health Care System. We used several quantitative audit tools to assess: the type and location of food outlets and healthy food availability; tobacco and alcohol points of sale; walkability of all streets and use of parks and public spaces. We also conducted 11 qualitative interviews with key informants to help understanding the relationships between urban environment and cardiovascular behaviors. We integrated quantitative and qualitative data following a mixed-methods merging approach. Electronic Health Records of the entire population of the area showed similar prevalence of risk factors compared to the rest of Madrid/Spain (prevalence of diabetes: 12 %, hypertension: 34 %, dyslipidemia: 32 %, smoking: 10 %, obesity: 20 %). The food environment was very dense, with many small stores (n = 44) and a large food market with 112 stalls. Residents highlighted the importance of these small stores for buying healthy foods. Alcohol and tobacco environments were also very dense (n = 91 and 64, respectively), dominated by bars and restaurants (n = 53) that also acted as food services. Neighbors emphasized the importance of drinking as a socialization mechanism. Public open spaces were mostly used by seniors that remarked the importance of accessibility to these spaces and the availability of destinations to walk to. This experience allowed testing and refining measurement tools, drawn from epidemiology, geography, sociology and anthropology, to better understand the urban environment in relation to cardiovascular health.

This paper examines the Willingness to Pay (WTP) for a quality-adjusted life year (QALY) expressed by people who attended the healthcare system as well as the association of attitude towards risk and other personal characteristics with their response.

Background: Tobacco addiction is the leading cause of preventable morbidity and mortality worldwide, but only 1 in 20 cessation attempts is supervised by a health professional. The potential advantages of mobile health (mHealth) can circumvent this problem and facilitate tobacco cessation interventions for public health systems. Given its easy scalability to large populations and great potential, chatbots are a potentially useful complement to usual treatment. Objective: This study aims to assess the effectiveness of an evidence-based intervention to quit smoking via a chatbot in smartphones compared with usual clinical practice in primary care. Methods: This is a pragmatic, multicenter, controlled, and randomized clinical trial involving 34 primary health care centers within the Madrid Health Service (Spain). Smokers over the age of 18 years who attended on-site consultation and accepted help to quit tobacco were recruited by their doctor or nurse and randomly allocated to receive usual care (control group [CG]) or an evidence-based chatbot intervention (intervention group [IG]). The interventions in both arms were based on the 5A’s (ie, Ask, Advise, Assess, Assist, and Arrange) in the US Clinical Practice Guideline, which combines behavioral and pharmacological treatments and is structured in several follow-up appointments. The primary outcome was continuous abstinence from smoking that was biochemically validated after 6 months by the collaborators. The outcome analysis was blinded to allocation of patients, although participants were unblinded to group assignment. An intention-to-treat analysis, using the baseline-observation-carried-forward approach for missing data, and logistic regression models with robust estimators were employed for assessing the primary outcomes. Results: The trial was conducted between October 1, 2018, and March 31, 2019. The sample included 513 patients (242 in the IG and 271 in the CG), with an average age of 49.8 (SD 10.82) years and gender ratio of 59.3% (304/513) women and 40.7% (209/513) men. Of them, 232 patients (45.2%) completed the follow-up, 104/242 (42.9%) in the IG and 128/271 (47.2%) in the CG. In the intention-to-treat analysis, the biochemically validated abstinence rate at 6 months was higher in the IG (63/242, 26%) compared with that in the CG (51/271, 18.8%; odds ratio 1.52, 95% CI 1.00-2.31; P=.05). After adjusting for basal CO-oximetry and bupropion intake, no substantial changes were observed (odds ratio 1.52, 95% CI 0.99-2.33; P=.05; pseudo-R2=0.045). In the IG, 61.2% (148/242) of users accessed the chatbot, average chatbot-patient interaction time was 121 (95% CI 121.1-140.0) minutes, and average number of contacts was 45.56 (SD 36.32). Conclusions: A treatment including a chatbot for helping with tobacco cessation was more effective than usual clinical practice in primary care. However, this outcome was at the limit of statistical significance, and therefore these promising results must be interpreted with caution. Trial Registration: Clinicaltrials.gov NCT 03445507; https://tinyurl.com/mrnfcmtd International Registered Report Identifier (IRRID): RR2-10.1186/s12911-019-0972-z