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Background Understanding the factors related to workload, could help hospital at home (HaH) managers to make decisions on the most appropriate and efficient use of the HaH services. Published studies on this topic are scarce, so we have conducted a systematic review to identify such factors according to published evidence. Methods Due to the heterogeneity of HaH models, HaH was defined as a care that provides a set of medical and nursing care and attention of hospital rank to patients at home, when they no longer require hospital infrastructure but still need active monitoring and complex care. The electronic data base literature search was conducted in MEDLINE (Ovid), EMBASE (Ovid), and Cinahl (EBSCOhost) from inception to December 2021, including grey literature. Search terms related to `hospital at home´, `workload´ and `care time´ were used. There was no restriction on language, type of study or year of publication. Quality of included studies was assessed using the Critical Appraisal Skills Programme (CASP) checklist and certainty in the body of evidence was assessed using the GRADE Pro Tool. Results were summarised in a tabulated format. Results Eighteen studies with 56,706 patients were included. Workload was measured as time, number of visits or both. The predictive factors of the workload included variables related to patient characteristics and other valid and reliable patient classification systems, as well as characteristics of the institutions where the studies were conducted. The factors associated with higher workloads were: being older, male, living in a rural environment, presenting a higher number of diagnoses, having worse functional status and being unable to assume self-care. Conclusions The identified predictors of workload are mostly associated with home nursing care. The results could be useful and applicable to different organisational models of HaH health systems. More studies that include physicians and proxy measures of workload are needed.

Smoking remains a major risk factor for chronic diseases. Health advice is considered one of the most cost-effective interventions; however, changes produced by counseling tend not to persist over time, it is necessary to implement enforcement mechanisms. Randomized clinical trial to evaluate the effectiveness of a combined program that includes health advice and text messaging to mobile phone (SMSalud®). Patients were randomized to one of two interventions: health advice (control group) or health advice and text messaging (intervention group). We included 320 smoker patients who met the inclusion criteria: being motivated, aged over 18 years, having a mobile phone, being able to read and send messages. Patients were excluded if they had a history of mental or behavioral disorders, or depression. The primary endpoint was the percentage of patients who had stopped smoking by 6 months and confirmed by CO breath test. By 6 months after the start of the program, 24.4% (39/160) of patients in the intervention group and 11.9% (19/160) of controls had stopped smoking (OR: 2.3; 95% CI: 1.3-4.3, p = .007). Patients with no dependence or mild dependence were more likely to stop (28.3%, 36/127 vs. 11.4%, 22/193; OR: 3.0, 95% CI: 1.7-5.5, p < .001). The rate of continuous abstinence at 12 months was 16.3% (26/160) in intervention group patients and 5.6% (9/160) in controls (OR: 3.2; 95% CI: 1.3-5.9).]. The combined program is effective for smoking cessation. Patients with less tobacco dependence have a higher probability of success. Health advice is effective for promoting changes in lifestyle but these changes do not persist over time, so we have to use strengthening mechanisms, as e-health, and specifically, mobile phone based interventions. SMSalud® is an innovate program that includes text messaging and health advice, and it's effective for smoking cessation. The only feature that seems to affect the probability of smoking cessation is the degree of tobacco dependence.

Despite the publication of great number of tools to aid decisions in COVID-19 patients, there is a lack of good instruments to predict clinical deterioration. COVID19-Osakidetza is a prospective cohort study recruiting COVID-19 patients. We collected information from baseline to discharge on: sociodemographic characteristics, comorbidities and associated medications, vital signs, treatment received and lab test results. Outcome was need for intensive ventilatory support (with at least standard high-flow oxygen face mask with a reservoir bag for at least 6 h and need for more intensive therapy afterwards or Optiflow high-flow nasal cannula or noninvasive or invasive mechanical ventilation) and/or admission to a critical care unit and/or death during hospitalization. We developed a Catboost model summarizing the findings using Shapley Additive Explanations. Performance of the model was assessed using area under the receiver operating characteristic and prediction recall curves (AUROC and AUPRC respectively) and calibrated using the Hosmer–Lemeshow test. Overall, 1568 patients were included in the derivation cohort and 956 in the (external) validation cohort. The percentages of patients who reached the composite endpoint were 23.3% vs 20% respectively. The strongest predictors of clinical deterioration were arterial blood oxygen pressure, followed by age, levels of several markers of inflammation (procalcitonin, LDH, CRP) and alterations in blood count and coagulation. Some medications, namely, ATC AO2 (antiacids) and N05 (neuroleptics) were also among the group of main predictors, together with C03 (diuretics). In the validation set, the CatBoost AUROC was 0.79, AUPRC 0.21 and Hosmer–Lemeshow test statistic 0.36. We present a machine learning-based prediction model with excellent performance properties to implement in EHRs. Our main goal was to predict progression to a score of 5 or higher on the WHO Clinical Progression Scale before patients required mechanical ventilation. Future steps are to externally validate the model in other settings and in a cohort from a different period and to apply the algorithm in clinical practice. Registration: ClinicalTrials.gov Identifier: NCT04463706.

Background Smoking in one of the most serious public health problems. It is well known that it constitutes a major risk factor for chronic diseases and the leading cause of preventable death worldwide. Due to high prevalence of smokers, new cost-effective strategies seeking to increase smoking cessation rates are needed. Methods We performed a Markov model-based cost-effectiveness analysis comparing two treatments: health advice provided by general practitioners and nurses in primary care, and health advice reinforced by sending motivational text messages to smokers’ mobile phones. A Markov model was used in which smokers transitioned between three mutually exclusive health states (smoker, former smoker and dead) after 6-month cycles. We calculated the cost-effectiveness ratio associated with the sending of motivational messages. Health care and society perspectives (separately) was adopted. Costs taken into account were direct health care costs and direct health care cost and costs for lost productivity, respectively. Additionally, deterministic sensitivity analysis was performed modifying the probability of smoking cessation with each option. Results Sending of text messages as a tool to support health advice was found to be cost-effective as it was associated with increases in costs of €7.4 and €1,327 per QALY gained (ICUR) for men and women respectively from a healthcare perspective, significantly far from the published cost-effectiveness threshold. From a societal perspective, the combined programmed was dominant. Conclusions Sending text messages is a cost-effective approach. These findings support the implantation of the combined program across primary care health centres.

Introduction: For the treatment of smoking, health advice is considered one of the most cost-effective interventions, but the behavioural changes achieved by counselling usually do not last for a long time. Thus, it is necessary to develop alternative strategies focused on improving outcomes with programs that include reinforcement mechanisms through Information and Communications Technologies (ICTs). Short description of practice change implemented: To assess this topic, we developed a text messaging program (SMSalud®) which sent motivational messages to patients’ mobile phone to encourage them in their efforts to quit tobacco.  This program was employed as a tool to reinforce the health advice provided by health care professionals. The effectiveness of this program (health advice + SMSalud®) was evaluated through a randomized clinical trial (RCT) in 320 smoker patients. We compared the percentage of quitters from combined program versus patients from clinical practice group (health advice) at 12 months, with a 16.26% and 5.6% of success respectively. This combined program will be implemented in primary care centres of Osakidetza, during next year. Aim of theory of change: Our objective is promoting changes in health related behaviour to prevent tobacco related chronic diseases. A large body of evidence supports the association between certain healthy lifestyles and lower rates of major chronic diseases and all-cause mortality. Targeted population and stakeholders: Motivated smoker patients belonging to any primary care centre of Osakidetza. Timeline: At this moment we are modifying SMSalud® program in a mobile application (Vive sin tabaco®), more attractive to patients. Transfer to clinical practice will begin in January in Araba. Training courses will be given in the management of the app, and a pilot study will be carried out. After pilot study, if there are not incidences, the program will be extended to the rest of the Basque Country in the second half of the year. Highligts: Several studies have highlighted the great potential of this technology for producing changes in health-related behaviour. Taking into account the prevalence of smoking in the Basque country, the penetration of mobile telephony, and the success rates achieved in the RCT, we have estimated a cost per quitter at 12 months of 104 euros (direct costs of program), which is a much lower than the cost of the pharmacological treatment. Comments on sustainability: A higher percentage of patients will quite tobacco, thus costs caused by smoking related diseases will decrease. That program will save costs in the future. Comments on transferability: Several services of Osakidetza are working in having this application finished in a short period of time. Once this program is implemented in routine clinical practice, the effectiveness will be reassessed. Conclussion: We think that results will be as effective in clinical practice as in the clinical trial. Due to difficulty of quitting tobacco, and the incidence of smoking related diseases, it is necessary to explore different alternatives to obtain greater success in treatments. Leason learned: ICTs have become useful tools to help smokers quit tobacco. Similar strategies could be applied to other clinical conditions.

Introduction: the readmissions rate for chronic obstructive pulmonary disease (COPD) is 66% a year and 25% for congestive heart failure (CHF). Strategies based on the treatment of these patients focused on prevention and health promotion of active patient through health education, have achieved a decrease of 51% in ICC readmission the following 6 months. Objectives: Determine the effectiveness of a multidisciplinary community intervention in patients with a history of potentially avoidable hospitalizations of COPD and CHF. Methods: Clinical randomized study in 32 patients admitted to hospital because of CHF or COPD and with one or more previous hospital admissions.  After hospital discharge 14 subjects were attended by a multidisciplinary team (a nurse, a nutritionist, a psychologist and a social worker - AUTOCUID program -) that provide individual health advice for good management and control of their illness. The 18 remaining subjects received routine clinical practice according to the disease that originates the hospital admission. Following evaluations were performed 1, 3, 6 and 12 months later: blood pressure, glycosylated hemoglobin, BNP, quality of life (SF-36, CAT and MLHFQ) questionnaires, self-management questionnaires for CHF and COPD, IPAQ physical activity questionnaire, functional dependence of Barthel and depression (PHQ9) questionnaires. Along the following year, admissions and visits to emergency and primary care physician were collected. A logistic regression model was constructed to quantify AUTOCUID Group patients hospital readmission probability regarding the control group. Covariance Analysis was used for comparing quality of life, functional dependency, depression, physical activity and self-care questionnaires Results: the proportion of subjects who return to the hospital, visit the emergency service or  primary care physician was similar in both treatment groups (25%  group AUTOCUID versus 75% - p = 0.412; 46% versus 54% - p = 1. 000 and 44% versus 56% - p = 1.000- respectively). The likelihood of hospital readmission in AUTOCUID group was 0.33 compared to the control group (95% 0.056-1995) in the unadjusted model, and 0.58 (IC95%0.067-5.097) after adjusting by age and BMI. There are no statistically significant differences in evaluated clinical characteristics (quality of life, functional dependence, depression, self-care and activity). Conclusions: the attention of patients with COPD and CHF by a multidisciplinary and multilevel team have a number of admissions a year similar to that obtained with the usual clinical practice. Their quality of life, self care and functional dependence do not differ. Limitations and future research:  it was necessary to study 144 subjects but only 32 out of 217 agreed to participate in the study. New studies are necessary to achieve a sufficient evidence level. The incorporation of new technologies, such as the Tele-assistance, could facilitate patients the accessibility to follow-up visits - the main cause of non-participation detected in this study.

Background: Beta blockers, ACE Inhibitors, and ARM are the treatments with IA degree of recommendation for secondary prevention in patients with CHF. However, the literature suggests that these therapies are not always prescribed in our hospitals and, mainly, that patients adherence is far from optimal. Additionally, first prescription adherence  is a prognostic factor in further adhesion. Objectives: Estimate these therapies  first prescription adherence degree after hospital discharge and identifying  risk factors associated to adhesion and socioeconomic differences. Methods: 1500 out of 3320 patients with CHF were treated for first time after being discharged from Basque Health Services hospitals. It was calculated how many patients collected the drug from the pharmacy during the first 10 days after hospital prescription. We determined witch factors were associated to treatment adherence by combining three drugs in a logistic regression model, using the patient as a random variable . Variables included: age, sex, number of chronic diseases, and medea deprivation index.  The information was collected with a Business intelligence platform that allows data extraction from the electronic clinical record of the Basque health system and treatments prescribed and dispensed. Results: the average adherence for CHF treatments was 85.4% for Beta blockers, ACE 82.4% and 87.7% for ARM. Differences in adhesion were not detected by sex (p=0.980), age (p=0.562), comorbidity (p=0.879) or socioeconomic level (p=0.793). Conclusions: Although adherence found is high, there is a chance for achieving optimal preventive treatment that involves hospital specialists, primary care doctors and pharmacies. Significant differences are not perceived  by age, sex or morbidity or socioeconomic level. This could be explained because Basque Health Service is a public health system so that patients don´t need to pay totally for their treatment. Geographical variability will be also research in the future

Hp(2) alleles of the haptoglobin alpha-chain polymorphism reduce the anti-oxidant properties and increase the pro-inflammatory actions of this acute-phase protein in a gene-dosage fashion. We hypothesized that the haptoglobin polymorphism might contribute to the increased oxidative stress and low-grade chronic inflammation frequently associated with polycystic ovary syndrome, obesity, and abnormalities of glucose tolerance. Serum haptoglobin and the haptoglobin alpha-chain polymorphism were determined in 141 patients with polycystic ovary syndrome and 102 non-hyperandrogenic women. Of the whole group of 243 premenopausal women, 117 were obese and 51 showed abnormal glucose tolerance. Although serum haptoglobin concentrations were similar in PCOS patients and controls, the former presented with an increased frequency of Hp(2) alleles (62% vs. 52%, P = 0.023). Circulating haptoglobin levels increased with obesity (P<0.001), yet no association was found between obesity and haptoglobin genotypes. No differences were observed in haptoglobin levels or genotype frequencies depending on glucose tolerance. Fifty percent of the variation in serum haptoglobin concentrations was explained by the variability in serum C-reactive protein concentrations, BMI, insulin sensitivity and haptoglobin genotypes. Serum haptoglobin concentrations in premenopausal women are largely dependent on the haptoglobin polymorphism and on the presence of obesity, with insulin resistance and chronic inflammation possibly modulating this relationship. The association of polycystic ovary syndrome with Hp(2) alleles suggests that the anti-oxidant and anti-inflammatory properties of haptoglobin may be reduced in these patients.

The factors that predispose an individual to a higher risk of death from COVID-19 are poorly understood. The goal of the study was to identify factors associated with risk of death among patients with COVID-19. This is a retrospective cohort study of people with laboratory-confirmed SARS-CoV-2 infection from February to May 22, 2020. Data retrieved for this study included patient sociodemographic data, baseline comorbidities, baseline treatments, other background data on care provided in hospital or primary care settings, and vital status. Main outcome was deaths until June 29, 2020. In the multivariable model based on nursing home residents, predictors of mortality were being male, older than 80 years, admitted to a hospital for COVID-19, and having cardiovascular disease, kidney disease or dementia while taking anticoagulants or lipid-lowering drugs at baseline was protective. The AUC was 0.754 for the risk score based on this model and 0.717 in the validation subsample. Predictors of death among people from the general population were being male and/or older than 60 years, having been hospitalized in the month before admission for COVID-19, being admitted to a hospital for COVID-19, having cardiovascular disease, dementia, respiratory disease, liver disease, diabetes with organ damage, or cancer while being on anticoagulants was protective. The AUC was 0.941 for this model’s risk score and 0.938 in the validation subsample. Our risk scores could help physicians identify high-risk groups and establish preventive measures and better follow-up for patients at high risk of dying.ClinicalTrials.gov Identifier: NCT04463706