Background Nursing homes are highly vulnerable to the occurrence of COVID-19 outbreaks, which result in high lethality rates. Most of them are not prepared to SARS-CoV-2 pandemic. Methods A coordinated on-site medicalization program (MP) in response to a sizeable COVID-19 outbreak in four nursing homes was organized, with the objectives of improving survival, offering humanistic palliative care to residents in their natural environment, and reducing hospital referrals. Ten key processes and interventions were established (provision of informatics infrastructure, medical equipment, and human resources, universal testing, separation of 'clean' and 'contaminated' areas, epidemiological surveys, and unified protocols stratifying for active or palliative care approach, among others). Main outcomes were a composite endpoint of survival or optimal palliative care (SOPC), survival, and referral to hospital. Results 272 out of 457 (59.5%) residents and 85 out of 320 (26.5%) staff members were affected. The SOPC, survival, and referrals to hospital, occurred in 77%, 72.5%, and 29% of patients diagnosed before MP start, with respect to 97%, 83.7% and 17% of those diagnosed during the program, respectively. The SOPC was independently associated to MP (OR=15 [3-81]); and survival in patients stratified to active approach, to the use of any antiviral treatment (OR=28 [5-160]). All outbreaks were controlled in 39 [37-42] days. Conclusions A coordinated on-site medicalization program of nursing homes with COVID-19 outbreaks achieved a higher survival or optimal palliative care rate, and a reduction in referrals to hospital, thus ensuring rigorous but also humanistic and gentle care to residents.

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Objective The 'LESS-CHRON criteria' (List of Evidence-Based Deprescribing for Chronic Patients criteria) is a newly created tool with 27 criteria to guide deprescribing. It was developed using a Delphi methodology. Each criterion consists of drugs and their indications, conditions under which deprescribing would be considered, a health variable to be monitored after deprescribing and a follow-up period. The aim of our study was to evaluate the reliability of the LESS-CHRON criteria in a population of patients with multimorbidity to determine the possible usefulness of this tool in clinical practice. Methods We selected chronic patients with multimorbidity from an internal medicine unit who were older than 80 years old and were alive at the time of the study. To determine interobserver reliability, each professional (internist or hospital pharmacy specialist) applied the questionnaire under the same conditions and with the same resources. To determine intraobserver reliability, each health professional applied the tool at baseline and 2 months later. We measured interobserver and intraobserver reliability using the kappa coefficient. The proportion of overall agreement was also determined. results We obtained a moderate overall kappa (ĸ=0.46, 95% CI 0.36 to 0.55) for interobserver reliability, and good (ĸ=0.65, 95% CI 0.57 to 0.78) and moderate (ĸ=0.59, 95% CI 0.49 to 0.74) values for intraobserver reliability for the internist and pharmacist, respectively. The proportion of overall agreement was very high: 92% (range: 62%-100%) for the interobserver, and 94% (80%-100%) and 93% (63%-100%) for the internist and pharmacist, respectively. Conclusions The LESS-CHRON criteria shows early promise as a reliable method to help guide deprescribing in patients with multimorbidity. Further, more complete testing with a larger sample of prescribers is needed.

It is unknown whether the digital application of automated ICD-9-CM codes recorded in the medical history are useful for a first screening in the detection of polypathological patients. In this study, the objective was to identify the degree of intra- and inter-observer concordance in the identification of in-patient polypathological patients between the standard clinical identification method and a new automatic method, using the basic minimum data set of ICD-9-CM codes in the digital medical history. For this, a cross-sectional multicenter study with 1518 administratively discharged patients from Andalusian hospitals during the period of 2013–2014 has been carried out. For the concordance between the clinical definition of a polypathological patient and the polypathological patient classification according to ICD-9-CM coding, a 0.661 kappa was obtained (95% confidence interval (CI); 0.622–0.701) with p < 0.0001. The intraclass correlation coefficient between both methods for the number of polypathological patient categories was 0.745 (95% CI; 0.721–0.768; p < 0.0001). The values of sensitivity, specificity, positive-, and negative predictive values of the automated detection using ICD-9-CM coding were 78%, 88%, 78%, and 88%, respectively. As conclusion, the automatic identification of polypathological patients by detecting ICD-9-CM codes is useful as a screening method for in-hospital patients.

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Aims Estimating the prognosis in heart failure (HF) is important to decide when to refer to palliative care (PC). Our objective was to develop a tool to identify the probability of death within 6 months in patients admitted with acute HF. Methods and results A total of 2848 patients admitted with HF in 74 Spanish hospitals were prospectively included and followed for 6 months. Each factor independently associated with death in the derivation cohort (60% of the sample) was assigned a prognostic weight, and a risk score was calculated. The accuracy of the score was verified in the validation cohort. The characteristics of the population were as follows: advanced age (mean 78 years), equal representation of men and women, significant comorbidity, and predominance of HF with preserved ejection fraction. During follow-up, 753 patients (26%) died. Seven independent predictors of mortality were identified: age, chronic obstructive pulmonary disease, cognitive impairment, New York Heart Association class III-IV, chronic kidney disease, estimated survival of the patient less than 6 months, and acceptance of a palliative approach by the family or the patient. The area under the ROC curve for 6 month death was 0.74 for the derivation and 0.68 for the validation cohort. The model showed good calibration (Hosmer and Lemeshow test, P value 0.11). The 6 month death rates in the score groups ranged from 6% (low risk) to 54% (very high risk). Conclusions The EPICTER score, developed from a prospective and unselected cohort, is a bedside and easy-to-use tool that could help to identify high-risk patients requiring PC.

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