Business intelligence for the visualization and data analysis of Telepharmacy activity indicators in a hospital pharmacy service scorecard

Objective: The consolidation of Telepharmacy during the COVID-19 pandemic has raised the need for managing large volumes of real-time activity data through data analysis. The aim of this project was to design a dynamic, user-friendly, customizable scorecard in a hospital pharmacy service for the visualization and analysis of Telepharmacy activity indicators through the use of advanced business intelligence technology. Method: The software tool was developed by a multidisciplinary team between April and May 2021, driven from the hospital pharmacy service. Once the Telepharmacy indicators of interest were established, datasets were extracted from raw databases (administrative databases, Telepharmacy database, outpatient dispensing software, drug catalogues) through data analysis. The different data sources were integrated in a scorecard using PowerBI®. The criteria for processing missing and duplicated data were defined, and data pre-processing, normalization and transformation were performed. Once the pilot scorecard was validated by different profiles of users, the structure was designed for the panels to automatically update as databases were updated. Results: Design and implementation of a scorecard of Telepharmacy activity: general descriptive panel (demographic profile of patients, count and delivery conditions, program and medical service);geolocation of destination;pharmacological profile;relative analysis of patients involved in the Telepharmacy program with respect to the total of outpatients. In the last updating as of January 2022, data from 16, 000 dispensations to more than 4, 000 patients had been collected. This means that 21.93% of outpatients had benefited at some time point from the Telepharmacy service. Filters enable the visualization of timeline progress and patient characterization, and measure Telepharmacy activity by program. Conclusions: The processing of large Telemedicine datasets from various sources through Business Intelligence in a hospital pharmacy service makes it possible to synthesize information, generate customized reports, and visualize information in a dynamic and attractive format. The application of this new technology will help us improve strategic clinical and management decision making. © 2022 Grupo Aula Medica S.L.. All rights reserved.

Capacity and organisation of Madrid's community hospitals during first wave of COVID-19 pandemic.

INTRODUCTION AND OBJECTIVES: The first wave of the SARS-CoV-2 pandemic exerted enormous stress on the healthcare system. Community of Madrid hospitals responded by restructuring and scaling their capacity to adapt to the high demand for care. METHODS: This was a retrospective observational study conducted between 18 March and 21 June 2020 with data from public and private hospitals in CoM, Spain. Absolute and relative frequencies were calculated for inpatients with and without COVID-19, available and occupied beds in intensive care unit (ICU) and non-ICU wards, daily new admissions (NA), individuals awaiting hospitalisation in the emergency department (ED), and discharges. RESULTS: Compared to pre-pandemic years, during the maximum care pressure period (18 March-17 April 2020), the average number of total available and occupied beds increased by 27% and 36%, respectively. Also, the average number of available and occupied ICU beds increased by 174% and 257% respectively, and average occupancy was 81%. The average daily NAs were 1,503 (90% from the ED) and 949 (63% due to COVID-19), and of these, 61 (6.4%) were admitted to the ICU. On average, at 6:00p.m., 1112 patients were waiting in the ED to be admitted and 299 (26.8%) patients waited for more than 24h. Discharges due to death for COVID-19 inpatients in the non-ICU and ICU wards were 16% and 36%, respectively. CONCLUSIONS: This study confirmed the critical role of the ICU and ED, especially in the care of patients before being hospitalizated, in pandemic or health crisis scenarios.

Comorbidities of Primary Care patients with COVID-19 during the first wave of the SARS-CoV-2 pandemic in the Community of Madrid.

OBJECTIVE: Recent publications on inpatients with COVID-19 describing their comorbidities and demographic profile exists, but data from large populations requiring only primary care (PC) are scarce. This paper aims to fill this gap and report the prevalence of eight comorbidities (high blood pressure, diabetes mellitus, cancer, cardiovascular disease, asthma, chronic kidney disease, chronic obstructive pulmonary disease, and chronic heart failure) among patients attending PC during the onset of the SARS-CoV-2 pandemic in the Community of Madrid (CoM), Spain. METHODS: This is an observational retrospective study that collects data registered in the CoM between February 25th and May 31st, 2020. Data are divided in two groups: Group-1 (N=339,890) consist of all patients with suspected or proven SARS-CoV-2 infection; and Group-2 is the subgroup (N=48,556, 14.3% of Group-1) of individuals with COVID-19 confirmed by positive RT-PCR test. RESULTS: Comparing Group-1 with Group-2, 339,890/48,556 patients, respectively, the main results were as follows: average age (60.9/69.9 years), presence of at least one comorbidity (33.51%/47.69%), high blood pressure (19.74%/32.74%), diabetes mellitus (7.13%/13.75%), cancer (6.56%/10.6%), cardiovascular disease (4.52%/9.26%), asthma (7.98%/6.56%), chronic kidney disease (1.84%/4.41%), chronic obstructive pulmonary disease (2%/4.03%), and chronic heart failure (1.14%/2.77%). High blood pressure and diabetes mellitus were seen to be the most frequent (6.56%/8.38%) association. CONCLUSIONS: Patients requiring PC attention during the first wave of the COVID-19 pandemic in the CoM presented with a very high rate of comorbidities, with marked differences among those with or without a confirmed SARS-CoV-2 infection.