Electronic Health Record Software Research Articles

Preoperative Counseling in Spinal Cord Stimulation: A Designated Driver in Implantable Pulse Generator–Related Inconveniences?

BackgroundSpinal cord stimulation (SCS) has been reported to cause substantial pain relief and improved quality of life (QoL) in patients with persistent spinal pain syndrome (PSPS). Despite implantable pulse generator (IPG)-related inconveniences such as pain, shame, and discomfort affecting QoL and patient satisfaction, these are often neglected. Hence, the current study aims to determine the associations between patient satisfaction, IPG-related inconveniences, and preoperative counseling in a homogeneous group of patients with PSPS receiving SCS with IPG implantation in the gluteal or abdominal area. Materials and MethodsRetrospective data on sample characteristics were gathered from the EPIC (electronic health record software) digital patient data base. Prospective data on patient satisfaction were obtained with a questionnaire that covered various topics such as shame, pain, disturbances in daily/intense activities, night rest and/or sleep, discomfort caused by clothing, and preoperative counseling. The exact location of the IPG and its scar were determined with photo analysis. Thereafter, the site of IPG placement was classified into separate quadrants within the gluteal and abdominal area. Patient satisfaction was defined as accepting the current location of the IPG without having the wish to undergo revision surgery. ResultsIn total, 81 participants (50.9 ± 10 years) were included in this analysis, with patient satisfaction observed in 61 patients (75.3%). Among satisfied patients, more extensive preoperative counseling concerning IPG pain and discomfort was reported compared with patients who were not satisfied (p < 0.001). When comparing the two groups, significant differences were found in shame (8/81, 9.9%), IPG site pain (21/81, 25.9%), disturbance of activities (42/81, 51.9%), and clothing-related discomfort (42/81, 51.9%). ConclusionsOn the basis of the current results, shared decision-making and comprehensive preoperative provision of information are recommended to optimize patient satisfaction regarding IPG pain, discomfort, and inconveniences. Although many patients experience these disadvantages despite successful SCS for pain related to PSPS, most of them accept this if they have received adequate preoperative information about expectations.

Low-dose overlap initiation with split tablets of buprenorphine in intubated intensive care unit patients with opioid use disorder

BackgroundAs the opioid public health crisis evolves to include fentanyl and other potent synthetic opioids, more patients are admitted to the hospital with serious complications of drug use and frequently require higher levels of care, including intensive care unit (ICU) admission, for acute and chronic conditions related to opioid use disorder (OUD). This patient population poses a unique challenge when managing sedation and ensuring adequate ventilation while intubated given their high opioid requirements. Starting a patient on medications such as buprenorphine may be difficult for inpatient providers unfamiliar with its use, which may lead to undertreatment of patients with OUD, prolonged mechanical ventilation and length of stay.MethodsWe developed a 7-day buprenorphine low dose overlap initiation (LDOI) schedule for patients with OUD admitted to the ICU (Table 1). Buprenorphine tablets were split by pharmacists and placed into pre-made blister packs as a kit to be loaded into the automated medication dispensing machine for nursing to administer daily. An internal quality review validated the appropriate dosing of split-dose tablets. To simplify order entry and increase prescriber comfort with this new protocol, we generated an order set within our electronic health record software with prebuilt buprenorphine titration orders. This protocol was implemented alongside patient and healthcare team education and counseling on the LDOI process, with follow-up offered to all patients upon discharge.ResultsHere we report a series of 6 ICU patients started on buprenorphine using the LDOI schedule with split buprenorphine tablets. None of the 6 patients experienced precipitated withdrawal upon buprenorphine initiation using the LDOI schedule, and 5/6 patients were successfully extubated during the buprenorphine initiation. Four of six patients had a decrease in daily morphine milligram equivalents, with 3 patients transitioning to buprenorphine alone.ConclusionInitiating buprenorphine via LDOI was found to be successful in the development of a protocol for critically ill patients with OUD. We examined LDOI of buprenorphine in intubated ICU patients and found no events of acute precipitated withdrawal. This protocol can be used as a guide for other institutions seeking to start critically ill patients on medication treatment for OUD during ICU admission.

Comparison of electronic health records and electronic source data in clinical research trials: a retrospective review

Accurate documentation of medications and medical history is a critical component in ensuring the integrity of subject data in clinical research trials. With a mandate to use electronic health records (EHR) in healthcare settings, there has been a parallel movement towards integrating EHR and electronic data capture (EDC) software in clinical trials to improve efficiency and accuracy of data entry. However, there is increasing evidence that EHR data tend to be erroneous. The present study is a retrospective review comparing the medications and medical history documented in the EHR versus the EDC of subjects in active, ongoing clinical research studies to assess the validity of the assumption of the utility of using EHR data directly. Our results show significant data deviation from the EHR to the EDC, where 98% of all records were modified for clarity in some capacity. Only 31.3% of all medication records were concordant, and only 45.7% of all medical problem records were concordant. This suggests that Principal Investigators play a crucial role in parsing out incomplete, inaccurate, and irrelevant information when transferring data from the EHR to the EDC.

User-centric evaluation of EHR software through NLP-driven investigation: Implications for product development and user experience

In today's rapidly digitising world, organisations often face challenges in achieving successful technology implementation, with low returns on investment and a significant gap between technology utilisation and acceptance. Electronic Health Record (EHR) software provides a comprehensive platform for storing, managing, and gaining access to patient data, enabling healthcare providers to provide high-quality care and make informed decisions. Conducting a comprehensive analysis of EHR software decision-level user reviews can contribute to improving and optimising EHR systems. Incorporating principles of user innovation, the study aims to investigate the significance of online review analysis in product development and reduce the technology acceptance gap. The study employs document-topic theme mining techniques, specifically BERTopic, a topic modelling technique, VADER sentiment analysis, and NRCLex Affect dictionary-based emotion analysis to extract meaningful aspect-based insights from the vast unstructured data of online reviews about EHR software. The study helps healthcare organisations get insights from user perspectives and highlights the importance of user review evaluation in purchasing or switching EHR software. It contributes to the existing literature on software evaluation, software requirement analysis, marketing and positioning strategy analysis, and online user review analysis. In addition to the challenges faced in the healthcare sector, the study recognises that technology transition issues are pervasive across various domains. Common challenges include the need for seamless integration with existing workflows, addressing resistance to change, navigating data security and privacy concerns, and fostering a technology-friendly culture. By exploring these challenges within the context of EHR software, the research contributes valuable insights with broader implications for diverse industries undergoing digital transformation.

Seamless Integration of Computer-Adaptive Patient Reported Outcomes into an Electronic Health Record.

Patient-reported outcome (PRO) measures have become an essential component of quality measurement, quality improvement, and capturing the voice of the patient in clinical care. In 2004, the National Institutes of Health endorsed the importance of PROs by initiating the Patient-Reported Outcomes Measurement Information System (PROMIS), which leverages computer-adaptive tests (CATs) to reduce patient burden while maintaining measurement precision. Historically, PROMIS CATs have been used in a large number of research studies outside the electronic health record (EHR), but growing demand for clinical use of PROs requires creative information technology solutions for integration into the EHR. This paper describes the introduction of PROMIS CATs into the Epic Systems EHR at a large academic medical center using a tight integration; we describe the process of creating a secure, automatic connection between the application programming interface (API) which scores and selects CAT items and Epic. The overarching strategy was to make CATs appear indistinguishable from conventional measures to clinical users, patients, and the EHR software itself. We implemented CATs in Epic without compromising patient data security by creating custom middleware software within the organization's existing middleware framework. This software communicated between the Assessment Center API for item selection and scoring and Epic for item presentation and results. The middleware software seamlessly administered CATs alongside fixed-length, conventional PROs while maintaining the display characteristics and functions of other Epic measures, including automatic display of PROMIS scores in the patient's chart. Pilot implementation revealed differing workflows for clinicians using the software. The middleware software was adopted in 27 clinics across the hospital system. In the first 2 years of hospital-wide implementation, 793 providers collected 70,446 PROs from patients using this system. This project demonstrated the importance of regular communication across interdisciplinary teams in the design and development of clinical software. It also demonstrated that implementation relies on buy-in from clinical partners as they integrate new tools into their existing clinical workflow.

Benefits of Using a Free Cloud-Based Electronic Health Record for Simulation in a Baccalaureate Nursing Program.

The rising cost of simulated electronic health record (EHR) software for students in a baccalaureate nursing program was risking student success. The need for faculty to decrease this financial burden on students was apparent. Simulation faculty created a free and cloud-based simulated EHR. High-fidelity features of the simulated EHR include barcode scanning capabilities and real-time diagnostic results. Students report that the simulated EHR is easy to navigate and they are particularly satisfied with the free cost. The EHR template, which can be customized for each simulated patient, and is now being used inside the classroom as an active learning strategy.

Patient headache questionnaires can improve headache diagnosis and treatment in children.

To examine trends in diagnosis of headache and migraine in a large pediatric neurology cohort, and test whether an electronic health record (EHR)-integrated headache questionnaire can increase specificity of diagnosis and likelihood of prescribing migraine treatment. Under-diagnosis of migraine contributes to the burden of disease. As we founded our Pediatric Headache Program in 2013, we recognized that the proportion of patients with headache who were given a diagnosis of migraine was much lower than expected. We developed a patient headache questionnaire, initially on paper (2013-2014), then in an electronic database (2014-2016), and finally integrated into our electronic health record (pilot: 2016, full: May 2017). We compared diagnoses and prescribed treatments for new patients who were given a headache diagnosis, looking at trends in the proportion of patients given specific diagnoses (migraine, etc.) versus the non-specific diagnosis, "headache." Next, we conducted a prospective cohort study to test for association between provider use of the form and the presence of a specific diagnosis, then for an association between specific diagnosis and prescription of migraine treatment. Between July 2011 and December 2022 the proportion of new headache patients who were given a diagnosis of migraine increased 9.7% and non-specific headache diagnoses decreased 21.0%. In the EHR cohort (June 2017-December 2022, n = 15,122), use of the provider form increased the rate of specific diagnosis to 87.2% (1839/2109) compared to 75.5% (5708/7560) without a patient questionnaire, nearly doubling the odds of making a specific diagnosis (odds ratio [OR] 1.90, 95% confidence interval [CI]: 1.65-2.19). Compared to those given only a non-specific headache diagnosis who were prescribed a migraine therapy 53.7% (1766/3286) of the time, 75.3% (8914/11836) of those given a specific diagnosis received a migraine therapy, more than doubling the odds of prescription (OR 2.39, 95% CI: 2.20-2.60). Interventions to improve specificity of diagnosis were effective and led to increased rates of prescription of migraine treatments. These results have been sustained over several years. This headache questionnaire was adapted into the Foundation system of EpicCare, so it is broadly available as a clinical and research tool for institutions that use this EHR software.

Utilization of electronic health records and associated factors among nurses in a faith-based teaching hospital, Ilishan, Nigeria.

It has been documented that nurses' use of electronic health records (EHRs) impacts clients' health outcomes positively. Some health facilities, primarily privately owned institutions, introduced EHRs for optimal healthcare. Evidence of such and associated factors among nurses must be documented to improve utilization and quality. The study assessed the utilization of EHRs and associated factors among nurses in a faith-based teaching hospital. This sequential explanatory mixed-methods study involved a sample of all 240 nurses from a teaching hospital where EHRs have been introduced. Quantitative data through semistructured questionnaires were collected and analyzed using Chi-square and logistic regression. Qualitative data were collected from 10 purposively selected nurses using an in-depth interview guide and analyzed through content analysis. The majority of participants reported availability of EHR computer software (62.8%), internet facility (84.2%), and desktops (76.3%), but EHR was poorly utilized (27.3%). Factors significantly associated were nurses who were females [OR (odds ratio) = 1.5, 95% CI (confidence interval), 0.21-11.24], BNSc degrees holders [OR = 4.3; 95% CI, 1.06-17.43]; had computer EHR software [OR = 7.4, 95% CI, 0.83-3.81], and sponsored EHR training [OR = 2.10; 95% CI, 0.24-18.6]. Noncapturing of nursing tasks and nursing standardized language by EHR software, lack of institutional enforcement on EHR use, and absence of clear EHR policies were the main identified themes for the key barriers to using EHRs. EHR was poorly utilized among nurses. Gender, educational qualification, EHR resources, and sponsored training were factors significantly associated with the use. There is an urgent need for comprehensive EHR packages, sustained sponsored training, and formulation of EHR policy for effective EHR implementation.

First dose COVID-19 vaccine coverage amongst adolescents and children in England: an analysis of 3.21 million patients' primary care records in situ using OpenSAFELY.

Background: The coronavirus disease 2019 (COVID-19) vaccination programme in England was extended to include all adolescents and children by April 2022. The aim of this paper is to describe trends and variation in vaccine coverage in different clinical and demographic groups amongst adolescents and children in England by August 2022. Methods: With the approval of NHS England, a cohort study was conducted of 3.21 million children and adolescents' records in general practice in England, in situand within the infrastructure of the electronic health record software vendor TPP using OpenSAFELY. Vaccine coverage across various demographic (sex, deprivation index and ethnicity) and clinical (risk status) populations is described. Results: Coverage is higher amongst adolescents than it is amongst children, with 53.5% adolescents and 10.8% children having received their first dose of the COVID-19 vaccine. Within those groups, coverage varies by ethnicity, deprivation index and risk status; there is no evidence of variation by sex. Conclusion: First dose COVID-19 vaccine coverage is shown to vary amongst various demographic and clinical groups of children and adolescents.

The development and evaluation of a predictive productivity model in the ambulatory oncology infusion setting.

Accurately describing pharmacy productivity in the ambulatory oncology infusion setting is important to ensure appropriate labor utilization. The purpose of this study was to develop a productivity model utilizing weighted medication complexity and prospective schedule data to determine if predicted productivity corresponds to actual productivity across 6 ambulatory oncology infusion sites. This study was a 2-part analysis. Part 1 was to modify the historic productivity model from dispense code weighting to individual medication complexity weighting. Medication-specific relative value units were determined by analyzing 12 months of historic timestamp data from the electronic health record and gravimetric technology software. The productivity model containing updated relative value units was compared to the historic model to determine if the difference in total calculated full-time equivalents (FTEs) was within 2.0 FTEs. Part 2 applied prospective infusion schedule data to the updated model to determine if predicted productivity corresponded to actual productivity (within 2.0 FTEs) for pharmacy infusion services. The mean difference in total calculated FTEs for infusion during the study period was 2.46 (standard deviation= 1.87) and was within the range of 2.0 FTEs (P= 0.54), indicating that the updated model was not statistically different from the historic model. The mean difference in total calculated FTEs between the predictive and actual productivity model for infusion was 18.28 (standard deviation= 1.00) and was out of the range of 2.0 FTEs (P < 0.001), indicating that predicted productivity was statistically different from the actual productivity. Medication complexity weighting can be used to provide a comprehensive assessment of workload and productivity across pharmacy infusion services. The methodology used to assess predictive productivity should be explored further.

First dose COVID-19 vaccine coverage amongst adolescents and children in England: an analysis of 3.21 million patients' primary care records in situ using OpenSAFELY

Background: The coronavirus disease 2019 (COVID-19) vaccination programme in England was extended to include all adolescents and children by April 2022. The aim of this paper is to describe trends and variation in vaccine coverage in different clinical and demographic groups amongst adolescents and children in England. Methods: With the approval of NHS England, a cohort study was conducted of 3.21 million children and adolescents’ records in general practice in England, in situ and within the infrastructure of the electronic health record software vendor TPP using OpenSAFELY. Vaccine coverage across various demographic (sex, deprivation index and ethnicity) and clinical (risk status) populations is described. Results: Coverage is higher amongst adolescents than it is amongst children, with 53.5% adolescents and 10.8% children having received their first dose of the COVID-19 vaccine. Within those groups, coverage varies by ethnicity, deprivation index and risk status; there is no evidence of variation by sex. Conclusion: First dose COVID-19 vaccine coverage is shown to vary amongst various demographic and clinical groups of children and adolescents.

The evolution of medical resident training and healthcare delivery: Good riddance to the "July effect".

Key Points The present observational study from the National Inpatient Sample found no evidence of a “July effect” associated with acute myocardial infarction (AMI) in‐hospital mortality rates in teaching hospitals. Multifactorial quality improvement in the delivery of care for AMI patients has ameliorated potentially detrimental effects of trainee inexperience historically observed in high‐risk admissions. Efforts to minimize unnecessary variability in care delivery and to consistently implement guideline‐directed medical therapy are ongoing via electronic health record software.

'No evidence' for some warnings of severe outcomes with antibiotics, say researchers

Researchers have found there is no evidence of substantial risk for drug–drug interactions involving antibiotics, despite warnings of severe outcomes in national formularies and electronic health record software. The authors of the study, which was published in Clinical Pharmacology and Therapeutics on 30 November 2022, said there was a need for the evidence base for […]

Evaluation of Reading Level of Result Letters Sent to Patients from an Academic Primary Care Practice.

In primary care, low health literacy, particularly reading ability, is associated with worse health outcomes. Most physicians do not receive feedback on the reading levels of written communication that they may provide to patients, including result letters. Our study compares the readability of result letters, written by resident versus attending physicians, to patients with positive or negative screens for reading ability, as determined by the single-item literacy screener (SILS). Result letters to 50 patients at high risk and 50 patients at low risk of low reading ability were randomly selected starting from January 1st, 2020 at Albany Medical Center. Flesch-Kincaid Grade Level (FKGL), Gunning Fog Index (GFI), Coleman-Liau Index (CLI), Simple Measure of Gobbledygook (SMOG), and Flesch Reading Ease (FRE) were used to compare the readability of resident versus attending result letters. For all SILS levels, attending physicians wrote result letters at a lower grade level than resident physicians based on the FKGL, GFI, and SMOG indices. The FKGL, GFI, and SMOG readability scores of result letters written to patients with SILS 3-5 were also lower when written by attending physicians compared to resident physicians. Result letters written by attending physicians may be easier to read than result letters written by resident physicians, especially for patients with low reading ability. Future electronic health record (EHR) software should give physicians and providers feedback on the reading level of their written communication.

Clinical Relevance of Drug-Drug Interactions With Antibiotics as Listed in a National Medication Formulary: Results From Two Large Population-Based Case-Control Studies in Patients Aged 65-100 Years Using Linked English Primary Care and Hospital Data.

This study evaluated drug-drug interactions (DDIs) between antibiotic and nonantibiotic drugs listed with warnings of severe outcomes in the British National Formulary based on adverse drug reaction (ADR) detectable with routine International Classification of Diseases, Tenth Revision coding. Data sources were Clinical Practice Research Databank GOLD and Aurum anonymized electronic health records from English general practices linked to hospital admission records. In propensity-matched case-control study, outcomes were ADR or emergency admissions. Analyzed were 121,546 ADR-related admission cases matched to 638,238 controls. For most antibiotics, adjusted odds ratios (aORs) for ADR-related hospital admission were large (aOR for trimethoprim 4.13; 95% confidence interval (CI), 3.97-4.30). Of the 51 DDIs evaluated for ADR-related admissions, 38 DDIs (74.5%) had statistically increased aORs of concomitant exposure compared with nonexposure (mean aOR 3.96; range 1.59-11.42); for the 89 DDIs for emergency hospital admission, the results were 75 (84.3%) and mean aOR 2.40; range 1.43-4.17. Changing reference group to single antibiotic exposure reduced aORs for concomitant exposure by 76.5% and 83.0%, respectively. Medicines listed to cause nephrotoxicity substantially increased risks that were related to number of medicines (aOR was 2.55 (95% CI, 2.46-2.64) for current use of 1 and 10.44 (95% CI, 7.36-14.81) for 3 or more medicines). In conclusion, no evidence of substantial risk was found for multiple DDIs with antibiotics despite warnings of severe outcomes in a national formulary and flagging in electronic health record software. It is proposed that the evidence base for inclusion of DDIs in national formularies be strengthened and made publicly accessible and indiscriminate flagging, which compounds alert fatigue, be reduced.

Pharmacogenomics driven decision support prototype with machine learning: A framework for improving patient care.

A growing number of healthcare providers make complex treatment decisions guided by electronic health record (EHR) software interfaces. Many interfaces integrate multiple sources of data (e.g., labs, pharmacy, diagnoses) successfully, though relatively few have incorporated genetic data. This study utilizes informatics methods with predictive modeling to create and validate algorithms to enable informed pharmacogenomic decision-making at the point of care in near real-time. The proposed framework integrates EHR and genetic data relevant to the patient's current medications including decision support mechanisms based on predictive modeling. We created a prototype with EHR and linked genetic data from the Department of Veterans Affairs (VA), the largest integrated healthcare system in the US. The EHR data included diagnoses, medication fills, and outpatient clinic visits for 2,600 people with HIV and matched uninfected controls linked to prototypic genetic data (variations in single or multiple positions in the DNA sequence). We then mapped the medications that patients were prescribed to medications defined in the drug-gene interaction mapping of the Clinical Pharmacogenomics Implementation Consortium's (CPIC) level A (i.e., sufficient evidence for at least one prescribing action) guidelines that predict adverse events. CPIC is a National Institute of Health funded group of experts who develop evidence based pharmacogenomic guidelines. Preventable adverse events (PAE) can be defined as a harmful outcome from an intervention that could have been prevented. For this study, we focused on potential PAEs resulting from a medication-gene interaction. The final model showed AUC scores of 0.972 with an F1 score of 0.97 with genetic data as compared to 0.766 and 0.73 respectively, without genetic data integration. Over 98% of people in the cohort were on at least one medication with CPIC level a guideline in their lifetime. We compared predictive power of machine learning models to detect a PAE between five modeling methods: Random Forest, Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), K Nearest neighbors (KNN), and Decision Tree. We found that XGBoost performed best for the prototype when genetic data was added to the framework and improved prediction of PAE. We compared area under the curve (AUC) between the models in the testing dataset.

The Coronavirus Disease 2019 Pandemic and Mental Health-Related School-Nurse Visits in United States Schools.

ObjectivesNo studies have examined school-nurse visits related to mental health (MH) during the COVID-19 pandemic. We examined changes in the rate of MH-related school-nurse visits before and during the COVID-19 pandemic.MethodsWe analyzed school-nurse visit data (n=3,445,240) for subjects Grade K-12 in U.S. public schools using electronic health record software (SchoolCare, Ramsey, NJ). Data between January 1-December 31 in 2019 (pre-COVID-19 pandemic) vs. January 1-December 31 in 2020 (during COVID-19 pandemic) were compared. For each year, total visits to a school-nurse were calculated for general MH, anxiety, and self-harm. The exposure was number of school-nurse visits in each time period (2019 vs. 2020). The main outcome was change in the rate of general MH, anxiety, and self-harm visits in 2019 vs. 2020.ResultsThere were 2,302,239 total school-nurse visits in 2019 vs. 1,143,001 in 2020. During the COVID-19 pandemic, the rate of visits for general MH increased by 30% (4.7 to 6.1 per 10,000 visits, 95%CI [18%,43%]; p<0.001), and visits for anxiety increased by 25% (24.8 to 31 per 10,000 visits, 95%CI [20%,30%]; p<0.001). There was no significant difference in self-harm visits across all ages during the COVID-19 pandemic.ConclusionsOur study found a significant increase in the rate of school-nurse visits for MH and anxiety during the COVID-19 pandemic, suggesting the pediatric population is at-risk for increased negative MH-effects associated with the pandemic and highlights a critical role of school-nurses in identifying youth with potential MH-needs.

O1-5 Digital tools for physical activity assessment and brief counselling in Primary Health Care: The Portuguese model

Issue/problemImplementation of national systems for patients' physical activity (PA) assessment and counselling is a cost-effective strategy recommended in the WHO Global Action Plan for PA 2018-2030. Although Primary Health Care (PHC) professionals are recognized as key agents for PA promotion, challenges remain on how to develop feasible and scalable tools to support them in promoting patients' PA. The Portuguese model could help other countries improve PA assessment and brief counselling in PHC settings. This study aims to describe the tools' development and usage.Description of the problemThe Portuguese Directorate-General of Health developed two evidence-based digital tools to support PA promotion by healthcare professionals: a) PA brief assessment tool; and b) brief counselling tool. The assessment tool was incorporated within the electronic medical health record software ?SClínico? in September 2017. It includes three questions: 1) how many days per week the patient performs any kind of PA (work, commuting or leisure-time); 2) how much time per day; and 3) how many hours per day the patient spends in sedentary behaviours. The PA brief counselling tool is available through the electronic medical prescription software ?PEM? since December 2017 and consists of five inter-related self-explanatory guides that can be delivered to patients (printed or by email), according to their motivation and PA levels. They facilitate person-centered and autonomy-supportive PA counselling, targeting specific behaviour change mediators, and using validated techniques.ResultsFrom September 2017 to December 2021, 159,179 patients had their PA assessed (2235 per 100,000 users of the National Health Service) and, from these, 16133 received PA brief counselling guides (177 per 100000 residents in Portugal, ≥ 15 years old), with a six-fold and three-fold increases, respectively, between 2018 and 2019 (previous to the COVID-19 pandemic). Future actions will address cost-effectiveness of this policy.LessonsThe brief assessment and brief counselling tools were well-accepted and are increasingly being used, with potential for generalized adoption within the Portuguese Health Care System.Main messagesPortugal has taken a decisive action to promote PA using PHC as a priority setting. PA tools usage is increasing considerably, highlighting the importance of making available easy-to-use PA promotion tools.

Smart Health Consultation and Record Management

There is currently a lot of study being done on the functioning of Electronic Health Records (EHR) software, and doctors are facing a lot of difficulties as they switch from a paper-based record management system to an electronic one.

Panelists Outline How to Address Patients’ Social Determinants of Health, Why It’s Important

Panelists Outline How to Address Patients’ Social Determinants of Health, Why It’s Important