Introduction to health information exchange

To support health care and public health in managing the array of information available about patients and populations, health systems have adopted a variety of information and communications technologies (ICT). Examples include electronic health record systems that document patient symptoms, diseases, and medications as well as health care processes. Yet, many ICT systems operate as islands unto themselves, unable to connect or share information with other ICT systems. Such fragmentation of data and information is an impediment to achieving the goal of efficient, coordinated health care delivery. It was further a major challenge during the COVID-19 pandemic when information was rapidly needed yet challenging to access. Health information exchange (HIE) seeks to address the challenges of connecting disparate ICT systems, enabling information to be available when and where it is needed by clinicians, administrators, and public health authorities. This chapter robustly defines HIE, including its core components and various forms. This chapter further discusses the role of HIE in supporting care delivery and public health. © 2023 Elsevier Inc. All rights reserved.

Mode of Hospital Rheumatology Appointments in People with Rheumatoid Arthritis: The Impact of the Pandemic in England

Background/Aims During the COVID-19 pandemic rheumatology services were advised to limit face to face contact, with remote telemedicine used instead. Although suitable for some people, issues have been highlighted with telemedicine. The frequency and proportion of remote appointments during the pandemic has not been described, or the socio-demographic characteristics of those accessing remote or in-person rheumatology care. This study aims to describe rheumatology healthcare utilisation and mode of appointment (remote/in-person) in people with rheumatoid arthritis (RA), prior to, and during the pandemic in England. Methods A retrospective prevalent cohort study of people with RA, identified using a validated algorithm, as of 1st April 2019 using electronic health record data (OpenSAFELY). Outpatient rheumatology appointments between 1st April 2019 and 31st March 2022 were identified. For each year, the number of outpatient appointments, mode of appointment (remote/in-person) and patient socio-demographic characteristics were described. Results 130,884 people with RA were identified. Since the start of the pandemic, the proportion of people without any appointments in a 12-month period increased from 28.5% in 2019/20 to 33.3% in 2020/ 21 and has not recovered. Older people were most frequently not seen (51% of people >80 years in 2020/21 and 2021/22). Of appointments where mode was known, 54.4% of people with appointments in the year from April 2020 were only seen remotely, reducing to 35.1% in the year from April 2021 (Table 1). The proportion with all remote appointments increased with increasing age, comprising 62% of people >80 years in 2020. This age gradient persisted in 2021, though proportions of those >80 years with all-remote appointments was lower (44%). Compared to urban dwellers, a higher proportion of those living in rural areas had all remote appointments in 2020 (58% vs 53%) and 2021 (38% vs 34%). Conclusion During the pandemic, one third of people with RA were not seen at all over a 12-month period and these were more frequently older people. Over half of people were only seen remotely in 2020, decreasing to one-third in 2021. Given the limitations of remote appointments it is unknown whether this increased frequency of remote appointments will impact long-term outcomes.

Shared longitudinal health records for clinical and population health

The ability of a health information exchange (HIE) to consolidate information, collected from multiple, disparate information systems, into a single, person-centric health record can provide a comprehensive and longitudinal representation of an individual's medical history. Shared, longitudinal health records can be leveraged to enhance the delivery of individual clinical care and provide opportunities to improve health outcomes at the population level. This chapter describes the clinical benefits imparted by the shared health record (SHR) component an HIE infrastructure. It also characterizes the potential public health benefits of the aggregate level, population health indicators calculated, stored, and distributed by a health management information system (HMIS) component. Tools for visualizing health indicators from the HMIS, including disease surveillance systems developed during the COVID-19 pandemic, are also described. Postpandemic components such as the SHR and HMIS will likely play critical roles in strengthening health information infrastructures in states and nations. © 2023 Elsevier Inc. All rights reserved.

Examining the Association of Air Quality on Covid-19 Patient Outcomes Using Area Level Data from the Electronic Health Record

Background: Within the coronavirus 2019 (COVID-19) pandemic, literature has found worsened patient outcomes and increased virus transmissibility associated with reduced air quality. This factor, a structural social determinant of health (SDOH), has shown great promise as a link between air quality and patient outcomes during the COVID-19 pandemic. Researching SDOH within our patient populations is often difficult and limited by poor documentation or extensive questionnaires or surveys. The use of demographic data derived from the electronic health record (EHR) to more accurately represent SDOH holds great promise. The use of area-level determinants of health outcomes has been shown to serve as a good surrogate for individual exposures. We posit that an area level measure of air quality, the county-level Air Quality Index (AQI), will be associated with disease worsening in intensive care unit (ICU) patients being treated for COVID-19. Method(s): We will calculate AQI using a combination of open-source records available via the United States Environmental Protection Agency (EPA) and manual calculations using geospatial informatics systems (GIS) methods. Subjects will be identified as adult (> 18 years) patients admitted to Vanderbilt University Medical Center's ICUs between January 1, 2020, and March 31, 2022 with a positive SARS-CoV-2 laboratory analysis result. We will exclude patients without a home address listed. Patient demographic and hospital data from ICU admission to 28 days following admission will include: age, sex, home address, race, insurance type, primary language, employment status, highest level of education, and hospital course data. Together these will be collated to produce our primary outcome variable of WHO Clinical Progression Scale score. These validated scores range from 0 (uninfected) to 10 (dead) to track clinically meaningful progression of COVID-19 infected patients. Our AQI variable will be obtained from the EPA available county-level monitoring station spatial data combined with open-source state/county center point spatial data. These data contain historic cataloguing to determine air quality at both specific time points and averages over time. Where a county's average yearly AQI is not available due to lack of a monitoring station, we will use spatial data tools to calculate an average based on data from nearby stations. We will utilize yearly averages of AQI in the year prior to COVID-19 diagnosis to describe overall impact of air quality on patients' respiratory outcomes as opposed to single day exposures. Linkage of patient data to AQI database will be performed using patient addresses. Discussion(s): By combining area level data with electronic health record (EHR) data, we will be positioned to understand the contribution of environmental and social determinants of health on patient outcomes. Our long-term goal is to elucidate which social and environmental determinants of health are associated with worse outcomes from COVID-19 and other respiratory viruses, using data extracted from the EHR.

Information Technology, Healthcare Data and Analytics, and Clinical Engineering

During a health crisis and a pandemic, information technology, analytics, and clinical engineering departments within an acute-care hospital setting play a significant role in the delivery of healthcare services. Electronic health record systems have become equally as important as the technology infrastructure that underpins them and the healthcare service itself. Both healthcare workers and patients require network access for effective communications, both within the hospital and beyond. Collaboration tools within and across departments at all levels have become essential for business continuity and clinical care. During the COVID-19 crisis, the virtual workspace became the "new normal” for healthcare workers, and virtual care through telehealth platforms, for patients and caregivers, enabled a quality of care to be maintained while still protecting both patients and healthcare workers throughout the infectious pandemic surge. Providing such services required agile project planning, along with a collaborative team effort, to quickly and effectively respond to expanded patient capacity within SBH. This chapter documents how the IT department at SBH Health System was able to successfully adapt to the demanding requirements of the initial COVID-19 surge in New York City, and it further highlights the key lessons learned to help recognize the tools needed to assist enhanced clinical innovations during a health crisis, especially an infectious pandemic. © SBH Health System 2022.

Janus Kinase Inhibitors in Rheumatoid Arthritis Patients: Real-World Experience from a Regional Centre in Uk

Background/Aims Tofacitinib and baricitinib were the first orally available, targeted synthetic Janus kinase (JAK) inhibitors approved for the treatment of rheumatoid arthritis (RA) in the UK. Evidence suggests that JAK inhibitors are as efficacious as biological DMARDs in the treatment of RA. Their safety profile has been demonstrated in long term extension studies and RCTs. However, real-world, long-term data remains as important in bridging the gap between controlled studies and routine practice. We report our initial real-world experience of a cohort of RA patients commenced on JAKi before the SARS-CoV-2 pandemic within a regional centre in the UK. Methods All patients commenced on JAKi for the treatment of RA between February 2018 and March 2020 were identified from our in-house database. Data was retrospectively collected from clinical notes and electronic health records from February 2018 up until April 2022. This included patient demographics, disease duration, serological status, concurrent csDMARD usage, history of bDMARD exposure, duration of use and reason for discontinuation of the drug if appropriate. DAS- 28 scores were recorded at baseline and quarterly. SPSS (version 22.0) was used for data analysis. Results One hundred thirty patients were treated with JAK inhibitors (Tofacitinib 22%, Baricitinib 78%);80% female, mean (S.D.) age 61.5 (12.3) years. 92 (70.8%) patients were seropositive. 70 (53.8%) patients were on concurrent csDMARDs and 23 (17.7%) on concurrent steroids. The mean number of previous bDMARDs was 1.8 +/- 1.7;41 (31.5%) were bDMARD naive. The mean baseline DAS-28 ESR (S.D.) score was 5.96 (0.96). There were significant differences in mean DAS- 28 ESR scores (compared with baseline) of 1.54, 1.96, 2.41, 2.33 and 1.80 at 3, 6, 12, 18 and 24 months respectively (p<0.0001). Mean DAS-28 ESR scores were not statistically significant between bDMARD naive patients and those that had previously received bDMARDs. Overall JAKi retention rate was 66.9% with a mean follow up duration of 27.4+/-13.1 months. Persistence was 88.5%, 76.9%, 73.2% and 68.5% at 6, 12, 18, and 24 months, respectively. Of the 38 patients who stopped JAK inhibitors, 11 stopped due to inefficacy (6, primary inefficacy). 3 patients were lost to follow-up and 6 deceased. Cause of death was sepsis (2), venous thromboembolism (1) and unknown (3). 18 patients stopped because of adverse events (AEs). The most common AEs were recurrent infections (11), gastrointestinal side effects (9), lymphopenia (7), thromboembolic events (6) and herpes zoster (5). In total 6 (4.1%) patients had thromboembolic events which included pulmonary embolism (4) and deep vein thrombosis (1) and central retinal artery thrombosis (1). Conclusion JAK inhibitors in this real-world population of RA patients were effective in reducing disease activity and patients had high persistence rates. Recurrent infections, herpes zoster and thrombo-embolism remain adverse events of concern.

Use of Deep Learning and Blockchain Technologies in Healthcare Industry

This editorial summarises the special issue entitled "Deep Learning Blockchain-enabled Technology for Improved Healthcare Industrial Systems”, which deals with the intersection and use of deep learning and blockchain technologies in the healthcare industry. This special issue consists of eleven scientific articles. © 2023 by the author(s). Licensee Prague University of Economics and Business, Czech Republic.