Background: Around 2 million people in the UK suffer from Long COVID (LC). Of concern is the disease impact on productivity and informal care burden. This study aimed to quantify and value productivity losses and informal care receipt in a sample of LC patients in the UK. Methods: The target population comprised LC patients referred to LC specialist clinics. The questionnaires included a health economics questionnaire (HEQ) measuring productivity impacts, informal care receipt and service utilisation, EQ-5D-5L, C19-YRS LC condition-specific measure, and sociodemographic and COVID-19 history variables. Outcomes were changes from the incident infection resulting in LC to the month preceding the survey in paid work status/h, work income, work performance and informal care receipt. The human capital approach valued productivity losses; the proxy goods method valued caregiving hours. The values were extrapolated nationally using published prevalence data. Multilevel regressions, nested by region, estimated associations between the outcomes and patient characteristics. Results: 366 patients responded to HEQ (mean LC duration 449.9 days). 51.7% reduced paid work hours relative to the pre-infection period. Mean monthly work income declined by 24.5%. The average aggregate value of productivity loss since incident infection was £10,929 (95% bootstrap confidence interval £8,844-£13,014) and £5.7 billion (£3.8-£7.6 billion) extrapolated nationally. The corresponding values for informal caregiving were £8,726 (£6,247-£11,204) and £4.8 billion (£2.6-£7.0 billion). Multivariate analyses found significant associations between each outcome and health utility and C19-YRS subscale scores. Conclusion: LC significantly impacts productivity losses and provision of informal care, exacerbated by high national prevalence of LC.

Background Long COVID (LC) is a novel multisystem clinical syndrome affecting millions of individuals worldwide. The modified COVID-19 Yorkshire Rehabilitation Scale (C19-YRSm) is a condition-specific patient-reported outcome measure designed for assessment and monitoring of people with LC. Objectives To evaluate the psychometric properties of the C19-YRSm in a prospective sample of people with LC. Methods 1314 patients attending 10 UK specialist LC clinics completed C19-YRSm and EuroQol 5D-5L (EQ-5D-5L) longitudinally. Scale characteristics were derived for C19-YRSm subscales (Symptom Severity (SS), Functional Disability (FD) and Overall Health (OH)) and internal consistency (Cronbach’s alpha). Convergent validity was assessed using the Functional Assessment of Chronic Illness Therapy (FACIT)—Fatigue Scale. Known groups validity was assessed for the Other Symptoms subscale as tertiles, as well as by hospitalisation and intensive care admission. Responsiveness and test–retest reliability was evaluated for C19-YRSm subscales and EQ-5D-5L. The minimal important difference (MID) and minimal clinically important difference (MCID) were estimated. Confirmatory factor analysis was applied to determine the instrument’s two-factor structure. Results C19-YRSm demonstrated good scale characteristic properties. Item-total correlations were between 0.37 and 0.65 (for SS and FD), with good internal reliability (Cronbach’s alphas>0.8). Item correlations between subscales ranged between 0.46 and 0.72. Convergent validity with FACIT was good (−0.46 to −0.62). The three subscales discriminated between different levels of symptom burden (p<0.001) and between patients admitted to hospital and intensive care. There was moderate responsiveness for the three subscales ranging from 0.22 (OH) to 0.50 (SS) which was greater than for the EQ-5D-5L. Test–retest reliability was good for both SS 0.86 and FD 0.78. MID was 2 for SS, 2 for FD and 1 for OH; MCID was 4 for both the SS and FD. The factor analysis supported the two-factor SS and FD structure. Conclusions The C19-YRSm is a condition-specific, reliable, valid and responsive patient-reported outcome measure for LC.

Background: Post–COVID-19 condition (PCC), colloquially known as long COVID, is a multisystem condition characterized by persistent symptoms beyond 4 weeks after the SARS-CoV-2 infection. More than 60 million people with PCC worldwide need prompt assessment, diagnosis, and monitoring, with many requiring specialist help from a multidisciplinary team of health care professionals (HCPs). Consequently, a scalable digital system is required for both people with PCC and HCPs to capture the breadth of symptoms and their impact on health, using patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs). Objective: We aim to develop and implement a novel PCC digital PROM (DPROM) platform for (1) securely collecting PROM and PREM data from people with PCC, (2) enabling users to monitor symptoms longitudinally and assess response to treatment, (3) generating reports for the electronic health records (EHRs), (4) providing summary reports on PCC services based on national requirements, and (5) facilitating the sharing of relevant data with authorized research teams to accelerate our understanding of this new condition and evaluate new strategies to manage PCC. Methods: We (1) undertook requirement analysis with people with PCC, HCPs, and researchers to identify the needs of the DPROM platform and determine its required functionalities; (2) designed and developed a clinically useful web portal for staff and a mobile app for patients, with a web-based alternative app to improve patient and staff choice, limit the risk of digital exclusion, and account for variability across services; (3) determined the PROMs and PREMs that PCC services would prefer to use on the platform; and (4) designed the summary report function that can be generated for each user for the EHR and for reporting to national health authorities. Results: A DPROM platform to record PCC symptom profile, condition severity, functional disability, and quality of life, based on the C19-YRS (Yorkshire Rehabilitation Scale) and other PROMs and PREMs, was developed. Individual-level medical information and details on the COVID-19 illness can be captured systematically. The platform generates easy-to-understand scores, radar plots and line graphs for people with PCC to self-monitor their condition and for HCPs to assess the natural course of the condition and the response to interventions. Clinics can configure a suite of PROMs and PREMs based on their local and national service and commissioning requirements and support research studies which require large-scale data collection on PROMs. The DPROM platform enables automatic aggregate data analysis for services to undertake service evaluation and cost-effectiveness analysis. The DPROM platform generated summary report can be uploaded to the EHRs of people with PCC. Conclusions: A multifunctional DPROM platform to assess, grade, and monitor PCC has been developed. Future research will analyze the system’s usability in specialist PCC clinical services and other long-term conditions.

Background: Long COVID (LC) is a multisystem clinical syndrome with functional disability and compromised overall health. Information on LC clinical severity types is emerging in cross-sectional studies. This study explored the pattern and consistency of long COVID (LC) clinical severity types over time in a prospective sample. Methods: Participants with LC completed the condition-specific outcome measure C19-YRSm (Yorkshire Rehabilitation Scale modified version) at two assessment time points. A cluster analysis for clinical severity types was undertaken at both time points using the k-means partition method. Results: The study included cross-sectional data for 759 patients with a mean age of 46.8 years (SD = 12.7), 69.4% females, and a duration of symptoms of 360 days (IQR 217 to 703 days). The cluster analysis at first assessment revealed three distinct clinical severity type clusters: mild (n = 96), moderate (n = 422), and severe (n = 241). Longitudinal data on 356 patients revealed that the pattern of three clinical severity types remained consistent over time between the two assessments, with 51% of patients switching clinical severity types between the assessments. Conclusions: This study is the first of its kind to demonstrate that the pattern of three clinical severity types is consistent over time, with patients also switching between severity types, indicating the fluctuating nature of LC.

Background: Two million people in the UK suffer from Long COVID (LC), imposing substantial health economic impacts. This study aimed to: 1) assess longitudinal changes in health utility scores and economic costs of LC, and number of services received at LC specialist clinics and clinic region to capture care intensity; 2) assess whether volume of services received responded to health needs; and 3) estimate the national economic impact of LC. Methods: LC patients from 10 specialist clinics participated in the LOCOMOTION study. Patient-reported outcomes measures (EQ-5D-5L, C19-YRS and Health Economics Questionnaire) were completed on a digital platform. Associations were assessed between changes in economic outcomes (EQ-5D-3L utility, health economic costs) and number/type of LC specialist services received and region. Per-person values of quality-adjusted life-year losses, public sector costs, productivity losses and informal care costs were multiplied by LC prevalence to estimate national economic impacts. Results: There was a statistically significant reduction in public sector costs over time. There was no significant association between the number of specialist services received and change in health utility scores. LC specialist clinic and outpatient service utilisation corresponded to health need and had significant regional variation after controlling for health need. LC is associated with a substantial economic impact nationally, estimated at £8.1 billion annually and £24.2 billion since its emergence, comparable to the annual cost of £9.4 billion for stroke. Conclusion: The effectiveness of LC specialist clinic services warrants further research. The substantial national economic impact of LC warrants a nationwide LC care strategy.

BACKGROUND Post–COVID-19 condition (PCC), colloquially known as long COVID, is a multisystem condition characterized by persistent symptoms beyond 4 weeks after the SARS-CoV-2 infection. More than 60 million people with PCC worldwide need prompt assessment, diagnosis, and monitoring, with many requiring specialist help from a multidisciplinary team of health care professionals (HCPs). Consequently, a scalable digital system is required for both people with PCC and HCPs to capture the breadth of symptoms and their impact on health, using patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs). OBJECTIVE We aim to develop and implement a novel PCC digital PROM (DPROM) platform for (1) securely collecting PROM and PREM data from people with PCC, (2) enabling users to monitor symptoms longitudinally and assess response to treatment, (3) generating reports for the electronic health records (EHRs), (4) providing summary reports on PCC services based on national requirements, and (5) facilitating the sharing of relevant data with authorized research teams to accelerate our understanding of this new condition and evaluate new strategies to manage PCC. METHODS We (1) undertook requirement analysis with people with PCC, HCPs, and researchers to identify the needs of the DPROM platform and determine its required functionalities; (2) designed and developed a clinically useful web portal for staff and a mobile app for patients, with a web-based alternative app to improve patient and staff choice, limit the risk of digital exclusion, and account for variability across services; (3) determined the PROMs and PREMs that PCC services would prefer to use on the platform; and (4) designed the summary report function that can be generated for each user for the EHR and for reporting to national health authorities. RESULTS A DPROM platform to record PCC symptom profile, condition severity, functional disability, and quality of life, based on the C19-YRS (Yorkshire Rehabilitation Scale) and other PROMs and PREMs, was developed. Individual-level medical information and details on the COVID-19 illness can be captured systematically. The platform generates easy-to-understand scores, radar plots and line graphs for people with PCC to self-monitor their condition and for HCPs to assess the natural course of the condition and the response to interventions. Clinics can configure a suite of PROMs and PREMs based on their local and national service and commissioning requirements and support research studies which require large-scale data collection on PROMs. The DPROM platform enables automatic aggregate data analysis for services to undertake service evaluation and cost-effectiveness analysis. The DPROM platform generated summary report can be uploaded to the EHRs of people with PCC. CONCLUSIONS A multifunctional DPROM platform to assess, grade, and monitor PCC has been developed. Future research will analyze the system’s usability in specialist PCC clinical services and other long-term conditions.