ABSTRACT
One hundred and sixty-five questionnaires were posted to patients who were regularly seen in the nurse-led haematology out-patient clinic. This is an established service that has been operating for approximately 14 years. These patients had all been seen prior to the Covid pandemic, and then during this period. The questionnaire was sent out in August 2021. These patients are treated for either chronic myeloid leukaemia (CML), myeloproliferative neoplasms (MPN) or non-primary polycythaemia/thrombocythaemia. The MPN patients were diagnosed with either essential thrombocythaemia, polycythaemia vera or myelofibrosis. One hundred and thirty-three questionnaires were returned by patients. This is an 81% response. Before the pandemic, patients were mainly seen face to face, with a small number by telephone or email. Patients were happy with this at the time. From March 2020, at the start of the Covid pandemic appointments were suddenly changed to telephone (96%), with a small number by email (2%) or face to face (2%). 96% of the telephone follow-up patients were happy with this method, as were all of the email follow-ups. Patients were asked how they would prefer to be communicated with in the future. The majority of patients would prefer a face to face or telephone appointment. Text, email and video consultations were generally unpopular. People found it easier to communicate face to face, and preferred seeing a healthcare professional this way. A recurring theme was that telephone appointments were acceptable, on the understanding that if there was a change in their condition, a face-to-face appointment could be booked. Patients who worked were very supportive of telephone appointments. People generally felt 'safer' having their appointments remotely, and their blood tests carried out nearer to where they live, instead of at the hospital. Very few patients wanted to have text, video calls or email in the future-they preferred the personal contact, and many did not have the necessary equipment. Issues of long waits in the Pathology department and the difficulty of car-parking at the hospital prepandemic were mentioned by patients. Patients were very happy with the nurse-led haematology clinics. They liked the continuity, and having a point of contact. Over the time of the pandemic, processes were changed, with more use of electronic prescribing, different ways of documenting discussions, and non-paper requesting of blood tests. Together with increased use of email and the telephone, this has meant that services have been continued despite staff being isolated at home. There are increasing numbers of nurse-led clinics in Haematology, and these have been shown to be cost-effective and safe, providing holistic care and continuity (Thompson et al 2012). As services are redesigned, it is important to consider the views of the patients who are users of the clinics. The Covid pandemic has forced changes to healthcare services, and there may be long-term effects on the way that services are delivered in Haematology for patients with chronic conditions. Resilience needs to be built into the way that patients are monitored in the future, to ensure that they can continue without interruption, both during and post pandemic.
ABSTRACT
Study Objectives: Purposefully designed and validated screening, triage, and severity scoring tools are needed to reduce mortality of COVID-19 in low-resource settings (LRS). This review aimed to identify currently proposed and/or implemented methods of screening, triaging, and severity scoring suspected COVID-19 patients upon initial presentation to the health care system, and to evaluate the utility of these tools in LRS. A scoping review was conducted to identify studies describing acute screening, triage, and severity scoring of suspected COVID-19 patients published between 12 December, 2019 and 01 April, 2020. Extracted information included clinical features, use of laboratory and imaging studies, and relevant tool validation data. The initial search strategy yielded 15232 articles;124 met inclusion criteria. Results: Most studies were from China (n=41, 33.1%) or the United States (n=23, 18·5%). In total, 57 screening, 54 severity scoring, and 23 triage tools were described. A total of 23 tools–16 screening, four triage, and three severity scoring–were identified as feasible for use in LRS. A total of 37 studies provided validation data: four prospective and 33 retrospective, with none from low-income and lower-middle-income countries. Conclusions: This study identified a number of screening, triage, and severity scoring tools implemented and proposed for suspected COVID-19 patients. No tools were specifically designed and validated in LRS. A tool specific to resource limited context is crucial to reducing mortality in the current pandemic.
ABSTRACT
Background: In many low- and middle-income countries, where vaccinations will be delayed and healthcare systems are underdeveloped, the COVID-19 pandemic will continue for the foreseeable future. Mortality scales can aid frontline providers in low-resource settings (LRS) in identifying those at greatest risk of death so that limited resources can be directed towards those in greatest need and unnecessary loss of life is prevented. While many prognostication tools have been developed for, or applied to, COVID-19 patients, no tools to date have been purpose-designed for, and validated in, LRS. Objectives: This study aimed to develop a pragmatic tool to assist LRS frontline providers in evaluating in-hospital mortality risk using only easy-to-obtain demographic and clinical inputs. Methods: Machine learning was used on data from a retrospective cohort of Sudanese COVID-19 patients at two government referral hospitals to derive contextually appropriate mortality indices for COVID-19, which were then assessed by C-indices. Findings: Data from 467 patients were used to derive two versions of the AFEM COVID-19 Mortality Scale (AFEM-CMS), which evaluates in-hospital mortality risk using demographic and clinical inputs that are readily obtainable in hospital receiving areas. Both versions of the tool include age, sex, number of comorbidities, Glasgow Coma Scale, respiratory rate, and systolic blood pressure; in settings with pulse oximetry, oxygen saturation is included and in settings without access, heart rate is included. The AFEM-CMS showed good discrimination: the model including pulse oximetry had a C-statistic of 0.775 (95% CI: 0.737-0.813) and the model excluding it had a C-statistic of 0.719 (95% CI: 0.678-0.760). Conclusions: In the face of an enduring pandemic in many LRS, the AFEM-CMS serves as a practical solution to aid frontline providers in effectively allocating healthcare resources. The tool's generalisability is likely narrow outside of similar extremely LRS settings, and further validation studies are essential prior to broader use.