'Here to stay': changes to prescribing medication in general practice during the COVID-19 pandemic in New Zealand.

INTRODUCTION The delivery of health care by primary care general practices rapidly changed in response to the coronavirus disease 2019 (COVID-19) pandemic in early 2020. AIM This study explores the experience of a large group of New Zealand general practice health-care professionals with changes to prescribing medication during the COVID-19 pandemic. METHODS We qualitatively analysed a subtheme on prescribing medication from the General Practice Pandemic Experience New Zealand (GPPENZ) study, where general practice team members nationwide were invited to participate in five surveys over 16 weeks from 8 May 2020. RESULTS Overall, 78 (48%) of 164 participants enrolled in the study completed all surveys. Five themes were identified: changes to prescribing medicines; benefits of electronic prescription; technical challenges; clinical and medication supply challenges; and opportunities for the future. There was a rapid adoption of electronic prescribing as an adjunct to use of telehealth, minimising in-person consultations and paper prescription handling. Many found electronic prescribing an efficient and streamlined processes, whereas others had technical barriers and transmission to pharmacies was unreliable with sometimes incompatible systems. There was initially increased demand for repeat medications, and at the same time, concern that vulnerable patients did not have usual access to medication. The benefits of innovation at a time of crisis were recognised and respondents were optimistic that e-prescribing technical challenges could be resolved. DISCUSSION Improving e-prescribing technology between prescribers and dispensers, initiatives to maintain access to medication, particularly for vulnerable populations, and permanent regulatory changes will help patients continue to access their medications through future pandemic disruption.

How well did Norwegian general practice prepare to address the COVID-19 pandemic?

OBJECTIVES: We aimed to describe the quality improvement measures made by Norwegian general practice (GP) during the COVID-19 pandemic, evaluate the differences in quality improvements based on region and assess the combinations of actions taken. DESIGN: Descriptive study. SETTING: Participants were included after taking part in an online quality improvement COVID-19 course for Norwegian GPs in April 2020. The participants reported whether internal and external measures were in place: COVID-19 sign on entrance, updated home page, access to video consultations and/or electronic written consultations, home office solutions, separate working teams, preparedness for home visits, isolation rooms, knowledge on decontamination, access to sufficient supplies of personal protective equipment (PPE) and COVID-19 clinics. PARTICIPANTS: One hundred GP offices were included. The mean number of general practitioners per office was 5.63. RESULTS: More than 80% of practices had the following preparedness measures: COVID-19 sign on entrance, updated home page, COVID-19 clinic in the municipality, video and written electronic consultations, knowledge on how to use PPE, and home office solutions for general practitioners. Less than 50% had both PPE and knowledge of decontamination. Lack of PPE was reported by 37%, and 34% reported neither sufficient PPE nor a dedicated COVID-19 clinic. 15% reported that they had an isolation room, but not enough PPE. There were no geographical differences. CONCLUSIONS: Norwegian GPs in this study implemented many quality improvements to adapt to the COVID-19 pandemic. Overall, the largest potentials for improvement seem to be securing sufficient supply of PPE and establishing an isolation room at their practices.

General practice's early response to the COVID-19 pandemic.

The COVID-19 pandemic has resulted in multiple changes in the delivery of general practice services. In response to the threat of the pandemic and in order to keep their businesses safe and viable, general practices have rapidly moved to new models of care, embraced Medicare-funded telehealth and responded to uncertain availability of personal protective equipment with innovation. These changes have shown the adaptability of general practice, helped keep patients and practice staff safe, and undoubtedly reduced community transmission and mortality. The pandemic, and the response to it, has emphasised the potential dangers of existing fragmentation within the Australian health system, and is affecting the viability of general practice. These impacts on primary care highlight the need for improved integration of health services, should inform future pandemic planning, and guide the development of Australia's long-term national health plan.

Population Health Management to identify and characterise ongoing health need for high-risk individuals shielded from COVID-19: a cross-sectional cohort study.

OBJECTIVES: To use Population Health Management (PHM) methods to identify and characterise individuals at high-risk of severe COVID-19 for which shielding is required, for the purposes of managing ongoing health needs and mitigating potential shielding-induced harm. DESIGN: Individuals at 'high risk' of COVID-19 were identified using the published national 'Shielded Patient List' criteria. Individual-level information, including current chronic conditions, historical healthcare utilisation and demographic and socioeconomic status, was used for descriptive analyses of this group using PHM methods. Segmentation used k-prototypes cluster analysis. SETTING: A major healthcare system in the South West of England, for which linked primary, secondary, community and mental health data are available in a system-wide dataset. The study was performed at a time considered to be relatively early in the COVID-19 pandemic in the UK. PARTICIPANTS: 1 013 940 individuals from 78 contributing general practices. RESULTS: Compared with the groups considered at 'low' and 'moderate' risk (ie, eligible for the annual influenza vaccination), individuals at high risk were older (median age: 68 years (IQR: 55-77 years), cf 30 years (18-44 years) and 63 years (38-73 years), respectively), with more primary care/community contacts in the previous year (median contacts: 5 (2-10), cf 0 (0-2) and 2 (0-5)) and had a higher burden of comorbidity (median Charlson Score: 4 (3-6), cf 0 (0-0) and 2 (1-4)). Geospatial analyses revealed that 3.3% of rural and semi-rural residents were in the high-risk group compared with 2.91% of urban and inner-city residents (p<0.001). Segmentation uncovered six distinct clusters comprising the high-risk population, with key differentiation based on age and the presence of cancer, respiratory, and mental health conditions. CONCLUSIONS: PHM methods are useful in characterising the needs of individuals requiring shielding. Segmentation of the high-risk population identified groups with distinct characteristics that may benefit from a more tailored response from health and care providers and policy-makers.

Diagnosis of physical and mental health conditions in primary care during the COVID-19 pandemic: a retrospective cohort study.

BACKGROUND: To date, research on the indirect impact of the COVID-19 pandemic on the health of the population and the health-care system is scarce. We aimed to investigate the indirect effect of the COVID-19 pandemic on general practice health-care usage, and the subsequent diagnoses of common physical and mental health conditions in a deprived UK population. METHODS: We did a retrospective cohort study using routinely collected primary care data that was recorded in the Salford Integrated Record between Jan 1, 2010, and May 31, 2020. We extracted the weekly number of clinical codes entered into patient records overall, and for six high-level categories: symptoms and observations, diagnoses, prescriptions, operations and procedures, laboratory tests, and other diagnostic procedures. Negative binomial regression models were applied to monthly counts of first diagnoses of common conditions (common mental health problems, cardiovascular and cerebrovascular disease, type 2 diabetes, and cancer), and corresponding first prescriptions of medications indicative of these conditions. We used these models to predict the expected numbers of first diagnoses and first prescriptions between March 1 and May 31, 2020, which were then compared with the observed numbers for the same time period. FINDINGS: Between March 1 and May 31, 2020, 1073 first diagnoses of common mental health problems were reported compared with 2147 expected cases (95% CI 1821 to 2489) based on preceding years, representing a 50·0% reduction (95% CI 41·1 to 56·9). Compared with expected numbers, 456 fewer diagnoses of circulatory system diseases (43·3% reduction, 95% CI 29·6 to 53·5), and 135 fewer type 2 diabetes diagnoses (49·0% reduction, 23·8 to 63·1) were observed. The number of first prescriptions of associated medications was also lower than expected for the same time period. However, the gap between observed and expected cancer diagnoses (31 fewer; 16·0% reduction, -18·1 to 36·6) during this time period was not statistically significant. INTERPRETATION: In this deprived urban population, diagnoses of common conditions decreased substantially between March and May 2020, suggesting a large number of patients have undiagnosed conditions. A rebound in future workload could be imminent as COVID-19 restrictions ease and patients with undiagnosed conditions or delayed diagnosis present to primary and secondary health-care services. Such services should prioritise the diagnosis and treatment of these patients to mitigate potential indirect harms to protect public health. FUNDING: National Institute of Health Research.

Telehealth uptake in general practice as a result of the coronavirus (COVID-19) pandemic.

In March 2020, the Australian Government added new temporary telehealth services to the Medicare Benefits Schedule (MBS) to reduce the risk of patient-patient and patient-clinician transmission of the 2019 coronavirus (COVID-19). Here, the MBS statistics for general practitioner activity and the associated costs are described; a small increase in both activity and costs for the new MBS telehealth items were observed. The opportunities for future research and policy implications are also discussed.

COVID-19: Generate and apply local modelled transmission and morbidity effects to provide an estimate of the variation in overall relative healthcare resource impact at general practice granularity.

INTRODUCTION: Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the name given to the 2019 novel coronavirus. COVID-19 is the name given to the disease associated with the virus. SARS-CoV-2 is a new strain of coronavirus not been previously identified in humans. METHODS: Two key factors, case incidence and case morbidity, were analysed for England. When taken together they give an estimate of relative demand on healthcare utilisation. To analyse case incidence, the latest values for indicators that could be associated with infection transmission rates were collected from the Office of National Statistics (ONS) and Quality Outcome Framework (QOF) sources. These included population density, %age >16, at fulltime work/education, %age over 60, %BME ethnicity, social deprivation as IMD2019, location as latitude/longitude, and patient engagement as %self-confident in their own long-term condition management. Average case morbidity was calculated. To provide a comparative measure of overall healthcare resource impact, individual GP practice impact scores were compared against the median practice. RESULTS: The case incidence regression is a dynamic situation but it currently shows that Urban, %Working, and age >60 were the strongest determinants of case incidence. The local population comorbidity remains unchanged. The range of relative healthcare impact was wide with 80% of practices falling at 20%-250% of the national median. Once practice population numbers were included we found that the top 33% of GP practices supporting 45% of the patient population would require 68% of COVID-19 healthcare resources. The model provides useful information about the relative impact of Covid-19 on healthcare workload at GP practice granularity in all parts of England. CONCLUSION: Covid-19 is impacting on the utilisation of health/social care resources across the world. This model provides a way of predicting relative local levels of disease burden based on defined criteria, thereby providing a method for targeting limited care resources to optimise national/regional/local responses to the COVID-19 outbreak.