scholarly journals The impact of the COVID-19 lockdown on HIV care in 65 South African primary care clinics: an interrupted time series analysis

2021 ◽  
Author(s):  
Jienchi Dorward ◽  
Thokozani Khubone ◽  
Kelly Gate ◽  
Hope Ngobese ◽  
Yukteshwar Sookrajh ◽  
...  
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Time Series Analysis ◽  
South African ◽  
Interrupted Time Series ◽  
Hiv Care ◽  
Interrupted Time Series Analysis ◽  
Primary Care Clinics ◽  
Series Analysis ◽  
The Impact

scholarly journals When donor funding leaves: an interrupted time-series analysis of the impact of integrating direct HIV care and treatment into public health services in a region of Johannesburg

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Naomi Lince-Deroche ◽  
Rahma Leuner ◽  
Gesine Meyer-Rath ◽  
Yogan Pillay ◽  
Lawrence Long
Keyword(s):  
Time Series ◽  
Service Delivery ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
Hiv Treatment ◽  
Hiv Care ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Public Clinics ◽  
The Impact

Abstract Background Early in South Africa’s HIV response, donor-funded organizations directly provided HIV treatment through Comprehensive HIV Care, Management and Treatment sites (CCMTs), using their own and government staff. From 2012 to 2014 the donor-funded CCMT model was phased out, leaving nurses in South Africa’s public clinics responsible for delivery of antiretroviral treatment (ART) services. We aimed to examine the impact on resources, staff workloads, and service delivery throughout this period of integration of HIV treatment into primary health clinics. Methods We conducted an Interrupted Time-Series Analysis (ITSA) using data from three public clinics, including one former CCMT site, in one administrative region of Johannesburg. The ITSA was complemented by visual inspection of the data in Excel. We compared trends in expenditure, clinical staffing levels, patient headcounts, and services rendered at the clinics during four periods: pre-CCMT (2004–2007), CCMT operational (2007–2012), CCMT closure (2012–2014), and post-CCMT (2014–2016). Data were drawn from the country’s District Health Information System, a national HIV treatment database, local budget and expenditure reports, National Health Laboratory Service charge records, and staff records. Results Closure of the CCMT differentially impacted the study clinics. As expected, ART services decreased at Clinic 1, where the CCMT was co-located, and increased at Clinics 2 and 3 possibly reflecting redistribution of patients. Despite a reduction in patient headcounts post-CCMT, Clinic 1 experienced a decrease in staff and a large increase in patients seen per clinical staff member per month. In contrast, Clinics 2 and 3 increased or maintained stable workforces, and staff workloads post closure were similar to pre-closure levels. Other primary care services—contraception and immunisations—seemed largely unaffected at Clinics 1 and 2. At Clinic 3, service delivery reduced, but this was accompanied by lowered patient headcounts generally, likely due to clinic renovations. Conclusions In this study, integration of HIV treatment into primary healthcare services did not result in large-scale reductions in overall service delivery. One facility did experience increased staff workloads, but we were unable to assess service quality. To mitigate potential problems, monitoring systems should be introduced in advance and acknowledge the disparate and decentralised management of various data sources.

scholarly journals Impact of guidance publication on primary care prescribing rates of simple analgesia: an interrupted time series analysis in England

2020 ◽  
pp. bjgp20X714101
Author(s):  
Hannah Reichel ◽  
Rhian Stanbrook ◽  
Hans Johnson ◽  
William Proto ◽  
Mary Shantikumar ◽  
...  
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Time Series Analysis ◽  
Health Inequality ◽  
Implementation Intentions ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Practice Level ◽  
Series Analysis ◽  
The Impact

Abstract Background: In March 2018, NHS England published guidance for Clinical Commissioning Groups (CCGs; NHS bodies that commission health services for local areas) to encourage implementation of policy to reduce primary care prescriptions of over-the-counter medications, including simple analgesia. Aims: To investigate: the impact of guidance publication on prescribing rates of simple analgesia (oral paracetamol, oral ibuprofen and topical non-steroidal anti-inflammatory drugs [NSAIDS]) in primary care; CCG implementation intentions; and whether it has created a health inequality based on socioeconomic status. Design and Setting: Interrupted time series analysis of primary care prescribing data in England. Methods: Practice-level prescribing data from January 2015 to March 2019 were obtained from NHS Digital. Interrupted time series analyses assessed the association of guidance publication with prescribing rates. The association between practice-level prescribing rates and Index of Multiple Deprivation score (a marker of socioeconomic deprivation) before and after publication was quantified using multivariable Poisson regression. Freedom of information requests were submitted to all CCGs. Results: There was a 4% reduction in prescribing of simple analgesia following guidance publication (adjusted incidence rate ratio [aIRR] 0.96, 95% CI 0.92-0.99, p=0.027), adjusting for underlying time trend and seasonality. Practice-level prescribing rates were greater in more deprived areas. There was considerable diversity across CCGs in whether or how they chose to implement the guidance. Conclusion: Guidance publication was associated with a small reduction in the prescribing rates of simple analgesia across England, without evidence of creating an additional health inequality.

scholarly journals COVID-19 and Antibiotic Prescribing in Pediatric Primary Care

PEDIATRICS ◽  
2022 ◽  
Author(s):  
Lauren Dutcher ◽  
Yun Li ◽  
Giyoung Lee ◽  
Robert Grundmeier ◽  
Keith W. Hamilton ◽  
...  
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
The United States ◽  
Pediatric Primary Care ◽  
Antibiotic Prescribing ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
The Impact

BACKGROUND AND OBJECTIVES: With the onset of the coronavirus disease 2019 (COVID-19) pandemic, pediatric ambulatory encounter volume and antibiotic prescribing both decreased; however, the durability of these reductions in pediatric primary care in the United States has not been assessed. METHODS: We conducted a retrospective observational study to assess the impact of the COVID-19 pandemic and associated public health measures on antibiotic prescribing in 27 pediatric primary care practices. Encounters from January 1, 2018, through June 30, 2021, were included. The primary outcome was monthly antibiotic prescriptions per 1000 patients. Interrupted time series analysis was performed. RESULTS: There were 69 327 total antibiotic prescriptions from April through December in 2019 and 18 935 antibiotic prescriptions during the same months in 2020, a 72.7% reduction. The reduction in prescriptions at visits for respiratory tract infection (RTI) accounted for 87.3% of this decrease. Using interrupted time series analysis, overall antibiotic prescriptions decreased from 31.6 to 6.4 prescriptions per 1000 patients in April 2020 (difference of −25.2 prescriptions per 1000 patients; 95% CI: −32.9 to −17.5). This was followed by a nonsignificant monthly increase in antibiotic prescriptions, with prescribing beginning to rebound from April to June 2021. Encounter volume also immediately decreased, and while overall encounter volume quickly started to recover, RTI encounter volume returned more slowly. CONCLUSIONS: Reductions in antibiotic prescribing in pediatric primary care during the COVID-19 pandemic were sustained, only beginning to rise in 2021, primarily driven by reductions in RTI encounters. Reductions in viral RTI transmission likely played a substantial role in reduced RTI visits and antibiotic prescriptions.

scholarly journals Does admission prevalence change after reconfiguration of inpatient services? An interrupted time series analysis of the impact of reconfiguration in five centres

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Joanne Martin ◽  
Edwin Amalraj Raja ◽  
Steve Turner
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Emergency Admission ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Emergency Admissions ◽  
Series Analysis ◽  
Inpatient Services ◽  
The Impact ◽  
Admission Prevalence

Abstract Background Service reconfiguration of inpatient services in a hospital includes complete and partial closure of all emergency inpatient facilities. The “natural experiment” of service reconfiguration may give insight into drivers for emergency admissions to hospital. This study addressed the question does the prevalence of emergency admission to hospital for children change after reconfiguration of inpatient services? Methods There were five service reconfigurations in Scottish hospitals between 2004 and 2018 where emergency admissions to one “reconfigured” hospital were halted (permanently or temporarily) and directed to a second “adjacent” hospital. The number of emergency admissions (standardised to /1000 children in the regional population) per month to the “reconfigured” and “adjacent” hospitals was obtained for five years prior to reconfiguration and up to five years afterwards. An interrupted time series analysis considered the association between reconfiguration and admissions across pairs comprised of “reconfigured” and “adjacent” hospitals, with adjustment for seasonality and an overall rising trend in admissions. Results Of the five episodes of reconfiguration, two were immediate closure, two involved closure only to overnight admissions and one with overnight closure for a period and then closure. In “reconfigured” hospitals there was an average fall of 117 admissions/month [95% CI 78, 156] in the year after reconfiguration compared to the year before, and in “adjacent” hospitals admissions rose by 82/month [32, 131]. Across paired reconfigured and adjacent hospitals, in the months post reconfiguration, the overall number of admissions to one hospital pair slowed, in another pair admissions accelerated, and admission prevalence was unchanged in three pairs. After reconfiguration in one hospital, there was a rise in admissions to a third hospital which was closer than the named “adjacent” hospital. Conclusions There are diverse outcomes for the number of emergency admissions post reconfiguration of inpatient facilities. Factors including resources placed in the community after local reconfiguration, distance to the “adjacent” hospital and local deprivation may be important drivers for admission pathways after reconfiguration. Policy makers considering reconfiguration might consider a number of factors which may be important determinants of admissions post reconfiguration.

Recession and risk of suicide in Denmark during the 2009 global financial crisis: an ecological register-based study

2021 ◽  
pp. 140349482110132
Author(s):  
Agnieszka Konieczna ◽  
Sarah Grube Jakobsen ◽  
Christina Petrea Larsen ◽  
Erik Christiansen
Keyword(s):  
Time Series ◽  
Financial Crisis ◽  
Time Series Analysis ◽  
Suicide Rate ◽  
Global Financial Crisis ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Prevention Programmes ◽  
The Impact

Aim: The aim of this study is to analyse the potential impact from the financial crisis (onset in 2009) on suicide rates in Denmark. The hypothesis is that the global financial crisis raised unemployment which leads to raising the suicide rate in Denmark and that the impact is most prominent in men. Method: This study used an ecological study design, including register data from 2001 until 2016 on unemployment, suicide, gender and calendar time which was analysed using Poisson regression models and interrupted time series analysis. Results: The correlation between unemployment and suicide rates was positive in the period and statistically significant for all, but at a moderate level. A dichotomised version of time (calendar year) showed a significant reduction in the suicide rate for women (incidence rate ratio 0.87, P=0.002). Interrupted time series analysis showed a significant decreasing trend for the overall suicide rate and for men in the pre-recession period, which in both cases stagnated after the onset of recession in 2009. The difference between the genders’ suicide rate changed significantly at the onset of recession, as the rate for men increased and the rate for women decreased. Discussion: The Danish social welfare model might have prevented social disintegration and suicide among unemployed, and suicide prevention programmes might have prevented deaths among unemployed and mentally ill individuals. Conclusions: We found some indications for gender-specific differences from the impact of the financial crises on the suicide rate. We recommend that men should be specifically targeted for appropriate prevention programmes during periods of economic downturn.

scholarly journals Impact of Removal of Automatic 7-Day Stop Orders for Inpatient Antimicrobials

2020 ◽  
Vol 41 (S1) ◽  
pp. s264-s265
Author(s):  
Afia Adu-Gyamfi ◽  
Keith Hamilton ◽  
Leigh Cressman ◽  
Ebbing Lautenbach ◽  
Lauren Dutcher
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
Antibiotic Use ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Treatment Interruptions ◽  
Days Of Therapy ◽  
Quasi Experimental ◽  
The Impact

Background: Automatic discontinuation of antimicrobial orders after a prespecified duration of therapy has been adopted as a strategy for reducing excess days of therapy (DOT) as part of antimicrobial stewardship efforts. Automatic stop orders have been shown to decrease antimicrobial DOT. However, inadvertent treatment interruptions may occur as a result, potentially contributing to adverse patient outcomes. To evaluate the effects of this practice, we examined the impact of the removal of an electronic 7-day ASO program on hospitalized patients. Methods: We performed a quasi-experimental study on inpatients in 3 acute-care academic hospitals. In the preintervention period (automatic stop orders present; January 1, 2016, to February 28, 2017), we had an electronic dashboard to identify and intervene on unintentionally missed doses. In the postintervention period (April 1, 2017, to March 31, 2018), the automatic stop orders were removed. We compared the primary outcome, DOT per 1,000 patient days (PD) per month, for patients in the automatic stop orders present and absent periods. The Wilcoxon rank-sum test was used to compare median monthly DOT/1,000 PD. Interrupted time series analysis (Prais-Winsten model) was used to compared trends in antibiotic DOT/1,000 PD and the immediate impact of the automatic stop order removal. Manual chart review on a subset of 300 patients, equally divided between the 2 periods, was performed to assess for unintentionally missed doses. Results: In the automatic stop order period, a monthly median of 644.5 antibiotic DOT/1,000 PD were administered, compared to 686.2 DOT/1,000 PD in the period without automatic stop orders (P < .001) (Fig. 1). Using interrupted time series analysis, there was a nonsignificant increase by 46.7 DOT/1,000 PD (95% CI, 40.8 to 134.3) in the month immediately following removal of automatic stop orders (P = .28) (Fig. 2). Even though the slope representing monthly change in DOT/1,000 PD increased in the period without automatic stop orders compared to the period with automatic stop orders, it was not statistically significant (P = .41). Manual chart abstraction revealed that in the period with automatic stop orders, 9 of 150 patients had 17 unintentionally missed days of therapy, whereas none (of 150 patients) in the period without automatic stop orders did. Conclusions: Following removal of the automatic stop orders, there was an overall increase in antibiotic use, although the change in monthly trend of antibiotic use was not significantly different. Even with a dashboard to identify missed doses, there was still a risk of unintentionally missed doses in the period with automatic stop orders. Therefore, this risk should be weighed against the modest difference in antibiotic utilization garnered from automatic stop orders.Funding: NoneDisclosures: None

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