Interrupted Time Series Regression Models Research Articles

Severe outcomes among adults with TB during COVID-19.

The COVID-19 pandemic prompted strict public health measures to reduce SARS-CoV-2 transmission, potentially interrupting TB programmes in the Western Cape, South Africa. We conducted a retrospective cohort study, estimating changes in new TB case rates and risk of death during TB-specific admissions within 6 months of TB first evidence, during the pre-pandemic (1 January 2019-26 March 2020) and after the implementation of public health and social measures (PHSM) periods (26 March 2020-30 September 2021), based on PHSM strictness. We used interrupted time series and logistic regression models to adjust for key characteristics. We found an average 22% reduction (95% CI 19-25) in monthly TB cases during the entire PHSM implementation period. Additionally, the risk of death during TB-specific admissions increased, with the adjusted odds ratio ranging across PHSM levels from 1.36 (95% CI 1.17-1.57) on Level 1 to 1.44 (95% CI 1.16-1.79) on Level 2 compared with the pre-pandemic period. There was a decline in the number of diagnosed TB cases and an increased risk of severe outcomes from 26 March 2020 to 30 September 2021 in the Western Cape. TB programme recovery strategies must be prioritised, and TB management programmes must be integrated into future pandemic responses.

Post-Pandemic Growth in 9-1-1 Paramedic Calls and Emergency Department Transports Surpasses Pre-Pandemic Rates in the COVID-19 Era: Implications for Paramedic Resource Planning

Objectives The COVID-19 pandemic led to a decline in emergency department (ED) visits and a subsequent return to baseline pre-pandemic levels. It is unclear if this trend extended to paramedic services and if patient cohorts accessing paramedics changed. We examined trends and associations between paramedic utilization (9-1-1 calls and ED transports) and the COVID-19 timeframe. Methods We conducted a retrospective cross-sectional study using paramedic call data from the Hamilton Paramedic Services from January 2016 to December 2023. We included all 9-1-1 calls where paramedics responded to an incident, excluding paramedic interfacility transfers. We calculated lines of best fit for the pre-pandemic period (January 2016 to January 2020) and compared their predictions to the actual volumes in the post-pandemic period (May 2021 to December 2023). We used an interrupted time series regression model to determine the association between pandemic timeframes (pre-, during-, post-COVID-19) and paramedic utilization (9-1-1 calls and ED transports), while testing for annual seasonality. Results During the study timeframe, 577,278 calls for paramedics were received and 413,491 (71.6%) were transported to the ED. Post-pandemic, 9-1-1 calls exceeded predicted pre-pandemic levels by 1,298 per month, while ED transports exceeded by 543 per month. The pandemic significantly reduced monthly 9-1-1 calls (-588.2, 95% CI −928.8 to −247.5) and ED transports (-677.3, 95% CI −927.0 to −427.5). Post-pandemic, there was a significant and sustained resurgence in monthly 9-1-1 calls (1,208.0, 95% CI 822.1 to 1,593.9) and ED transports (868.8, 95% CI 585.8 to 1,151.7). Both models exhibited seasonal variations. Conclusions Post-pandemic, 9-1-1-initiated paramedic calls experienced a substantial increase, surpassing pre-pandemic growth rates. ED transports returned to pre-pandemic levels but with a steeper and continuous pattern of growth. The resurgence in paramedic 9-1-1 calls and ED transports post-COVID-19 emphasizes an urgent necessity to expedite development of new care models that address how paramedics respond to 9-1-1 calls and transport to overcrowded EDs.

Enhancing patient outcomes: Integrating electronic cardiology consultation in primary care for cancer patients.

The prevalence of cancer patients with concomitant cardiovascular (CV) disease is on the rise due to improved cancer prognoses. The aim of this study is to evaluate the long-term outcomes of cancer patients referred to a cardiology department (CD) via primary care using e-consultation. We analysed data from cancer patients with prior referrals to a CD between 2010 and 2021 (n = 6889) and compared two care models: traditional in-person consultations and e-consultations. In e-consultation model, cardiologists reviewed electronic health records (e-consultation) to determine whether the demand could be addressed remotely or necessitated an in-person consultation. We used an interrupted time series regression model to assess outcomes during the two periods: (1) time to cardiology consultation, (2) rates of all-cause and CV related hospital admissions and (3) rates of all-cause and CV-related mortality within the first year after the initial consultation or e-consultation at the CD. Introduction of e-consultation for cancer patients referred to cardiology care led to a 51.8% reduction (95%CI: 51.7%-51.9%) in waiting times. Furthermore, we observed decreased 1-year incidence rates, with incidence rate ratios (iRRs) [IC95%] of .75 [.73-.77] for CV-related hospitalizations, .43 [.42-.44] for all-cause hospitalizations, and .87 [.86-.88] for all-cause mortality. Compared to traditional in-person consultations, an outpatient care program incorporating e-consultation for cancer patients significantly reduced waiting times for cardiology care and demonstrated safety, associated with lower rates of hospital admissions.

A universal electronic consultation programme at the cardiology department after general practitioner referrals improves healthcare outcomes in patients with health failure

Abstract Background Electronic consultation (e-Consult) is an emerging health care innovation developed to address excess wait times for specialist care by enabling primary care physicians (PCPs) to obtain a specialist consultant’s expert opinion in a timely manner 1. A recent wait time report in England showed that in the first 7 months of 2017, 89.4% of patients waited up to 18 weeks to see a specialist. This result failed to meet their standard of 92% of patients waiting no more than 18 weeks for their consult 2. e-Consult services were shown to be effective in terms of providing faster access to specialist’s advice, with short response times (from 1 to 6 days) of the participating specialists and resulting in substantial avoidance of face-to-face referral visits 3. The recent ESC HF guideline made a "may be considered" recommendation for the use of home-based telemonitoring, according on a meta-analysis published in 2017 4,5. Nevertheless, never has been evaluated the impact on access to care and clinical outcomes of a clinician-to-clinician e-consult program as a first step for all the PCPs referrals to cardiologist in heart failure patients. Purpose We aimed to assess in patients with heart failure (HF) the clinical impact of the implementation of an outpatient care model that includes an initial e-consultation (from 2013 to 2021) and to compare it with a one-time in-person consultation model (from 2010 to 2012) for all the primary care physicians’ referrals to a cardiology department. Methods We selected 6,859 HF patients who visited the cardiology service at least once between 2010 and 2021: 4,851 were attended in e-consultation and 2,008 in one-time in-person consultations. Using an interrupted time series regression model, we analysed the impact of incorporating e-consultation into the health care model (started in 2013), and evaluated the elapsed time to cardiology care, cardiovascular (CV) and HF hospital admissions, and HF, CV and all-cause mortality. Results The interrupted time series regression model showed that the introduction of e-consultation substantially decreased waiting times to cardiology care (8.6 [8.7] vs 55.4 [79.9] days, p<0.001). and a reduction in the need for visits to the emergency department 1-year after e-consultation compared with the previous period (HR [IC95%]: 0.07 [0.05-0.08]). After e-consultation implantation, hospital admissions were reduced (RRi [IC95%]: 0,867 [0,875-0,838] for HF, 0,838 [0,825-0,856] for CV and 0,639 [0,635-0,651] all-cause), figure 1; and lower mortality (RRi [IC95%]: 0,981 [0,977-0,983] due to HF, 0,977 [0,970-0,980] for CV and 0,985 [0,984-0,985] for all-cause), figure 2. These results were maintained during the COVID-19 pandemic. Conclusion In HF patients, an outpatient care program that includes an e-consultation significantly reduced waiting times to cardiology care and was safe, with a lower rate of hospital admissions and mortality in the first year.Figure 1Figure 2

Physician-to-physician universal electronic consultation program (e-consultation) in a Cardiology Department: Impact on elapsed time to cardiology care and cardiovascular outcomes

Abstract Background Many health systems have initiated electronic consultation programs, although little is known about their impact on accessibility, safety and satisfaction. In 2019, we began to analyse our model1. The first results showed that it was an efficient model2 and safe, with a reduction in emergency department visits, mortality and hospitalization3. In the last 3 years we have live a lot of changes. In one hand, all models need a continuous evaluation of their results, and confirm that the outcomes are similar to the beginning. In the other hand, we lived a world pandemic and our health models have changed in these years. In an e-consultation, the Primary Care Physician, who referred the patient, uses the shared electronic records and the Cardiologist who answer also uses the same electronic records to review all the clinical information and to send an answer. The Cardiologist can resolve directly the referral or to make an appointment with the patient in person in cases where it is necessary4. Purpose The aim of this study is to assess the clinical impact of the implementation of a model of ambulatory care that includes an initial electronic consultation (e-consultation), comparing it with a face-to-face single act model. Methods We selected patients with at least one visit to the Cardiology Service between 2010 and 2021. Using an interrupted time series regression model, we analysed the impact of incorporating the e-consultation into the healthcare model (started in 2013), evaluating: waiting time for care, hospitalizations and mortality in the first year. Results We analysed 61,306 patients: 66,0% attended by incorporating the e-consultation and 34,0% in the one-time face-to-face consultation model. The delay time for care in the e-consultation model (mean [SD]: 8.4 days [9.1]) was shorter than in the face-to-face model (mean [SD]: 50.6 days [72.2]), p < 0.001. The regression model for interrupted time series showed that the incorporation of e-consultation contributed a very important decrease in the delay of attention, remaining around 8 days, although with slight oscillations. The e-consultation model represented a reduction in hospitalizations (iRR [95%CI]: 0.635 [0.635-0.641]), cardiovascular hospitalizations (iRR [95%CI]: 0.857 [0.846-0.868]), Figure 1, mortality (iRR [95%CI]: 0.936 [0.923-0.951]) and cardiovascular mortality (iRR [95%CI]: 0.979 [0.964-0.996]), Figure 2. Conclusions An outpatient care program that includes an e-consultation has shown to reduce waiting times significantly and is a safe model with a lower rate of hospitalizations and mortality in the first year.Figure 1Figure 2

Impact of a clinician-to-clinician electronic consultation in heart failure patients with previous hospital admissions.

To evaluate the impact of an outpatient care management programme that includes a clinician-to-clinician e-consultation on delay time in care, hospital admissions, and mortality in a high-risk group of patients with heart failure (HF) and previous episodes of HF hospitalization (HFH). We selected 6444 HF patients who visited the cardiology service at least once between 2010 and 2021. Of these, 4851 were attended in e-consult, and 2230 had previous HFH. Using an interrupted time series regression model, we analysed the impact of incorporating e-consult into the healthcare model in the group of patients with HFH and evaluated the elapsed time to cardiology care, HF, cardiovascular (CV), and all-cause hospital admissions and mortality, calculating the incidence relative risk (iRR). In the group of patients with HFH, the introduction of e-consult substantially decreased waiting times to cardiology care (8.6 [8.7] vs. 55.4 [79.9] days, P < 0.001). In that group of patients, after e-consult implantation, hospital admissions for HF were reduced (iRR [95%CI]: 0.837 [0.840-0.833]), 0.900 [0.862-0.949] for CV and 0.699 [0.678-0.726] for all-cause hospitalizations. There was also lower mortality (iRR [95%CI]: 0.715 [0.657-0.798] due to HF, 0.737 [0.764-0.706] for CV and 0.687 [0.652-0.718] for all-cause). The improved outcomes after e-consultation implementation were significantly higher in the group of patients with previous HFH. In patients with HFH, an outpatient care programme that includes an e-consult significantly reduced waiting times to cardiology care and was safe, with a lower rate of hospital admissions and mortality in the first year.

In-Person and Teleconsultation Services at a National Hospital in Peru: Time Series Analysis of General and Psychiatric Care Amid the COVID-19 Pandemic.

The COVID-19 pandemic led to a global reduction in health care accessibility for both infected and noninfected patients, posing a particular burden on those with chronic conditions, including mental health issues. Peru experienced significant devastation from the pandemic, resulting in a collapsed health care system and leading to the world's highest per capita mortality rate as a result of COVID-19. Understanding the trends in health care utilization, particularly in mental health care, is crucial for informing pandemic response efforts and guiding future recovery strategies. This study aims to analyze the trends of outpatient medical and psychiatric consultations during the COVID-19 pandemic in a national hospital in Peru. This observational study was conducted at a national hospital in Lima, Peru. We analyzed data on user care across all services, including psychiatric services, from May 2019 to December 2022. The data were calculated for users served per month, including the number of users seen monthly in mental health services. Sociodemographic variables such as sex (female or male), age (≥0 years), type of medical appointment (regular or additional), and modality of care (in-person or teleconsultations) were taken into account. An interrupted time series regression model was conducted to assess the number of outpatient medical and psychiatric consultations. Subgroup analyses were performed based on service modality, including overall consultations, telemonitoring/teleconsultations only, or face-to-face only, for all service users and for mental health service users. A total of 1,515,439 participants were included, with females comprising 275,444/484,994 (56.80%) of the samples. Only 345,605/1,515,439 (22.81%) visits involved telemedicine. The total monthly outpatient visits were significantly reduced compared with the expected projection (P<.001) at the beginning of the pandemic, followed by a later monthly increment of 298.7 users. Face-to-face interventions experienced a significant reduction at the beginning of the pandemic (P<.001), gradually recovering in the following months. By contrast, telemedicine use initially increased but subsequently declined toward the end of the pandemic. A similar trend was observed in mental health units. During the pandemic years, health care utilization in both general and psychiatric services experienced a significant decrease, particularly at the beginning of the pandemic (March 2020). However, no significant trends were observed in either case throughout the pandemic period. Telemedicine consultations witnessed a significant increase overall during this period, particularly among mental health users.

Trends and Prescriber Variation in the Duration of Oxaliplatin-Containing Adjuvant Chemotherapy for Stage III Colon Cancer From 2007 to 2019: A Population-Based Retrospective Cohort Study

The International Duration Evaluation of Adjuvant Therapy (IDEA) collaboration in 2017 established 3 months of adjuvant therapy as an alternative to 6 months of therapy for stage III colon cancer. We determined the association between the IDEA publication, changes in clinical practice, and prescriber variation. Using linked databases, we identified Ontarians aged ≥18 years at diagnosis of stage III colon cancer between 2007 and 2019 who received oxaliplatin-containing adjuvant therapy. The outcome was duration of therapy, categorized as ≤25%, >25% to ≤50%, >50% to ≤75%, and >75% of a 6-month course of therapy to approximate treatment durations in the IDEA collaboration. We examined trends in duration over time using an interrupted time series regression model. We analyzed treatment duration after accounting for patient and prescriber characteristics, using multivariable mixed effects logistic regression models to quantify between-prescriber variation. We included 4695 patients with stage III colon cancer who received oxaliplatin-containing adjuvant chemotherapy, of whom 77.5% initiated treatment pre-IDEA and 22.5% initiated treatment post-IDEA. Post-IDEA, there was a 16.4% (95% CI, 12.5%-20.3%) absolute increase in the proportion of patients treated with ≤50% of a maximal course of therapy. This trend was greatest among patients with low-risk tumors. Prescriber variation increased pre-IDEA to 15.6% post-IDEA (variance partition coefficient 5.4% pre-IDEA and 15.6% post-IDEA). The publication of IDEA was associated with increases in short duration adjuvant therapy and prescriber-level practice variation for stage III colon cancer. Clinicians should be better supported to make consistent recommendations about adjuvant duration under conditions of uncertainty and trade-offs.

Gender differences on healthcare accessibility and outcomes of a electronic inter-clinician consultation program at the cardiology department in a Galician Health Area.

To assess the longer-term results (hospital admissions and mortality) in women versus men referred to a cardiology department from primary care using an e-consultation in our outpatient care program. We selected 61,306 patients (30,312 women and 30,994 men) who visited the cardiology service at least once between 2010 and 2021: 69,1% (19,997 women and 20,462 men) were attended in e-consultation (from 2013 to 2021) and 30,9% (8,920 women and 9,136 men) in in-person consultations (from 2010 to 2012) without gender differences in the proportion of patients attended in each period. Using an interrupted time series regression model, we analysed the impact of incorporating e-consultation into the health care model and evaluated the elapsed time to cardiology care, heart failure (HF), cardiovascular (CV), and all-cause hospital admissions and mortality during the one-year after cardiology consultation. The introduction of e-consultation substantially decreased waiting times to cardiology care; during the in-person consultation period, the mean delay for cardiology care was 57.9 (24.8) days in men and 55.8 (22.8) days in women. During the e-consultation period, the waiting time to cardiology care was markedly reduced to 9.41 (4.02) days in men and 9.46 (4.18) in women. After e-consultation implantation, there was a significant reduction in the 1-year rate of hospital admissions and mortality, both in women and men iRR [IC95%]: 0.95 [0.93-0.96] for HF, 0.90 [0.89-0.91] for CV, and 0.70 [0.69-0.71] for all-cause hospitalization; and 0.93 [0.92-0.95] for HF, 0.86 [0.86-0.87] for CV, and 0.88 [0.87-0.89] for all-cause mortality in women; and 0.91 [0.89-0.92] for HF, 0.90 [0.89-0.91] for CV and 0.72 [0.71-0.73] for all-cause hospitalization; and 0.96 [0.93-0.97] for HF, 0.87 [95%CI: 0.86-0.87] for CV, and 0.87 [0.86-0.87] for all-cause mortality, in men. Compared with the in-person consultation period, an outpatient care program that includes an e-consultation significantly reduced waiting time to cardiology care and was safe, with a lower rate of hospital admissions and mortality in the first year, without significative gender differences.

Disparities in Telemedicine Use Among Louisiana Medicaid Beneficiaries During the COVID-19 Pandemic.

The COVID-19 pandemic led to an increased reliance on telemedicine. Whether this exacerbated existing disparities within vulnerable populations is not yet known. Characterize changes in outpatient telemedicine evaluation and management (E&M) services for Louisiana Medicaid beneficiaries by race, ethnicity, and rurality during the COVID-19 pandemic. Interrupted time series regression models estimated pre-COVID-19 trends and changes in E&M service use at the April and July 2020 peaks in COVID-19 infections in Louisiana and in December 2020 after those peaks had subsided. Louisiana Medicaid beneficiaries continuously enrolled between January 2018 and December 2020 who were not also enrolled in Medicare. Monthly outpatient E&M claims per 1000 beneficiaries. Prepandemic differences in service use between non-Hispanic White and non-Hispanic Black beneficiaries narrowed by 34% through December 2020 (95% CI: 17.6%-50.6%), while differences between non-Hispanic White and Hispanic beneficiaries increased by 10.5% (95% CI: 0.1%-20.7%). Non-Hispanic White beneficiaries used telemedicine at higher rates than non-Hispanic Black (difference=24.9 claims per 1000 beneficiaries, 95% CI: 22.3-27.4) and Hispanic beneficiaries (difference=42.3 claims per 1000 beneficiaries, 95% CI: 39.1-45.5) during the first wave of COVID-19 infections in Louisiana. Telemedicine use increased slightly for rural beneficiaries compared with urban beneficiaries (difference=5.3 claims per 1000 beneficiaries, 95% CI: 4.0-6.6). The COVID-19 pandemic narrowed gaps in outpatient E&M service use between non-Hispanic White and non-Hispanic Black Louisiana Medicaid beneficiaries, though gaps in telemedicine use emerged. Hispanic beneficiaries experienced large reductions in service use and relatively small increases in telemedicine use.

Universal electronic consultation program (e-consultation) of a cardiology department: long-term results in mortality

Abstract Background Many health systems have initiated electronic consultation programs, although little is known about their impact on accessibility, safety and satisfaction (1). The implementation of integrated electronic medical record projects between healthcare levels allows all healthcare professionals access to all the clinical information of patients, which is a key factor in optimizing the management of healthcare resources, facilitating the communication between professionals and avoiding medical acts that do not add value, always from the premise of safety and quality for patients (2). In our model, a General Practitioner sends an e-referral to the Cardiology Department (CD). A Cardiologist can either answer without needing the face-to-face consultation, or schedule the patient for a single act consultation. In our health area, from 2009 to 2012, a “single act” cardiology consultation model was implemented, according to which the appointment includes, on the same day, all the complementary tests that might be necessary for the diagnosis. From 2013 until present, an electronic consultation or e-consultation model has been implemented; consisting of a telematic evaluation of the e-consultation by a cardiologist, who can either solve the GP's requests directly or book an appointment for the patient in person, in cases where it is considered necessary (3). Purpose The aim of this study is to assess the clinical impact of the implementation of a model of outpatient care that includes an initial electronic consultation (e-consultation), comparing it with a face-to-face single act model. Methods We selected patients with at least one visit to the Cardiology Department between 2010 and 2019. Using an interrupted time series regression model, we analysed the impact of incorporating the e-consultation into the healthcare model (started in 2013), evaluating: waiting time for care and mortality. Results We analysed 47,377 patients: 61.9% attended by incorporating the e-consultation and 38.1% in the face-to-face consultation model. The delay time for care in the e-consultation model (median [IQR]: 7 days [5–13]) was shorter than in the face-to-face model (median [IQR]: 33 days [14–81]), p&amp;lt;0.001. The regression model for interrupted time series showed that the incorporation of e-consultation contributed a very important decrease in the delay of attention, remaining around 9 days, although with slight oscillations, Figure 1. The patients evaluated via e-consultation had less mortality (2.5% vs 3.9%, p&amp;lt;0.001), Figure 2. Conclusions An outpatient care program that includes an e-consultation has shown to reduce waiting times significantly and is a safe model with a lower rate of mortality over the first year after the consultation. Funding Acknowledgement Type of funding sources: None.

Examining the Effectiveness of the 2012 Canadian Graphic Warning Label Policy Change by Sex, Income, and Education.

We examined the differential impact of the 2012 Canadian GWL policy changes on key indicators of warning label impact and quit intentions using national cohorts of Canadian and U.S. adults who smoke. We used data from all waves of the International Tobacco Control surveys (2002-2020) in Canada and the United States. Our key measures were quit intentions and an index of warning label effectiveness (salience, cognitive and behavioral reactions). We estimated overall policy impact by comparing Canada (treatment group) with the United States (control group) using controlled interrupted time series (CITS) regression models, with interactions to examine whether policy impact varied by sex, education, and income. The CITS model showed a statistically significant increase in the warning label effectiveness in Canada post-policy, compared to the United States (β = 0.84, 95% CI 0.35,1.33). Similarly, the odds of quit intentions were relatively higher among adults who smoked in Canada compared to the United States (OR = 1.89, 95% CI 1.51,2.36) post-policy. The three-way interaction model showed that these associations were greater among adults from low socioeconomic status (SES) groups than in high SES groups. The 2012 change in the Canadian GWL policy was associated with stronger cognitive and behavioral responses to GWLs and higher odds of quit intentions among adults who smoked in Canada when compared to the United States, specifically among individuals from low SES groups, suggesting a positive equity impact. Our findings affirm the need for countries to implement or enhance GWLs, in line with the WHO Framework Convention on Tobacco Control (FCTC). The evidence on the potential health equity benefit of GWL policies is mixed. To further understand the influence of GWL policies on tobacco use disparities, more systematic research using pre/post-policy designs with control groups is needed. Using a CITS model, we aimed to strengthen the available evidence on the causal influence of this tobacco control approach. Our findings show that the 2012 GWL policy change had a greater impact on adults who smoked from low SES groups than it did on adults who smoked from high SES groups, indicating a potentially positive equity impact and confirming the need for countries to implement or maximize the size of GWLs, as recommended by the WHO FCTC.

Universal electronic consultation program (e-consultation) of a cardiology department: long-term results in mortality

Abstract Background Many health systems have initiated electronic consultation programs, although little is known about their impact on accessibility, safety and satisfaction (1). The implementation of integrated electronic medical record projects between healthcare levels allows all healthcare professionals access to all the clinical information of patients, which is a key factor in optimizing the management of healthcare resources, facilitating the communication between professionals and avoiding medical acts that do not add value, always from the premise of safety and quality for patients (2). In our model, a General Practitioner sends an e-referral to the Cardiology Department (CD). A Cardiologist can either answer without needing the face-to-face consultation, or schedule the patient for a single act consultation. In our health area, from 2009 to 2012, a “single act” cardiology consultation model was implemented, according to which the appointment includes, on the same day, all the complementary tests that might be necessary for the diagnosis. From 2013 until present, an electronic consultation or e-consultation model has been implemented; consisting of a telematic evaluation of the e-consultation by a cardiologist, who can either solve the GP's requests directly or book an appointment for the patient in person, in cases where it is considered necessary (3). Purpose The aim of this study is to assess the clinical impact of the implementation of a model of outpatient care that includes an initial electronic consultation (e-consultation), comparing it with a face-to-face single act model. Methods We selected patients with at least one visit to the Cardiology Department between 2010 and 2019. Using an interrupted time series regression model, we analysed the impact of incorporating the e-consultation into the healthcare model (started in 2013), evaluating: waiting time for care and mortality. Results We analysed 47,377 patients: 61.9% attended by incorporating the e-consultation and 38.1% in the face-to-face consultation model. The delay time for care in the e-consultation model (median [IQR]: 7 days [5–13]) was shorter than in the face-to-face model (median [IQR]: 33 days [14–81]), p&amp;lt;0.001. The regression model for interrupted time series showed that the incorporation of e-consultation contributed a very important decrease in the delay of attention, remaining around 9 days, although with slight oscillations, Figure 1. The patients evaluated via e-consultation had less mortality (2.5% vs 3.9%, p&amp;lt;0.001), Figure 2. Conclusions An outpatient care program that includes an e-consultation has shown to reduce waiting times significantly and is a safe model with a lower rate of mortality over the first year after the consultation. Funding Acknowledgement Type of funding sources: None.

Influence of the COVID-19 Pandemic on Author Sex and Manuscript Acceptance Rates among Pulmonary and Critical Care Journals.

Rationale: The coronavirus disease (COVID-19) pandemic has negatively affected women more than men and may influence the publication of non-COVID-19 research. Objectives: To evaluate whether the COVID-19 pandemic is associated with changes in manuscript acceptance rates among pulmonary/critical care journals and sex-based disparities in these rates. Methods: We analyzed first, senior, and corresponding author sex (female vs. male, identified by matching first names in a validated Genderize database) of manuscripts submitted to four pulmonary/critical care journals between January 1, 2018 and December 31, 2020. We constructed interrupted time series regression models to evaluate whether the proportion of female first and senior authors of non-COVID-19 original research manuscripts changed with the pandemic. Next, we performed multivariable logistic regressions to evaluate the association of author sex with acceptance of original research manuscripts. Results: Among 8,332 original research submissions, women represented 39.9% and 28.3% of first and senior authors, respectively. We found no change in the proportion of female first or senior authors of non-COVID-19 or COVID-19 submitted research manuscripts during the COVID-19 era. Non-COVID-19 manuscripts submitted during the COVID-19 era had reduced odds of acceptance, regardless of author sex (first author adjusted OR [aOR], 0.46 [95% confidence interval (CI), 0.36-0.59]; senior author aOR, 0.46 [95% CI, 0.37-0.57]). Female senior authorship was associated with decreased acceptance of non-COVID-19 research manuscripts (crude rates, 14.4% [male] vs. 13.2% [female]; aOR, 0.84 [95% CI, 0.71-0.99]). Conclusions: Although female author submissions were not disproportionately influenced by COVID-19, we found evidence suggesting sex disparities in manuscript acceptance rates. Journals may need to consider strategies to reduce this disparity, and academic institutions may need to factor our findings, including lower acceptance rates for non-COVID-19 manuscripts, into promotion decisions.

Impact of the naloxone standing order on trends in opioid fatal overdose: an ecological analysis

ABSTRACT Background: Maryland expanded its “Statewide Naloxone Standing Order” (NSO) in 2017 to eliminate training and prescription requirements for obtaining naloxone, improve naloxone access, help reverse opioid overdose, and reduce overdose fatality rates. Objectives: To assess the change in the trends of fatal opioid overdose rates following the expansion of the Naloxone Standing Order (eNSO) and its association with the social determinants of health (SDoH). Methods: Data on overdose deaths and SDoH from 2015–2019 was collected and analyzed using interrupted time series and multivariate Poisson regression models to study the change in trends and the associations. Results: There was a significant decrease in the rate of fatal overdoses after the intervention: prescription opioid estimate number of deaths declined by .25 per 100,000 (p = .02), heroin estimate number of deaths declined by 1.83 per 100,000 (p < .001), fentanyl estimate number of deaths declined by 2.54 per 100,000 (p < .001). After controlling for eNOS implementation in Maryland, state-level estimates with high proportions of female residents and those with bachelor’s degree or higher were associated with reduction in overdose, while state-level estimates with high proportions of African Americans and higher employment rates were associated with an increase in overdose. Conclusions: Our analysis shows that the expanded naloxone standing order is associated with reducing opioid-related overdose death rates. Even though we observed a significant reduction in overdose death rate in fentanyl-related deaths, the rate of deaths post-eNSO was still increasing, suggesting the need for additional measures to impact the rates of fentanyl.

The impact of Facebook’s vaccine misinformation policy on user endorsements of vaccine content: An interrupted time series analysis

ObjectivesTo evaluate the impact of Facebook’s vaccine misinformation policy in March 2019 on user endorsements of vaccine content on its platform. MethodsWe identified 172 anti- and pro-vaccine Facebook Pages and collected posts from these Pages six months before and after the policy. Using interrupted time series regression models, we evaluated the policy impact on user endorsements (i.e., likes) of anti- and pro-vaccine posts on Facebook. ResultsThe number of likes for posts on anti-vaccine Pages had decreased after the policy implementation (policy = 153.2, p < 0.05; policy*day = −0.838, p < 0.05; marginal effect at the mean = −22.74, p < 0.01; marginal effect at the median = −24.56, p < 0.01). When the number of subscribers was considered, the policy effect on the number of likes for anti-vaccine posts was much smaller, but still statistically significant (policy = 4.849, p < 0.05; policy*day = −0.027, p < 0.05; marginal effect at the mean = −0.742, p < 0.01; marginal effect at the median = −0.800, p < 0.01). There was no policy effect observed for posts on pro-vaccine Pages. ConclusionsOur analysis suggested that Facebook’s March 2019 vaccine misinformation policy moderately impacted the number of endorsements of anti-vaccine content on its platform. Social media companies can take measures to limit the popularity of anti-vaccine content by reducing their reach and visibility. Future research efforts should focus on evaluating additional policies and examining policies across platforms.

Impact of COVID-19 on healthcare waste generation: correlations and trends from a tertiary hospital

Abstract Background COVID-19 has represented an emergency not only for the sanitary issues, but also from the environmental and operative perspective, with largely increased waste disposal due to non-reusable personal protective equipment and packaging. This study aimed at estimating the increase in healthcare waste (HW) generation during the outbreak, based on data from a tertiary hospital. Methods From the purveying office statements of “SS Antonio e Biagio e Cesare Arrigo” Hospital of Alessandria (Italy), monthly data on HW generation from January 2015 to March 2021 were retrospectively retrieved. Trend analyses were performed through linear regression and the impact of COVID was evaluated following the Interrupted-Time Series regression model. Moreover, HW generation data were compared to the proportion of patient-days and admissions due to COVID (out of respective totals) through Pearson's correlation test. Results HW generation rose from a baseline of 35.9 ± 3.8 tons/month (2.4 ± 0.2 kg per patient-day, kg/PD) in 2015-2019, to 46.3 ± 6.0 tons/month (3.3 ± 0.6 kg/PD) during the outbreak (2020-2021), with a peak in March-April 2020. Segmented regression showed that the already increasing trend was not appreciably modified as for its slope, whereas a significant level change could be detected between baseline and outbreak period (+0.6 kg/PD, corresponding to a 28.6% increase compared to baseline intercept, p &amp;lt; 0.001). HW generation was significantly correlated to the proportion of admissions (p = 0.005, R2=0.70) and patient-days (p = 0.006, R2=0.69) related to COVID-19. Conclusions The study showed a significant rise in HW generation in 2020-2021, reasonably due to the COVID-19 outbreak. Moreover, this happened without affecting the generally increasing trend. These results underline the effect of the pandemic on the amounts of waste generated by healthcare facilities, with noticeable impact on the environment and higher costs associated with HW management and disposal. Key messages Due to extensive use of disposable equipment and packaging, COVID-19 strongly impacted on healthcare waste generation, with an average 28.6% increase compared to baseline levels (+0.6 kg/patient-day). The generally increasing trend in healthcare waste generation, along with the remarkable increase due to COVID-19, results in high environmental impact and management costs for healthcare facilities.

Impact of a multifaceted intervention to improve emergency care on newborn and child health outcomes in Rwanda.

Implementing context-appropriate neonatal and paediatric advanced life support management interventions has increasingly been recommended as one of the approaches to reduce under-five mortality in resource-constrained settings like Rwanda. One such intervention is ETAT+, which stands for Emergency Triage, Assessment and Treatment plus Admission care for severely ill newborns and children. In 2013, ETAT+ was implemented in Rwandan district hospitals. We evaluated the impact of the ETAT+ intervention on newborn and child health outcomes. We used monthly time-series data from the DHIS2-enabled Rwanda Health Management Information System from 2012 to 2016 to examine neonatal and paediatric hospital mortality rates. Each hospital contributed data for 12 and 36 months before and after ETAT+ implementation, respectively. Using controlled interrupted time-series analysis and segmented regression model, we estimated longitudinal changes in neonatal and paediatric hospital mortality rates in intervention hospitals relative to matched concurrent control hospitals. We also studied changes in case fatality rate specifically for ETAT+-targeted conditions. Our study cohort consisted of 7 intervention hospitals and 14 matched control hospitals contributing 142 424 neonatal and paediatric hospital admissions. After controlling for secular trends and autocorrelations, we found that the ETAT+ implementation had no statistically significant impact on the rate of all-cause neonatal and paediatric hospital mortality in intervention hospitals relative to control hospitals. However, the case fatality rate for ETAT+-targeted neonatal conditions decreased immediately following implementation by 5% (95% confidence interval: -9.25, -0.77) and over time by 0.8% monthly (95% confidence interval: -1.36, -0.25) in intervention hospitals compared with control hospitals. Case fatality rate for ETAT+-targeted paediatric conditions did not decrease following the ETAT+ implementation. While ETAT+ focuses on improving the quality of hospital care for both newborns and children, we only found an impact on neonatal hospital mortality for ETAT+-targeted conditions that should be interpreted with caution given the relatively short pre-intervention period and potential regression to the mean.

Effect of relaxing hepatitis C treatment restrictions on direct-acting antiviral use in a Medicaid program: an interrupted time series analysis.

BACKGROUND: Although direct-acting antivirals (DAA) have revolutionized the treatment of chronic hepatitis C virus (HCV), many state Medicaid programs have limited coverage because of their expense. In 2015, the Centers for Medicare & Medicaid Services (CMS) notified states about the legality of Medicaid coverage limitations, particularly within managed care programs. OBJECTIVES: To (1) examine how relaxation and alignment of hepatitis C policies within the Oregon Medicaid program affected DAA utilization and (2) describe changes in DAA coverage policies and patient characteristics of treated individuals over time. METHODS: We manually collected DAA Medicaid drug policies in the state of Oregon before and after the CMS notification was released. After categorizing DAA policies into 2 groups based on baseline prior authorization criteria (restrictive and permissive), we evaluated how changes in these DAA policies affected utilization over 3 time periods (pre-CMS period, post-CMS period, and fibrosis policy alignment). Immediate and gradual changes in trend were assessed using an interrupted time series regression model. Finally, we examined patient characteristics and liver disease complications over time as policy restrictions were removed and aligned with one another. RESULTS: From 2014 to 2018, Oregon's coordinated care organizations and fee-for-service drug policies relaxed liver fibrosis and substance abstinence coverage criteria leading to immediate increases in DAA use in 2016 (0.62 prescriptions per 10,000 enrollees per month; 95% CI = 0.17 to 1.08) and 2018 (1.07 prescriptions per 10,000 enrollees per month; 95% CI = 0.63 to 1.51) among more restrictive coordinated care organizations at baseline. This was followed by a decrease in trend after the 2016 and 2018 impact (-0.05; 95% CI = -0.11 to -0.001 and -0.07; 95% CI = -0.13 to -0.02, respectively). Over the 3 periods, there was a decrease in treated individuals with liver-related complications (P < 0.0001) and an increase in those with a substance use diagnosis (P = 0.0013). CONCLUSIONS: Reducing coverage limitations resulted in treatment of patients with fewer liver-related complications and more substance use disorders. Expanding access to treatment did not result in sustained increases in utilization, and additional interventions may be necessary to meet HCV elimination goals. DISCLOSURES: This study was funded in part by AbbVie Pharmaceuticals, which did not have any role in the study design, collection, analysis and interpretation of data, writing the report, or the decision to submit the report for publication. Hartung received support for his work on this study via a grant from AbbVie Pharmaceuticals. The other authors did not receive any financial support for their contributions to this study. The authors have no other financial disclosures to report. This study was presented at the Academy Health Annual Research Meeting in Washington, DC, on June 3, 2019.

Universal electronic consultation (e-consultation) program of a cardiology service. Long-term results

Introduction and objectivesMany health systems have initiated electronic consultation (e-consultation) programs, although little is known about their impact on accessibility, safety, and satisfaction. The aim of this study was to assess the clinical impact of the implementation of an outpatient care model that includes an initial e-consultation and to compare it with a one-time face-to-face consultation model. MethodsWe selected patients who visited the cardiology service at least once between 2010 and 2019. Using an interrupted time series regression model, we analyzed the impact of incorporating e-consultation into the health care model (started in 2013), and evaluated waiting times, emergency services, hospital admissions, and mortality. ResultsWe analyzed 47 377 patients: 61.9% were attended in e-consultation and 38.1% in one-time face-to-face consultations. The waiting time for care was shorter in the e-consultation model (median [IQR]: 7 [5-13] days) than in the face-to-face model (median [IQR]: 33 [14-81] days), P<.001. The interrupted time series regression model showed that the introduction of e-consultation substantially decreased waiting times, which held steady at around 9 days, although with slight oscillations. Patients evaluated via e-consultation had fewer hospital admissions (0.9% vs 1.2%, P=.0017) and lower mortality (2.5% vs 3.9%, P<.001). ConclusionsAn outpatient care program that includes an e-consultation reduced waiting times significantly and was safe, with a lower rate of hospital admissions and mortality in the first year.