Demonstrating the impact and model of care of a Statewide psychiatric intensive care service

2013 ◽  
Vol 21 (5) ◽  
pp. 466-471 ◽  
Author(s):  
Stuart Lee ◽  
Yitzchak Hollander ◽  
Lisa Scarff ◽  
Ryan Dube ◽  
Sandra Keppich-Arnold ◽  
...  
Keyword(s):  
Intensive Care ◽  
Care Service ◽  
Model Of Care ◽  
The Impact

scholarly journals Impact of COVID-19 on non-COVID intensive care unit service utilization, case mix and outcomes: A registry-based analysis from India

2021 ◽  
Vol 6 ◽  
pp. 159
Author(s):  
◽  
Neill KJ Adhikari ◽  
Abi Beane ◽  
Dedeepiya Devaprasad ◽  
Robert Fowler ◽  
...  
Keyword(s):  
Critical Care ◽  
Intensive Care ◽  
Service Utilization ◽  
Care Service ◽  
Severity Of Illness ◽  
Apache Ii Score ◽  
Case Mix ◽  
Icu Mortality ◽  
The Impact ◽  
Registry Database

Background: Coronavirus disease 2019 (COVID-19) has been responsible for over 3.4 million deaths globally and over 25 million cases in India. As part of the response, India imposed a nation-wide lockdown and prioritized COVID-19 care in hospitals and intensive care units (ICUs). Leveraging data from the Indian Registry of IntenSive care, we sought to understand the impact of the COVID-19 pandemic on critical care service utilization, case-mix, and clinical outcomes in non-COVID ICUs.  Methods: We included all consecutive patients admitted between 1 st October 2019 and 27 th September 2020. Data were extracted from the registry database and included patients admitted to the non-COVID or general ICUs at each of the sites. Outcomes included measures of resource-availability, utilisation, case-mix, acuity, and demand for ICU beds. We used a Mann-Whitney test to compare the pre-pandemic period (October 2019 - February 2020) to the pandemic period (March-September 2020). In addition, we also compared the period of intense lockdown (March-May 31 st 2020) with the pre-pandemic period. Results: There were 3424 patient encounters in the pre-pandemic period and 3524 encounters in the pandemic period. Comparing these periods, weekly admissions declined (median [Q1 Q3] 160 [145,168] to 113 [98.5,134]; p<0.001); unit turnover declined (median [Q1 Q3] 12.1 [11.32,13] to 8.58 [7.24,10], p<0.001), and APACHE II score increased (median [Q1 Q3] 19 [19,20] to 21 [20,22] ; p<0.001). Unadjusted ICU mortality increased (9.3% to 11.7%, p=0.015) and the length of ICU stay was similar (median [Q1 Q3] 2.11 [2, 2] vs. 2.24 [2, 3] days; p=0.151). Conclusion: Our registry-based analysis of the impact of COVID-19 on non-COVID critical care demonstrates significant disruptions to healthcare utilization during the pandemic and an increase in the severity of illness.

Economic Assessment of a New Model of Care to Support Patients With Cancer Experiencing Cancer- and Treatment-Related Toxicities

2020 ◽  
Vol 16 (9) ◽  
pp. e884-e892
Author(s):  
Sophy T. F. Shih ◽  
Angela Mellerick ◽  
Georgina Akers ◽  
Kathryn Whitfield ◽  
Marj Moodie
Keyword(s):  
Cancer Care ◽  
Care Service ◽  
Economic Assessment ◽  
Additional Treatment ◽  
Model Of Care ◽  
Patients With Cancer ◽  
The Cost ◽  
Cost Offsets ◽  
The Impact ◽  
Inpatient Units

PURPOSE: The aim of this economic assessment was to evaluate the impact of a new nurse-led model of care, the Symptom and Urgent Review Clinic (SURC), for patients with cancer experiencing disease- or treatment-related symptoms. METHODS: An economic assessment was undertaken to estimate costs of the SURC from the service funder perspective and to compare the cost with cost offsets stemming from the implementation of the SURC. The cost offsets focused on the changes in emergency department (ED) presentations and inpatient admissions during a comparable 6-month period before and after the SURC implementation. Costs were analyzed in 2018 Australian dollars, and return on investment was calculated by comparing the cost offsets in the ED and inpatient units with the cost of the SURC. RESULTS: After the implementation of the SURC, patients were less likely to present to the ED (7.2% v 8.5%; P = .01), and patients who did present to the ED were more likely to be admitted to inpatient units (78% v 71%; P = .03) for additional treatment. The post-SURC period had a net cost savings of $37,090 compared with the pre-SURC period. From the service funder perspective, the SURC achieved an investment return of $1.73 for every dollar invested in the new service. CONCLUSION: Our study establishes the economic credentials of a new care model using empirical linked hospital service data. The SURC presents a new cancer care service for policy consideration from an economic standpoint. It demonstrates an efficient approach to hospital resource allocation to deliver quality cancer care.

scholarly journals Impact of COVID-19 on non-COVID intensive care unit service utilization, case mix and outcomes: A registry-based analysis from India

2021 ◽  
Vol 6 ◽  
pp. 159
Author(s):  
◽  
Neill KJ Adhikari ◽  
Abi Beane ◽  
Dedeepiya Devaprasad ◽  
Robert Fowler ◽  
...  
Keyword(s):  
Critical Care ◽  
Intensive Care ◽  
Service Utilization ◽  
Care Service ◽  
Severity Of Illness ◽  
Apache Ii Score ◽  
Case Mix ◽  
Icu Mortality ◽  
The Impact ◽  
Registry Database

Background: Coronavirus disease 2019 (COVID-19) has been responsible for over 3.4 million deaths globally and over 25 million cases in India. As part of the response, India imposed a nation-wide lockdown and prioritized COVID-19 care in hospitals and intensive care units (ICUs). Leveraging data from the Indian Registry of IntenSive care, we sought to understand the impact of the COVID-19 pandemic on critical care service utilization, case-mix, and clinical outcomes in non-COVID ICUs.  Methods: We included all consecutive patients admitted between 1st October 2019 and 27th September 2020. Data were extracted from the registry database and included patients admitted to the non-COVID or general ICUs at each of the sites. Outcomes included measures of resource-availability, utilisation, case-mix, acuity, and demand for ICU beds. We used a Mann-Whitney test to compare the pre-pandemic period (October 2019 - February 2020) to the pandemic period (March-September 2020). In addition, we also compared the period of intense lockdown (March-May 31st 2020) with the pre-pandemic period. Results: There were 3424 patient encounters in the pre-pandemic period and 3524 encounters in the pandemic period. Comparing these periods, weekly admissions declined (median [Q1 Q3] 160 [145,168] to 113 [98.5,134]; p=0.00002); unit turnover declined (median [Q1 Q3] 12.1 [11.32,13] to 8.58 [7.24,10], p<0.00001), and APACHE II score increased (median [Q1 Q3] 19 [19,20] to 21 [20,22] ; p<0.00001). Unadjusted ICU mortality increased (9.3% to 11.7%, p=0.01519) and the length of ICU stay was similar (median [Q1 Q3] 2.11 [2, 2] vs. 2.24 [2, 3] days; p=0.15096). Conclusion: Our registry-based analysis of the impact of COVID-19 on non-COVID critical care demonstrates significant disruptions to healthcare utilization during the pandemic and an increase in the severity of illness.

The Impact of Mobile Phone Technology in Bridging the Gaps in The Health Care Service Delivery in Kenya: A Case of Nairobi County. (Preprint)

2019 ◽  
Author(s):  
Alice Ndwiga
Keyword(s):  
Service Delivery ◽  
Mobile Phone ◽  
Care Service ◽  
Health Care Service ◽  
Informal Settlements ◽  
Healthcare Services ◽  
P Value ◽  
Delivery Of Healthcare ◽  
Mobile Phone Technology ◽  
The Impact

BACKGROUND INTRODUCTION: The Kenyan constitution seeks to guarantee every citizen the right to quality healthcare services. Quite often this delivery is hampered by geographical location, socio-economic statuses among other factors. The country has a high mobile phone penetration rate. Digitalization of the healthcare sector is a vital aspect that contributes to effective delivery of care services. This study set out to assess the impact of mobile technology in closing the gaps within the health care service delivery. The objective of the study was to investigate the impact of mobile phone technology in bridging the gap in healthcare service delivery in Kenya with a focus on Nairobi, Kibera informal settlements. Hypothesis testing using P-value of 0.05 also showed that use of mobile phone technology positively impacted the delivery of healthcare services. OBJECTIVE The objective of the study was to investigate the impact of mobile phone technology in bridging the gap in healthcare service delivery in Kenya with a focus on Nairobi, Kibera informal settlements. Hypothesis testing using P-value of 0.05 also showed that use of mobile phone technology positively impacted the delivery of healthcare services. METHODS The target population were patients visiting Médecins Sans Frontières (MSF) clinic in Kibera informal settlements. A cross-sectional study design was employed. Purposive and simple random sampling method was used to select the study sample of 210 participants and 3 healthcare providers. Data were collected using survey questionnaire that was provider-administered and Data were analyzed using SPSS version. RESULTS The characteristics of the respondents were general (mean age, education level, social economic status) to only patients who visited the clinics for HIV tests and other related services such as going for ARVs. The main findings showed that 66.12% of the respondents (14.29% strongly agreed + 55.24% agreed) that the use of mobile phone technology improved their access to healthcare services. Using chi square, there was a statistical difference due to the positive impact of mobile technology on healthcare delivery (p=0.05). CONCLUSIONS The study findings showed that 66.12% of the respondents agreed that the use of mobile phone technology and SMS improved their access to healthcare services. The results hypothesis also proved that use of mobile phone technology positively impacts the delivery of healthcare services.

scholarly journals Outcomes of non-COVID-19 critically ill patients during the COVID-19 pandemic

2021 ◽  
Author(s):  
Răzvan Bologheanu ◽  
Mathias Maleczek ◽  
Daniel Laxar ◽  
Oliver Kimberger
Keyword(s):  
Intensive Care ◽  
Length Of Stay ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Medical Specialty ◽  
Routine Care ◽  
Treatment Pathways ◽  
Icu Length Of Stay ◽  
Matched Study ◽  
The Impact

Summary Background Coronavirus disease 2019 (COVID-19) disrupts routine care and alters treatment pathways in every medical specialty, including intensive care medicine, which has been at the core of the pandemic response. The impact of the pandemic is inevitably not limited to patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and their outcomes; however, the impact of COVID-19 on intensive care has not yet been analyzed. Methods The objective of this propensity score-matched study was to compare the clinical outcomes of non-COVID-19 critically ill patients with the outcomes of prepandemic patients. Critically ill, non-COVID-19 patients admitted to the intensive care unit (ICU) during the first wave of the pandemic were matched with patients admitted in the previous year. Mortality, length of stay, and rate of readmission were compared between the two groups after matching. Results A total of 211 critically ill SARS-CoV‑2 negative patients admitted between 13 March 2020 and 16 May 2020 were matched to 211 controls, selected from a matching pool of 1421 eligible patients admitted to the ICU in 2019. After matching, the outcomes were not significantly different between the two groups: ICU mortality was 5.2% in 2019 and 8.5% in 2020, p = 0.248, while intrahospital mortality was 10.9% in 2019 and 14.2% in 2020, p = 0.378. The median ICU length of stay was similar in 2019: 4 days (IQR 2–6) compared to 2020: 4 days (IQR 2–7), p = 0.196. The rate of ICU readmission was 15.6% in 2019 and 10.9% in 2020, p = 0.344. Conclusion In this retrospective single center study, mortality, ICU length of stay, and rate of ICU readmission did not differ significantly between patients admitted to the ICU during the implementation of hospital-wide COVID-19 contingency planning and patients admitted to the ICU before the pandemic.

Differential impact of on-site or telepharmacy in the intensive care unit: a controlled before–after study

2021 ◽  
Vol 33 (1) ◽  
Author(s):  
Joao Gabriel Rosa Ramos ◽  
Sandra Cristina Hernandes ◽  
Talita Teles Teixeira Pereira ◽  
Shana Oliveira ◽  
Denis de Melo Soares ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Phase 1 ◽  
Phase 2 ◽  
Differential Impact ◽  
Scarce Resources ◽  
Clinical Pharmacists ◽  
Versus Phase ◽  
Quasi Experimental ◽  
The Impact

Abstract Background Clinical pharmacists have an important role in the intensive care unit (ICU) team but are scarce resources. Our aim was to evaluate the impact of on-site pharmacists on medical prescriptions in the ICU. Methods This is a retrospective, quasi-experimental, controlled before-after study in two ICUs. Interventions by pharmacists were evaluated in phase 1 (February to November 2016) and phase 2 (February to May 2017) in ICU A (intervention) and ICU B (control). In phase 1, both ICUs had a telepharmacy service in which medical prescriptions were evaluated and interventions were made remotely. In phase 2, an on-site pharmacist was implemented in ICU A, but not in ICU B. We compared the number of interventions that were accepted in phase 1 versus phase 2. Results During the study period, 8797/9603 (91.6%) prescriptions were evaluated, and 935 (10.6%) needed intervention. In phase 2, there was an increase in the proportion of interventions that were accepted by the physician in comparison to phase 1 (93.9% versus 76.8%, P &lt; 0.001) in ICU A, but there was no change in ICU B (75.2% versus 73.9%, P = 0.845). Conclusion An on-site pharmacist in the ICU was associated with an increase in the proportion of interventions that were accepted by physicians.

Intra-aortic balloon pump as a bridge therapy to heart transplant in refractory heart failure

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
G.A.B Boros ◽  
V.S.C Bellini ◽  
D Fatori ◽  
C Bernoche ◽  
M.F Macatrao-Costa ◽  
...  
Keyword(s):  
Heart Failure ◽  
Intensive Care ◽  
Heart Transplant ◽  
Insertion Site ◽  
Laboratory Data ◽  
Central Venous Oxygen Saturation ◽  
Single Center ◽  
Intra Aortic Balloon Pump ◽  
The Impact ◽  
Bridge Therapy

Abstract Background The role of intra-aortic balloon pump (IABP) in advanced heart failure (HF) treatment is still under debate. Some heart transplant (HTx) candidates on the waiting list require mechanical support, and IABP may be the simple and most available device. Purpose Describe the impact of IABP treatment in advanced HF patients who underwent HTx. Methods We retrospectively analysis patients who underwent HTx from a single center intensive care unit (ICU), between 2009 and 2018, to evaluate the use of IABP as bridge therapy. Selection included decompensated chronic HF patients that required intensive care with optimized intravenous drugs before IABP placement. Exclusion criteria were acute myocardial infarction or cardiac surgery 90 days prior to admission, and implant of ventricular assist device before HTx. Results We included 134 HF patients with IABP therapy before HTx. Insertion site was exclusively femoral. Mean time of IABP onset to HTx were 26±21 days, and hospital admission to HTx 65±45 days. The main cardiomyopathy etiology was Chagas Disease (46%) and mean LVEF was 23±6% (TABLE 1). Clinical and laboratory data were compared before and 96 hours after IABP therapy. Mean central venous oxygen saturation (SvO2) increased from 49.7±14.6% to 67.4±11.3% (p&lt;0.001), creatinine decreased from 1.77±0.9 mg/dL to 1.40±0.6 mg/dL (p&lt;0.001), and urine output increased from 1552±886 mL/24h to 2189±1029 mL/24h (p&lt;0.001). These differences were sustained or improved until the day before HTx (FIGURE 1). After 96 hours dobutamine was maintained in 98% of patients, nitroprusside increased from 56% to 67%, milrinone decreased from 26% to 20%, and norepinephrine decreased from 18% to 3%. Significant IABP complications were few (5.2%; n=7: 3 infections, 2 major bleeding, 2 arterial injury). Conclusion In this single center ICU sample, IABP improved hemodynamic status and renal function in refractory HF patients waiting for HTx. IABP can be a reasonable, available and effective bridging therapy. Figure 1 Funding Acknowledgement Type of funding source: None

The presence of liver cirrhosis is a strong negative predictor of survival for patients admitted to the intensive care unit – Cirrhosis in intensive care patients

2021 ◽  
Author(s):  
Jörg Bojunga ◽  
Mireen Friedrich-Rust ◽  
Alica Kubesch ◽  
Kai Henrik Peiffer ◽  
Hannes Abramowski ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Liver Cirrhosis ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Intensive Care Treatment ◽  
Matched Cohort ◽  
Care Treatment ◽  
Cirrhotic Patients ◽  
The Impact ◽  
Cirrhotic Group

Abstract Background and Aims Liver cirrhosis is a systemic disease that substantially impacts the body’s physiology, especially in advanced stages. Accordingly, the outcome of patients with cirrhosis requiring intensive care treatment is poor. We aimed to analyze the impact of cirrhosis on mortality of intensive care unit (ICU) patients compared to other frequent chronic diseases and conditions. Methods In this retrospective study, patients admitted over three years to the ICU of the Department of Medicine of the University Hospital Frankfurt were included. Patients were matched for age, gender, pre-existing conditions, simplified acute physiology score (SAPS II), and therapeutic intervention scoring system (TISS). Results A total of 567 patients admitted to the ICU were included in the study; 99 (17.5 %) patients had liver cirrhosis. A total of 129 patients were included in the matched cohort for the sensitivity analysis. In-hospital mortality was higher in cirrhotic patients than non-cirrhotic patients (p < 0.0001) in the entire and matched cohort. Liver cirrhosis remained one of the strongest independent predictors of in-hospital mortality (entire cohort p = 0.001; matched cohort p = 0.03) along with dialysis and need for transfusion in the multivariate logistic regression analysis. Furthermore, in the cirrhotic group, the need for kidney replacement therapy (p < 0.001) and blood transfusion (p < 0.001) was significantly higher than in the non-cirrhotic group.  Conclusions In the presented study, liver cirrhosis was one of the strongest predictors of in-hospital mortality in patients needing intensive care treatment along with dialysis and the need for ventilation. Therefore, concerted efforts are needed to improve cirrhotic patients’ outcomes, prevent disease progression, and avoid complications with the need for ICU treatment in the early stages of the disease.

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