scholarly journals Feasible Surgical Site Infection Surveillance in Resource-Limited Settings: A Pilot in Sierra Leone

2020 ◽  
Vol 41 (S1) ◽  
pp. s38-s38
Author(s):  
Matthew Westercamp ◽  
Aqueelah Barrie ◽  
Christiana Conteh ◽  
Danica Gomes ◽  
Hassan Benya ◽  
...  
Keyword(s):  
Data Collection ◽  
Cesarean Delivery ◽  
Sierra Leone ◽  
Clinical Decision Making ◽  
Case Finding ◽  
Surveillance Strategy ◽  
Case Definitions ◽  
Patient Interviews ◽  
Resource Limited ◽  
Infection Surveillance

Background: Surgical site infections (SSIs) are among the most common healthcare-associated infections (HAIs) in low- and middle-income countries (LMICs). SSI surveillance can be challenging and resource-intensive to implement in LMICs. To support feasible LMIC SSI surveillance, we piloted a multisite SSI surveillance protocol using simplified case definitions and methodology in Sierra Leone. Methods: A standardized evaluation tool was used to assess SSI surveillance knowledge, capacity, and attitudes at 5 proposed facilities. We used simplified case definitions restricted to objective, observable criteria (eg, wound purulence or intentional reopening) without considering the depth of infection. Surveillance was limited to post-cesarean delivery patients to control variability of patient-level infection risk and to decrease data collection requirements. Phone-based patient interviews at 30-days facilitated postdischarge case finding. Surveillance activities utilized existing clinical staff without monetary incentives. The Ministry of Health provided training and support for data management and analysis. Results: Three facilities were selected for initial implementation. At all facilities, administration and surgical staff described most, or all, infections as “preventable” and all considered SSIs an “important problem” at their facility. However, capacity assessments revealed limited staff availability to support surveillance activities, limited experience in systematic data collection, nonstandardized patient records as the basis for data collection, lack of unique and consistent patient identifiers to link patient encounters, and no quality-assured microbiology services. To limit system demands and to maximize usefulness, our surveillance data collection elements were built into a newly developed clinical surgical safety checklist that was designed to support surgeons’ clinical decision making. Following implementation and 2 months of SSI surveillance activities, 77% (392 of 509) of post-cesarean delivery patients had a checklist completed within the surveillance system. Only 145 of 392 patients (37%) under surveillance were contacted for final 30-day phone interview. Combined SSI rate for the initial 2-months of data collection in Sierra Leone was 8% (32 of 392) with 31% (10 of 32) identified through postdischarge case finding. Discussion: The surveillance strategy piloted in Sierra Leone represents a departure from established HAI strategies in the use of simplified case definitions and implementation methods that prioritize current feasibility in a resource-limited setting. However, our pilot implementation results suggest that even these simplified SSI surveillance methods may lack sustainability without additional resources, especially in postdischarge case finding. However, even limited phone-based patient interviews identified a substantial number of infections in this population. Although it was not addressed in this pilot study, feasible laboratory capacity building to support HAI surveillance efforts and promote appropriate treatment should be explored.Funding: NoneDisclosures: None

scholarly journals Supporting Healthcare-Associated Infection (HAI) Surveillance in Resource-Limited Settings: Lessons Learned, 2015–2019

2020 ◽  
Vol 41 (S1) ◽  
pp. s395-s396
Author(s):  
Matthew Westercamp ◽  
Paul Malpiedi ◽  
Amber Vasquez ◽  
Danica Gomes ◽  
Carmen Hazim ◽  
...  
Keyword(s):  
Data Collection ◽  
Sierra Leone ◽  
Clinical Care ◽  
Lessons Learned ◽  
External Support ◽  
Healthcare Associated Infection ◽  
Case Definitions ◽  
Resource Limited Settings ◽  
Resource Limited ◽  
Healthcare Associated

Background: Since 2015, the CDC has supported the development and implementation of healthcare-associated infection (HAI) surveillance in resource-limited settings through technical support of case definitions and methods that are feasible with existing surveillance capacity and integration with clinical care to maximize sustainability and data use for action. Methods: Surveillance initiatives included facility-level implementation programs in Kenya, Sierra Leone, Thailand, and Georgia; larger national or regional network-level projects in India and Vietnam were also supported. For assessment and planning, surveillance capacities were grouped into 3 domains: staff, informatics, and diagnostic capacities. Based on these capacities, simplified case definitions surveillance methodologies were devised to balance resources and effort with the anticipated value and use of findings. Results: There was broad understanding of the importance of HAI surveillance; however, the required resources and other challenges (eg, training, staffing, quality of available data) were underappreciated. Staff capacities were often influenced by a lack of dedicated surveillance staff and limited experience in systematic data collection and analysis. Informatics capacities were generally limited by the lack of digital data management, nonstandardized clinical data collection and storage, and the inability to assign and maintain unique patient identifiers. We found that capacity for diagnostics, a critical component of traditional HAI surveillance systems, was limited by its availability, frequency of use, and inconsistent rationale in clinical care. We found that successful surveillance strategies were generally simple, matched existing capacities, and targeted specific HAI priorities identified by clinical teams. For example, in Kenya and Sierra Leone, participating facilities established, with minimal external support, simplified SSI surveillance among post–caesarean-delivery patients. These initiatives improved integration of surveillance with clinical care through encouraging participation of the clinical team in surveillance and planning. Furthermore, these models directly linked surveillance activities to improved patient care (eg, combined clinical checklists with surveillance data collection forms). Discussion: In resource-limited settings, the local cost and effort required to establish and sustain the necessary infrastructure for HAI surveillance can be substantial. Establishing actionable and sustainable HAI surveillance can be achieved through simplifying HAI surveillance to match existing capacities and can result in valuable surveillance programs, even in very resource-limited settings.Funding: NoneDisclosures: None

scholarly journals Common data elements for predictors of pediatric sepsis: A framework to standardize data collection

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253051
Author(s):  
Alishah Mawji ◽  
Edmond Li ◽  
Arjun Chandna ◽  
Teresa Kortz ◽  
Samuel Akech ◽  
...  
Keyword(s):  
Data Collection ◽  
Clinical Decision Making ◽  
Research Community ◽  
Resource Limited Settings ◽  
Common Data Elements ◽  
Future Studies ◽  
Resource Limited ◽  
The Common ◽  
Pediatric Sepsis ◽  
Data Elements

Background Standardized collection of predictors of pediatric sepsis has enormous potential to increase data compatibility across research studies. The Pediatric Sepsis Predictor Standardization Working Group collaborated to define common data elements for pediatric sepsis predictors at the point of triage to serve as a standardized framework for data collection in resource-limited settings. Methods A preliminary list of pediatric sepsis predictor variables was compiled through a systematic literature review and examination of global guideline documents. A 5-round modified Delphi that involved independent voting and active group discussions was conducted to select, standardize, and prioritize predictors. Considerations included the perceived predictive value of the candidate predictor at the point of triage, intra- and inter-rater measurement reliability, and the amount of time and material resources required to reliably collect the predictor in resource-limited settings. Results We generated 116 common data elements for implementation in future studies. Each common data element includes a standardized prompt, suggested response values, and prioritization as tier 1 (essential), tier 2 (important), or tier 3 (exploratory). Branching logic was added to the predictors list to facilitate the design of efficient data collection methods, such as low-cost electronic case report forms on a mobile application. The set of common data elements are freely available on the Pediatric Sepsis CoLab Dataverse and a web-based feedback survey is available through the Pediatric Sepsis CoLab. Updated iterations will continuously be released based on feedback from the pediatric sepsis research community and emergence of new information. Conclusion Routine use of the common data elements in future studies can allow data sharing between studies and contribute to development of powerful risk prediction algorithms. These algorithms may then be used to support clinical decision making at triage in resource-limited settings. Continued collaboration, engagement, and feedback from the pediatric sepsis research community will be important to ensure the common data elements remain applicable across a broad range of geographical and sociocultural settings.

scholarly journals N-CDAD in Canada: Results of the Canadian Nosocomial Infection Surveillance Program 1997 N-CDAD Prevalence Surveillance Project

2001 ◽  
Vol 12 (2) ◽  
pp. 81-88 ◽  
Author(s):  
Meaghen Hyland ◽  
Marianna Ofner-Agostini ◽  
Mark Miller ◽  
Shirley Paton ◽  
Marie Gourdeau ◽  
...  
Keyword(s):  
Health Care ◽  
Nosocomial Infection ◽  
Toxin Production ◽  
Health Care Facilities ◽  
Surveillance Program ◽  
Prevention Measures ◽  
Case Definitions ◽  
Infection Surveillance ◽  
Positive Stool ◽  
The Impact

BACKGROUND:A 1996 preproject survey among Canadian Hospital Epidemiology Committee (CHEC) sites revealed variations in the prevention, detection, management and surveillance ofClostridium difficile-associated diarrhea (CDAD). Facilities wanted to establish national rates of nosocomially acquired CDAD (N-CDAD) to understand the impact of control or prevention measures, and the burden of N-CDAD on health care resources. The CHEC, in collaboration with the Laboratory Centre for Disease Control (Health Canada) and under the Canadian Nosocomial Infection Surveillance Program, undertook a prevalence surveillance project among selected hospitals throughout Canada.OBJECTIVE:To establish national prevalence rates of N-CDAD.METHODS:For six weeks in 1997, selected CHEC sites tested all diarrheal stools from inpatients for eitherC difficiletoxin orC difficilebacteria with evidence of toxin production. Questionnaires were completed for patients with positive stool assays who met the case definitions.RESULTS:Nineteen health care facilities in eight provinces participated in the project. The overall prevalence of N-CDAD was 13.0% (95% CI 9.5% to 16.5%). The mean number of N-CDAD cases were 66.3 cases/100,000 patient days (95% CI

scholarly journals Collecting quantitative experimental data from a non-WEIRD population: challenges and practical recommendations from a field experiment in rural Sierra Leone

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Hanna Luetke Lanfer ◽  
Doreen Reifegerste ◽  
Sorie Ibrahim Kargbo
Keyword(s):  
Data Collection ◽  
Field Experiment ◽  
Sierra Leone ◽  
Ethical Dilemmas ◽  
Research Process ◽  
Health Programs ◽  
Considerable Time ◽  
Collection Strategies ◽  
Practical Recommendations ◽  
Extensive Pilot

Abstract Objective Standardized pretest–posttest experimental designs with quantitative surveys are frequently applied to evaluate the effectiveness of health programs. However, this method is strongly informed by research on samples from Western, Educated, Industralized, Rich, and Democratic (WEIRD) societies and may not produce meaningful results in a distinct cultural, educational and socioeconomic context. Results This paper reports several methodological challenges encountered along the research process of collecting quantitative survey data (i.e., during recruitment, obtaining informed consent, matching pretest–posttest data and data collection) for a mixed-methods field experiment on domestic handwashing in Sierra Leone. Ethical dilemmas of certain research practices are pointed out and potential solutions or alternatives are recommended for each challenge. Analysis of these challenges highlights the importance of reflecting on the aptness of research methodologies for non-WEIRD samples. While this is not to say that quantitative surveys are not suitable in a non-WEIRD context, their employment require considerable time for extensive pilot testing, involving local interviewers and participants in designing research projects and the modification of data collection strategies.

scholarly journals COVID-19 control strategies and intervention effects in resource limited settings: A modeling study

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252570
Author(s):  
Kiran Raj Pandey ◽  
Anup Subedee ◽  
Bishesh Khanal ◽  
Bhagawan Koirala
Keyword(s):  
Control Strategies ◽  
Case Finding ◽  
Contact Tracing ◽  
Active Case Finding ◽  
Resource Limited Settings ◽  
Peak Demand ◽  
Active Case ◽  
Resource Limited ◽  
Base Scenario ◽  
Annual Mortality

Introduction Many countries with weaker health systems are struggling to put together a coherent strategy against the COVID-19 epidemic. We explored COVID-19 control strategies that could offer the greatest benefit in resource limited settings. Methods Using an age-structured SEIR model, we explored the effects of COVID-19 control interventions–a lockdown, physical distancing measures, and active case finding (testing and isolation, contact tracing and quarantine)–implemented individually and in combination to control a hypothetical COVID-19 epidemic in Kathmandu (population 2.6 million), Nepal. Results A month-long lockdown will delay peak demand for hospital beds by 36 days, as compared to a base scenario of no intervention (peak demand at 108 days (IQR 97-119); a 2 month long lockdown will delay it by 74 days, without any difference in annual mortality, or healthcare demand volume. Year-long physical distancing measures will reduce peak demand to 36% (IQR 23%-46%) and annual morality to 67% (IQR 48%-77%) of base scenario. Following a month long lockdown with ongoing physical distancing measures and an active case finding intervention that detects 5% of the daily infection burden could reduce projected morality and peak demand by more than 99%. Conclusion Limited resource settings are best served by a combination of early and aggressive case finding with ongoing physical distancing measures to control the COVID-19 epidemic. A lockdown may be helpful until combination interventions can be put in place but is unlikely to reduce annual mortality or healthcare demand.

#38: Bacteremia Analysis of Three Hospitals in Hispaniola Island

2021 ◽  
Vol 10 (Supplement_2) ◽  
pp. S19-S19
Author(s):  
Johanny Contreras ◽  
Karina Rivera ◽  
María Castillo ◽  
Genara Santana ◽  
María Dolores Gil ◽  
...  
Keyword(s):  
Lymphoblastic Leukemia ◽  
Mucosal Barrier ◽  
Infection Prevention And Control ◽  
Coagulase Negative Staphylococcus ◽  
Case Definitions ◽  
Culture Methods ◽  
Isolation And Identification ◽  
Infection Surveillance ◽  
Prophylactic Measures ◽  
Healthcare Associated

Abstract Background In October 2018, the Hispaniola Project was initiated to build local expertise in infection care and prevention at three pediatric oncology units (POUs) in Haiti and the Dominican Republic. Surveillance of healthcare-associated infections (HAI) was a central aim. Severe and prolonged neutropenia is a frequent risk factor for infections in oncology patients. Among HAIs, bacteremia is one of the most serious; bacteremia requires timely isolation and identification of the offending microorganism and the antimicrobial susceptibility. These diagnostic interventions allow informed therapeutic and prophylactic measures. Here, we report our experience in bacteremia in these 3 POUs. Methods We conducted prospective infection surveillance of all patients admitted to three POUs in Hispaniola Island. Blood culture methods followed standard national procedures. We used the 2018 US Centers for Disease Control National Healthcare Safety Network case definitions for primary laboratory-confirmed bloodstream infections (LCBI), and we categorized infections as healthcare-associated or present on admission (POA). We reviewed data collected from January 2019 to December 2020 and used descriptive statistics to report our results. Results Our review identified 66 LCBIs with an overall rate of 3.52 infections per 1000 patient-days. Of these, 40 (61%) were healthcare-associated, and 26 were POA. The majority (41, 62%) of patients were undergoing chemotherapy at the time of the infection, with induction being the most common phase (23). The most common oncologic diagnosis was acute lymphoblastic leukemia (43, 65%), followed by solid tumor (12, 18%). Fifty-three (80%) of the infections met the LCBI-1 criteria, with the other 13 categorized as LBCI-2. Of the 53 LCBI-1, 7 (13%) were considered related to mucosal barrier injury (MBI-LCBI 1 definition). The most commonly identified organisms were Klebsiella spp. (13, 19%) and coagulase-negative Staphylococcus (13, 19%). Antibiotic resistance was observed in many of the identified pathogens, with nearly half (25, 44%) of the 57 bacterial isolates having any resistance and a quarter (14, 25%) with resistance to multiple classes, including cephalosporins, fluoroquinolones, and aminoglycosides. Eleven (17%) patients were admitted to the Intensive Care Unit as a result of the LCBI. Thirteen deaths were recorded among the patients with LCBIs, with 6 (46%) associated with the HAI and 7 (54%) related to disease progression. Conclusions Our findings demonstrate that resistant pathogens were frequent among the LCBI isolates. Our preliminary results are guiding clinical management to be vigilant in our care of patients at high risk for bacteremia and poor clinical response by initiating more effective antimicrobials sooner. Importantly, reviewing reasons for antimicrobial resistance and implementing best antimicrobial use practices will protect our fragile antibiotic arsenal. Infection surveillance programs, such as ours, and other initiatives which promote infection prevention and control in POU will increase the quality of care for these vulnerable patients.

scholarly journals Design thinking during a health emergency: building a national data collection and reporting system

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Kara N. Durski ◽  
Shalini Singaravelu ◽  
Dhamari Naidoo ◽  
Mamoudou Harouna Djingarey ◽  
Ibrahima Soce Fall ◽  
...  
Keyword(s):  
Data Collection ◽  
Sierra Leone ◽  
Design Thinking ◽  
Reporting System ◽  
Laboratory Data ◽  
Health Information System ◽  
Stage Design ◽  
Strong Focus ◽  
Institute Of Design ◽  
The Many

Abstract Background Design thinking allows challenging problems to be redefined in order to identify alternative user-center strategies and solutions. To address the many challenges associated with collecting and reporting data during the 2014 Ebola outbreak in Guinea, Liberia and Sierra Leone, we used a design thinking approach to build the Global Ebola Laboratory Data collection and reporting system. Main text We used the five-stage Design Thinking model proposed by Hasso-Plattner Institute of Design at Stanford in Guinea, Liberia and Sierra Leone. This approach offers a flexible model which focuses on empathizing, defining, ideating, prototyping, and testing. A strong focus of the methodology includes end-users’ feedback from the beginning to the end of the process. This is an iterative methodology that continues to adapt according to the needs of the system. The stages do not need to be sequential and can be run in parallel, out of order, and repeated as necessary. Design thinking was used to develop a data collection and reporting system, which contains all laboratory data from the three countries during one of the most complicated multi-country outbreaks to date. The data collection and reporting system was used to orient the response interventions at the district, national, and international levels within the three countries including generating situation reports, monitoring the epidemiological and operational situations, providing forecasts of the epidemic, and supporting Ebola-related research and the Ebola National Survivors programs within each country. Conclusions Our study demonstrates the numerous benefits that arise when using a design thinking methodology during an outbreak to solve acute challenges within the national health information system and the authors recommend it’s use during future complex outbreaks.

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