Use of Technology to Improve the Adherence to Surgical Safety Checklists in the Operating Room.

BACKGROUND: Although checklists can improve safety in the operating room (OR), compliance with their use is variable. Use of a forcing function, a principle of human factors engineering, has not been reported earlier as a method of increasing checklist use. The authors conducted this study to determine the feasibility and effects of introducing a forcing function on OR surgical safety checklist implementation and adherence. METHODS: The authors developed and introduced the use of an electronic version of the surgical safety checklist on an Android application, provided on a personal device available in the OR. This application was linked by Bluetooth to electrocautery equipment, which could not be started before the electronic checklist was completed on the screen of the personal device. In the same OR, retrospective data from use of the traditional (paper-based) checklist were compared with data from the new electronic checklist for frequency of use, and completeness (percentage of all checklist items completed) at three stages of the surgical process-sign-in, time-out, and sign-out. RESULTS: The frequency of use was 100.0% for the electronic checklist, compared with 97.9% for the traditional checklist. The frequency of completeness was 27.1% for the traditional vs. 100.0% for the electronic (p < 0.001).The manual checklist's sign-out component was completed only 37.0% of the time. CONCLUSION: Although checklist use in some form was already high with the traditional checklist, completion rate was low and significantly increased with the use of the electronic checklist with a forcing function.

Risk Perception and Preventive Practice During the COVID-19 Pandemic in the General Population.

Background People's perceptions of the COVID-19 pandemic and its associated risk are very essential to prevent the spread of the infection. The awareness among individuals may contribute to preventing COVID-19 infections. Coronavirus disease is a serious public health issue. However, preventive practices toward COVID-19 are relatively unknown. The present study aims to survey the risk perception and preventive practice during the COVID-19 pandemic among the general population in Odisha. Method A cross-sectional online survey among 395 participants was conducted by adopting the convenience sampling technique. The tools used for the survey consist of three divisions: collection of sociodemographic data, assessment of risk perception toward COVID-19, and assessment of preventive practices during COVID-19 through an online survey method. Results The majority (83.29%) of the participants strongly agreed that social distancing is necessary to control the transmission of COVID-19, 65.82% strongly agreed that lockdown is relevant to control COVID-19 spread, 49.62% strongly agreed that wearing a mask protects from the infection, and 40.25% strongly agreed that they will be able to connect with healthcare professionals if they are infected with COVID-19 infection. The finding revealed that the highest number of participants are always practicing all the preventive measures such as maintaining hand hygiene (77.21%), wearing a mask (68.10%), avoiding shaking hands (87.59%), willingness to seek medical help (90.37%), avoiding going to the market or meeting friends (80.75%), discussing preventive measures related to COVID-19 with their family members (76.45%), and eating only homemade food (87.34%). Conclusion This study found that an average number of study participants who had the highest level of practice on preventive measures are those who had higher perceived risk among the general population. Expanding the knowledge regarding the infection and its ill effect on health through the proper channel can bring a drastic change in the attitude of the general public. As many people depend on television and social media for acquiring information about COVID-19, any information that reaches the public should be accurate and based on evidence. To avoid miscommunication and the further spread of COVID-19, health education and awareness have to be implemented to increase self-efficacy and risk identification among the general public, which eventually increases the practice of preventive measures.

Socioeconomic Burden of Critically Ill Patients: A Descriptive Study.

Background The cost of critical illness treatment is generally recognized as expensive and increasing in India. Critical illness of the individual will affect the socioeconomic status of the individual and the family. The direct and indirect costs of intensive care and its impact on the socioeconomic status of critically ill patients and their families need to be estimated. The present study was carried out to evaluate the socioeconomic burden of critically ill patients admitted to ICUs in Eastern India. Methods A descriptive survey was conducted to measure the socioeconomic burden. One hundred fifteen critically ill patients and their family members were conveniently selected for the study. Critically ill patients admitted to ICUs and those who were bedridden for more than seven days along with anyone the family member, i.e., spouse, father, or mother, were included in the study to estimate the impact of long-term illness on the care providers in the family. Socio-demographic and socioeconomic burdens were analyzed through the interview method. Results Half (49.6%) of the critically ill patients were heads of the family, and their employment is the primary source of income for the family members. Most (60.9%) of the patients belonged to lower socioeconomic status. Critically ill patients spend a maximum (38169.6±3996.2) amount for pharmaceutical expenses. Eventually, the family members accompanying patients lost maximum working days because of the long length of hospital stay. Below upper-lower (p=0.046) class socioeconomic family, age less than 40 (p=0.018) years, and those families depending (p=0.003) on patients' income significantly reported higher socioeconomic burden. Conclusions Critical care hospitalization of patients increases the socioeconomic burden on the whole family, especially in lower-middle-income countries like India. It soberly affects younger age group patients with low socioeconomic status and families depending on the patient's income during their man days.

Long COVID following Omicron wave in Eastern India-A retrospective cohort study.

Long coronavirus disease (COVID) or postacute sequelae of coronavirus disease of 2019 (COVID-19) is widely reported but the data of long COVID after infection with the Omicron variant is limited. This study was conducted to estimate the incidence, characteristics of symptoms, and predictors of long COVID among COVID-19 patients diagnosed during the Omicron wave in Eastern India. The cohort of COVID-19 patients included were adults (≥18 years) diagnosed as severe acute respiratory syndrome coronavirus 2 positive with Reverse Transcription Polymerase Chain Reaction. After 28 days of diagnosis; participants were followed up with a telephonic interview to capture data on sociodemographic, clinical history, anthropometry, substance use, COVID-19 vaccination status, acute COVID-19 symptoms, and long COVID symptoms. The long COVID symptoms were self-reported by the participants. Logistic regression was used to determine the predictors of long COVID. The median follow-up of participants was 73 days (Interquartile range; 67-83). The final analysis had 524 participants' data; among them 8.2% (95% Confidence Interval [CI]: 6%-10.9%) self-reported long COVID symptoms. Fatigue (34.9%) was the most common reported symptom followed by cough (27.9%). In multivariable logistic regression only two predictors were statistically significant-number of acute COVID-19 symptoms ≥ five (Adjusted odds ratio (aOR) = 2.95, 95% CI: 1.30-6.71) and past history of COVID-19 (aOR = 2.66, 95% CI: 1.14-6.22). The proportion of self-reported long COVID is considerably low among COVID-19 patients diagnosed during the Omicron wave in Eastern India when compared with estimates during Delta wave in the same setting.

Characteristics and predictors of Long COVID among diagnosed cases of COVID-19.

BACKGROUND: Long COVID or long-term symptoms after COVID-19 has the ability to affect health and quality of life. Knowledge about the burden and predictors could aid in their prevention and management. Most of the studies are from high-income countries and focus on severe acute COVID-19 cases. We did this study to estimate the incidence and identify the characteristics and predictors of Long COVID among our patients. METHODOLOGY: We recruited adult (≥18 years) patients who were diagnosed as Reverse Transcription Polymerase Chain Reaction (RTPCR) confirmed SARS-COV-2 infection and were either hospitalized or tested on outpatient basis. Eligible participants were followed up telephonically after four weeks and six months of diagnosis of SARS-COV-2 infection to collect data on sociodemographic, clinical history, vaccination history, Cycle threshold (Ct) values during diagnosis and other variables. Characteristics of Long COVID were elicited, and multivariable logistic regression was done to find the predictors of Long COVID. RESULTS: We have analyzed 487 and 371 individual data with a median follow-up of 44 days (Inter quartile range (IQR): 39,47) and 223 days (IQR:195,251), respectively. Overall, Long COVID was reported by 29.2% (95% Confidence interval (CI): 25.3%,33.4%) and 9.4% (95% CI: 6.7%,12.9%) of participants at four weeks and six months of follow-up, respectively. Incidence of Long COVID among patients with mild/moderate disease (n = 415) was 23.4% (95% CI: 19.5%,27.7%) as compared to 62.5% (95% CI: 50.7%,73%) in severe/critical cases(n = 72) at four weeks of follow-up. At six months, the incidence among mild/moderate (n = 319) was 7.2% (95% CI:4.6%,10.6%) as compared to 23.1% (95% CI:12.5%,36.8%) in severe/critical (n = 52). The most common Long COVID symptom was fatigue. Statistically significant predictors of Long COVID at four weeks of follow-up were-Pre-existing medical conditions (Adjusted Odds ratio (aOR) = 2.00, 95% CI: 1.16,3.44), having a higher number of symptoms during acute phase of COVID-19 disease (aOR = 11.24, 95% CI: 4.00,31.51), two doses of COVID-19 vaccination (aOR = 2.32, 95% CI: 1.17,4.58), the severity of illness (aOR = 5.71, 95% CI: 3.00,10.89) and being admitted to hospital (Odds ratio (OR) = 3.89, 95% CI: 2.49,6.08). CONCLUSION: A considerable proportion of COVID-19 cases reported Long COVID symptoms. More research is needed in Long COVID to objectively assess the symptoms and find the biological and radiological markers.

Home Care of Tracheostomized Chronically Critically Ill Patients: A Study of Caregivers' Burden and Comparison with the Burden of Palliative Care Patients in India.

Introduction: Chronically critically ill (CCI) patients often have high costs of care and poor outcomes. Disease management programs offering home care may reduce costs but need buy-in from informal caregivers. An understanding of caregiver burden in this population is lacking. We aimed to study the caregiver burden, its change over time, and factors affecting it, in post-ICU tracheostomized patients. We compared the caregiver burden among CCI carers to that of palliative caregivers. Materials and methods: Informal caregivers of thirty chronically critically ill tracheostomized patients (CGcci) were administered the Caregivers Burden Scale (CBS) tool at discharge, 2 and 4 weeks after discharge. A one-point assessment of burden was made in 30 caregivers of patients enrolled in Pain and Palliative care clinic (CGpc). Linear mixed models for repeated measures were used to analyze score of CGcci over time and compared to the burden in physical, psychologic, economic, time, and social domains between groups. Results: All 60 caregivers were young (33-35 years), predominantly male, and children of the patients. Both CGcci and CGpc had moderate burden score of 60.5 (14.7) vs 61.5 (13), respectively. Physical burden (11.5 vs 8) was greater in CGcci (p = 0.001) compared to psychologic domain (10 vs 12.5) in CGpc (p = 0.01). Burden score over all domains in CGcci decreased rapidly from 67.5 (8) to 55 (16.5) (p = 0.001) in the first month after discharge. Conclusion: Burden of care among caregivers of tracheostomized chronically critically ill patients is comparable to those of palliative caregivers and reduces significantly with time. CTRI: 2020/11/029443 (registered on: 27/11/2020). How to cite this article: Hansda U, Tripathy S, Sahoo AK, Panda I, Shetty AP, Mitra JK, et al. Home Care of Tracheostomized Chronically Critically Ill Patients: A Study of Caregivers' Burden and Comparison with the Burden of Palliative Care Patients in India. Indian J Crit Care Med 2022;26(5):579-583.

Spectrum of Bacterial Pathogens in Critical COVID-19 Patients Admitted in Intensive Care Units of a Tertiary Care Hospital During the First and Second Wave of the Pandemic.

OBJECTIVE: This study intends to compare the clinical characteristics and the prevalence and spectrum of bacterial pathogens in COVID-19 patients admitted to ICU during the first and second waves at a tertiary care, teaching and referral hospital of eastern India. METHOD: This is a hospital-based retrospective study which analysed demographic details, clinical profile and bacterial culture results of severe and critically ill COVID-19 patients admitted in intensive care units (ICU) during April -Oct 2020 (1st wave) and April -July 2021 (2nd wave). RESULT: The patients admitted during the 2nd wave were comparatively older and had multiple comorbidities compared to the 1st wave. (23.8%) (45/189) and 50% (173/346) of the COVID-19 patients admitted to ICU developed bacterial infection during the 1st and 2nd wave respectively. Overall, there was predominance of multidrug resistant Gram negative bacilli in both the waves. There was increased isolation of intrinsic colistin resistant microorganisms. CONCLUSION: Multidrug resistant Gram negative bacterial infections, remain a dreaded complication in severe and critically ill hospitalised COVID-19 patients requiring ICU care and high usage of colistin spirals the emergence and spread of pathogens intrinsically resistant to colistin.