Cost analysis of treating cardiovascular diseases in a super-specialty hospital

Cardiovascular care is expensive; hence, economic evaluation is required to estimate resources being consumed and to ensure their optimal utilization. There is dearth of data regarding cost analysis of treating various diseases including cardiac diseases from developing countries. The study aimed to analyze resource consumption in treating cardio-vascular disease patients in a super-specialty hospital. An observational and descriptive study was carried out from April 2017 to June 2018 in the Department of Cardiology, Cardio-Thoracic (CT) Centre of All India Institute of Medical Sciences, New Delhi, India. As per World Health Organization, common cardiovascular diseases i.e. Coronary Artery Disease (CAD), Rheumatic Heart Disease (RHD), Cardiomyopathy, Congenital heart diseases, Cardiac Arrhythmias etc. were considered for cost analysis. Medical records of 100 admitted patients (Ward & Cardiac Care Unit) of cardiovascular diseases were studied till discharge and number of patient records for a particular CVD was identified using prevalence-based ratio of admitted CVD patient data. Traditional Costing and Time Driven Activity Based Costing (TDABC) methods were used for cost computation. Per bed per day cost incurred by the hospital for admitted patients in Cardiac Care Unit, adult and pediatric cardiology ward was calculated to be Indian Rupee (INR) 28,144 (US$ 434), INR 22,210 (US$ 342) and INR 18,774 (US$ 289), respectively. Inpatient cost constituted almost 70% of the total cost and equipment cost accounted for more than 50% of the inpatient cost followed by human resource cost (28%). Per patient cost of treating any CVD was computed to be INR 2,47,822 (US $ 3842). Cost of treating Rheumatic Heart Disease was the highest among all CVDs followed by Cardiomyopathy and other CVDs. Cost of treating cardiovascular diseases in India is less than what has been reported in developed countries. Findings of this study would aid policy makers considering recent radical changes and massive policy reforms ushered in by the Government of India in healthcare delivery.

HUBUNGAN LAMA HARI RAWAT DENGAN TINGKAT KECEMASAN KELUARGA PASIEN DI RUANG INTENSIVE CARDIAC CARE UNIT

Selama pasien dirawat di ruang Intensive Cardiac Care Unit (ICCU), keluarga pasien mengalami kesulitan dan ketidakberdayaan. Bagi keluarga pasien, ruang rawat intensif merupakan tempat yang tidak menyenangkan. Keluarga masuk dalam kondisi yang tidak terduga dan dibutuhkan ketepatan keluarga dalam mengambil keputusan guna keberlangsungan hidup terkait kondisi pasien yang membutuhkan penanganan.Lama perawatan pasien di ruang ICCU sangat beragam. Lama rawat pasien ICCU berdampak langsung terhadap kualitas hidup pasien dan keluarga, risiko terjadinya di masa depan, dan besarnya pembiayaan dampak dari perawatan. Selama keluarga mendampingi perawatan pasien di ruang ICCU, keluarga akan mengalami berbagai reaksi emosional seperti kecemasan. Tujuan: Mengetahui hubungan lama hari rawat dengan tingkat kecemasan keluarga pasien di ruang ICCU. Metode: Korelasi dengan pendekatan cross sectional dengan sampel 42 responden di ruang ICCU, yang dipilih dengan menggunakan metode purposive sampling. Instrumen penelitian ini menggunakan kuesioner HARS. Data dianalisis dengan uji korelasi Spearman. Hasil: Lama hari rawat pasien rata-rata 3,14 hari. Kecemasan keluarga pasien ICCU paling banyak berada pada tingkat kecemasan berat (33,3%). Terdapat hubungan yang bermakna antara lama hari rawat dengan tingkat kecemasan keluarga pasien (p=0,0003) dengan keeratan hubungan yang sedang (r=0,532) di ruang ICCU. Diskusi: Semakin lama pasien dirawat di ruang ICCU maka semakin tinggi tingkat kecemasan yang dirasakan keluarga pasien karena kondisi pasien yang tidak stabil ataupun semakin parah. Kesimpulan: Keluarga pasien perlu diberikan informasi dan edukasi yang jelas terkait kondisi pasien dalam sehari atau saat ada perburukan kondisi.Kata kunci: kecemasan, keluarga, lama hari rawat, perawatan intensif, perawatan kritis. Correlation Between Length of Stay and Anxiety Levels of Patients’ Family in Intensive Cardiac Care Unit Room ABSTRACTWhile a patient is being treated in the Intensive Cardiac Care Unit (ICCU), the patient's family experiences difficulties and helplessness. For the patient's family, the intensive care unit is an unpleasant place. The family enters into unexpected conditions and is required to make proper decisions for survival related to patient conditions. The patient's length of stay in the ICCU room is very diverse. The length of stay of ICCU patients directly impacts patients' quality of life and their families, the risk of future incidence, and the extent of the treatment cost. While the family accompanies the patient treated in the ICCU room, the family will experience various emotional reactions such as anxiety. Objective: To reveal the correlation between length of stay and the anxiety levels of the patient’s family in the ICCU room. Methods: Correlation with cross-sectional approach with a sample of 42 respondents in the ICCU room, who were selected using a purposive sampling method. The research instrument used the HARS questionnaire. Data were analyzed using the Spearman correlation test. Results: The average length of the patient's stay was 3.14 days. Family anxiety of ICCU patients was mostly at the level of severe anxiety (33.3%). There was a significant correlation between length of stay and anxiety levels of the patient’s family (p=0.0003) with a moderate correlation coefficient (r=0.532) in the ICCU room. Discussion: The longer the patient is treated in the ICCU room, the higher the anxiety level felt by the patient’s family due to the patient's unstable or worsened condition. Conclusion: Clear information and education should be given to the patient's family regarding the patient's condition within one day or when the condition worsens.Keywords: anxiety, family, length of stay, intensive care, critical care

Diagnostic Performance of Serial High-Sensitivity Cardiac Troponin Measurements in the Emergency Setting

Serial high-sensitivity cardiac troponin (hsTn) testing in the emergency department (ED) and the intensive cardiac care unit may assist physicians in ruling out or ruling in acute myocardial infarction (MI). There are three major algorithms proposed for high-sensitivity cardiac troponin I (hsTnI) using serial measurements while incorporating absolute concentration changes for MI or death following ED presentation. We sought to determine the diagnostic estimates of these three algorithms and if one was superior in two different Canadian ED patient cohorts with serial hsTnI measurements. An undifferentiated ED population (Cohort-1) and an ED population with symptoms suggestive of acute coronary syndrome (ACS; Cohort-2) were clinically managed with non-hsTn testing with the hsTnI testing performed in real-time with physicians blinded to these results (i.e., hsTnI not reported). The three algorithms evaluated were the European Society of Cardiology (ESC), the High-STEACS pathway, and the COMPASS-MI algorithm. The diagnostic estimates were derived for each algorithm for the 30-day MI/death outcome for the rule-out and rule-in arm in each cohort and compared to proposed diagnostic benchmarks (i.e., sensitivity ≥ 99.0% and specificity ≥ 90.0%) with 95% confidence intervals (CI). In Cohort-1 (n = 2966 patients, 15.3% had outcome) and Cohort-2 (n = 935 patients, 15.6% had outcome), the algorithm that obtained the highest sensitivity (97.8%; 95% CI: 96.0–98.9 and 98.6%; 95% CI: 95.1–99.8, respectively) in both cohorts was COMPASS-MI. Only Cohort-2 with both the ESC and COMPASS-MI algorithms exceeded the specificity benchmark (97.0%; 95% CI: 95.5–98.0 and 96.7%; 95% CI: 95.2–97.8, respectively). Patient selection for serial hsTnI testing will affect specificity estimates, with no algorithm achieving a sensitivity ≥ 99% for 30-day MI or death.

Admission of COVID-19 Patients to the Cardiac Care Unit: Challenges and Solutions

The article's abstract is not available.

Cost analysis of treating cardiovascular diseases in a super-specialty hospital

Background Cardiovascular care is expensive; hence, economic evaluation is required to estimate resources being consumed and to ensure their optimal utilization. There is dearth of data regarding cost analysis of treating various diseases including cardiac diseases from developing countries. The study aimed to analyze resource consumption in treating cardio-vascular disease patients in a super-specialty hospital.Methods An observational and descriptive study was carried out from April 2017 to June 2018 in the Department of Cardiology, Cardio-Thoracic (CT) Centre of All India Institute of Medical Sciences, New Delhi, India. As per World Health Organization, common cardiac diseases i.e. Coronary Artery Disease (CAD), Rheumatic Heart Disease (RHD), Cardiomyopathy, Congenital heart diseases, Cardiac Arrhythmias etc. were considered for cost analysis. A total of 100 admitted patients (Ward & Cardiac Care Unit) of cardiovascular diseases were enrolled in the study using prevalence-based sampling. They were followed up till discharge. Traditional Costing and Time Driven Activity Based Costing (TDABC) methods were used for cost computation.Results Per bed per day cost incurred by the hospital for admitted patients in Cardiac Care Unit, adult and pediatric cardiology ward was calculated to be INR 28,144 (US$ 434), INR 22,210 (US$ 342) and INR 18,774 (US$ 289), respectively. Inpatient cost constituted almost 70% of the total cost and equipment cost accounted for more than 50% of the inpatient cost followed by human resource cost (28%). Per patient cost of treating any cardiovascular disease was computed to be INR 2,47,822 (US $ 3842).Conclusion Cost of treating Rheumatic Heart Disease is the highest among all CVDs followed by Cardiomyopathy and other CVDs. Cost of treating cardiovascular diseases in India is less than what has been reported in developed countries. Findings of this study would aid policy makers considering recent radical changes and massive policy reforms ushered in by the Government of India in healthcare delivery.

Causation of potential drug to drug interactions alerts, alert overrides, and adverse drug events

Background: Drug-drug interactions (DDIs) leading to adverse drug event (ADEs) are of special interest because they represent preventable medication errors. Preventable ADE can result in errors involving the manifestation of adverse patient outcomes. Given the high complexity of critically ill cardiac patients, it is important to learn how CDDSS affects outcomes in this population and the number of alerts that likely be safely suppressed. Purpose: Identify adverse DDIs that is clinically detected and review the appropriateness of the doctor’s actions to the potential DDIs (PDDIs) alert. Study Design: This is a prospective observational study conducted at critical cardiac care unit (CCU) in a selected tertiary cardiac center for a duration of six months. Methods: Physicians treating critically ill cardiac patients were presented with PDDIs data which were acquired from two commercially available CDDSS. The relationship between the decision to prescribe and factors hypothesized to affect physicians' decisions were examined. Results: Evaluation of 709 patient medication profiles were conducted, resulting in 521 assessed patient profiles having had one or more PDDIs with 87% of them were influenced by polypharmacy. Ninety-one patients (17.5%) were associated with one or more adverse DDIs. Of the total 3284 potential DDIs alerts, 95.5% of the alerts were overridden. Preventable ADE as an outcome of inappropriate override have resulted 83.1 %. (236/284) of adverse DDIs. Whereas, appropriate overrides as an outcome of clinically irrelevant ADE were 16.9 % (48/284). Conclusion: Poor preventive actions taken by the doctors caused drug related harm to the patients despite having CDDSS in place. This suggests that CDDSS is an important application to minimize the harm associated with adverse DDIs by alerting physicians of potentially unsafe situations.

Clinical and echocardiographic predictors of delirium in acute cardiac care unit after transfemoral aortic valve implantation

Funding Acknowledgements Type of funding sources: None. Background. Delirium is frequent in patients admitted to critical care units. Its incidence after transcatheter aortic valve implantation (TAVI) is up to 30%. Clinical and demographic factors have been related to delirium, but echocardiographic parameters have not been evaluated. Purpose. The aim of this study was to assess clinical and echocardiographic predictors of delirium in patients admitted to an acute cardiac care unit (ACCU) after transfemoral TAVI. Methods. 501 patients admitted to ACCU after TAVI were included. Delirium was evaluated by Confusion Assessment Method. Clinical cardiovascular and geriatric conditions were assessed, as well as echocardiographic parameters. Results. The incidence of delirium was 22% (110 patients). Delirium was associated with age (83.8 ± 4.6 vs 82.6 ± 6.1 years, p = 0.026), dyslipidaemia (50.0% vs 61.4%, p = 0.032), prior peripheral arterial disease (11.9% vs 5.4%, p = 0.017) and cognitive impairment (10.0% vs 1.8%, p < 0.001). There was no relationship to gender, other cardiovascular risk factors or geriatric conditions. Table shows echocardiographic parameters at baseline and after TAVI, with no statistical association with delirium. Conclusion. Delirium is a common complication after TAVI in ACCU. Age, the absence of dyslipidaemia, or the presence of cognitive impairment or prior peripheral arterial disease are clinical predictors of delirium. There are not echocardiographic predictors of delirium. Echocardiographic parametersWithout delirium(n = 391)With delirium(n = 110)p valueBaseline echocardiographic parametersLeft ventricular ejection fraction (%)57.7 ± 13.457.5 ± 14.10.912Mitral regurgitation (moderate to severe)106 (27.1)34 (30.9)0.433Pulmonary hypertension168 (43.0)53 (49.1)0.258Aortic regurgitation (moderate to severe)74 (18.9)21 (19.1)0.969Peak aortic gradient (mmHg)78.7 ± 25.278.5 ± 23.30.935Mean aortic gradient (mmHg)47.1 ± 16.146.7 ± 14.80.838Aortic valvular area (cm2)0.6 ± 0.20.6 ± 0.20.589Aortic annulus diameter (mm)22.5 ± 2.722.4 ± 2.50.615After TAVI echocardiographic parametersAortic regurgitation (moderate to severe)36 (9.3)11 (10.0)0.813Peak aortic gradient (mmHg)17.6 ± 9.617.7 ± 8.30.916Mean aortic gradient (mmHg)8.9 ± 5.49.3 ± 4.90.481Aortic valvular area (cm2)2.0 ± 0.62.2 ± 0.60.478Values are mean ± standard deviation, or n (%).