METHODS: Data were derived from 360 inpatient medical records from six types C public and private hospitals in an Indonesian rural province. These data were accumulated from inpatient medical records from four major disciplines: medicine, surgery, obstetrics and gynecology, and pediatrics. The dependent variable was provider moral hazards, which included indicators of up-coding, readmission, and unnecessary admission. The independent variables are Physicians' characteristics (age, gender, and specialization), coders' characteristics (age, gender, education level, number of training, and length of service), and patients' characteristics (age, birth weight, length of stay, the discharge status, and the severity of patient's illness). We use logistic regression to investigate the determinants of moral hazard.
RESULTS: We found that the incidences of possible unnecessary admissions, up-coding, and readmissions were 17.8%, 11.9%, and 2.8%, respectively. Senior physicians, medical specialists, coders with shorter lengths of service, and patients with longer lengths of stay had a significant relationship with the incidence of moral hazard.
CONCLUSION: Unnecessary admission is the most common form of a provider's moral hazard. The characteristics of physicians and coders significantly contribute to the incidence of moral hazard. Hospitals should implement reward and punishment systems for doctors and coders in order to control moral hazards among the providers.
METHODS: Published literature on multicriteria decision analysis (MCDA) were studied and five sessions of expert group discussions were conducted to build the MAST framework and to review the evidence. The attributes identified and selected for analysis were efficacy (clinical efficacy, clinical endpoints), safety (drug interactions, serious side effects and documentation), drug applicability (drug strength/formulation, indications, dose frequency, side effects, food-drug interactions, and dose adjustments), and cost. The average weights assigned by the members for efficacy, safety, drug applicability and cost were 32.6%, 26.2%, 24.1%, and 17.1%, respectively. The utility values of the attributes were scored based on the published evidence or/and agreements during the group discussions. The attribute scores were added up to provide the total utility score.
RESULTS: Using the MAST, the six statins under review were successfully scored and ranked. Atorvastatin scored the highest total utility score (TUS) of 84.48, followed by simvastatin (83.11). Atorvastatin and simvastatin scored consistently high, even before drug costs were included. The low scores on the side effects for atorvastatin were compensated for by the higher scores on the clinical endpoints resulting in a higher TUS for atorvastatin. Fluvastatin recorded the lowest TUS.
CONCLUSION: The multiattribute scoring tool was successfully applied to organize decision variables in reviewing statins for the formulary. Based on the TUS, atorvastatin is recommended to remain in the formulary and be considered as first-line in the treatment of hypercholesterolemia.
OBJECTIVE: This study aims to determine the total cost of managing COVID-19 in-patients in Kuwait.
METHOD: A cross-sectional design was employed for this study. A total of 485 COVID-19 patients admitted to a general hospital responsible for COVID-19 cases management were randomly selected for this study from May 1st to September 31st, 2021. Data on sociodemographic information, length of stay (LOS), discharge status, and comorbidities were obtained from the patients' medical records. The data on costs in this study cover administration, utility, pharmacy, radiology, laboratory, nursing, and ICU costs. The unit cost per admission was calculated using a step-down costing method with three levels of cost centers. The unit cost was then multiplied by the individual patient's length of stay to determine the cost of care per patient per admission.
FINDINGS: The mean cost of COVID-19 in-patient care per admission was KD 2,216 (SD = 2,018), which is equivalent to USD 7,344 (SD = 6,688), with an average length of stay of 9.4 (SD = 8.5) days per admission. The total treatment costs for COVID-19 in-patients (n = 485) were estimated to be KD 1,074,644 (USD 3,561,585), with physician and nursing care costs constituting the largest share at 42.1%, amounting to KD 452,154 (USD 1,498,529). The second and third-largest costs were intensive care (20.6%) at KD 221,439 (USD 733,893) and laboratory costs (10.2%) at KD 109,264 (USD 362,123). The average cost for severe COVID-19 patients was KD 4,626 (USD 15,332), which is almost three times higher than non-severe patients of KD 1,544 (USD 5,117).
CONCLUSION: Managing COVID-19 cases comes with substantial costs. This cost information can assist hospital managers and policymakers in designing more efficient interventions, especially for managing high-risk groups.
OBJECTIVES: To assess the effectiveness of a home-based carer-assisted in comparison to hospital-based therapist-delivered therapy for community-dwelling stroke survivors.
METHODS: An assessor blinded randomised controlled trial was conducted on 91 stroke survivors (mean age 58.9±10.6 years, median time post-onset 13.0 months, 76.5% males) who had completed individual rehabilitation. The control group received hospital-based group therapy delivered by physiotherapists as out-patients and the test group was assigned to a home-based carer-assisted therapy. Targeted primary outcomes were physical functions (mobility, balance, lower limb strength and gait speed). A secondary outcome index was health-related quality of life. An intention-to-treat analysis was used to evaluate outcomes at week 12 of intervention.
RESULTS: Both therapy groups improved significantly in all the functional measures; mobility (p 0.05).
CONCLUSIONS: The home-based carer-assisted therapy is as effective as the hospital-based therapist-delivered training in improving post-stroke functions and quality of life.
METHODS: The main data source in this study was the MY-DRG Casemix database of a teaching hospital in Malaysia. Cases with principal and secondary diagnoses coded in the International Classification of Diseases version 10 (ICD-10) as J09, J10.0, J10.1, J10.8, J11.0, J11.1, J11.8, J12.8, and J12.9, which represent influenza and its complications, were included in the study. The direct cost of influenza at all severity levels was calculated from the casemix data and guided by a clinical pathway developed by experts. The effect of the variations in costs and incidence rate of influenza for both the casemix and clinical pathway costing approaches was assessed with sensitivity analysis.
RESULTS: A total of 1,599 inpatient and 407 outpatient influenza cases were identified from the MY-DRG Casemix database. Most hospitalised cases were aged <18 years (90.6%), while 77 cases (4.8%) involved older people. Mild, moderate, and severe cases comprised 56.5%, 35.1%, and 8.4% of cases, respectively. The estimated average annual direct costs for managing mild, moderate, and severe influenza were RM2,435 (USD579), RM6,504 (USD1,549), and RM13,282 (USD3,163), respectively. The estimated total annual economic burden of influenza on older adults in Malaysia was RM3.28 billion (USD782 million), which was equivalent to 10.7% of the Ministry of Health Malaysia budget for 2020. The sensitivity analysis indicated that the influenza incidence rate and cost of managing severe influenza were the most important factors influencing the total economic burden.
CONCLUSIONS: Overall, our results demonstrated that influenza imposes a substantial economic burden on the older Malaysian population. The high cost of influenza suggested that further efforts are required to implement a preventive programme, such as immunisation for older people, to reduce the disease and economic burdens.
METHODS: We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs).
FINDINGS: In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505).
INTERPRETATION: Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.
METHODS: In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced.
RESULTS: GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes.
CONCLUSIONS: GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.
METHODS: We used results from the Global Burden of Disease (GBD) 2017 study to report incidence, prevalence, years lived with disability, deaths, years of life lost and disability-adjusted life years for all locations in the GBD 2017 hierarchy from 1990 to 2017 for road injuries. Second, we measured mortality-to-incidence ratios by location. Third, we assessed the distribution of the natures of injury (eg, traumatic brain injury) that result from each road injury.
RESULTS: Globally, 1 243 068 (95% uncertainty interval 1 191 889 to 1 276 940) people died from road injuries in 2017 out of 54 192 330 (47 381 583 to 61 645 891) new cases of road injuries. Age-standardised incidence rates of road injuries increased between 1990 and 2017, while mortality rates decreased. Regionally, age-standardised mortality rates decreased in all but two regions, South Asia and Southern Latin America, where rates did not change significantly. Nine of 21 GBD regions experienced significant increases in age-standardised incidence rates, while 10 experienced significant decreases and two experienced no significant change.
CONCLUSIONS: While road injury mortality has improved in recent decades, there are worsening rates of incidence and significant geographical heterogeneity. These findings indicate that more research is needed to better understand how road injuries can be prevented.