The burden of bacterial antimicrobial resistance in Croatia in 2019: a country-level systematic analysis.

AIM: To deliver the most wide-ranging set of antimicrobial resistance (AMR) burden estimates for Croatia to date. METHODS: A complex modeling approach with five broad modeling components was used to estimate the disease burden for 12 main infectious syndromes and one residual group, 23 pathogenic bacteria, and 88 bug-drug combinations. This was represented by two relevant counterfactual scenarios: deaths/disability-adjusted life years (DALYs) that are attributable to AMR considering a situation where drug-resistant infections are substituted with sensitive ones, and deaths/DALYs associated with AMR considering a scenario where people with drug-resistant infections would instead present without any infection. The 95% uncertainty intervals (UI) were based on 1000 posterior draws in each modeling step, reported at the 2.5% and 97.5% of the draws' distribution, while out-of-sample predictive validation was pursued for all the models. RESULTS: The total burden associated with AMR in Croatia was 2546 (95% UI 1558-3803) deaths and 46958 (28,033-71,628) DALYs, while the attributable burden was 614 (365-943) deaths and 11321 (6,544-17,809) DALYs. The highest number of deaths was established for bloodstream infections, followed by peritoneal and intra-abdominal infections and infections of the urinary tract. Five leading pathogenic bacterial agents were responsible for 1808 deaths associated with resistance: Escherichia coli, Staphylococcus aureus, Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa (ordered by the number of deaths). Trimethoprim/sulfamethoxazole-resistant E coli and methicillin-resistant S. aureus were dominant pathogen-drug combinations in regard to mortality associated with and attributable to AMR, respectively. CONCLUSION: We showed that AMR represented a substantial public health concern in Croatia, which reflects global trends; hence, our detailed country-level findings may fast-track the implementation of multipronged strategies tailored in accordance with leading pathogens and pathogen-drug combinations.

All-cause and cause-specific mortality among people with severe mental illness in Brazil's public health system, 2000-15: a retrospective study.

BACKGROUND: People with severe mental illness have a mortality rate higher than the general population, living an average of 10-20 years less. Most studies of mortality among people with severe mental illness have occurred in high-income countries (HICs). We aimed to estimate all-cause and cause-specific relative risk (RR) and excess mortality rate (EMR) in a nationwide cohort of inpatients with severe mental illness compared with inpatients without severe mental illness in a middle income country, Brazil. METHODS: This national retrospective cohort study included all patients hospitalised through the Brazilian Public Health System (Sistema Único de Saúde [SUS]-Brazil) between Jan 1, 2000, and April 21, 2015. Probabilistic and deterministic record linkages integrated data from the Hospital Information System (Sistema de informações Hospitalares) and the National Mortality System (Sistema de Informação sobre Mortalidade). Follow-up duration was measured from the date of the patients' first hospitalisation until their death, or until April 21, 2015. Severe mental illness was defined as schizophrenia, bipolar disorder, or depressive disorder by ICD-10 codes used for the admission. RR and EMR were calculated with 95% CIs, comparing mortality among patients with severe mental illness with those with other diagnoses for patients aged 15 years and older. We redistributed deaths using the Global Burden of Diseases, Injuries, and Risk Factors Study methodology if ill-defined causes of death were stated as an underlying cause. FINDINGS: From Jan 1, 2000, to April 21, 2015, 72 021 918 patients (31 510 035 [43·8%] recorded as male and 40 974 426 [56·9%] recorded as female; mean age 41·1 (SD 23·8) years) were admitted to hospital, with 749 720 patients (372 458 [49·7%] recorded as male and 378 670 [50·5%] as female) with severe mental illness. 5 102 055 patient deaths (2 862 383 [56·1%] recorded as male and 2 314 781 [45·4%] as female) and 67 485 deaths in patients with severe mental illness (39 099 [57·9%] recorded as male and 28 534 [42·3%] as female) were registered. The RR for all-cause mortality in patients with severe mental illness was 1·27 (95% CI 1·27-1·28) and the EMR was 2·52 (2·44-2·61) compared with non-psychiatric inpatients during the follow-up period. The all-cause RR was higher for females and for younger age groups; however, EMR was higher in those aged 30-59 years. The RR and EMR varied across the leading causes of death, sex, and age groups. We identified injuries (suicide, interpersonal violence, and road injuries) and cardiovascular disease (ischaemic heart disease) as having the highest EMR among those with severe mental illness. Data on ethnicity were not available. INTERPRETATION: In contrast to studies from HICs, inpatients with severe mental illness in Brazil had high RR for idiopathic epilepsy, tuberculosis, HIV, and acute hepatitis, and no significant difference in mortality from cancer compared with inpatients without severe mental illness. These identified causes should be addressed as a priority to maximise mortality prevention among people with severe mental illness, especially in a middle-income country like Brazil that has low investment in mental health. FUNDING: Bill and Melinda Gates Foundation, Fundação de Amparo a Pesquisa do Estado de Minas Gerais, FAPEMIG, and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brasil.

Accounting for misclassified and unknown cause of death data in vital registration systems for estimating trends in HIV mortality.

INTRODUCTION: Misclassification of HIV deaths can substantially diminish the usefulness of cause of death data for decision-making. In this study, we describe the methods developed by the Global Burden of Disease Study to account for the misclassified cause of death data from vital registration systems for estimating HIV mortality in 132 countries and territories. METHODS: The cause of death data were obtained from the World Health Organization Mortality Database and official country-specific mortality databases. We implemented two steps to adjust the raw cause of death data: (1) redistributing garbage codes to underlying causes of death, including HIV/AIDS by applying methods, such as analysis of multiple cause data and proportional redistribution, and (2) reassigning HIV deaths misclassified as other causes to HIV/AIDS by examining the age patterns of underlying causes in location and years with and without HIV epidemics. RESULTS: In 132 countries, during the period from 1990 to 2018, 1,848,761 deaths were reported as caused by HIV/AIDS. After garbage code redistribution in these 132 countries, this number increased to 4,165,015 deaths. An additional 1,944,291 deaths were added through correction of HIV deaths misclassified as other causes in 44 countries. The proportion of HIV deaths derived from garbage code redistribution decreased over time, from 0.4 in 1990 to 0.1 in 2018. The proportion of deaths derived from HIV misclassification correction peaked at 0.4 in 2006 and declined afterwards to 0.08 in 2018. The greatest contributors to garbage code redistribution were "immunodeficiency antibody" (ICD 9: 279-279.1; ICD 10: D80-D80.9) and "immunodeficiency other" (ICD 9: 279, 279.5-279.9; ICD 10: D83-D84.9, D89, D89.8-D89.9), which together contributed 77% of all redistributed deaths at their peak in 1995. Respiratory tuberculosis (ICD 9: 010-012.9; ICD 10: A10-A14, A15-A16.9) contributed the greatest proportion of all HIV misclassified deaths (25-62% per year) over the most years. CONCLUSIONS: Correcting for miscoding and misclassification of cause of death data can enhance the utility of the data for analyzing trends in HIV mortality and tracking progress toward the Sustainable Development Goal targets.

Public health utility of cause of death data: applying empirical algorithms to improve data quality.

BACKGROUND: Accurate, comprehensive, cause-specific mortality estimates are crucial for informing public health decision making worldwide. Incorrectly or vaguely assigned deaths, defined as garbage-coded deaths, mask the true cause distribution. The Global Burden of Disease (GBD) study has developed methods to create comparable, timely, cause-specific mortality estimates; an impactful data processing method is the reallocation of garbage-coded deaths to a plausible underlying cause of death. We identify the pattern of garbage-coded deaths in the world and present the methods used to determine their redistribution to generate more plausible cause of death assignments. METHODS: We describe the methods developed for the GBD 2019 study and subsequent iterations to redistribute garbage-coded deaths in vital registration data to plausible underlying causes. These methods include analysis of multiple cause data, negative correlation, impairment, and proportional redistribution. We classify garbage codes into classes according to the level of specificity of the reported cause of death (CoD) and capture trends in the global pattern of proportion of garbage-coded deaths, disaggregated by these classes, and the relationship between this proportion and the Socio-Demographic Index. We examine the relative importance of the top four garbage codes by age and sex and demonstrate the impact of redistribution on the annual GBD CoD rankings. RESULTS: The proportion of least-specific (class 1 and 2) garbage-coded deaths ranged from 3.7% of all vital registration deaths to 67.3% in 2015, and the age-standardized proportion had an overall negative association with the Socio-Demographic Index. When broken down by age and sex, the category for unspecified lower respiratory infections was responsible for nearly 30% of garbage-coded deaths in those under 1 year of age for both sexes, representing the largest proportion of garbage codes for that age group. We show how the cause distribution by number of deaths changes before and after redistribution for four countries: Brazil, the United States, Japan, and France, highlighting the necessity of accounting for garbage-coded deaths in the GBD. CONCLUSIONS: We provide a detailed description of redistribution methods developed for CoD data in the GBD; these methods represent an overall improvement in empiricism compared to past reliance on a priori knowledge.

"We just get paid for 12 hours a day, but we work 24": home health aide restrictions and work related stress.

BACKGROUND: Home-bound patients in New York State requiring long-term care services have seen significant changes to their benefits due to turmoil in the Managed Long Term Care (MLTC) market. While there has been research conducted regarding the effect of MLTC challenges on beneficiaries, the impact of MLTC regulatory changes on home health aides has not been explored. METHODS: Qualitative interviews were conducted with formal caregivers, defined as paid home health aides (HHAs) (n = 13) caring for patients in a home-based primary care program in the New York City metropolitan area. HHAs were asked about their satisfaction with the home based primary care program, their own job satisfaction, and whether HHA restrictions affect their work in any way. Interviews were audio-recorded, transcribed, and analyzed. RESULTS: Two main themes emerged: (1) Pay, benefits and hours worked and (2) Concerns about patient well-being afterhours. HHAs are working more hours than they are compensated for, experience wage stagnation and loss of benefits, and experience stress related to leaving frail clients alone after their shifts end. CONCLUSIONS: HHAs experience significant job-related stress when caring for frail elderly patients at home, which may have implications for both patient care and HHA turnover. As government bodies contemplate new policy directions for long-term care programs which rely on HHAs the impact of these changes on this vulnerable workforce must be considered.

Care Team Perspectives and Acceptance of Telehealth in Scaling a Home-Based Primary Care Program: Qualitative Study.

BACKGROUND: Novel and sustainable approaches to optimizing home-based primary care (HBPC) programs are needed to meet the medical needs of a growing number of homebound older adults in the United States. Telehealth may be a viable option for scaling HBPC programs. OBJECTIVE: The purpose of this qualitative study was to gain insight into the perspectives of HBPC staff regarding adopting telehealth technology to increase the reach of HBPC to more homebound patients. METHODS: We collected qualitative data from HBPC staff (ie, physicians, registered nurses, nurse practitioners, care managers, social workers, and medical coordinators) at a practice in the New York metropolitan area through 16 semistructured interviews and three focus groups. Data were analyzed thematically using the template analysis approach with Self-Determination Theory concepts (ie, relatedness, competence, and autonomy) as an analytical lens. RESULTS: Four broad themes-pros and cons of scaling, technology impact on staff autonomy, technology impact on competence in providing care, and technology impact on the patient-caregiver-provider relationship-and multiple second-level themes emerged from the analysis. Staff acknowledged the need to scale the program without diminishing effective patient-centered care. Participants perceived alerts generated from patients and caregivers using telehealth as potentially increasing burden and necessitating a rapid response from an already busy staff while increasing ambiguity. However, they also noted that telehealth could increase efficiency and enable more informed care provision. Telehealth could enhance the patient-provider relationship by enabling caregivers to be an integral part of the patient's care team. Staff members raised the concern that patients or caregivers might unnecessarily overutilize the technology, and that some home visits are more appropriate in person rather than via telehealth. CONCLUSIONS: These findings suggest the importance of considering the perspectives of medical professionals regarding telehealth adoption. A proactive approach exploring the benefits and concerns professionals perceive in the adoption of health technology within the HBPC program will hopefully facilitate the optimal integration of telehealth innovations.

Assessing feasibility of resources at health facilities in Uganda to diagnose pregnancy and neonatal outcomes.

BACKGROUND: Standardized case definitions for obstetric and neonatal outcomes were developed by the Global Alignment of Immunization Safety Assessment in Pregnancy (GAIA) project. These definitions can facilitate comparable assessment of maternal immunization safety surveillance and research. This study assessed the capabilities of health centers (HC) in Uganda to implement these definitions in a low income country, which has not been explored. METHODS: Healthcare practitioners at 15 government-accredited health centers and one government-funded district hospital in the Iganga-Mayuge Health and Demographic Surveillance Site (IMHDSS) in Uganda were interviewed about the facility's clinical diagnostic and laboratory capabilities. Five obstetric and five neonatal case definitions were evaluated. Definitions with the highest diagnostic certainty were designated as level 1, while definitions that decreased in certainty were designated as level 2 or 4. HCs were evaluated on diagnostic and laboratory capabilities to apply the GAIA definitions. RESULTS: Higher-level facilities in the IMHDSS demonstrated the ability to diagnose more specific levels of the GAIA obstetric and neonatal outcomes than lower-level facilities. Furthermore, for the neonatal outcome assessment, there was an increased ability to diagnose outcomes moving from GAIA level 1 to level 3. CONCLUSIONS: The ability of health centers to implement globally standardized definitions is promising for implementation of standardized data collection methods for global vaccine safety surveillance and research.