Longitudinal trends in screening males and females for intimate partner violence as part of a systemic multi-specialty health system intervention

Objective To assess intimate partner violence screening for males and females in a health system that underwent a systemic intervention to improve survivor identification and response. Electronic health record data from 13 clinics were accessed for February of 2017, 2018, and 2019 to calculate screening rates and positive screening rates for intimate partner violence by clinic and sex-race groups (n = 11,693 non-Hispanic White females; n = 4318 Other females; n = 9184 non-Hispanic White males; n = 3441 Other males). Linear mixed effects models were used to examine whether screening rates differed significantly over time and by sex-race group. Results Screening rates were 31% for the first 2 years and 16% for 2019. Screening rates varied greatly by clinic. Dermatology, psychiatry, and otolaryngology clinics had average or above screening rates all 3 years. Differences in screening rates across sex-race groups were minimal. Average positive screen rates were 1.3%, 0.4%, and 2.6% in 2017, 2018, and 2019, respectively, with psychiatry having the highest positive screen rate. Positive screen rates were highest for non-Hispanic White females (3.5%). Universal screening in this health system was not yielding survivors comparable to existing estimates among clinic-based populations. Other identification approaches require testing to effectively identify survivors within the health sector.

COVID-19 mortality across selected states in India: the role of age structure.

Background Mortality rates provide an opportunity to identify and act on the health system intervention for preventing deaths. Hence, it is essential to appreciate the influence of age structure while reporting mortality for a better summary of the magnitude of the epidemic. Objectives We described and compared the pattern of COVID-19 mortality standardized by age between selected states and India from January to November 2020. Methods We initially estimated the Indian population for 2020 using the decadal growth rate from the previous census (2011). This was followed by estimations of crude and age-adjusted mortality rate per million for India and the selected states. We used this information to perform indirect standardization and derive the age-standardized mortality rates for the states for comparison. In addition, we derived a ratio for age-standardized mortality to compare across age groups within the state. We extracted information regarding COVID-19 deaths from the Integrated Disease Surveillance Programme special surveillance portal up to November 16, 2020. Results The crude mortality rate of India stands at 88.9 per million population(118,883/1,337,328,910). Age-adjusted mortality rate (per million) was highest for Delhi (300.5) and lowest for Kerala (35.9).The age-standardized mortality rate (per million) for India is (<15 years=1.6, 15-29 years=6.3, 30-44 years=35.9, 45-59 years=198.8, 60-74 years=571.2, & ≥75 years=931.6). The ratios for age-standardized mortality increase proportionately from 45-59 years age group across all the states. Conclusion There is high COVID-19 mortality not only among the elderly ages, but we also identified heavy impact of COVID-19 on the working population. Therefore, we recommend further evaluation of age-adjusted mortality for all States and inclusion of variables like gender, socio-economic status for standardization while identifying at-risk populations and implementing priority public health actions. Keywords COVID-19, Mortality, Age Standardized Mortality Rate, Indirect Standardization.

Effect of maternal education and encouragement on newborn care utilization: a health system intervention

Background The objective of this health system interventional study was to determine the effect of delivering newborn-care-oriented education and encouragement on newborn care utilization. Methods This study was performed in the urban health centers of the catchment area of Tehran Defined Population, which covered 10 of the 22 municipality districts of Tehran. The two catchment areas included 10,000 families in the intervention and 20,000 families in the control areas. As many as 4837 newborns (intervention = 1544, control = 3293) were enrolled and followed until the end of the second month of life. The utilization of the three newborn care visits, as recommended by national guidelines, was compared among the intervention and control groups. Results As many as 877 (56.8%) newborns in the intervention group and 1214 (36.9%) in the control group received all their three newborn care visits. The mean number of newborn care visits was higher in the intervention group compared to the control group: 2.26 (0.99) versus 1.84 (1.07), p < 0.001. The number of newborns who did not attend any of their three newborn care visits was 143 (9.3%) in the intervention group and 468 (14.2%) in the control group. Conclusions The intervention improved newborn care utilization during the first 2 months after birth. It could be suggested that active follow-up be added to newborn care guidelines. Parents need to be informed of the necessity and benefits of newborn care and be encouraged to perform all three newborn care visits.

Effect of Maternal Education and Encouragement on Newborn Care Utilization: A Health System Intervention

Background: The objective of this health system interventional study was to determine the effect of delivering newborn-care-oriented education and encouragement to receive newborn care on newborn care utilization.Methods: This study was performed in the urban health centers of the catchment area of Tehran Defined Population, which covered 10 of the 22 municipality districts of Tehran. The two catchment areas included 10,000 families in the intervention and 20,000 families in the control areas. As many as 4837 newborns (intervention=1544, control=3293) were enrolled and followed until the end of the second month of life. The utilization of newborn care was compared among the intervention and control groups. Results: Almost 99.6% in the intervention group and 99.5% in the control group did their screening tests. The mean number of newborn care visits was higher in the intervention group compared to the control group: 2.26 (0.99) versus 1.84 (1.07), p<0.001. Newborns' attendance in the first newborn care visit was more among newborns who were born through normal birth compared to those who were born through the caesarian section: 51.2% CI [48.1, 54.3] versus 38.6%; 95% CI [37.1, 40.2], p<0.001. Conclusions: The intervention improved newborn care utilization during the first two months after birth. It could be suggested that active follow-up be added to newborn care guidelines, and parents be informed of the necessity and benefits of newborn care and be encouraged to perform all three newborn care visits.

Crossing borders: the PACK experience of spreading a complex health system intervention across low-income and middle-income countries

Developing a health system intervention that helps to improve primary care in a low-income and middle-income country (LMIC) is a considerable challenge; finding ways to spread that intervention to other LMICs is another. The Practical Approach to Care Kit (PACK) programme is a complex health system intervention that has been developed and adopted as policy in South Africa to improve and standardise primary care delivery. We have successfully spread PACK to several other LMICs, including Botswana, Brazil, Nigeria and Ethiopia. This paper describes our experiences of localising and implementing PACK in these countries, and our evolving mentorship model of localisation that entails our unit providing mentorship support to an in-country team to ensure that the programme is tailored to local resource constraints, burden of disease and on-the-ground realities. The iterative nature of the model’s development meant that with each country experience, we could refine both the mentorship package and the programme itself with lessons from one country applied to the next—a ‘learning health system’ with global reach. While not yet formally evaluated, we appear to have created a feasible model for taking our health system intervention across more borders.