Linking individual-level data on diagnoses and dispensing for research on antibiotic use: Evaluation of a novel data source from English secondary care

People’s movement trace harvested from mobile phone signals has become an important new data source for studying human behavior and related socioeconomic topics in social science. With growing concern about privacy leakage of big data, mobile phone data holders now tend to provide aggregate-level mobility data instead of individual-level data. However, most algorithms for measuring mobility are based on individual-level data—how the existing mobility algorithms can be properly transformed to apply on aggregate-level data remains undiscussed. This paper explores the transformation of individual data-based mobility metrics to fit with grid-aggregate data. Fifteen candidate metrics measuring five indicators of mobility are proposed and the most suitable one for each indicator is selected. Future research about aggregate-level mobility data may refer to our analysis to assist in the selection of suitable mobility metrics.

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The value of the Skåne Health-care Register: Prospectively collected individual-level data for population-based studies

Scandinavian Journal of Public Health ◽

10.1177/1403494819868042 ◽

2019 ◽

Vol 48 (1) ◽

pp. 56-63 ◽

Cited By ~ 1

Author(s):

Sofia Löfvendahl ◽

Maria E.C. Schelin ◽

Anna Jöud

Keyword(s):

Health Care ◽

Population Based ◽

Individual Level ◽

Levels Of Care ◽

Cohort Design ◽

Level Data ◽

Bibliographic Search ◽

Data Source ◽

Clinical Changes ◽

Study Designs

Aims: This study aimed to examine the population-based Skåne Health-care Register (SHR) regarding feasibility for scientific research and also strengths and weaknesses. Methods: To analyse the feasibility of the SHR, we performed a bibliographic search for peer-reviewed articles based on SHR data from 2000 to 2018. To analyse strengths and weaknesses, we used original SHR data about coverage and validity. Results: We identified 58 articles based on SHR data, covering different study designs and disorders. Most studies focused on musculoskeletal disorders with a cohort design. The majority of all consultations recorded in the SHR have an assigned diagnosis. However, this differs between the levels of care and between types of consultation. For inpatient care, the proportion of consultations with an assigned diagnosis was close to 100% between 1998 and 2017. The proportion of consultations with an assigned diagnosis was lowest within primary care, although the proportion markedly increased in 2004 when the prerequisite for consultation reimbursement was linked to the requirement for an assigned diagnosis. Limitations are that the SHR does not cover health-care provided within nursing homes and equivalent facilities or treatments received by the population of Skåne outside the region. Conclusions: The SHR may be used as a reliable data source for analyses of clinical changes and improvements. Extended use of the SHR in a research context may highlight important shortcomings within the register and thus serve as a way of indirect quality control. To enhance the use of the SHR further, better harmonisation between registers, within and outside of the region and internationally, is of crucial importance.

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Islam and Female Education: Evidence from Individual-level Data

SSRN Electronic Journal ◽

10.2139/ssrn.366340 ◽

2003 ◽

Author(s):

Mandana Hajj ◽

Ugo G. Panizza

Keyword(s):

Female Education ◽

Individual Level ◽

Level Data

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Clinical Team Distribution and Antibiotic Use Patterns at a Tertiary-Care Academic Medical Center

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.695 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s168-s169

Author(s):

Rebecca Choudhury ◽

Ronald Beaulieu ◽

Thomas Talbot ◽

George Nelson

Keyword(s):

Medical Center ◽

Academic Medical Center ◽

Tertiary Care ◽

Antibiotic Use ◽

Care Hospital ◽

Hospital Units ◽

Antibiotic Utilization ◽

Academic Medical ◽

Level Data ◽

Utilization Data

Background: As more US hospitals report antibiotic utilization to the CDC, standardized antimicrobial administration ratios (SAARs) derived from patient care unit-based antibiotic utilization data will increasingly be used to guide local antibiotic stewardship interventions. Location-based antibiotic utilization surveillance data are often utilized given the relative ease of ascertainment. However, aggregating antibiotic use data on a unit basis may have variable effects depending on the number of clinical teams providing care. In this study, we examined antibiotic utilization from units at a tertiary-care hospital to illustrate the potential challenges of using unit-based antibiotic utilization to change individual prescribing. Methods: We used inpatient pharmacy antibiotic use administration records at an adult tertiary-care academic medical center over a 6-month period from January 2019 through June 2019 to describe the geographic footprints and AU of medical, surgical, and critical care teams. All teams accounting for at least 1 patient day present on each unit during the study period were included in the analysis, as were all teams prescribing at least 1 antibiotic day of therapy (DOT). Results: The study population consisted of 24 units: 6 ICUs (25%) and 18 non-ICUs (75%). Over the study period, the average numbers of teams caring for patients in ICU and non-ICU wards were 10.2 (range, 3.2–16.9) and 13.7 (range, 10.4–18.9), respectively. Units were divided into 3 categories by the number of teams, accounting for ≥70% of total patient days present (Fig. 1): “homogenous” (≤3), “pauciteam” (4–7 teams), and “heterogeneous” (>7 teams). In total, 12 (50%) units were “pauciteam”; 7 (29%) were “homogeneous”; and 5 (21%) were “heterogeneous.” Units could also be classified as “homogenous,” “pauciteam,” or “heterogeneous” based on team-level antibiotic utilization or DOT for specific antibiotics. Different patterns emerged based on antibiotic restriction status. Classifying units based on vancomycin DOT (unrestricted) exhibited fewer “heterogeneous” units, whereas using meropenem DOT (restricted) revealed no “heterogeneous” units. Furthermore, the average number of units where individual clinical teams prescribed an antibiotic varied widely (range, 1.4–12.3 units per team). Conclusions: Unit-based antibiotic utilization data may encounter limitations in affecting prescriber behavior, particularly on units where a large number of clinical teams contribute to antibiotic utilization. Additionally, some services prescribing antibiotics across many hospital units may be minimally influenced by unit-level data. Team-based antibiotic utilization may allow for a more targeted metric to drive individual team prescribing.Funding: NoneDisclosures: None

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Review of Associations between Built Environment Characteristics and Severe Acute Respiratory Syndrome Coronavirus 2 Infection Risk

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18147561 ◽

2021 ◽

Vol 18 (14) ◽

pp. 7561

Author(s):

Jingjing Wang ◽

Xueying Wu ◽

Ruoyu Wang ◽

Dongsheng He ◽

Dongying Li ◽

...

Keyword(s):

Severe Acute Respiratory Syndrome ◽

Built Environment ◽

Longitudinal Research ◽

Empirical Studies ◽

Infection Risk ◽

Design Guidelines ◽

Individual Level ◽

Transit Accessibility ◽

Level Data ◽

Transmission Pathways

The coronavirus disease 2019 pandemic has stimulated intensive research interest in its transmission pathways and infection factors, e.g., socioeconomic and demographic characteristics, climatology, baseline health conditions or pre-existing diseases, and government policies. Meanwhile, some empirical studies suggested that built environment attributes may be associated with the transmission mechanism and infection risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, no review has been conducted to explore the effect of built environment characteristics on the infection risk. This research gap prevents government officials and urban planners from creating effective urban design guidelines to contain SARS-CoV-2 infections and face future pandemic challenges. This review summarizes evidence from 25 empirical studies and provides an overview of the effect of built environment on SARS-CoV-2 infection risk. Virus infection risk was positively associated with the density of commercial facilities, roads, and schools and with public transit accessibility, whereas it was negatively associated with the availability of green spaces. This review recommends several directions for future studies, namely using longitudinal research design and individual-level data, considering multilevel factors and extending to diversified geographic areas.

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The Role of Snack Choices, Body Weight Stereotypes and Smoking Behavior in Assessing Risk Factors for Adolescent Overweight and Obesity

Foods ◽

10.3390/foods10030557 ◽

2021 ◽

Vol 10 (3) ◽

pp. 557

Author(s):

Elena Raptou

Keyword(s):

Body Weight ◽

Smoking Behavior ◽

Negative Influence ◽

Overweight And Obesity ◽

Individual Level ◽

Level Data ◽

Prevention Interventions ◽

Frequent Consumption ◽

Adolescent Overweight ◽

Relationship Of

This study investigated the relationship of behavioral factors, such as snack choices, obesity stereotypes and smoking with adolescents’ body weight. Individual-level data for 1254 Greek youths were selected via a formal questionnaire. Snack choices seem to be gender specific with girls showing a stronger preference for healthier snacks. Frequent consumption of high-calorie and more filling snacks was found to increase Body Mass Index (BMI) in both genders. Fruit/vegetable snacks were associated with lower body weight in females, whereas cereal/nut snacks had a negative influence in males’ BMI. The majority of participants expressed anti-fat attitudes and more boys than girls assigned positive attributes to lean peers. The endorsement of the thin-ideal was positively associated with the BMI of both adolescent boys and girls. This study also revealed that neglecting potential endogeneity issues can lead to biased estimates of smoking. Gender may be a crucial moderator of smoking–BMI relationships. Male smokers presented a higher obesity risk, whereas female smokers were more likely to be underweight. Nutrition professionals should pay attention to increase the acceptance of healthy snack options. Gender differences in the influence of weight stereotypes and smoking on BMI should be considered in order to enhance the efficacy of obesity prevention interventions.

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When Marriage Gets Hard: Intra-Coalition Conflict and Electoral Accountability

Comparative Political Studies ◽

10.1177/00104140211024307 ◽

2021 ◽

pp. 001041402110243

Author(s):

Carolina Plescia ◽

Sylvia Kritzinger

Keyword(s):

Economic Performance ◽

Political Representation ◽

Economic Evaluations ◽

Responsibility Attribution ◽

Electoral Accountability ◽

Individual Level ◽

Coalition Governments ◽

Level Data ◽

European Election ◽

Election Studies

Combining individual-level with event-level data across 25 European countries and three sets of European Election Studies, this study examines the effect of conflict between parties in coalition government on electoral accountability and responsibility attribution. We find that conflict increases punishment for poor economic performance precisely because it helps clarify to voters parties’ actions and responsibilities while in office. The results indicate that under conditions of conflict, the punishment is equal for all coalition partners when they share responsibility for poor economic performance. When there is no conflict within a government, the effect of poor economic evaluations on vote choice is rather low, with slightly more punishment targeted to the prime minister’s party. These findings have important implications for our understanding of electoral accountability and political representation in coalition governments.

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Missing Data in Research on Youth and Family Programs

Psychological Reports ◽

10.1177/00332941211026851 ◽

2021 ◽

pp. 003329412110268

Author(s):

Jaime Ballard ◽

Adeya Richmond ◽

Suzanne van den Hoogenhof ◽

Lynne Borden ◽

Daniel Francis Perkins

Keyword(s):

Missing Data ◽

Statistical Methods ◽

Self Report ◽

Program Participation ◽

Multilevel Data ◽

Individual Level ◽

Level Data ◽

Before And After ◽

Post Test ◽

The Individual

Background Multilevel data can be missing at the individual level or at a nested level, such as family, classroom, or program site. Increased knowledge of higher-level missing data is necessary to develop evaluation design and statistical methods to address it. Methods Participants included 9,514 individuals participating in 47 youth and family programs nationwide who completed multiple self-report measures before and after program participation. Data were marked as missing or not missing at the item, scale, and wave levels for both individuals and program sites. Results Site-level missing data represented a substantial portion of missing data, ranging from 0–46% of missing data at pre-test and 35–71% of missing data at post-test. Youth were the most likely to be missing data, although site-level data did not differ by the age of participants served. In this dataset youth had the most surveys to complete, so their missing data could be due to survey fatigue. Conclusions Much of the missing data for individuals can be explained by the site not administering those questions or scales. These results suggest a need for statistical methods that account for site-level missing data, and for research design methods to reduce the prevalence of site-level missing data or reduce its impact. Researchers can generate buy-in with sites during the community collaboration stage, assessing problematic items for revision or removal and need for ongoing site support, particularly at post-test. We recommend that researchers conducting multilevel data report the amount and mechanism of missing data at each level.

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How does area-level deprivation depress an individual’s self-rated health and life satisfaction? Evidence from a nationwide population-based survey in Japan

BMC Public Health ◽

10.1186/s12889-021-10578-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Takashi Oshio ◽

Hiromi Kimura ◽

Toshimi Nishizaki ◽

Takashi Omori

Keyword(s):

Life Satisfaction ◽

Health Behavior ◽

Well Being ◽

Population Based ◽

Internet Survey ◽

Subjective Well Being ◽

Individual Level ◽

Self Rated Health ◽

Level Data ◽

The Impact

Abstract Background Area-level deprivation is well known to have an adverse impact on mortality, morbidity, or other specific health outcomes. This study examined how area-level deprivation may affect self-rated health (SRH) and life satisfaction (LS), an issue that is largely understudied. Methods We used individual-level data obtained from a nationwide population-based internet survey conducted between 2019 and 2020, as well as municipality-level data obtained from a Japanese government database (N = 12,461 living in 366 municipalities). We developed multilevel regression models to explain an individual’s SRH and LS scores using four alternative measures of municipality-level deprivation, controlling for individual-level deprivation and covariates. We also examined how health behavior and interactions with others mediated the impact of area-level deprivation on SRH and LS. Results Participants in highly deprived municipalities tended to report poorer SRH and lower LS. For example, when living in municipalities falling in the highest tertile of municipality-level deprivation as measured by the z-scoring method, SRH and LS scores worsened by a standard deviation of 0.05 (p < 0.05) when compared with those living in municipalities falling in the lowest tertile of deprivation. In addition, health behavior mediated between 17.6 and 33.1% of the impact of municipality-level deprivation on SRH and LS, depending on model specifications. Conclusion Results showed that area-level deprivation modestly decreased an individual’s general health conditions and subjective well-being, underscoring the need for public health policies to improve area-level socioeconomic conditions.

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Variations in reproductive events across life: a pooled analysis of data from 505 147 women across 10 countries

Human Reproduction ◽

10.1093/humrep/dez015 ◽

2019 ◽

Vol 34 (5) ◽

pp. 881-893 ◽

Cited By ~ 11

Author(s):

Keyword(s):

Age At Menarche ◽

Age At First Birth ◽

First Birth ◽

Natural Menopause ◽

Individual Level ◽

Level Data ◽

Education Levels ◽

Reproductive Events ◽

Racial Ethnic ◽

Reproductive Indices

Abstract STUDY QUESTION How has the timing of women’s reproductive events (including ages at menarche, first birth, and natural menopause, and the number of children) changed across birth years, racial/ethnic groups and educational levels? SUMMARY ANSWER Women who were born in recent generations (1970–84 vs before 1930) or those who with higher education levels had menarche a year earlier, experienced a higher prevalence of nulliparity and had their first child at a later age. WHAT IS KNOWN ALREADY The timing of key reproductive events, such as menarche and menopause, is not only indicative of current health status but is linked to the risk of adverse hormone-related health outcomes in later life. Variations of reproductive indices across different birth years, race/ethnicity and socioeconomic positions have not been described comprehensively. STUDY DESIGN, SIZE, DURATION Individual-level data from 23 observational studies that contributed to the International Collaboration for a Life Course Approach to Reproductive Health and Chronic Disease Events (InterLACE) consortium were included. PARTICIPANTS/MATERIALS, SETTING, METHODS Altogether 505 147 women were included. Overall estimates for reproductive indices were obtained using a two-stage process: individual-level data from each study were analysed separately using generalised linear models. These estimates were then combined using random-effects meta-analyses. MAIN RESULTS AND THE ROLE OF CHANCE Mean ages were 12.9 years at menarche, 25.7 years at first birth, and 50.5 years at natural menopause, with significant between-study heterogeneity (I2 > 99%). A linear trend was observed across birth year for mean age at menarche, with women born from 1970 to 1984 having menarche one year earlier (12.6 years) than women born before 1930 (13.5 years) (P for trend = 0.0014). The prevalence of nulliparity rose progressively from 14% of women born from 1940–49 to 22% of women born 1970–84 (P = 0.003); similarly, the mean age at first birth rose from 24.8 to 27.3 years (P = 0.0016). Women with higher education levels had fewer children, later first birth, and later menopause than women with lower education levels. After adjusting for birth year and education level, substantial variation was present for all reproductive events across racial/ethnic/regional groups (all P values < 0.005). LIMITATIONS, REASONS FOR CAUTION Variations of study design, data collection methods, and sample selection across studies, as well as retrospectively reported age at menarche, age at first birth may cause some bias. WIDER IMPLICATIONS OF THE FINDINGS This global consortium study found robust evidence on variations in reproductive indices for women born in the 20th century that appear to have both biological and social origins. STUDY FUNDING/COMPETING INTEREST(S) InterLACE project is funded by the Australian National Health and Medical Research Council project grant (APP1027196). GDM is supported by the Australian National Health and Medical Research Council Principal Research Fellowship (APP1121844).

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