Person-level Data Research Articles

Disorders of the eye, ear, skin, and nervous system in women with Turner syndrome -a nationwide cohort study.

The literature about eye, ear, nose, skin, and nervous system disorders in women with Turner syndrome is equivocal. Impaired vision and hearing in women with Turner syndrome have been described, and case reports of Turner syndrome girls suffering from epilepsy have been published, but no large population-based-studies have explored the occurrence of any of these disorders. We aimed to investigate the risk of admission with disorders related to the eye, ear, nose, skin, and nervous system, compared with background females, and the impact of hormone replacement therapy on these conditions. 1,156 females with TS diagnosed during 1960-2014 were identified using the Danish Cytogenetic Central Registry and linked with personal-level data from the National Patient Registry and the Medication Statistics Registry. Statistics Denmark randomly identified 115,577 age-matched background females. Negative binomial regression was used to analyze hospital discharge diagnoses, reporting incidence rate ratios (IRR). Women with Turner syndrome have an increased risk of developing eye disorders (IRR 4.3 (95% CI 3.5-5.4), including cataract, glaucoma, ocular movement, and accommodation. The risk of ear disorders (IRR 35.0 (27.9-43.9)) and nose (IRR 2.2 (1.4-3.6)) was increased in women with Turner syndrome, due to otitis media, cholesteatoma, and hearing loss. Disorders of the nervous system such as epilepsy were increased IRR 6.2 (2.4-15.9), along with skin conditions IRR 2.2 (95%CI 1.7-2.7) like psoriasis, atopic dermatitis, and ingrown nails.

Is urban green space associated with lower mental healthcare expenditure?

IntroductionWhile the evidence of mental health benefits from investing in green space accumulates, claims of reduced healthcare expenditure are rarely supported by evidence from analyses of actual healthcare data. Additionally, the question of ‘who pays?’ has been ignored. We addressed these gaps using person-level data in three Australian cities. Methods55,339 participants with a mean follow-up time of 4.97 years in the Sax Institute's 45 and Up Study (wave 2, collected 2012–2015) were linked to fee-for-service records of antidepressant prescriptions and talking therapy subsidised by the Australian Government (including data on per unit fee, state subsidy, and individual co-payment). Total green space, tree canopy and open grass within 1.6 km road network distances were linked to each participant. Multilevel logistic, negative binomial, and generalised linear models with gamma distribution adjusted for demographic and socioeconomic confounders were used to assess association between each green space variable and prescribing/referral and costs of antidepressants and talking therapy. ResultsPrescription of at least one course of antidepressants occurred for 20.01% (n = 11,071). Referral for at least one session of talking therapy occurred in 8.95% (n = 4954). 13,482 participants (24.4%) had either a prescription or a referral. A 10% increase in green space was associated with higher levels of antidepressant prescribing (e.g. incident rate ratio (IRR) = 1.06, 95%CI = 1.04–1.08). Tree canopy was not associated with antidepressant prescribing or referrals for talking therapy. Open grass was associated with higher odds (OR = 1.17, 95%CI = 1.13–1.20) and counts (IRR = 1.05, 95%CI = 1.02–1.08) of antidepressant prescriptions. Open grass was also associated with lower odds (OR = 0.87, 95%CI = 0.82–0.92) and counts (IRR = 0.93, 95%CI = 0.90–0.96) of talking therapy referrals. Open grass was associated with higher total and mean per-person levels of expenditure on antidepressant prescriptions. ConclusionAlthough green space supports mental health, these unexpected results provide pause for reflection on whether greening strategies will always result in purported reductions in mental healthcare expenditure.

123 Deep-Learning Generated B-Line Score Mirrors Clinical Progression of Disease for Patients Admitted With Shortness of Breath or Hypoxia

Thoracic ultrasound can evaluate the lungs for fluid in the alveolar and interstitial spaces of the lung, based on the presence of artifacts known as B-lines. Degree of B-lines may provide an independent measure of severity of pulmonary edema in congestive heart failure. Artificial intelligence can be used to provide objective data, improve interpretations by novice users, and allow processing of large amount of data for research. The aim of this study is to determine the association between a B-line score using a deep learning algorithm with the degree of pulmonary congestion based on clinical assessment and its variation with response to treatment. This single-center, prospective, observational study enrolled adult patients presenting with dyspnea or hypoxia and suspected to have congestive heart failure at an urban academic ED from July 2018 to May 2019. Subjects found to have any B-lines on initial lung ultrasound were followed through their hospital course and included in this analysis. Admitted patients underwent daily ultrasonography. Clips of 8 lung zones (right and left anterior/lateral and superior/inferior) were obtained using the Philips LumifyTM ultrasound system with sector probe. Demographics, vital signs, lab values, and imaging results were also collected. A previously published deep learning algorithm was refined to rate the severity of B-lines on a scale of 0-4 in 0.5 increments. Average severity for all 8 zones at each time-point for each patient was calculated. A clinical congestion score (0-18 scale), based on presence of dyspnea, orthopnea, fatigue, JVD, rales and pedal edema was calculated. Mixed effects modeling was used to investigate the association between B-line score as independent variable and clinical congestion score as dependent variable, accounting for variation on the person level and longitudinal data. Missing data was excluded from analysis. Covariates tested included patient and exam level data (sex, age, presence of selected comorbidities, baseline sodium and hemoglobin, creatinine, vital signs, oxygen delivery amount and delivery method, diuretic dose). There were 242 unique subjects with 722 complete sets of 8-zone clips included in the analysis. For the mixed effects model, chosen covariates were: sex, baseline sodium, baseline hemoglobin, respiratory rate, CHF, chronic obstructive pulmonary disease, fraction of inspired oxygen, oxygen delivery method (eg, nasal cannula, non-rebreather, ventilator), total loop diuretic dose on day of exam, and the 8-zone DL obtained B-line score. There was no collinearity. The 8-zone B-line score was significantly associated with clinical congestions core, with coefficient of 0.73 (p<0.001). A deep learning generated B-line score mirrors clinical course for subjects admitted patients with shortness of breath or hypoxia, independent of other patient and clinical factors. B-line quantification using AI can provide an objective and independent measure of pulmonary congestion in patients with congestive heart failure and can be used to help monitor clinical progress.

Are market mechanisms associated with alcohol and other drug treatment outcomes?

The configuration of alcohol and other drug treatment service systems has been influenced by the uptake of market mechanisms for treatment funding and purchasing. This study measured the impact of market mechanisms for funding and purchasing alcohol and drug treatment services on client outcomes. An observational cross-sectional study, employing multi-level analysis: episodes of care data, nested within person-level data, nested within treatment site and nested within organization. One hundred and seventy-eight alcohol and other drug treatment service sites in Australia. Client outcome variables were length of stay and successful treatment completion. Predictor variables were competitive tendering, number of funding contracts, recurrent funding, the ratio of episodes to staff, type of professions, years of clinical experience, staff turnover and type of provider (government; non-government). Analyses controlled for drug type, type of treatment received and client characteristics. There were no significant associations between the procurement and contracting variables and length of stay [incidence rate ratios (IRRs) ranged between 1.01 and 1.07, all P > 0.05; Bayes factors (BF) < 0.03], and inconclusive results for treatment completion [odds ratios (ORs) ranged between 1.04 and 1.15, all P > 0.05, BF = 0.51-0.63]. Having an alcohol and other drug (AOD) work-force relative to an 'other' work-force (IRR = 0.79, P = 0.021) and lower case-loads (IRR = 0.99, P = 0.047) may be associated with longer stay in treatment. Receiving services from a government compared to non-government provider may also be associated with less treatment completion (OR = 0.34, P = 0.023, BF = 2.14). There appears to be no association between client outcomes and procurement and funding contract arrangements for alcohol and drug treatment services.

Association Between Dementia Care Programs in Assisted Living Facilities and Transitions to Nursing Homes in Ontario, Canada: A Population-Based Cohort Study

ObjectiveWe investigate whether older adults who were newly diagnosed with dementia (severity unspecified) and resided in an assisted living facility that offered a dementia care program had a lower rate of transition to a nursing home, compared to those who resided in an assisted living facility without such a program. DesignPopulation-based retrospective cohort study. Setting and ParticipantsLinked, person-level health system administrative data on older adults who were newly diagnosed with dementia and resided in an assisted living facility in Ontario, Canada, from 2014 to 2019 (n = 977). MethodsAccess to a dementia care program in an assisted living facility (n = 57) was examined. Multivariable Cox proportional hazards regression with robust standard errors clustered on the assisted living facility was used to model the time to transition to a nursing home from the new dementia diagnosis. ResultsThere were 11.8 transitions to a nursing home per 100 person-years among older adults who resided in an assisted living facility with a dementia care program, compared with 20.5 transitions to a nursing home per 100 person-years among older adults who resided in an assisted living facility without a dementia care program. After adjustment for relevant characteristics at baseline, older adults who resided in an assisted living facility with a dementia care program had a 40% lower rate of transition to a nursing home (hazard ratio 0.60, 95% confidence interval 0.44, 0.81), compared with those in an assisted living facility without such a program at any point during the follow-up period. Conclusions and ImplicationsThe rate of transition to a nursing home was significantly lower among older adults who resided in an assisted living facility that offered a dementia care program. These findings support the expansion of dementia care programs in assisted living facilities.

A disproportionate epidemic: COVID-19 cases and deaths among essential workers in Toronto, Canada

Shelter-in-place mandates and closure of nonessential businesses have been central to COVID19 response strategies including in Toronto, Canada. Approximately half of the working population in Canada are employed in occupations that do not allow for remote work suggesting potentially limited impact of some of the strategies proposed to mitigate COVID-19 acquisition and onward transmission risks and associated morbidity and mortality. We compared per-capita rates of COVID-19 cases and deaths from January 23, 2020 to January 24, 2021, across neighborhoods in Toronto by proportion of the population working in essential services. We used person-level data on laboratory-confirmed COVID-19 community cases and deaths, and census data for neighborhood-level attributes. Cumulative per-capita rates of COVID-19 cases and deaths were 3.3-fold and 2.5-fold higher, respectively, in neighborhoods with the highest versus lowest concentration of essential workers. Findings suggest that the population who continued to serve the essential needs of society throughout COVID-19 shouldered a disproportionate burden of transmission and deaths. Taken together, results signal the need for active intervention strategies to complement restrictive measures to optimize both the equity and effectiveness of COVID-19 responses.

Digital media use and suicidal behavior in U.S. adolescents, 2009–2017

U.S. adolescent suicidal behavior and digital media use prevalence have contemporaneously increased this decade in population-level ecological analyses. The purpose of this study was to determine whether these two trends are directly associated by using multi-year person-level data to test whether the association of year with suicidal behavior was mediated by digital media use. Data were from the Youth Risk Behavior Surveillance System (2009–2017), a nationally-representative biennial cross-sectional self-report survey of U.S. students (N = 72,942). Mediation analysis was used to estimate the proportion of cross-year changes in suicidal behavior that were mediated by concurrent changes in leisure-time digital media use. Past-year suicidal behavior in 2011 (19.6%), 2013 (20.4%), 2015 (21.7%), and 2017 (20.5%) increased relative to 2009 (17.1%). Hours of daily digital media use in 2011 (mean[SD] = 2.65[1.86]), 2013 (mean[SD] = 3.02[2.08]), 2015 (mean[SD] = 2.97[2.12]), and 2017 (mean[SD] = 3.01[2.18) increased vs. 2009 (mean[SD] = 2.31[1.81]). The association of survey year with suicidal behavior was mediated by digital media use—20.5%(95%CI = 16.2, 24.8), 34.3%(95%CI = 24.5, 44.1), 22.8%(95%CI = 17.3, 28.0), and 41.4%(95%CI = 33.9, 49.5) of cross-year suicidal behavior prevalence increases (vs. 2009) for 2011, 2013, 2015, and 2017, respectively, were mediated by concurrent digital media use increases. Therefore, small proportions of the 2009–2017 increases in U.S. adolescent suicidal behavior are associated with concurrent increasing digital media use trends. Further exploration of these trends is warranted.

COVID-19: A case for the collection of race data in Canada and abroad.

Racialized populations have consistently been shown to have poorer health outcomes worldwide. This pattern has become even more prominent in the wake of the coronavirus disease 2019 (COVID-19) pandemic. In countries where race disaggregated data are routinely collected, such as the United States and the United Kingdom, preliminary reports have identified that racialized populations are at a heightened risk of COVID-19 infection and mortality. Similar patterns are emerging in Canada but rely on proxy measures such as neighbourhood diversity to account for race, in the absence of person-level data. It follows that the collection of race disaggregated data in Canada is a crucial element in identifying individuals at risk of poorer COVID-19 outcomes and developing targeted public health interventions to mitigate risk among Canada's racialized populations. Given this continuing gap, advocating for timely access to this data is of great importance owing to the challenges that the COVID-19 pandemic has highlighted amongst racialized populations in Canada and worldwide.

Temporal trends and forecasting of COVID-19 hospitalisations and deaths in Scotland using a national real-time patient-level data platform: a statistical modelling study

SummaryBackgroundAs the COVID-19 pandemic continues, national-level surveillance platforms with real-time individual person-level data are required to monitor and predict the epidemiological and clinical profile of COVID-19 and inform public health policy. We aimed to create a national dataset of patient-level data in Scotland to identify temporal trends and COVID-19 risk factors, and to develop a novel statistical prediction model to forecast COVID-19-related deaths and hospitalisations during the second wave.MethodsWe established a surveillance platform to monitor COVID-19 temporal trends using person-level primary care data (including age, sex, socioeconomic status, urban or rural residence, care home residence, and clinical risk factors) linked to data on SARS-CoV-2 RT-PCR tests, hospitalisations, and deaths for all individuals resident in Scotland who were registered with a general practice on Feb 23, 2020. A Cox proportional hazards model was used to estimate the association between clinical risk groups and time to hospitalisation and death. A survival prediction model derived from data from March 1 to June 23, 2020, was created to forecast hospital admissions and deaths from October to December, 2020. We fitted a generalised additive spline model to daily SARS-CoV-2 cases over the previous 10 weeks and used this to create a 28-day forecast of the number of daily cases. The age and risk group pattern of cases in the previous 3 weeks was then used to select a stratified sample of individuals from our cohort who had not previously tested positive, with future cases in each group sampled from a multinomial distribution. We then used their patient characteristics (including age, sex, comorbidities, and socioeconomic status) to predict their probability of hospitalisation or death.FindingsOur cohort included 5 384 819 people, representing 98·6% of the entire estimated population residing in Scotland during 2020. Hospitalisation and death among those testing positive for SARS-CoV-2 between March 1 and June 23, 2020, were associated with several patient characteristics, including male sex (hospitalisation hazard ratio [HR] 1·47, 95% CI 1·38–1·57; death HR 1·62, 1·49–1·76) and various comorbidities, with the highest hospitalisation HR found for transplantation (4·53, 1·87–10·98) and the highest death HR for myoneural disease (2·33, 1·46–3·71). For those testing positive, there were decreasing temporal trends in hospitalisation and death rates. The proportion of positive tests among older age groups (>40 years) and those with at-risk comorbidities increased during October, 2020. On Nov 10, 2020, the projected number of hospitalisations for Dec 8, 2020 (28 days later) was 90 per day (95% prediction interval 55–125) and the projected number of deaths was 21 per day (12–29).InterpretationThe estimated incidence of SARS-CoV-2 infection based on positive tests recorded in this unique data resource has provided forecasts of hospitalisation and death rates for the whole of Scotland. These findings were used by the Scottish Government to inform their response to reduce COVID-19-related morbidity and mortality.FundingMedical Research Council, National Institute for Health Research Health Technology Assessment Programme, UK Research and Innovation Industrial Strategy Challenge Fund, Health Data Research UK, Scottish Government Director General Health and Social Care.

Estimating the Total Number of Residential Fire-Related Incidents and Underreported Residential Fire Incidents in New South Wales, Australia by Using Linked Administrative Data.

The rate of fires, and particularly residential fires, is a serious concern in industrialized countries. However, there is considerable uncertainty regarding the reported numbers of residential fire incidents as official figures are based on fires reported to fire response agencies only. This population-based study aims to quantify the total number of residential fire incidents regardless of reporting status. The cohort comprised linked person-level data from Fire and Rescue New South Wales (FRNSW) and health system and death records. It included all persons residing at a residential address in New South Wales, Australia, that experienced a fire between 1 January 2005 and 31 December 2014. The capture-recapture method was used to estimate the underreporting number of residential fire-related incidents. Over the study period, 43,707 residential fire incidents were reported to FRNSW, and there were 2795 residential fire-related health service utilizations, of which 2380 were not reported. Using the capture-recapture method, the total number of residential fire incidents was estimated at 267,815 to 319,719, which is more than six times the official records. This study found that 15% of residential fire incidents that were identified in health administrative dataset were reported. The residential fire incidents that were not reported occurred mainly in socio-economically disadvantaged areas among males and adults.

Real-world cost-effectiveness of pertuzumab (P) with trastuzumab + chemo (T+Chemo) in patients (pts) with metastatic breast cancer (MBC): A population-based retrospective cohort study by the Canadian Real-world Evidence for Value in Cancer Drugs (CanREValue) collaboration.

1048 Background: Addition of P to T+chemo for MBC pts has been shown to improve overall survival (OS) in a pivotal randomized trial (hazard ratio [HR] = 0.66, 95% CI: 0.52, 0.84) (Baselga et al., NEJM 2012). In Canada, the manufacturer submission to the health technology assessment agency estimated that P produced 0.64 life years gained (LYG) with an incremental cost-effectiveness ratio (ICER) of $187,376/LYG over 10 years (CADTH-pCODR, 2013). This retrospective cohort analysis aims to determine the comparative real-world population-based effectiveness and cost-effectiveness of P among MBC pts in Ontario, Canada. Methods: MBC pts were identified from the Ontario Cancer Registry and linked to the New Drug Funding Program database to identify receipt of treatment between 1/1/2008 and 3/31/2018. Cases received P-T-chemo after universal public funding of P (Nov 2013) and controls received T-chemo before. Demographic (age, socioeconomic, rurality) and clinical (comorbidities, prior adjuvant treatments, prior breast cancer surgery, prior radiation, stage at diagnosis, ER/PR status) characteristics were identified from linked admin databases balanced between cases and controls using propensity score matching. Kaplan-Meier methods and Cox regressions accounting for matched pairs were used to estimate median OS and HR. 5-year mean total costs from the public health system perspective were estimated from admin claims databases using established direct statistical methods and adjusted for censoring of both cost and effectiveness using inverse probability weighting. ICERs and 95% bootstrapped CIs were calculated, along with incremental net benefit (INB) at various willingness-to-pay values using net benefit regression. Results: We identified 1,823 MBC pts with 912 cases and 911 controls (mean age = 55 years), of which 579 pairs were matched. Cases had improved OS (HR = 0.66; 95% CI: 0.57, 0.78), with median 3.4 years, compared to controls median OS of 2.1. P provided an additional 0.63 (95% CI: 0.48 – 0.84) LYG at an incremental cost of $196,622 (95% CI: $180,774, $219,172), with a mean ICER = $312,147/LYG (95% CI: $260,752, $375,492). At threshold of $100,000/LYG, the INB was -$133,632 (95% CI: -$151,525, -$115,739) with &lt; 1% probability of being cost-effective. Key drivers of incremental cost increase between groups included drug and cancer clinic costs. Conclusions: The addition of P to T-chemo for MBC increased survival but at significant costs. The ICER based on direct real-world data was higher than the initial economic model due to higher total costs for pts receiving P. This study demonstrated feasibility to derive ICER from person-level real-world data to inform cancer drug life-cycle health technology reassessment.

Calibration and validation of person-based trip production models of optional trip purposes

ABSTRACT Trip generation models are typically calibrated using zone-based aggregated data, despite some theoretical drawbacks pertaining to the use of aggregated data. This study demonstrates that models calibrated with disaggregated data not only have a better theoretical basis, but also forecast more accurate trip productions. In particular, optional trip purposes are focused on the calibration of trip production models, of which trips tend to be irregularly generated, rendering it difficult to build more reliable models. There are three models calibrated: an aggregate model with zone-level data, a disaggregate model with household-level data, and with household and person-level data using household survey data for two years. The prediction accuracy and stability of the models are compared and verified using statistical methods. It is discovered that calibrating a trip production model using household and person-level data jointly yields a better calibration method.

Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource

ObjectiveTo describe a novel England-wide electronic health record (EHR) resource enabling whole population research on covid-19 and cardiovascular disease while ensuring data security and privacy and maintaining public trust.DesignData resource...

Register-based metrics of years lived with disability associated with mental and substance use disorders: a register-based cohort study in Denmark

Mental disorders account for a substantial proportion of the years lived with disability (YLDs) globally. These estimates have generally been calculated top down based on summary statistics. The aim for this study was to calculate YLDs and a novel related measure, Health Loss Proportion (HeLP), for 18 mental and substance use disorders, based on person-level register data (bottom up). A cohort of 6 989 627 Danish residents (5·9% had a diagnosis of a mental or substance use disorder registered in the Danish Psychiatric Central Research Register) was investigated. YLDs (the duration of disease multiplied by a disability weight) were calculated for the disorder of interest and for comorbid mental and substance use disorders. HeLPs were estimated as YLDs associated with an index disorder and comorbid mental and substance use disorders divided by person-years at risk in persons with the index disorder. All analyses were adjusted for mental and substance use comorbidity using a multiplicative model of disability weights. Major depressive disorder was the most prevalent disorder, although schizophrenia was the leading cause of YLDs in both sexes combined (YLDs 273·3 [95 % CI 232·3-313·6] per 100 000 person-years). People diagnosed with schizophrenia lost the equivalent of 73% (63-83%) of healthy life per year due to mental and substance use disorders, the largest HeLP of all mental and substance use disorders. Comorbidity of mental and substance use disorders accounted for 69-83% of HeLPs in people with either cannabis use disorders, other drug use disorder and ADHD. By contrast, comorbidity explained 11-23% of the HeLPs in people with autism spectrum disorders, conduct disorder, and schizophrenia. Substantial variation in disability was observed across age, sex, and disorders. The new HeLP metric provides novel details of the contribution of comorbidity to the disability associated with mental and substance use disorders. The Danish National Research Foundation, Queensland Government Department of Health, European Union's Horizon 2020, Lundbeck Foundation, Stanley Medical Research Institute. For the Danish translation of the abstract see Supplementary Materials section.

Does the Health Loss Proportion help us to understand disability in mental health?

Mental and substance use disorders are a major contributor to the global burden of disease, making substantial contributions to years lived with disability.1 Therefore, the paper by Nanna Weye and colleagues2 makes a welcome contribution to this literature through their development of a new measure for disability, the Health Loss Proportion (HeLP), which can be applied to person-level data, particularly through measures captured in electronic health records.2

Data Quality in Web and App Diaries: A Person-Level Comparison

The time-use diary is a complex and burdensome data collection instrument. This can negatively affect data quality, leading to less detailed and/or inaccurate activity reporting as the surveyed time period unfolds. However, it can also be argued that data quality may actually improve over time as respondents become more familiar with the diary instrument format and more interested in the diary task. These competing hypotheses have only been partially tested on data from paper and telephone-administered diaries, which are traditionally used for large-scale data collection. Less is known about self-administered modes that make use of new technologies, despite their increasing popularity among researchers. This research note rectifies this omission by comparing diary quality in self-administered web and app diaries, drawing on data from the Millennium Cohort Study. We construct a person-level data quality typology, using information on missing data, episode changes, and reporting of key daily activity domains. Results show significant mode differences on person-level data quality, after controlling for characteristics known to influence diary mode selection and data quality. App diarists were more likely to return two diaries of inconsistent quality. Both respondent fatigue and improvement of completion over time appear more common among app diarists.

Trends in fall‐related mortality and fall risk increasing drugs among older individuals in the United States,1999–2017

Previous studies have demonstrated increasing mortality due to falls among older adults. The objective of this study was to determine whether there was an increase in fall risk increasing drug prescribing and if this is concurrent with an increase in fall-related mortality in persons 65 years and older in the United States. The study is a serial cross-sectional analysis utilizing data from both the National Vital Statistics System (NVSS) and the medical expenditure panel survey (MEPS) for years 1999-2017. Adults aged 65 years and older were evaluated for death due to falls from the NVSS and for prescription fills of fall risk increasing drugs per the Stopping Elderly Accidents, Deaths, and Injuries-Rx (STEADI-Rx) fall checklist from the MEPS. The analysis included 374 972 fall-related mortalities and 7858 177 122 fills of fall risk increasing drugs. 563 037964 persons age 65 and older received at least one fall risk increasing drug. Age-adjusted mortality due to falls increased from 29.40 per 100 000 in 1999 to 63.27 per 100 000 in 2017. The percent of persons who received at least one prescription for a fall risk increasing drug increased from 57% in 1999 to 94% in 2017 (p for trend <.0001). Both use of fall risk increasing drugs and mortality due to falls are on the rise. Fall risk increasing drugs may partially explain the increase in mortality due to falls; this cannot be firmly concluded from the current study. Future research examining the potential relationship between fall risk increasing drugs and fall-related mortality utilizing nationally representative person-level data are needed.

Increased occurrence of liver and gastrointestinal diseases and anaemia in women with Turner syndrome - a nationwide cohort study.

Liver and gastrointestinal diseases are frequent in women with Turner syndrome. However, their association with bleeding disorders, anaemia and the impact of hormone replacement therapy is unknown. To investigate the risk of liver and gastrointestinal diseases, haemorrhage and anaemia in women with Turner syndrome compared with the female background population, and the long-term impact of hormone replacement therapy on these conditions. One thousand one hundred and fifty-six women with Turner syndrome diagnosed during 1960-2014 were identified using the Danish Cytogenetic Central Registry and linked with personal-level data from the National Patient Registry and the Medication Statistics Registry. Statistics Denmark randomly identified 115577 age-matched female controls. Negative binomial regression was used to analyse hospital discharge diagnoses. Medical prescriptions, mortality and the effect of hormone replacement therapy were estimated using stratified Cox regression. Liver disease increased 13-fold (IRR 12.9 (95% CI 5.8-28.8)), due to toxic liver disease (IRR 8.0 (95% CI 1.8-35.4)), liver insufficiency (IRR 6.7 (95% CI 1.7-26.9)), fibrosis/cirrhosis (IRR 16.5 (95% CI 2.2-122.1)) and unspecified liver disease (IRR 10.6 (95% CI 4.4-25.3)). Furthermore, presence of abnormal liver enzymes increased 12-fold (IRR 12.4 (95% CI 4.2-36.6)). The risk of gastrointestinal haemorrhage (IRR 3.4 (95% CI 1.8-6.2)), anaemia (IRR 3.2 (95% CI 2.0-5.0)) and coagulation disorders (IRR 2.9 (95% CI 1.1-7.1)) was increased. However these diagnoses were not associated with inflammatory bowel disease. Gastrointestinal mortality was increased three-fold (HR 3.1 (95% CI 1.5-6.2)), partly due to death by liver disease (HR 3.0 (95% CI 1.1-8.2)), gastrointestinal haemorrhage (HR 29.6 (95% CI 3.1-285.1)) and capillary malformations (HR 18.6 (95% CI 4.1-85.0)). There was no effect of hormone replacement therapy on gastrointestinal risk but a trend towards a beneficial impact on liver diseases. The risk of being diagnosed with liver disease was higher than previously reported. The occurrence of gastrointestinal haemorrhage and anaemia was increased in Turner syndrome. There was no effect of hormone replacement therapy on gastrointestinal risk but a trend towards a beneficial impact on liver diseases was detected.

Receipt of Cessation Treatments Among Medicaid Enrollees Trying to Quit Smoking.

Cigarette smoking prevalence is higher among adults enrolled in Medicaid than adults with private health insurance. State Medicaid coverage of cessation treatments has been gradually improving in recent years; however, the extent to which this has translated into increased use of these treatments by Medicaid enrollees remains unknown. Using Medicaid Analytic eXtract (MAX) files, we estimated state-level receipt of smoking cessation treatments and associated spending among Medicaid fee-for service (FFS) enrollees who try to quit. MAX data are the only national person-level data set available for the Medicaid program. We used the most recent MAX data available for each state and the District of Columbia (ranging from 2010 to 2014) for this analysis. Among the 37 states with data, an average of 9.4% of FFS Medicaid smokers with a past-year quit attempt had claims for cessation medications, ranging from 0.2% (Arkansas) to 32.9% (Minnesota). Among the 20 states with data, an average of 2.7% of FFS Medicaid smokers with a past-year quit attempt received cessation counseling, ranging from 0.1% (Florida) to 5.6% (Missouri). Estimated Medicaid spending for cessation medications and counseling for these states totaled just over $13 million. If all Medicaid smokers who tried to quit were to have claims for cessation medications, projected annual Medicaid expenditures would total $0.8 billion, a small fraction of the amount ($45.9 billion) that Medicaid spends annually on treating smoking-related disease. The receipt of cessation medications and counseling among FFS Medicaid enrollees was low and varied widely across states. Few studies have examined use of cessation treatments among Medicaid enrollees. We found that many FFS Medicaid smokers made quit attempts, but few had claims for proven cessation treatments, especially counseling. The receipt of cessation treatments among FFS Medicaid enrollees varied widely across states, suggesting opportunities for additional promotion of the full range of Medicaid cessation benefits. Continued monitoring of Medicaid enrollees' use of cessation treatments could inform state and national efforts to help more Medicaid enrollees quit smoking.

How does general practitioner discontinuity affect healthcare utilisation? An observational cohort study of 2.4 million Norwegians 2007–2017

ObjectivesPatients may benefit from continuity of care by a personal physician general practitioner (GP), but there are few studies on consequences of a break in continuity of GP. Investigate how...