Young adults with a 22q11.2 microdeletion and the cost of aging with complexity in a population-based context.

PURPOSE: Information about the impact on the adult health care system is limited for complex rare pediatric diseases, despite their increasing collective prevalence that has paralleled advances in clinical care of children. Within a population-based health care context, we examined costs and multimorbidity in adults with an exemplar of contemporary genetic diagnostics. METHODS: We estimated direct health care costs over an 18-year period for adults with molecularly confirmed 22q11.2 microdeletion (cases) and matched controls (total 60,459 person-years of data) by linking the case cohort to health administrative data for the Ontario population (∼15 million people). We used linear regression to compare the relative ratio (RR) of costs and to identify baseline predictors of higher costs. RESULTS: Total adult (age ≥ 18) health care costs were significantly higher for cases compared with population-based (RR 8.5, 95% CI 6.5-11.1) controls, and involved all health care sectors. At study end, when median age was <30 years, case costs were comparable to population-based individuals aged 72 years, likelihood of being within the top 1st percentile of health care costs for the entire (any age) population was significantly greater for cases than controls (odds ratio [OR], for adults 17.90, 95% CI 7.43-43.14), and just 8 (2.19%) cases had a multimorbidity score of zero (vs 1483 (40.63%) controls). The 22q11.2 microdeletion was a significant predictor of higher overall health care costs after adjustment for baseline variables (RR 6.9, 95% CI 4.6-10.5). CONCLUSION: The findings support the possible extension of integrative models of complex care used in pediatrics to adult medicine and the potential value of genetic diagnostics in adult clinical medicine.

An Update to the Kaiser Permanente Inpatient Risk Adjustment Methodology Accurately Predicts In-Hospital Mortality: a Retrospective Cohort Study.

BACKGROUND: Methods to accurately predict the risk of in-hospital mortality are important for applications including quality assessment of healthcare institutions and research. OBJECTIVE: To update and validate the Kaiser Permanente inpatient risk adjustment methodology (KP method) to predict in-hospital mortality, using open-source tools to measure comorbidity and diagnosis groups, and removing troponin which is difficult to standardize across modern clinical assays. DESIGN: Retrospective cohort study using electronic health record data from GEMINI. GEMINI is a research collaborative that collects administrative and clinical data from hospital information systems. PARTICIPANTS: Adult general medicine inpatients at 28 hospitals in Ontario, Canada, between April 2010 and December 2022. MAIN MEASURES: The outcome was in-hospital mortality, modeled by diagnosis group using 56 logistic regressions. We compared models with and without troponin as an input to the laboratory-based acute physiology score. We fit and validated the updated method using internal-external cross-validation at 28 hospitals from April 2015 to December 2022. KEY RESULTS: In 938,103 hospitalizations with 7.2% in-hospital mortality, the updated KP method accurately predicted the risk of mortality. The c-statistic at the median hospital was 0.866 (see Fig. 3) (25th-75th 0.848-0.876, range 0.816-0.927) and calibration was strong for nearly all patients at all hospitals. The 95th percentile absolute difference between predicted and observed probabilities was 0.038 at the median hospital (25th-75th 0.024-0.057, range 0.006-0.118). Model performance was very similar with and without troponin in a subset of 7 hospitals, and performance was similar with and without troponin for patients hospitalized for heart failure and acute myocardial infarction. CONCLUSIONS: An update to the KP method accurately predicted in-hospital mortality for general medicine inpatients in 28 hospitals in Ontario, Canada. This updated method can be implemented in a wider range of settings using common open-source tools.

Outcomes in patients with and without disability admitted to hospital with COVID-19: a retrospective cohort study.

BACKGROUND: Disability-related considerations have largely been absent from the COVID-19 response, despite evidence that people with disabilities are at elevated risk for acquiring COVID-19. We evaluated clinical outcomes in patients who were admitted to hospital with COVID-19 with a disability compared with patients without a disability. METHODS: We conducted a retrospective cohort study that included adults with COVID-19 who were admitted to hospital and discharged between Jan. 1, 2020, and Nov. 30, 2020, at 7 hospitals in Ontario, Canada. We compared in-hospital death, admission to the intensive care unit (ICU), hospital length of stay and unplanned 30-day readmission among patients with and without a physical disability, hearing or vision impairment, traumatic brain injury, or intellectual or developmental disability, overall and stratified by age (≤ 64 and ≥ 65 yr) using multivariable regression, controlling for sex, residence in a long-term care facility and comorbidity. RESULTS: Among 1279 admissions to hospital for COVID-19, 22.3% had a disability. We found that patients with a disability were more likely to die than those without a disability (28.1% v. 17.6%), had longer hospital stays (median 13.9 v. 7.8 d) and more readmissions (17.6% v. 7.9%), but had lower ICU admission rates (22.5% v. 28.3%). After adjustment, there were no statistically significant differences between those with and without disabilities for in-hospital death or admission to ICU. After adjustment, patients with a disability had longer hospital stays (rate ratio 1.36, 95% confidence interval [CI] 1.19-1.56) and greater risk of readmission (relative risk 1.77, 95% CI 1.14-2.75). In age-stratified analyses, we observed longer hospital stays among patients with a disability than in those without, in both younger and older subgroups; readmission risk was driven by younger patients with a disability. INTERPRETATION: Patients with a disability who were admitted to hospital with COVID-19 had longer stays and elevated readmission risk than those without disabilities. Disability-related needs should be addressed to support these patients in hospital and after discharge.

Predictors of ICU admission associated with gastrointestinal endoscopy in medical inpatients: A retrospective cohort study.

BACKGROUND AND AIM: Gastrointestinal (GI) endoscopic procedures are commonly performed in medical inpatients. Limited prior research has examined factors associated with intensive care unit (ICU) admission after GI endoscopy in medical inpatients. METHODS: This retrospective cohort study was conducted using routinely-collected clinical and administrative data from all general medicine hospitalizations at five academic hospitals in Toronto, Canada between 2010 and 2020. We describe ICU admission and death within 48 h of GI endoscopy in medical inpatients. We examined adjusted associations of patient and procedural factors with ICU admission or death using multivariable logistic regression. RESULTS: Among 18 290 medical inpatients who underwent endoscopy, 900 (4.9%) required ICU admission or died within 48 h of endoscopy. Following risk adjustment, ICU admission or death were associated with the following procedural factors: endoscopy on the day of hospital admission (aOR 3.16 [2.38-4.21]) or 1 day after admission (aOR 1.92 [1.51-2.44]) and esophagogastroduodenoscopy (EGD) procedures; and the following patient factors: Charlson comorbidity index of two (aOR 1.38 [1.05-1.81]) or three or greater (aOR 1.84 [1.47-2.29]), older age, male sex, lower hemoglobin prior to endoscopy, increased creatinine prior to endoscopy, an admitting diagnosis of liver disease and certain medications (antiplatelet agents and corticosteroids). CONCLUSIONS: ICU admission or death after endoscopy was associated with procedural factors such as EGD and timing of endoscopy, and patient factors indicative of acute illness and greater comorbidity. These findings can contribute to improved triage and monitoring for patients requiring inpatient endoscopy.

Outcomes for upper gastrointestinal bleeding during the first wave of the COVID-19 pandemic in the Toronto area.

BACKGROUND AND AIM: Changes to endoscopy service availability during the COVID-19 pandemic may have affected management of upper gastrointestinal bleeding (UGIB). The aim of this study was to describe the impact of the pandemic on UGIB outcomes in the Toronto area in Canada. METHODS: We described all adults admitted to general medicine wards or intensive care units at six hospitals in Toronto and Mississauga, Canada, with UGIB during the first wave of the COVID-19 pandemic (March 1 to June 30, 2020) and compared them with a historical cohort (March 1 to June 30, 2018 and 2019). We compared clinical outcomes (in-hospital mortality, length of stay, 30-day readmission, intensive care utilization, receipt of endoscopy, persistent bleeding, receipt of second endoscopy, and need for angiographic or surgical intervention) using multivariable regression models, controlling for demographics, comorbidities, and severity of clinical presentation. RESULTS: There were 82.5 and 215.5 admissions per month for UGIB during the COVID-19 and control periods, respectively. There were no baseline differences between groups for demographic characteristics, comorbidities, or severity of bleeding. Patients in the COVID-19 group did not have significantly different unadjusted (3.9% vs 4.2%, P = 0.983) or adjusted mortality (adjusted odds ratio [OR] = 0.64, 95% confidence interval [CI] = 0.25-1.48, P = 0.322). Patients in COVID-19 group were less likely to receive endoscopy for UGIB in the unadjusted (61.8% vs 71.0%, P = 0.003) and adjusted (adjusted OR = 0.64, 95% CI = 0.49-0.84, P < 0.01) models. There were no differences between groups for other secondary outcomes. CONCLUSIONS: While patients admitted for UGIB during the first wave of the pandemic were less likely to receive endoscopy, this had no impact on mortality or any secondary outcomes.

Using machine learning to predict severe hypoglycaemia in hospital.

AIM: To predict the risk of hypoglycaemia using machine-learning techniques in hospitalized patients. METHODS: We conducted a retrospective cohort study of patients hospitalized under general internal medicine (GIM) and cardiovascular surgery (CV) at a tertiary care teaching hospital in Toronto, Ontario. Three models were generated using supervised machine learning: least absolute shrinkage and selection operator (LASSO) logistic regression; gradient-boosted trees; and a recurrent neural network. Each model included baseline patient data and time-varying data. Natural-language processing was used to incorporate text data from physician and nursing notes. RESULTS: We included 8492 GIM admissions and 8044 CV admissions. Hypoglycaemia occurred in 16% of GIM admissions and 13% of CV admissions. The area under the curve for the models in the held-out validation set was approximately 0.80 on the GIM ward and 0.82 on the CV ward. When the threshold for hypoglycaemia was lowered to 2.9 mmol/L (52 mg/dL), similar results were observed. Among the patients at the highest decile of risk, the positive predictive value was approximately 50% and the sensitivity was 99%. CONCLUSION: Machine-learning approaches can accurately identify patients at high risk of hypoglycaemia in hospital. Future work will involve evaluating whether implementing this model with targeted clinical interventions can improve clinical outcomes.

Characteristics and outcomes of hospital admissions for COVID-19 and influenza in the Toronto area.

BACKGROUND: Patient characteristics, clinical care, resource use and outcomes associated with admission to hospital for coronavirus disease 2019 (COVID-19) in Canada are not well described. METHODS: We described all adults with COVID-19 or influenza discharged from inpatient medical services and medical-surgical intensive care units (ICUs) between Nov. 1, 2019, and June 30, 2020, at 7 hospitals in Toronto and Mississauga, Ontario. We compared patient outcomes using multivariable regression models, controlling for patient sociodemographic factors and comorbidity level. We validated the accuracy of 7 externally developed risk scores to predict mortality among patients with COVID-19. RESULTS: There were 1027 hospital admissions with COVID-19 (median age 65 yr, 59.1% male) and 783 with influenza (median age 68 yr, 50.8% male). Patients younger than 50 years accounted for 21.2% of all admissions for COVID-19 and 24.0% of ICU admissions. Compared with influenza, patients with COVID-19 had significantly greater in-hospital mortality (unadjusted 19.9% v. 6.1%, adjusted relative risk [RR] 3.46, 95% confidence interval [CI] 2.56-4.68), ICU use (unadjusted 26.4% v. 18.0%, adjusted RR 1.50, 95% CI 1.25-1.80) and hospital length of stay (unadjusted median 8.7 d v. 4.8 d, adjusted rate ratio 1.45, 95% CI 1.25-1.69). Thirty-day readmission was not significantly different (unadjusted 9.3% v. 9.6%, adjusted RR 0.98, 95% CI 0.70-1.39). Three points-based risk scores for predicting in-hospital mortality showed good discrimination (area under the receiver operating characteristic curve [AUC] ranging from 0.72 to 0.81) and calibration. INTERPRETATION: During the first wave of the pandemic, admission to hospital for COVID-19 was associated with significantly greater mortality, ICU use and hospital length of stay than influenza. Simple risk scores can predict in-hospital mortality in patients with COVID-19 with good accuracy.

Insecurity, polio vaccination rates, and polio incidence in northwest Pakistan.

Pakistan is one of three countries in which endemic transmission of poliovirus has never been stopped. Insecurity is often cited but poorly studied as a barrier to eradicating polio. We analyzed routinely collected health data from 32 districts of northwest Pakistan and constructed an index of insecurity based on journalistic reports of the monthly number of deaths and injuries resulting from conflict-related security incidents. The primary outcomes were the monthly incidence of paralytic polio cases within each district between 2007 and 2014 and the polio vaccination percentage from 666 district-level vaccination campaigns between 2007 and 2009, targeting ∼5.7 million children. Multilevel Poisson regression controlling for time and district fixed effects was used to model the association between insecurity, vaccinator access, vaccination rates, and polio incidence. The number of children inaccessible to vaccinators was 19.7% greater (95% CI: 19.2-20.2%), and vaccination rates were 5.3% lower (95% CI: 5.2-5.3%) in "high-insecurity" campaigns compared with "secure" campaigns. The unadjusted mean vaccination rate was 96.3% (SD = 8.6) in secure campaigns and 88.3% (SD = 19.2) in high-insecurity campaigns. Polio incidence was 73.0% greater (95% CI: 30-131%) during high-insecurity months (unadjusted mean = 0.13 cases per million people, SD = 0.71) compared with secure months (unadjusted mean = 1.23 cases per million people, SD = 4.28). Thus, insecurity was associated with reduced vaccinator access, reduced polio vaccination, and increased polio incidence in northwest Pakistan. These findings demonstrate that insecurity is an important obstacle to global polio eradication.

A genetic model for multimorbidity in young adults.

PURPOSE: Multimorbidity is increasing in younger adults but is understudied in this population. We used 22q11.2 deletion syndrome (22q11.2DS) as a genetic model to investigate multimorbidity in young to middle-aged adults. METHODS: Using the Anatomical Therapeutic Chemical (ATC) Classification System and setting five or more concurrent prescription medications as a proxy for multimorbidity, we compared data on 264 adults with 22q11.2DS (median age 27.8, range 17.3-68.3 years) with that for a community-based Canadian general population sample (n = 25,287). We used logistic regression to examine possible predictors of multimorbidity in 22q11.2DS. RESULTS: Multimorbidity in 22q11.2DS in the 25-44 year age group (34.7%) was significantly more prevalent than in the general population, both for the same age group (2.9%, prevalence ratio [PR] = 11.9, 95% CI 8.4-17.1) and compared with those aged 45-64 years (16.4%, PR = 2.1, 95% CI 1.6-2.7). Neuropsychiatric and endocrinological medication classes predominated. Within 22q11.2DS, older age and psychotic illness, but not sex, major congenital heart disease, or intellectual disability, were significant predictors of multimorbidity. CONCLUSION: The results indicate that adults with 22q11.2DS have a significant burden of illness with levels of multimorbidity comparable with those of the general population several decades older. In younger adults with multimorbidity, certain disease patterns may help identify genetic disorders in "big data."

Preprints: a Timely Counterbalance for Big Data-Driven Research.

Big data promises to spark new discoveries but may also distort clinical research. Large datasets that permit numerous analyses could increase the number of spurious findings and threaten the reproducibility and validity of clinical research. The publication of unreproducible research is incentivized by a scientific culture that rewards novelty over rigor. Introducing preprint publication to clinical research could change the culture. The first clinical preprint platform, medRxiv, allows researchers to publish working papers in advance of peer-review to more easily share preliminary findings. Preprint publishing aims to be fast and frictionless, which fundamentally changes the incentive structure of academic publishing. Preprints offer a relatively weak reward (a preprint publication) for substantially less effort than peer-review publication. By reducing barriers to publication, preprints may help encourage scientists to publish null findings, which could mitigate publication bias. By enabling scientists to share preliminary work and publish evolving versions of manuscripts, preprints may also facilitate "workshopping" of ideas and detailed methodological review. This would better reflect the iterative nature of observational research than peer-reviewed publications, which immutably document the "final" results of a study. Preprint platforms are a timely innovation that may buffer the undesired effects of big data on clinical research.

Empiric Antibiotic Treatment Thresholds for Serious Bacterial Infections: A Scenario-based Survey Study.

BACKGROUND: Physicians face competing demands of maximizing pathogen coverage while minimizing unnecessary use of broad-spectrum antibiotics when managing sepsis. We sought to identify physicians' perceived likelihood of coverage achieved by their usual empiric antibiotic regimen, along with minimum thresholds of coverage they would be willing to accept when managing these patients. METHODS: We conducted a scenario-based survey of internal medicine physicians from across Canada using a 2 × 2 factorial design, varied by infection source (undifferentiated vs genitourinary) and severity (mild vs severe) denoted by the Quick Sequential Organ Failure Assessment (qSOFA) score. For each scenario, participants selected their preferred empiric antibiotic regimen, estimated the likelihood of coverage achieved by that regimen, and considered their minimum threshold of coverage. RESULTS: We had 238 respondents: 87 (36.6%) residents and 151 attending physicians (63.4%). The perceived likelihood of antibiotic coverage and minimum thresholds of coverage (with interquartile range) for each scenario were as follows: (1) severe undifferentiated, 90% (89.5%-95.0%) and 90% (80%-95%), respectively; (2) mild undifferentiated, 89% (80%-95%) and 80% (70%-89.5%); (3) severe genitourinary, 91% (87.3%-95.0%) and 90% (80.0%-90.0%); and (4) mild genitourinary, 90% (81.8%-91.3%) and 80% (71.8%-90%). Illness severity and infectious disease specialty predicted higher thresholds of coverage whereas less clinical experience and lower self-reported prescribing intensity predicted lower thresholds of coverage. CONCLUSIONS: Pathogen coverage of 80% and 90% are physician-acceptable thresholds for managing patients with mild and severe sepsis from bacterial infections. These data may inform clinical guidelines and decision-support tools to improve empiric antibiotic prescribing.

Value of routine echocardiography in the management of stroke.

BACKGROUND: Transthoracic echocardiography is routinely performed in patients with stroke or transient ischemic attack (TIA) to help plan secondary stroke management, but recent data evaluating its usefulness in this context are lacking. We sought to evaluate the value of echocardiography for identifying clinically actionable findings for secondary stroke prevention. METHODS: We conducted a multicentre cohort study of patients admitted to hospital with stroke or TIA between 2010 and 2015 at 2 academic hospitals in Toronto, Ontario, Canada. Clinically actionable echocardiographic findings for secondary stroke prevention included cardiac thrombus, patent foramen ovale, atrial myxoma or valvular vegetation. We identified patient characteristics associated with clinically actionable findings using logistic regression. RESULTS: Of the 1862 patients with stroke or TIA we identified, 1272 (68%) had at least 1 echocardiogram. Nearly all echocardiograms were transthoracic; 1097 (86%) were normal, 1 (0.08%) had an atrial myxoma, 2 (0.2%) had a valvular vegetation, 11 (0.9%) had a cardiac thrombus and 66 (5.2%) had a PFO. Patent foramen ovale was less likely among patients older than 60 years (adjusted odds ratio [OR] 0.34, 95% confidence interval [CI] 0.20-0.57), with prior stroke or TIA (adjusted OR 0.31, 95% CI 0.09-0.76) or with dyslipidemia (adjusted OR 0.39, 95% CI 0.15-0.84). Among the 130 patients with cryptogenic stroke who had an echocardiogram (n = 110), a PFO was detected in 19 (17%) on transthoracic echocardiogram. INTERPRETATION: Most patients with stroke or TIA had a normal echocardiogram, with few having clinically actionable findings for secondary stroke prevention. Clinically actionable findings, specifically PFO, were more common in patients with cryptogenic stroke.

Fixed-dose combination antihypertensive medications, adherence, and clinical outcomes: A population-based retrospective cohort study.

BACKGROUND: The majority of people with hypertension require more than one medication to achieve blood pressure control. Many patients are prescribed multipill antihypertensive regimens rather than single-pill fixed-dose combination (FDC) treatment. Although FDC use may improve medication adherence, the impact on patient outcomes is unclear. We compared clinical outcomes and medication adherence with FDC therapy versus multipill combination therapy in a real-world setting using linked clinical and administrative databases. METHODS AND FINDINGS: We conducted a population-based retrospective cohort study of 13,350 individuals 66 years and older in Ontario, Canada with up to 5 years of follow-up. We included individuals who were newly initiated on one angiotensin-converting enzyme inhibitor (ACEI) or angiotensin II-receptor blocker (ARB) plus one thiazide diuretic. High-dimensional propensity score matching was used to compare individuals receiving FDC versus multipill therapy. The primary outcome was a composite of death or hospitalization for acute myocardial infarction (AMI), heart failure, or stroke. We conducted 2 analyses to examine the association between adherence and patient outcomes. First, we performed an on-treatment analysis to determine whether outcomes differed between groups while patients were on treatment, censoring patients when they first discontinued treatment, defined as not receiving medications within 150% of the previous days' supply. Second, we conducted an intention-to-treat analysis that followed individuals allowing for breaks in treatment to quantify the difference in drug adherence between groups and assess its impact on clinical outcomes. As expected, there was no significant difference in the primary outcome between groups in the on-treatment analysis (HR 1.06, 95% CI 0.86-1.31, P = 0.60). In the intention-to-treat analysis, the proportion of total follow-up days covered with medications was significantly greater in the FDC group (70%; IQR 19-98) than in the multipill group (42%, IQR 11-91, P < 0.01), and the primary outcome was less frequent in FDC recipients (3.4 versus 3.9 events per 100 person-years; HR 0.89, 95% CI 0.81-0.97, P < 0.01). The main limitations of this study were the lack of data regarding cause of death and blood pressure measurements and the possibility of residual confounding. CONCLUSIONS: Among older adults initiating combination antihypertensive treatment, FDC therapy was associated with a significantly lower risk of composite clinical outcomes, which may be related to better medication adherence.

Prevalence and Costs of Discharge Diagnoses in Inpatient General Internal Medicine: a Multi-center Cross-sectional Study.

BACKGROUND: Understanding the most common and costly conditions treated by inpatient general medical services is important for implementing quality improvement, developing health policy, conducting research, and designing medical education. OBJECTIVE: To determine the prevalence and cost of conditions treated on general internal medicine (GIM) inpatient services. DESIGN: Retrospective cross-sectional study involving 7 hospital sites in Toronto, Canada. PARTICIPANTS: All patients discharged between April 1, 2010 and March 31, 2015 who were admitted to or discharged from an inpatient GIM service. MAIN MEASURES: Hospital administrative data were used to identify diagnoses and costs associated with admissions. The primary discharge diagnosis was identified for each admission and categorized into clinically relevant and mutually exclusive categories using the Clinical Classifications Software (CCS) tool. KEY RESULTS: Among 148,442 admissions, the most common primary discharge diagnoses were heart failure (5.1%), pneumonia (5.0%), urinary tract infection (4.6%), chronic obstructive pulmonary disease (4.5%), and stroke (4.4%). The prevalence of the 20 most common conditions was significantly correlated across hospitals (correlation coefficients ranging from 0.55 to 0.95, p ≤ 0.01 for all comparisons). No single condition represented more than 5.1% of all admissions or more than 7.9% of admissions at any hospital site. The costliest conditions were stroke (median cost $7122, interquartile range 5587-12,354, total cost $94,199,422, representing 6.0% of all costs) and the group of delirium, dementia, and cognitive disorders (median cost $12,831, IQR 9539-17,509, total cost $77,372,541, representing 4.9% of all costs). The 10 most common conditions accounted for only 36.2% of hospitalizations and 36.8% of total costs. The remaining hospitalizations included 223 different CCS conditions. CONCLUSIONS: GIM services care for a markedly heterogeneous population but the most common conditions were similar across 7 hospitals. The diversity of conditions cared for in GIM may be challenging for healthcare delivery and quality improvement. Initiatives that cut across individual diseases to address processes of care, patient experience, and functional outcomes may be more relevant to a greater proportion of the GIM population than disease-specific efforts.

Emerging Trends in Clinical Research: With Implications for Population Health and Health Policy.

Policy Points: Significant advances in clinical medicine that have broader societal relevance may be less accessible to population health researchers and policymakers because of increased specialization within fields. We describe important recent clinical advances and discuss their broader societal impact. These advances include more expansive strategies for disease prevention, the rise of precision medicine, applications of human microbiome research, and new and highly successful treatments for hepatitis C infection. These recent developments in clinical research raise important issues surrounding health care costs and equitable resource allocation that necessitate an ongoing dialogue among the fields of clinical medicine, population health, and health policy. CONTEXT: Developments in clinical medicine have important implications for population health, and there is a need for interdisciplinary engagement among clinical medicine, the social sciences, and public health research. The aim of this article is to help bridge the divide between these fields by exploring major recent advances in clinical medicine that have important implications for population health. METHODS: We reviewed the most cited articles published from 2010 to 2015 in 5 high-impact clinical journals and selected 5 randomized controlled trials and 2 related clinical practice guidelines that are broadly relevant to population health and policy. FINDINGS: We discuss the following themes: (1) expanding indications for drug therapy and the inherent medicalization of the population as highlighted by studies and clinical guidelines supporting lower blood pressure targets or widespread statin use; (2) the tension in nutritional research between quantifying the impact of isolated nutrients and studying specific foods and dietary patterns, for example, the role of the Mediterranean diet in the primary prevention of cardiovascular disease; (3) the issue of high medication costs and the challenge of providing equitable access raised by the development of new and effective treatments for hepatitis C infection; (4) emerging clinical applications of research on the human microbiome as illustrated by fecal transplant to treat Clostridium difficile infections; and (5) the promise and limitations of precision medicine as demonstrated by the rise of novel targeted therapies in oncology. CONCLUSIONS: These developments in clinical science hold promise for improving individual and population health and raise important questions about resource allocation, the role of prevention, and health disparities.

Paramedic-Initiated Home Care Referrals and Use of Home Care and Emergency Medical Services.

OBJECTIVE: We examined the association between paramedic-initiated home care referrals and utilization of home care, 9-1-1, and Emergency Department (ED) services. METHODS: This was a retrospective cohort study of individuals who received a paramedic-initiated home care referral after a 9-1-1 call between January 1, 2011 and December 31, 2012 in Toronto, Ontario, Canada. Home care, 9-1-1, and ED utilization were compared in the 6 months before and after home care referral. Nonparametric longitudinal regression was performed to assess changes in hours of home care service use and zero-inflated Poisson regression was performed to assess changes in the number of 9-1-1 calls and ambulance transports to ED. RESULTS: During the 24-month study period, 2,382 individuals received a paramedic-initiated home care referral. After excluding individuals who died, were hospitalized, or were admitted to a nursing home, the final study cohort was 1,851. The proportion of the study population receiving home care services increased from 18.2% to 42.5% after referral, representing 450 additional people receiving services. In longitudinal regression analysis, there was an increase of 17.4 hours in total services per person in the six months after referral (95% CI: 1.7-33.1, p = 0.03). The mean number of 9-1-1 calls per person was 1.44 (SD 9.58) before home care referral and 1.20 (SD 7.04) after home care referral in the overall study cohort. This represented a 10% reduction in 9-1-1 calls (95% CI: 7-13%, p < 0.001) in Poisson regression analysis. The mean number of ambulance transports to ED per person was 0.91 (SD 8.90) before home care referral and 0.79 (SD 6.27) after home care referral, representing a 7% reduction (95% CI: 3-11%, p < 0.001) in Poisson regression analysis. When only the participants with complete paramedic and home care records were included in the analysis, the reductions in 9-1-1 calls and ambulance transports to ED were attenuated but remained statistically significant. CONCLUSIONS: Paramedic-initiated home care referrals in Toronto were associated with improved access to and use of home care services and may have been associated with reduced 9-1-1 calls and ambulance transports to ED.

Failing to protect humanitarian workers: lessons from Britain and Voluntary Aid Detachments in the Second World War.

This paper draws on official records of international and British organizations, newspaper reports, and volunteer memoirs to study the failure to protect humanitarian workers in the Second World War. The Second World War saw a significant expansion in the use of air warfare and flying missiles and these technological advances posed a grave threat to civilians and humanitarian workers. In this context, the International Committee of the Red Cross advocated unsuccessfully to restrict air warfare and create safe hospital zones. The British Government grappled with the tension between military and humanitarian objectives in setting its bombardment policy. Ultimately, humanitarian principles were neglected in pursuit of strategic aims, which endangered civilians and left humanitarian workers particularly vulnerable. British Voluntary Aid Detachment nurses experienced more than six-fold greater fatality rates than civil defence workers and the general population. The lessons from failures to protect humanitarian workers in the face of evolutions in warfare remain profoundly relevant.