A qualitative study of health information technology in the Canadian public health system

Background: Although the adoption of health information technology (HIT) has advanced in Canada over the past decade, considerable challenges remain in supporting the development, broad adoption, and effective use of HIT in the public health system. Policy makers and practitioners have long recognized that improvements in HIT infrastructure are necessary to support effective and efficient public health practice. The objective of this study was to identify aspects of health information technology (HIT) policy related to public health in Canada that have succeeded, to identify remaining challenges, and to suggest future directions to improve the adoption and use of HIT in the public health system. Methods: A qualitative case study was performed with 24 key stakeholders representing national and provincial organizations responsible for establishing policy and strategic direction for health information technology. Results: Identified benefits of HIT in public health included improved communication among jurisdictions, increased awareness of the need for interoperable systems, and improvement in data standardization. Identified barriers included a lack of national vision and leadership, insufficient investment, and poor conceptualization of the priority areas for implementing HIT in public health. Conclusions: The application of HIT in public health should focus on automating core processes and identifying innovative applications of HIT to advance public health outcomes. The Public Health Agency of Canada should develop the expertise to lead public health HIT policy and should establish a mechanism for coordinating public health stakeholder input on HIT policy

Consumer Directed Healthcare: Except for the Healthy and Wealthy It’s Unwise

Many politicians and business leaders are advocating high deductible health insurance plans linked with health savings accounts—so-called consumer-directed healthcare. These policies penalize the sick, discourage needed care (especially primary and preventive care), and direct tax subsidies towards the wealthiest Americans. They offer little hope of slowing the growth of health care costs and add further bureaucratic costs and complexity to our health care financing system

A bayesian way to correct for measurement error in drug risk estimates from EHR data.

Introduction Data from electronic medical records is now readily available and records information needed in pharmacoepidemiological studies not usually found in administrative data such as risk factors and biometrics. Yet, EMR data leads to measurement error due to primary non-adherence. Bayesian bias correction could provide corrected estimates from administrative data. Objectives and Approach We present a method for correcting risk estimates from EMR data using linked data. In our example, we estimate the risk of cardiovascular events from oral-hypoglycemics in patients with type-2 diabetes in Boston, Quebec, and the UK between 2009 and 2012. Using linked EMR and administrative data in Quebec, we compute a positive and negative predicting value of prescription on dispensation for each class of oral-hypoglycemics. The cardiovascular risk is then analysed using a bayesian Weibull survival model adjusted for potential confounders. A similar model is then computed that accounts for exposure measurement error using the PPV and NPV. Results The Quebec and Boston cohorts have similar sizes with 1197 and 2346 patients, but the UK was bigger at 41370 patients. In Quebec's data, there were important differences in PPV and NPV by class of oral-hypoglycemics with PPVs for Biguanides at 0.81, Sulphonylureas at 0.65, and others at 0.50. The pattern for NPV differed with the same classes having respectively values of 0.56, 0.97, and 0.99. Estimates from the naïve model are typical of similar analysis but compared to their correction, they were generally overprecise and biased towards the null. The adjusted estimated were adequately representing the increased uncertainty with hazard ratios for Sulphonylureas going from 1.72 (1.22, 2.41) to 3.19 (1.36, 5.93), and from 1.09 (0.86, 1.39) to 1.05 (0.45, 2.16) for no drugs Conclusion/Implications Bayesian adjustment for measurement error allowed us to use linked data to regenerate uncertainty and to correct the bias in our risk estimates. Our approach was impacted by the observed low predictive value of prescribing, by reduced transportability of our PPV and NPV estimates, and other sources of bias

Using linked administrative, clinical and primary data to explore the impact of and factors associated with non-adherence to in-hospital medication changes in 30-days post hospital discharge

Introduction Identifying strategies to prevent hospital readmissions remains elusive since the reasons for returning to hospital can include a number of interlinked patient, health provider and system level factors. The impact of patient medications are of significant interest since a large proportion of re-admissions are related to adverse drug events. Objectives and Approach The objective was to determine which factors are associated with non-adherence to in-hospital medications and the impact of non-adherence on re-hospitalization, emergency department visits and death in the 30-days post discharge for patients admitted at two tertiary care academic hospitals in Montreal, Quebec between October 2014 and May 2016. Non-adherence to in-hospital changes was measured by comparing patient discharge prescriptions (patient chart) to medications filled in community 30-days post-discharge (dispensing data) and included i) community medications stopped in-hospital and filled post-discharge, ii) community medications modified in-hospital but not filled at the modified daily-dose, and iii) new medications not filled post-discharge. Results Among 2,895 included patients, mean age was 70 (SD 15) and 58% were males. A median of 4 in-hospital medication changes were made (IQR:3-6) and 54% of patients were non-adherent to at least one change. Multivariable Poisson models suggested that the most important factor associated with the number of new medications not filled post discharge was out of pocket cost; for each additional $10 increase in costs there was a 20% increase in the number of new medications not filled. Multivariable time-varying Cox models suggested that in patients who filled medications post-discharge, selective non-adherence to new and discontinued medications reduced the risk adverse health outcomes in 30-days, while not filling any medications post discharge more than doubled the risk of an adverse event in 30-days. Conclusion/Implications Not only did the majority of patients not follow all medication changes that were made during hospitalization, the extent to which this occurred significantly impacted the risk of hospital re-admissions and ED visits. Policy and patient level interventions should be developed specifically targeting barriers for adherence to medication changes

International Comparison in Opiate Prescribing for New Users in Primary Care using Electronic Medical Record Data

Introduction The opioid epidemic in North America has, in part, been attributed to an increase in opiate use for non-cancer pain and the prescription of more potent molecules. In contrast, the United Kingdom appears unaffected by this crisis, possibly because of differences in primary care prescribing, or health system policies. Objective To determine if there are differences in opiate prescribing for new users in primary care in the United Kingdom, United States, and Canada. Approach Electronic health record data from Quebec, Canada (MOXXI), the United States (Partners Health Care, Boston MA), and the United Kingdom (CPRD random sample of 600,000) were used to identify new users of opiates (no prior prescription in 2 years), at least 18 years old between 2006-2016. Cancer patients were excluded after harmonizing equivalent READ and ICD9/10 codes. Generic drug names in each jurisdiction were mapped to the WHO ATC classification, and characterized using morphine milligram equivalents (MME). Results Overall 655,877 new users were identified, of whom 78% of 58,286 (U.S.), 88% of 6,251 (Canada), and 96% of 600,000 (UK) were non-cancer patients. Mean age of new users was 49 (SD 16) in the US, 57 (SD 16) in Canada, and 52 (SD 19) in the UK. 57.6% (UK) to 67.3% (US) of new users were women. In the UK, 86.5% of patients were started on codeine (MME:0.15), compared to 43.9% in Canada and 8.5% in the U.S. In the U.S 65.0\% were started on oxycodone (MME:1.5), and 10.9% on hydrocodone (MME:1). In Canada, tramadol (18.2%; MME: 0.1) followed by oxycodone (13.2%) were the next most commonly prescribed drugs. Conclusion/Implications Substantial differences in opioid prescribing practices for non-cancer pain were observed between the UK and Canadian and United States sites. The predilection to start patients on more potent opiates in North America may be a contributing cause to the opiate epidemic

Adverse performance effects of acute lorazepam administration in elderly long-term users: pharmacokinetic and clinical predictors.

BACKGROUND: The benzodiazepine lorazepam is widely utilized in the treatment of elderly individuals with anxiety disorders and related conditions. Negative effects of acute lorazepam administration on cognitive performance, especially memory, have been reported in both previously untreated elderly and in individuals who have received short term (up to three weeks) treatment with therapeutic doses. However, it remains unclear if these adverse cognitive effects also persist after long-term use, which is frequently found in clinical practice. METHODS: Cognitively intact elderly individuals (n=37) on long-term (at least three months) daily treatment with lorazepam were studied using a double-blind placebo-controlled cross-over study design. Subjects were administered their highest daily unit dose of lorazepam (0.25-3.00 mg) or placebo on different days, approximately 1 week apart in a random order, and were assessed on memory, psychomotor speed, and subjective mood states. RESULTS: Subjects had significantly poorer recall and slowed psychomotor performance following acute lorazepam administration. There were no significant effects on self-ratings of mood, sedation, or anxiety in the whole group, but secondary analyses suggested a differential response in subjects with Generalized Anxiety Disorder. CONCLUSIONS: The reduced recall and psychomotor slowing that we observed, along with an absence of significant therapeutic benefits, following acute lorazepam administration in elderly long-term users reinforces the importance of cognitive toxicity as a clinical factor in benzodiazepine use, especially in this population

Cardiovascular comorbidities among public health clinic patients with diabetes: the Urban Diabetics Study

BACKGROUND: We sought to determine the frequency and distribution of cardiovascular comorbidities in a large cohort of low-income patients with diabetes who had received primary care for diabetes at municipal health clinics. METHODS: Outpatient data from the Philadelphia Health Care Centers was linked with hospital discharge data from all Pennsylvania hospitals and death certificates. RESULTS: Among 10,095 primary care patients with diabetes, with a mean observation period of 4.6 years (2.8 after diabetes diagnosis), 2,693 (14.3%) were diagnosed with heart disease, including 270 (1.4%) with myocardial infarction and 912 (4.8%) with congestive heart failure. Cerebrovascular disease was diagnosed in 588 patients (3.1%). Over 77% of diabetic patients were diagnosed with hypertension. Incidence rates of new complications ranged from 0.6 per 100 person years for myocardial infarction to 26.5 per 100 person years for hypertension. Non-Hispanic whites had higher rates of myocardial infarction, and Hispanics and Asians had fewer comorbid conditions than African Americans and non-Hispanic whites. CONCLUSION: Cardiovascular comorbidities were common both before and after diabetes diagnosis in this low-income cohort, but not substantially different from mixed-income managed care populations, perhaps as a consequence of access to primary care and pharmacy services

Star Formation and Dynamics in the Galactic Centre

The centre of our Galaxy is one of the most studied and yet enigmatic places in the Universe. At a distance of about 8 kpc from our Sun, the Galactic centre (GC) is the ideal environment to study the extreme processes that take place in the vicinity of a supermassive black hole (SMBH). Despite the hostile environment, several tens of early-type stars populate the central parsec of our Galaxy. A fraction of them lie in a thin ring with mild eccentricity and inner radius ~0.04 pc, while the S-stars, i.e. the ~30 stars closest to the SMBH (<0.04 pc), have randomly oriented and highly eccentric orbits. The formation of such early-type stars has been a puzzle for a long time: molecular clouds should be tidally disrupted by the SMBH before they can fragment into stars. We review the main scenarios proposed to explain the formation and the dynamical evolution of the early-type stars in the GC. In particular, we discuss the most popular in situ scenarios (accretion disc fragmentation and molecular cloud disruption) and migration scenarios (star cluster inspiral and Hills mechanism). We focus on the most pressing challenges that must be faced to shed light on the process of star formation in the vicinity of a SMBH.Comment: 68 pages, 35 figures; invited review chapter, to be published in expanded form in Haardt, F., Gorini, V., Moschella, U. and Treves, A., 'Astrophysical Black Holes'. Lecture Notes in Physics. Springer 201