Data Analytics in Higher Education: Key Concerns and Open Questions

“Big Data” and data analytics affect all of us. Data collection, analysis, and use on a large scale is an important and growing part of commerce, governance, communication, law enforcement, security, finance, medicine, and research. And the theme of this symposium, “Individual and Informational Privacy in the Age of Big Data,” is expansive; we could have long and fruitful discussions about practices, laws, and concerns in any of these domains. But a big part of the audience for this symposium is students and faculty in higher education institutions (HEIs), and the subject of this paper is data analytics in our own backyards. Higher education learning analytics (LA) is something that most of us involved in this symposium are familiar with. Students have encountered LA in their courses, in their interactions with their law school or with their undergraduate institutions, instructors use systems that collect information about their students, and administrators use information to help understand and steer their institutions. More importantly, though, data analytics in higher education is something that those of us participating in the symposium can actually control. Students can put pressure on administrators, and faculty often participate in university governance. Moreover, the systems in place in HEIs are more easily comprehensible to many of us because we work with them on a day-to-day basis. Students use systems as part of their course work, in their residences, in their libraries, and elsewhere. Faculty deploy course management systems (CMS) such as Desire2Learn, Moodle, Blackboard, and Canvas to structure their courses, and administrators use information gleaned from analytics systems to make operational decisions. If we (the participants in the symposium) indeed care about Individual and Informational Privacy in the Age of Big Data, the topic of this paper is a pretty good place to hone our thinking and put into practice our ideas

Insurance and Incentives for Medical Innovation

This paper studies the interactions between health insurance and the incentives for innovation. Although we focus on pharmaceutical innovation, our discussion applies to other industries producing novel technologies for sale in markets with subsidized demand. Standard results in the growth and productivity literatures suggest that firms in many industries may possess inadequate incentives to innovate. Standard results in the health literature suggest that health insurance leads to the overutilization of health care. Our study of innovation in the pharmaceutical industry emphasizes the interaction of these incentives. Because of the large subsidies to demand from health insurance, limits on the lifetime of patents and possibly limits on monopoly pricing may be necessary to ensure that pharmaceutical companies do not possess excess incentives for innovation.

Medical errors : Healthcare professionals’ perspective at a tertiary hospital in Kuwait

Medical errors are of economic importance and can contribute to serious adverse events for patients. Medical errors refer to preventable events resulting from healthcare interactions, whether these events harm the patient or not. In Kuwait, there is a paucity literature detailing the causes, forms, and risks of medical errors in their state-funded healthcare facilities. This study aimed to explore medical errors, their causes and preventive strategies in a Kuwait tertiary hospital based on the perceptions and experience of a cross-section of healthcare professionals using a questionnaire with 27 open (n = 10) and closed (n = 17) questions. The recruited healthcare professionals in this study included pharmacists, nurses, physicians, dentists, radiographers, hospital administrators, surgeons, nutritionists, and physiotherapists. The collected data were analysed quantitatively using descriptive statistics. A total of 203 participants filled and completed the survey questionnaire. The frequency of medical errors in Kuwait was found to be high at 60.3% ranging from incidences of prolonged hospital stays (32.9%), adverse events and life-threatening complications (32.3%), and fatalities (20.9%). The common medical errors result from incomplete instructions, incorrect dosage, and incorrect route of administration, diagnosis errors, and labelling errors. The perceived causes of these medical errors include high workload, lack of support systems, stress, medical negligence, inadequate training, miscommunication, poor collaboration, and non-adherence to safety guidelines among the healthcare professionals.Peer reviewe

A general method to access underexplored ylideneamino sulfates as interrupted Beckmann-type rearrangement intermediates

The Beckmann rearrangement of ketoximes to their corresponding amides, using a Brønsted acid-mediated fragmentation and migration sequence, has found wide-spread industrial application. We postulated that the development of a methodology to access ylideneamino sulfates using tributylsulfoammonium betaine (TBSAB) would afford isolable Beckmann-type intermediates and competent partners for subsequent rearrangement cascades. The ylideneamino sulfates generated, isolated as their tributylammonium salts, are sufficiently activated to undergo Beckmann rearrangement without additional reagent activation. The generation of sulfuric acid in situ from the ylideneamino sulfate giving rise to a routine Beckmann rearrangement and additional amide bond cleavage to the corresponding aniline was detrimental to reaction success. The screening of bases revealed inexpensive sodium bicarbonate to be an effective additive to prevent classic Brønsted acid-mediated fragmentation and achieve optimal conversions of up to 99%

The Relationship Between Suspected Adverse Drug Reactions Of HMG-Coa Reductase Inhibitors And Polypharmacology Using A National Registry Approach

Aims The aim of this study was to explore the suspected adverse drug reaction (ADR) data of five licensed statins in the UK: atorvastatin, fluvastatin, pravastatin, rosuvastatin and simvastatin. A secondary aim was to determine if there was a link between the polypharmacological properties of the statins and their associated muscle-related side effects. Methods The chemical database of bioactive molecules with drug-like properties, European Molecular Biology Laboratory (ChEMBL) was used to obtain data on the pharmacological interactions of statins with human proteins. The Medicines and Healthcare products Regulatory Agency (MHRA) Yellow Card Scheme was used to obtain reports of suspected ADRs from 2018 to 2022. The OpenPrescribing database was used to obtain the prescribing rates for statistical interpretation. Results The study found no significant difference between the statins in causing ADRs across all organ classes (X2, P &gt; .05). Fluvastatin was found to have a higher incidence of ADRs/100,000 Rx across multiple organ classes. Conclusion No significant difference was found between the suspected ADR incidence of the statins across all organ classes. No evidence of higher intensity statins causing more muscle symptoms than moderate intensity statins was found.<br/

Rearrangement of Arylsulfamates and Sulfates To Para-Sulfonyl Anilines and Phenols

The C(sp2)-aryl sulfonate functional group is found in bioactive molecules, but their synthesis can involve extreme temperatures (&gt;190 °C or flash vacuum pyrolysis) and strongly acidic reaction conditions. Inspired by the 1917 Tyrer industrial process for a sulfa dye that involved an aniline N(sp2)-SO3 intermediate en route to a C(sp2)-SO3 rearranged product, we investigated tributylsulfoammonium betaine (TBSAB) as a milder N-sulfamation to C-sulfonate relay reagent. Initial investigations of a stepwise route involving TBSAB on selected anilines at room temperature enabled the isolation of N(sp2)-sulfamate. Subsequent thermal rearrangement demonstrated the intermediary of a sulfamate en route to the sulfonate; however, it was low-yielding. Investigation of the N-sulfamate to C--sulfonate mechanism through control experiments with variation at the heteroatom positions and kinetic isotope experiments (KIEH/D) confirmed the formation of a key N(sp2)-SO3 intermediate and further confirmed an intermolecular mechanism. Furthermore, compounds without an accessible nitrogen (or oxygen) lone pair did not undergo sulfamation- (or sulfation) -to-sulfonation under these conditions. A one-pot sulfamation and thermal sulfonation reaction was ultimately developed and explored on a range of aniline and heterocyclic scaffolds with high conversions, including N(sp2)-sulfamates (O(sp2)-sulfates) and C(sp2)-sulfonates, in up to 99 and 80% (and 88% for a phenolic example) isolated yield, respectively. Encouragingly, the ability to modulate the ortho-para selectivity of the products obtained was observed under thermal control. A sulfonated analog of the intravenous anesthetic propofol was isolated (88% yield), demonstrating a proof-of-concept modification of a licensed drug alongside a range of nitrogen- and sulfur-containing heterocyclic fragments used in drug discovery

The Temptation of Data-enabled Surveillance: Are Universities the Next Cautionary Tale?

There is increasing concern about “surveillance capitalism,” whereby for-profit companies generate value from data, while individuals are unable to resist (Zuboff 2019). Non-profits using data-enabled surveillance receive less attention. Higher education institutions (HEIs) have embraced data analytics, but the wide latitude that private, profit-oriented enterprises have to collect data is inappropriate. HEIs have a fiduciary relationship to students, not a narrowly transactional one (see Jones et al, forthcoming). They are responsible for facets of student life beyond education. In addition to classrooms, learning management systems, and libraries, HEIs manage dormitories, gyms, dining halls, health facilities, career advising, police departments, and student employment. HEIs collect and use student data in all of these domains, ostensibly to understand learner behaviors and contexts, improve learning outcomes, and increase institutional efficiency through “learning analytics” (LA). ID card swipes and Wi-Fi log-ins can track student location, class attendance, use of campus facilities, eating habits, and friend groups. Course management systems capture how students interact with readings, video lectures, and discussion boards. Application materials provide demographic information. These data are used to identify students needing support, predict enrollment demands, and target recruiting efforts. These are laudable aims. However, current LA practices may be inconsistent with HEIs’ fiduciary responsibilities. HEIs often justify LA as advancing student interests, but some projects advance primarily organizational welfare and institutional interests. Moreover, LA advances a narrow conception of student interests while discounting privacy and autonomy. Students are generally unaware of the information collected, do not provide meaningful consent, and express discomfort and resigned acceptance about HEI data practices, especially for non-academic data (see Jones et al. forthcoming). The breadth and depth of student information available, combined with their fiduciary responsibility, create a duty that HEIs exercise substantial restraint and rigorous evaluation in data collection and use