168 research outputs found

    Active Social Media Management: The Case of Health Care

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    Given the demand for authentic personal interactions over social media, it is unclear how much firms should actively manage their social media presence. We study this question empirically in a health care setting. We show that active social media management drives more user-generated content. However, we find that this is due to an incremental increase in user postings from an organization's employees rather than from its clients. This result holds when we explore exogenous variation in social media policies, employees, and clients that are explained by medical marketing laws, medical malpractice laws, and distortions in Medicare incentives. Further examination suggests that content being generated mainly by employees can be avoided if a firm's postings are entirely client focused. However, most firm postings seem not to be specifically targeted to clients' interests, instead highlighting more general observations or achievements of the firm itself. We show that untargeted postings like these provoke activity by employees rather than clients. This may not be a bad thing because employee-generated content may help with employee motivation, recruitment, or retention, but it does suggest that social media should not be funded or managed exclusively as a marketing function of the firm

    Frontiers of Health Policy: Digital Data and Personalized Medicine

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    This paper argues that due to two unstoppable mechanisms, some of the most pressing future questions in health policy will relate to the use of digital technologies to analyze data concerning patient health. The first mechanism is the shift away from a system where patient data was essentially temporary and not intended to be reused or easily accessed again, to a new digital world where patient data is easily transferred and accessed repeatedly. The second mechanism is a fundamental deepening of the nature of patient data that enables increased personalization of health care for each individual patient, based on not only their detailed medical history, but also their likely future medical history that can be projected for their genetic makeup. We summarize our research investigating the potential consequences of policies in this new world where patient data is virtually costless to store, share, and individualize. We emphasize that issues of data management and privacy are now at the forefront of health policy considerations. Digital data and digital technologies have the potential to transform medicine through two mechanisms. First, digital patient data is far easier to share and access than traditional paper records. This has many potential upsides, but also raises the question of how the potential benefits of sharing patient data are moderated by privacy concerns. Second, the advent of digital storage has now made it possible to store, virtually costlessly, vast swathes of data about any one individual patient. Such individualized data also enables a patient-centric approach to medicine, often referred to as “personalized” or “precision” medicine, based on that individual patient’s genetic makeup. This article discusses the potential benefits and possible policy consequences of this digital shift. It emphasizes that the benefits of digital technologies are found when data is actually transferred and repeatedly accessed. This emphasizes that policies that wish to encourage the potential upside of digital technologies should emphasize easy data transfer. Empirical evidence suggests that health-care providers may not individually have the right incentives to share data, and therefore if a policy aims to encourage data transfer it needs to not only subsidize the adoption of digital technologies, but also make sure that there are the right incentives to use these technologies to share data. Often, well-meaning policies toward data security and data privacy can hamper this process. This article also suggests that there are distinct concerns related to the deepening and individualizing of data that is associated with personalized medicine, and that while there is potentially a large upside in terms of medical outcomes, the risks associated with this data are unusual. If policymakers seek to encourage personalized medicine, they might be especially successful to employ an approach to data management that gives control of the use of the data to the patient.National Science Foundation (U.S.) (Career Award 6923256

    Electronic Discovery and the Adoption of Information Technology

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    After firms adopt electronic information and communication technologies, their decision-making leaves a trail of electronic information that may be more extensive and accessible than a paper trail. We ask how the expected costs of litigation affect decisions to adopt technologies, such as electronic medical records (EMRs), which leave more of an electronic trail. EMRs allow hospitals to document electronically both patient symptoms and health providers’ reactions to those symptoms and may improve the quality of care that makes the net impact of their adoption on expected litigation costs ambiguous. This article studies the impact of state rules that facilitate the use of electronic records in court. We find evidence that hospitals are one-third less likely to adopt EMRs after these rules are enacted

    Does Workplace Competition Increase Labor Supply? Evidence from a Field Experiment

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    This paper develops a novel field experiment to test the implicit prediction of tournament theory thatcompetition increases work time and can therefore contribute to the long work hours required in eliteoccupations. A majority of workers in the treatment without explicit financial incentives worked pastthe minimum time, but awarding a tournament prize increased work time and effort by over 80% andlowered costs of effort or output by over a third. Effort was similar with alternative (piece rate, low-prizetournament) bonuses. Men worked longer than women in the high-prize tournament, but for the sameduration in other treatments

    Effects of COVID-19 shutdowns on domestic violence in US cities

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    We empirically investigate the impact of COVID-19 shutdowns on domestic violence using incident-level data on both domestic-related calls for service and crime reports of domestic violence assaults from the 18 major US police departments for which both types of records are available. Although we confirm prior reports of an increase in domestic calls for service at the start of the pandemic, we find that the increase preceded mandatory shutdowns, and there was an incremental decline following the government imposition of restrictions. We also find no evidence that domestic violence crimes increased. Rather, police reports of domestic violence assaults declined significantly during the initial shutdown period. There was no significant change in intimate partner homicides during shutdown months and victimization survey reports of intimate partner violence were lower. Our results fail to support claims that shutdowns increased domestic violence and suggest caution before drawing inference or basing policy solely on data from calls to police

    Privacy Protection and Technology Diffusion: The Case of Electronic Medical Records

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    Some policymakers argue that consumers need legal protection of their privacy before they adopt interactive technologies. Others contend that privacy regulations impose costs that deter adoption. We contribute to this growing debate by quantifying the effect of state privacy regulation on the diffusion of Electronic Medical Record technology (EMR). EMR allows medical providers to store and exchange patient information using computers rather than paper records. Hospitals may not adopt EMR if patients feel their privacy is not safeguarded by regulation. Alternatively, privacy protection may inhibit adoption if hospitals cannot benefit from exchanging patient information with one another. In the US, medical privacy laws that restrict the ability of hospitals to disclose patient information vary across time and across states. We exploit this variation to explore how privacy laws affect whether hospitals adopt EMR. Our results suggest that inhibition of EMR's network benefits reduces hospital adoption by up to 25 percent. We find similar evidence when we control for the endogeneity of state laws using variation in signups to the 'Do Not Call' list

    System Size, Lock-in and Network Effects for Patient Records

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    We examine empirically whether the size of a firm using a network affects the scope of its network usage, and consequently network effects and lock-in within the network. We use the example of hospital information exchange. We find that hospitals in larger hospital systems are more likely to exchange electronic patient information only within their system and less likely to exchange patient information externally. We show that hospitals are also more likely to exchange information externally if others hospitals also do so. This implies that the disinclination of large hospital systems to exchange data externally harms overall levels of network use. Our results highlight that makers of technology policy designed to encourage the optimal use of networks should consider regulating the behavior of network users as well as technology vendors

    Frontotemporal dementia and its subtypes: a genome-wide association study

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    SummaryBackground Frontotemporal dementia (FTD) is a complex disorder characterised by a broad range of clinical manifestations, differential pathological signatures, and genetic variability. Mutations in three genes—MAPT, GRN, and C9orf72—have been associated with FTD. We sought to identify novel genetic risk loci associated with the disorder. Methods We did a two-stage genome-wide association study on clinical FTD, analysing samples from 3526 patients with {FTD} and 9402 healthy controls. To reduce genetic heterogeneity, all participants were of European ancestry. In the discovery phase (samples from 2154 patients with {FTD} and 4308 controls), we did separate association analyses for each {FTD} subtype (behavioural variant FTD, semantic dementia, progressive non-fluent aphasia, and {FTD} overlapping with motor neuron disease FTD-MND), followed by a meta-analysis of the entire dataset. We carried forward replication of the novel suggestive loci in an independent sample series (samples from 1372 patients and 5094 controls) and then did joint phase and brain expression and methylation quantitative trait loci analyses for the associated (p<5 × 10−8) single-nucleotide polymorphisms. Findings We identified novel associations exceeding the genome-wide significance threshold (p<5 × 10−8). Combined (joint) analyses of discovery and replication phases showed genome-wide significant association at 6p21.3, \{HLA\} locus (immune system), for rs9268877 (p=1·05 × 10−8; odds ratio=1·204 95% \{CI\} 1·11–1·30), rs9268856 (p=5·51 × 10−9; 0·809 0·76–0·86) and rs1980493 (p value=1·57 × 10−8, 0·775 0·69–0·86) in the entire cohort. We also identified a potential novel locus at 11q14, encompassing RAB38/CTSC (the transcripts of which are related to lysosomal biology), for the behavioural \{FTD\} subtype for which joint analyses showed suggestive association for rs302668 (p=2·44 × 10−7; 0·814 0·71–0·92). Analysis of expression and methylation quantitative trait loci data suggested that these loci might affect expression and methylation in cis. Interpretation Our findings suggest that immune system processes (link to 6p21.3) and possibly lysosomal and autophagy pathways (link to 11q14) are potentially involved in FTD. Our findings need to be replicated to better define the association of the newly identified loci with disease and to shed light on the pathomechanisms contributing to FTD. Funding The National Institute of Neurological Disorders and Stroke and National Institute on Aging, the Wellcome/MRC Centre on Parkinson's disease, Alzheimer's Research UK, and Texas Tech University Health Sciences Center

    Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

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    We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development
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