The use of electronic health records (EHR) is widely recommended as a means to improve the quality, safety and efficiency of US healthcare. Relatively little is known, however, about how implementation and use of this technology affects the work of clinicians and support staff who provide primary health care in small, independent practices.
To study the impact of EHR use on clinician and staff work burden in small, community-based primary care practices.
We conducted in-depth field research in seven community-based primary care practices. A team of field researchers spent 9–14 days over a 4–8 week period observing work in each practice, following patients through the practices, conducting interviews with key informants, and collecting documents and photographs. Field research data were coded and analyzed by a multidisciplinary research team, using a grounded theory approach.
All practice members and selected patients in seven community-based primary care practices in the Northeastern US.
The impact of EHR use on work burden differed for clinicians compared to support staff. EHR use reduced both clerical and clinical staff work burden by improving how they check in and room patients, how they chart their work, and how they communicate with both patients and providers. In contrast, EHR use reduced some clinician work (i.e., prescribing, some lab-related tasks, and communication within the office), while increasing other work (i.e., charting, chronic disease and preventive care tasks, and some lab-related tasks). Thoughtful implementation and strategic workflow redesign can mitigate the disproportionate EHR-related work burden for clinicians, as well as facilitate population-based care.
The complex needs of the primary care clinician should be understood and considered as the next iteration of EHR systems are developed and implemented.
electronic health records; primary care; work burden; qualitative research
To identify key principles for establishing a national clinical decision support (CDS) knowledge sharing framework.
Materials and methods
As part of an initiative by the US Office of the National Coordinator for Health IT (ONC) to establish a framework for national CDS knowledge sharing, key stakeholders were identified. Stakeholders' viewpoints were obtained through surveys and in-depth interviews, and findings and relevant insights were summarized. Based on these insights, key principles were formulated for establishing a national CDS knowledge sharing framework.
Nineteen key stakeholders were recruited, including six executives from electronic health record system vendors, seven executives from knowledge content producers, three executives from healthcare provider organizations, and three additional experts in clinical informatics. Based on these stakeholders' insights, five key principles were identified for effectively sharing CDS knowledge nationally. These principles are (1) prioritize and support the creation and maintenance of a national CDS knowledge sharing framework; (2) facilitate the development of high-value content and tooling, preferably in an open-source manner; (3) accelerate the development or licensing of required, pragmatic standards; (4) acknowledge and address medicolegal liability concerns; and (5) establish a self-sustaining business model.
Based on the principles identified, a roadmap for national CDS knowledge sharing was developed through the ONC's Advancing CDS initiative.
The study findings may serve as a useful guide for ongoing activities by the ONC and others to establish a national framework for sharing CDS knowledge and improving clinical care.
Knowledge management; clinical decision support systems; office of the national coordinator for health information technology; meaningful use; standards
Aims: Nrf2 is an essential transcription factor for protection against oxidant disorders. However, its role in organ development and neonatal disease has received little attention. Therapeutically administered oxygen has been considered to contribute to bronchopulmonary dysplasia (BPD) in prematurity. The current study was performed to determine Nrf2-mediated molecular events during saccular-to-alveolar lung maturation, and the role of Nrf2 in the pathogenesis of hyperoxic lung injury using newborn Nrf2-deficient (Nrf2−/−) and wild-type (Nrf2+/+) mice. Results: Pulmonary basal expression of cell cycle, redox balance, and lipid/carbohydrate metabolism genes was lower while lymphocyte immunity genes were more highly expressed in Nrf2−/− neonates than in Nrf2+/+ neonates. Hyperoxia-induced phenotypes, including mortality, arrest of saccular-to-alveolar transition, and lung edema, and inflammation accompanying DNA damage and tissue oxidation were significantly more severe in Nrf2−/− neonates than in Nrf2+/+ neonates. During lung injury pathogenesis, Nrf2 orchestrated expression of lung genes involved in organ injury and morphology, cellular growth/proliferation, vasculature development, immune response, and cell–cell interaction. Bioinformatic identification of Nrf2 binding motifs and augmented hyperoxia-induced inflammation in genetically deficient neonates supported Gpx2 and Marco as Nrf2 effectors. Innovation: This investigation used lung transcriptomics and gene targeted mice to identify novel molecular events during saccular-to-alveolar stage transition and to elucidate Nrf2 downstream mechanisms in protection from hyperoxia-induced injury in neonate mouse lungs. Conclusion:
Nrf2 deficiency augmented lung injury and arrest of alveolarization caused by hyperoxia during the newborn period. Results suggest a therapeutic potential of specific Nrf2 activators for oxidative stress-associated neonatal disorders including BPD. Antioxid. Redox Signal. 00, 000–000.
Electronic health record (EHR) systems are often modified through the addition of new features over time. Few studies have examined the specific effects of such changes. We examined whether implementation of a bidirectional laboratory interface for order entry and data reporting within an existing ambulatory EHR would result in more prompt responses to laboratory indications for antiretroviral therapy (ART) changes or in improved communication with HIV+ patients about relevant laboratory results.
We conducted a single-arm intervention study comparing the timeliness of ART regimen changes, HIV viral load (VL) outcomes and patient-reported assessments of care before and after implementation of a laboratory data exchange interface within an existing EHR, without changing the EHR ordering or results reporting user interface. Patient data was extracted from the EHR covering the period from 1 year before to 2 years after the intervention for a cohort of 1181 patients who had received care during the baseline year. The timeliness of ART changes was represented by the days from a laboratory-result “signal” (CD4 dropping below 350 or 200 or VL increasing by a half-log or to a value over 100,000) to an ART-change “response.” Patient assessments of care were collected by interviewing 100 anonymous patients at baseline and another 125 at 2 years post-intervention.
A total of 171 laboratory “signal” events were followed within 80 days by a change in ART therapy. The mean time from signal to therapy change (adjusted for clustering by patient) initially increased, from 37.7 days during the pre-intervention year to 48.2 days during the quarter immediately following activation of the lab intervention. It then declined to a mean of 31.4 days over the remaining 21 months of observation (P=0.03 for the 6-day improvement from the pre-period). A majority of patients (65%) achieved undetectable VL values by the end of the observation period; faster signal-response times were not associated with greater achievement of undetectable VL. Patients rated communication about laboratory tests more highly after implementation of the interface (91 vs. 83 on a 100-point scale, P=0.01); ratings were not higher for other aspects of care.
Adding laboratory data exchange interfaces within existing EHRs holds promise for improving HIV care, both in the timeliness of responses to important laboratory results and in the quality of provider communication about lab tests. However, the benefits from this incremental change may be modest unless more extensive redesign of laboratory follow-up workflows is undertaken, with support from enhanced user interfaces that take advantage of the laboratory information delivered. Providers should also consider increased staffing to compensate for dips in follow-up performance during the initial post-implementation months.
HIV Infections/prevention & control; Computer Communication Networks; Ambulatory Care Information Systems; Clinical Laboratory Information Systems; Medical Order Entry Systems; Electronic Health Records; Communication; Evaluation Studies
To estimate the impact of chronic medical conditions on depression diagnosis, treatment, and follow-up care in primary care settings.
This was a cross-sectional study that used interviewer-administered surveys and medical record reviews. Three hundred fifteen participants were recruited from 3 public primary care clinics. Depression diagnosis, guideline-concordant treatment, and follow-up care were the primary outcomes examined in individuals with depression alone compared with individuals with depression and chronic medical conditions measured using the Charlson Comorbidity Index (CCI).
Physician diagnosis of depression (32.6%), guideline-concordant depression treatment (32.7%), and guideline-concordant follow-up care (16.3%) were all low. Logistic regression analysis showed no significant difference in the likelihood of depression diagnosis, guideline-concordant treatment, or follow-up care in individuals with depression alone compared with those with both depression and chronic medical conditions. Participants with severe depression were, however, twice as likely to receive a diagnosis of depression as participants with moderate depression. In addition, participants with moderately severe and severe depression received much less appropriate follow-up care than participants with moderate depression. Among participants receiving a depression diagnosis, 74% received guideline-concordant treatment.
Physician depression care in primary care settings is not influenced by competing demands for care for other comorbid medical conditions.
The p53 tumor suppressor gene has a common polymorphism at codon 72 that alters its function. We previously reported that the proline 72 polymorphic variant of p53 (P72) demonstrates increased ability to transactivate a subset of genes, relative to arginine 72 (R72); one of these genes is macrophage colony stimulating factor (CSF1). At present, the mechanism(s) underlying the increased transcriptional activity of P72 toward genes like CSF1 have not been completely elucidated. Additionally, the consequences of increased transcription of genes like CSF1 by the P72 variant to the downstream p53 pathway are unknown. In this report, we address these issues. We show that the CSF1 gene contains a conserved binding site for p53, and interestingly that the P72 variant shows increased ability to bind to this site. Moreover, we show that increased CSF1/CSF1R signaling in P72 cells feeds back on the p53 pathway to enhance p53 phosphorylation, levels, and transactivation of target genes, particularly the cyclin-dependent kinase inhibitor p21 (CDKN1A). This leads to an increase in p53-mediated growth arrest, along with a concomitant decrease in apoptosis. Notably, the CSF1/CSF1R signaling axis is overexpressed in several epithelial cancers, and there is clinical evidence that this pathway plays a role in radio-resistance of some cancers. We show that cells expressing CSF1 and CSF1R are indeed radio-resistant, and further, that this effect requires p53. These combined data are the first to implicate the CSF1/CSF1R pathway in the decision between p53-mediated growth arrest and apoptosis. They are also the first to highlight a cytokine as influential in cell fate determined by p53 in epithelial cells. Finally, these data may explain the association of the P72 variant and the CSF1/CSF1R pathway with increased senescence and radio-resistance in some epithelial tumor types.
To develop a set of high-severity, clinically significant drug–drug interactions (DDIs) for use in electronic health records (EHRs).
A panel of experts was convened with the goal of identifying critical DDIs that should be used for generating medication-related decision support alerts in all EHRs. Panelists included medication knowledge base vendors, EHR vendors, in-house knowledge base developers from academic medical centers, and both federal and private agencies involved in the regulation of medication use. Candidate DDIs were assessed by the panel based on the consequence of the interaction, severity levels assigned to them across various medication knowledge bases, availability of therapeutic alternatives, monitoring/management options, predisposing factors, and the probability of the interaction based on the strength of evidence available in the literature.
Of 31 DDIs considered to be high risk, the panel approved a final list of 15 interactions. Panelists agreed that this list represented drugs that are contraindicated for concurrent use, though it does not necessarily represent a complete list of all such interacting drug pairs. For other drug interactions, severity may depend on additional factors, such as patient conditions or timing of co-administration.
The panel provided recommendations on the creation, maintenance, and implementation of a central repository of high severity interactions.
A set of highly clinically significant drug-drug interactions was identified, for which warnings should be generated in all EHRs. The panel highlighted the complexity of issues surrounding development and implementation of such a list.
Alerts; Medication-related decision support; electronic health records; alert fatigue; Office of the National Coordinator for health information Technology; drug-drug interaction; clinical decision support; medical informatics; knowledge bases; knowledge acquisition and knowledge management; knowledge representations; uncertain reasoning and decision theory; designing usable (responsive) resources and systems; personal health records and self-care systems; knowledge acquisition and knowledge management; demonstrating return on it investment; other specific EHR applications (results review); medication administration; disease progression; patient safety; decision support; data exchange
High override rates for drug-drug interaction (DDI) alerts in electronic health records (EHRs) result in the potentially dangerous consequence of providers ignoring clinically significant alerts. Lack of uniformity of criteria for determining the severity or validity of these interactions often results in discrepancies in how these are evaluated. The purpose of this study was to identify a set of criteria for assessing DDIs that should be used for the generation of clinical decision support (CDS) alerts in EHRs.
We conducted a 20-year systematic literature review of MEDLINE and EMBASE to identify characteristics of high-priority DDIs. These criteria were validated by an expert panel consisting of medication knowledge base vendors, EHR vendors, in-house knowledge base developers from academic medical centers, and both federal and private agencies involved in the regulation of medication use.
Forty-four articles met the inclusion criteria for assessing characteristics of high-priority DDIs. The panel considered five criteria to be most important when assessing an interaction- Severity, Probability, Clinical Implications of the interaction, Patient characteristics, and the Evidence supporting the interaction. In addition, the panel identified barriers and considerations for being able to utilize these criteria in medication knowledge bases used by EHRs.
A multi-dimensional approach is needed to understanding the importance of an interaction for inclusion in medication knowledge bases for the purpose of CDS alerting. The criteria identified in this study can serve as a first step towards a uniform approach in assessing which interactions are critical and warrant interruption of a provider’s workflow.
Clinical decision support; Drug-drug interaction; Medication-related decision support system; Electronic health record; Alerts
To investigate provider opinions about responsibility for medication adherence and examine physician-patient interactions to illustrate how adherence discussions are initiated.
Focus group discussions with healthcare providers and audiotaped outpatient office visits with a separate group of providers.
Focus group participants were recruited from multi-specialty practice groups in New Jersey and Washington, D.C. Outpatient office visits were conducted in primary care offices in Northern California.
Twenty-two healthcare providers participated in focus group discussions. One hundred patients aged 65 and older and 28 primary care physicians had their visits audiotaped.
Inductive content analysis of focus groups and audiotaped encounters.
Focus group analyses indicated that providers feel responsible for assessing medication adherence during office visits and for addressing mutable factors underlying nonadherence. However, they believed that patients are ultimately responsible for taking medications and voiced reluctance about confronting patients about nonadherence. The 100 patients participating in audio taped encounters were taking a total of 410 medications. Of these, 254 (62%) were discussed in a way that might touch upon adherence; physicians made simple inquiries about current patient medication use for 31.5%, but they made in-depth inquiries about adherence for only 4.3%. Of 39 identified instances of nonadherence, patients spontaneously disclosed 51%.
The lack of intrusive questions about medication taking during actual office visits may reflect poor provider recognition of the questions needed to fully assess adherence. Alternatively, provider beliefs about patient responsibility for adherence may hinder detailed queries. A paradigm of joint provider-patient responsibility may be needed to better guide discussions about medication adherence.
medication adherence; patient-physician relationship; provider-patient communication; prescription medication
Nuclear factor- (erythroid-derived 2) like 2 (NFE2L2, NRF2) is a key transcriptional activator of the antioxidant response pathway and is closely related to erythroid transcription factor NFE2. Under oxidative stress, NRF2 heterodimerizes with small Maf proteins and binds cis-acting enhancer sequences found near oxidative stress response genes. Using the dietary isothiocyanate sulforaphane (SFN) to activate NRF2, chromatin immunoprecipitation sequencing (ChIP-seq) identified several hundred novel NRF2-mediated targets beyond its role in oxidative stress. Activated NRF2 bound the antioxidant response element (ARE) in promoters of several known and novel target genes involved in iron homeostasis and heme metabolism, including known targets FTL and FTH1, as well as novel binding in the globin locus control region. Five novel NRF2 target genes were chosen for followup: AMBP, ABCB6, FECH, HRG-1 (SLC48A1), and TBXAS1. SFN-induced gene expression in erythroid K562 and lymphoid cells were compared for each target gene. NRF2 silencing showed reduced expression in lymphoid, lung, and hepatic cells. Furthermore, stable knockdown of NRF2 negative regulator KEAP1 in K562 cells resulted in increased NQO1, AMBP, and TBXAS1 expression. NFE2 binding sites in K562 cells revealed similar binding profiles as lymphoid NRF2 sites in all potential NRF2 candidates supporting a role for NRF2 in heme metabolism and erythropoiesis.
Background: Epigenetic modifications, such as DNA methylation, due to in utero exposures may play a critical role in early programming for childhood and adult illness. Maternal smoking is a major risk factor for multiple adverse health outcomes in children, but the underlying mechanisms are unclear.
Objective: We investigated epigenome-wide methylation in cord blood of newborns in relation to maternal smoking during pregnancy.
Methods: We examined maternal plasma cotinine (an objective biomarker of smoking) measured during pregnancy in relation to DNA methylation at 473,844 CpG sites (CpGs) in 1,062 newborn cord blood samples from the Norwegian Mother and Child Cohort Study (MoBa) using the Infinium HumanMethylation450 BeadChip (450K).
Results: We found differential DNA methylation at epigenome-wide statistical significance (p-value < 1.06 × 10–7) for 26 CpGs mapped to 10 genes. We replicated findings for CpGs in AHRR, CYP1A1, and GFI1 at strict Bonferroni-corrected statistical significance in a U.S. birth cohort. AHRR and CYP1A1 play a key role in the aryl hydrocarbon receptor signaling pathway, which mediates the detoxification of the components of tobacco smoke. GFI1 is involved in diverse developmental processes but has not previously been implicated in responses to tobacco smoke.
Conclusions: We identified a set of genes with methylation changes present at birth in children whose mothers smoked during pregnancy. This is the first study of differential methylation across the genome in relation to maternal smoking during pregnancy using the 450K platform. Our findings implicate epigenetic mechanisms in the pathogenesis of the adverse health outcomes associated with this important in utero exposure.
epigenetics; epigenome-wide; in utero; maternal smoking; methylation
The U.S. Centers for Medicare and Medicaid Services established the Electronic Health Record (EHR) Incentive Program in 2009 to stimulate the adoption of EHRs. One component of the program requires eligible providers to implement clinical decision support (CDS) interventions that can improve performance on one or more quality measures pre-selected for each specialty. Because the unique decision-making challenges and existing HIT capabilities vary widely across specialties, the development of meaningful objectives for CDS within such programs must be supported by deliberative analysis.
We developed a conceptual framework and protocol that combines evidence review with expert opinion to elicit clinically meaningful objectives for CDS directly from specialists. The framework links objectives for CDS to specialty-specific performance gaps while ensuring that a workable set of CDS opportunities are available to providers to address each performance gap. Performance gaps may include those with well-established quality measures but also priorities identified by specialists based on their clinical experience. Moreover, objectives are not constrained to performance gaps with existing CDS technologies, but rather may include those for which CDS tools might reasonably be expected to be developed in the near term, for example, by the beginning of Stage 3 of the EHR Incentive program. The protocol uses a modified Delphi expert panel process to elicit and prioritize CDS meaningful use objectives. Experts first rate the importance of performance gaps, beginning with a candidate list generated through an environmental scan and supplemented through nominations by panelists. For the highest priority performance gaps, panelists then rate the extent to which existing or future CDS interventions, characterized jointly as “CDS opportunities,” might impact each performance gap and the extent to which each CDS opportunity is compatible with specialists’ clinical workflows. The protocol was tested by expert panels representing four clinical specialties: oncology, orthopedic surgery, interventional cardiology, and pediatrics.
To evaluate the ability of the structure and code sets specified in the National Council for Prescription Drug Programs Structured and Codified Sig Format to represent ambulatory electronic prescriptions.
We parsed the Sig strings from a sample of 20 161 de-identified ambulatory e-prescriptions into variables representing the fields of the Structured and Codified Sig Format. A stratified random sample of these representations was then reviewed by a group of experts. For codified Sig fields, we attempted to map the actual words used by prescribers to the equivalent terms in the designated terminology.
Proportion of prescriptions that the Format could fully represent; proportion of terms used that could be mapped to the designated terminology.
The fields defined in the Format could fully represent 95% of Sigs (95% CI 93% to 97%), but ambiguities were identified, particularly in representing multiple-step instructions. The terms used by prescribers could be codified for only 60% of dose delivery methods, 84% of dose forms, 82% of vehicles, 95% of routes, 70% of sites, 33% of administration timings, and 93% of indications.
The findings are based on a retrospective sample of ambulatory prescriptions derived mostly from primary care physicians.
The fields defined in the Format could represent most of the patient instructions in a large prescription sample, but prior to its mandatory adoption, further work is needed to ensure that potential ambiguities are addressed and that a complete set of terms is available for the codified fields.
Greater use of computerized decision support (DS) systems could address continuing safety and quality problems in healthcare, but the healthcare field has struggled to implement DS technology. This study surveys DS experience across multiple non-healthcare disciplines for new insights that are generalizable to healthcare provider decisions. In particular, it sought design principles and lessons learned from the other disciplines that could inform efforts to accelerate the adoption of clinical decision support (CDS).
Our systematic review drew broadly from non-healthcare databases in the basic sciences, social sciences, humanities, engineering, business, and defense: PsychINFO, BusinessSource Premier, Social Sciences Abstracts, Web of Science, and Defense Technical Information Center. Because our interest was in DS that could apply to clinical decisions, we selected articles that (1) provided a review, overview, discussion of lessons learned, or an evaluation of design or implementation aspects of DS within a non-healthcare discipline and (2) involved an element of human judgment at the individual level, as opposed to decisions that can be fully automated or that are made at the organizational level.
Clinical decisions share some similarities with decisions made by military commanders, business managers, and other leaders: they involve assessing new situations and choosing courses of action with major consequences, under time pressure, and with incomplete information. We identified seven high-level DS system design features from the non-healthcare literature that could be applied to CDS: providing broad, system-level perspectives; customizing interfaces to specific users and roles; making the DS reasoning transparent; presenting data effectively; generating multiple scenarios covering disparate outcomes (e.g., effective; effective with side effects; ineffective); allowing for contingent adaptations; and facilitating collaboration. The article provides examples of each feature. The DS literature also emphasizes the importance of organizational culture and training in implementation success. The literature contrasts “rational-analytic” vs. “naturalistic-intuitive” decision-making styles, but the best approach is often a balanced approach that combines both styles. It is also important for DS systems to enable exploration of multiple assumptions, and incorporation of new information in response to changing circumstances.
Complex, high-level decision-making has common features across disciplines as seemingly disparate as defense, business, and healthcare. National efforts to advance the health information technology agenda through broader CDS adoption could benefit by applying the DS principles identified in this review.
We studied the influence of glacial oscillations on the genetic structure of seven species of white-headed gull that breed at high latitudes (Larus argentatus, L. canus, L. glaucescens, L. glaucoides, L. hyperboreus, L. schistisagus, and L. thayeri). We evaluated localities hypothesized as ice-free areas or glacial refugia in other Arctic vertebrates using molecular data from 11 microsatellite loci, mitochondrial DNA (mtDNA) control region, and six nuclear introns for 32 populations across the Holarctic. Moderate levels of genetic structure were observed for microsatellites (FST= 0.129), introns (ΦST= 0.185), and mtDNA control region (ΦST= 0.461), with among-group variation maximized when populations were grouped based on subspecific classification. Two haplotype and at least two allele groups were observed across all loci. However, no haplotype/allele group was composed solely of individuals of a single species, a pattern consistent with recent divergence. Furthermore, northernmost populations were not well differentiated and among-group variation was maximized when L. argentatus and L. hyberboreus populations were grouped by locality rather than species, indicating recent hybridization. Four populations are located in putative Pleistocene glacial refugia and had larger τ estimates than the other 28 populations. However, we were unable to substantiate these putative refugia using coalescent theory, as all populations had genetic signatures of stability based on mtDNA. The extent of haplotype and allele sharing among Arctic white-headed gull species is noteworthy. Studies of other Arctic taxa have generally revealed species-specific clusters as well as genetic structure within species, usually correlated with geography. Aspects of white-headed gull behavioral biology, such as colonization ability and propensity to hybridize, as well as their recent evolutionary history, have likely played a large role in the limited genetic structure observed.
Genetic structure; hybridization; Larus; Pleistocene glacial refugia; white-headed gulls
Cellular oxidative and electrophilic stress triggers a protective response in mammals regulated by NRF2 (nuclear factor (erythroid-derived) 2-like; NFE2L2) binding to deoxyribonucleic acid-regulatory sequences near stress-responsive genes. Studies using Nrf2-deficient mice suggest that hundreds of genes may be regulated by NRF2. To identify human NRF2-regulated genes, we conducted chromatin immunoprecipitation (ChIP)-sequencing experiments in lymphoid cells treated with the dietary isothiocyanate, sulforaphane (SFN) and carried out follow-up biological experiments on candidates. We found 242 high confidence, NRF2-bound genomic regions and 96% of these regions contained NRF2-regulatory sequence motifs. The majority of binding sites were near potential novel members of the NRF2 pathway. Validation of selected candidate genes using parallel ChIP techniques and in NRF2-silenced cell lines indicated that the expression of about two-thirds of the candidates are likely to be directly NRF2-dependent including retinoid X receptor alpha (RXRA). NRF2 regulation of RXRA has implications for response to retinoid treatments and adipogenesis. In mouse, 3T3-L1 cells’ SFN treatment affected Rxra expression early in adipogenesis, and knockdown of Nrf2-delayed Rxra expression, both leading to impaired adipogenesis.
Differences in rates of diabetes-related lower extremity amputations represent one of the largest and most persistent health disparities found for African-Americans and Hispanics compared to whites in the United States. Since many minority patients receive care in under-resourced settings, quality improvement (QI) initiatives in these settings may offer a targeted approach to improve diabetes outcomes in these patient populations. Health information technology (health IT) is widely viewed as an essential component of health care QI and may be useful in decreasing diabetes disparities in under-resourced settings. This article reviews the effectiveness of health care interventions utilizing health IT to improve diabetes process of care and intermediate diabetes outcomes in African-American and Hispanic patients. Health IT interventions have addressed patient, provider, and system challenges in the provision of diabetes care but require further testing in minority patient populations to evaluate their effectiveness in improving diabetes outcomes and reducing diabetes-related complications.
diabetes; health information technology; health disparities; quality improvement; under resourced settings
Rationale: The NF-E2 related factor 2 (Nrf2)–antioxidant response element (ARE) pathway is essential for protection against oxidative injury and inflammation including hyperoxia-induced acute lung injury. Microarray expression profiling revealed that lung peroxisome proliferator activated receptor γ (PPARγ) induction is suppressed in hyperoxia-susceptible Nrf2-deficient (Nrf2−/−) mice compared with wild-type (Nrf2+/+) mice. PPARγ has pleiotropic beneficial effects including antiinflammation in multiple tissues.
Objectives: We tested the hypothesis that PPARγ is an important determinant of pulmonary responsivity to hyperoxia regulated by Nrf2.
Methods: A computational bioinformatic method was applied to screen potential AREs in the Pparg promoter for Nrf2 binding. The functional role of a potential ARE was investigated by in vitro promoter analysis. A role for PPARγ in hyperoxia-induced acute lung injury was determined by temporal silencing of PPARγ via intranasal delivery of PPARγ-specific interference RNA and by administration of a PPARγ ligand 15-deoxy-Δ12,14-prostaglandin J2 in mice.
Measurements and Main Results: Deletion or site-directed mutagenesis of a potential ARE spanning -784/-764 sequence significantly attenuated hyperoxia-increased Pparg promoter activity in airway epithelial cells overexpressing Nrf2, indicating that the -784/-764 ARE is critical for Nrf2-regulated PPARγ expression. Mice with decreased lung PPARγ by specific interference RNA treatment had significantly augmented hyperoxia-induced pulmonary inflammation and injury. 15 Deoxy-Δ12,14-prostaglandin J2 administration significantly reduced hyperoxia-induced lung inflammation and edema in Nrf2+/+, but not in Nrf2−/− mice.
Conclusions: Results indicate for the first time that Nrf2-driven PPARγ induction has an essential protective role in pulmonary oxidant injury. Our observations provide new insights into the therapeutic potential of PPARγ in airway oxidative inflammatory disorders.
antioxidant response element; hyperoxia; inflammation; siRNA; 15d-PGJ2
Poor communication between primary care and specialists often leads to delays, inefficiencies and suboptimal patient outcomes. This study examined implementation of an electronic referral system (eReferral) that creates direct communication between primary care providers and specialist reviewers. Semi-structured interviews were conducted to assess factors affecting the success of eReferral implementation; transcripts were analyzed using qualitative methods. Primary and specialty care providers were enthusiastic about the system. Primary care providers had favorable attitudes despite a number of challenges including increased workload due to a shift in tasks from specialists and administrative personnel, poor connectivity, and insufficient hardware. System acceptance was driven by perceptions of improved access to specialty care, better appointment tracking, and improved communication between primary and specialty care providers. Synergy among development processes, implementation practices, and technical factors, including human-centered design, iterative development, a phased rollout, and an intuitive user interface, also fostered uptake of the system.
The p53 protein is crucial for adapting programs of gene expression in response to stress. Recently, we revealed that this occurs partly through the formation of stress-specific p53 binding patterns. However, the mechanisms that generate these binding patterns remain largely unknown. It is not established whether the selective binding of p53 is achieved through modulation of its binding affinity to certain response elements (REs) or via a chromatin-dependent mechanism. To shed light on this issue, we used a microsphere assay for protein–DNA binding to measure p53 binding patterns on naked DNA. In parallel, we measured p53 binding patterns within chromatin using chromatin immunoprecipitation and DNase I coupled to ligation-mediated polymerase chain reaction footprinting. Through this experimental approach, we revealed that UVB and Nutlin-3 doses, which lead to different cellular outcomes, induce similar p53 binding patterns on naked DNA. Conversely, the same treatments lead to stress-specific p53 binding patterns on chromatin. We show further that altering chromatin remodeling using an histone acetyltransferase inhibitor reduces p53 binding to REs. Altogether, our results reveal that the formation of p53 binding patterns is not due to the modulation of sequence-specific p53 binding affinity. Rather, we propose that chromatin and chromatin remodeling are required in this process.
p53 coordinates the expression of an intricate network of genes in response to stress signals. Sequence-specific DNA binding is essential for p53-mediated tumor suppression. We evaluated the impact of single-nucleotide polymorphisms (SNPs) in p53 response elements (p53RE) on DNA binding and gene expression in response to DNA damage. Using a bioinformatics approach based on incorporating p53 binding strength into a position weight matrix, we selected 32 SNPs in putative and validated p53REs. The microsphere assay for protein–DNA binding (MAPD) and allele-specific expression analysis was employed to assess the impact of SNPs on p53-DNA binding and gene expression, respectively. Comparing activated p53 binding in nuclear extracts from doxorubicin- or ionizing radiation (IR)-treated human cells, we observed little difference in binding profiles. Significant p53 binding was observed for most polymorphic REs and several displayed binding comparable to the p21 RE. SNP alleles predicted to lower p53 binding indeed reduced binding in 25 of the 32 sequences. Chromatin immunoprecipitation-sequencing in lymphoblastoid cells confirmed p53 binding to seven polymorphic p53 REs in response to doxorubicin. In addition, five polymorphisms were associated with altered gene expression following doxorubicin treatment. Our findings demonstrate an effective strategy to identify and evaluate SNPs that may alter p53-mediated stress responses.
Prior microarray studies of smokers at high risk for lung cancer have demonstrated that heterogeneity in bronchial airway epithelial cell gene expression response to smoking can serve as an early diagnostic biomarker for lung cancer. As a first step in applying functional genomic analysis to population studies, we have examined the relationship between gene expression variation and genetic variation in a central molecular pathway (NRF2-mediated antioxidant response) associated with smoking exposure and lung cancer. We assessed global gene expression in histologically normal airway epithelial cells obtained at bronchoscopy from smokers who developed lung cancer (SC, n = 20), smokers without lung cancer (SNC, n = 24), and never smokers (NS, n = 8). Functional enrichment analysis showed that the NRF2-mediated, antioxidant response element (ARE)-regulated genes, were significantly lower in SC, when compared with expression levels in SNC. Importantly, we found that the expression of MAFG (a binding partner of NRF2) was correlated with the expression of ARE genes, suggesting MAFG levels may limit target gene induction. Bioinformatically we identified single nucleotide polymorphisms (SNPs) in putative ARE genes and to test the impact of genetic variation, we genotyped these putative regulatory SNPs and other tag SNPs in selected NRF2 pathway genes. Sequencing MAFG locus, we identified 30 novel SNPs and two were associated with either gene expression or lung cancer status among smokers. This work demonstrates an analysis approach that integrates bioinformatics pathway and transcription factor binding site analysis with genotype, gene expression and disease status to identify SNPs that may be associated with individual differences in gene expression and/or cancer status in smokers. These polymorphisms might ultimately contribute to lung cancer risk via their effect on the airway gene expression response to tobacco-smoke exposure.
US hospitals have had voluntary incident reporting systems for many years, but the effectiveness of these systems is unknown. To facilitate substantial improvements in patient safety, the systems should capture incidents reflecting the spectrum of adverse events that are known to occur in hospitals.
To characterise the incidents from established voluntary hospital reporting systems.
Observational study examining about 1000 reports of hospitalised patients at each of two hospitals.
Patients and setting
16 575 randomly selected patients from an academic and a community hospital in the US in 2001.
Main outcome measures
Rates of incidents reported per hospitalised patient and characteristics of reported incidents.
9% of patients had at least one reported incident; 17 incidents were reported per 1000 patient‐days in hospital. Nurses filed 89% of reports, physicians 1.9% and other providers 8.9%. The most common types were medication incidents (29%), falls (14%), operative incidents (15%) and miscellaneous incidents (16%); 59% seemed preventable and preventability was not clear for 32%. Among the potentially preventable incidents, 43% involved nurses, 16% physicians and 19% other types of providers. Qualitative examination of reports indicated that very few involved prescribing errors or high‐risk procedures.
Hospital reporting systems receive many reports, but capture a spectrum of incidents that differs from the adverse events known to occur in hospitals, thereby substantially underdetecting physician incidents, particularly those involving operations, high‐risk procedures and prescribing errors. Increasing the reporting of physician incidents will be essential to enhance the effectiveness of hospital reporting systems; therefore, barriers to reporting such incidents must be minimised.
Poor communication between referring clinicians and specialists may lead to inefficient use of specialist services. San Francisco General Hospital implemented an electronic referral system (eReferral) that facilitates iterative pre-visit communication between referring and specialty clinicians to improve the referral process.
The purpose of the study was to determine the impact of eReferral (compared with paper-based referrals) on specialty referrals.
The study was based on a visit-based questionnaire appended to new patient charts at randomly selected specialist clinic sessions before and after the implementation of eReferral.
The questionnaire focused on the self-reported difficulty in identifying referral question, referral appropriateness, need for and avoidability of follow-up visits.
We collected 505 questionnaires from speciality clinicians. It was difficult to identify the reason for referral in 19.8% of medical and 38.0% of surgical visits using paper-based methods vs. 11.0% and 9.5% of those using eReferral (p-value 0.03 and <0.001). Of those using eReferral, 6.4% and 9.8% of medical and surgical referrals using paper methods vs. 2.6% and 2.1% were deemed not completely appropriate (p-value 0.21 and 0.03). Follow-up was requested for 82.4% and 76.2% of medical and surgical patients with paper-based referrals vs. 90.1% and 58.1% of eReferrals (p-value 0.06 and 0.01). Follow-up was considered avoidable for 32.4% and 44.7% of medical and surgical follow-ups with paper-based methods vs. 27.5% and 13.5% with eReferral (0.41 and <0.001).
Use of technology to promote standardized referral processes and iterative communication between referring clinicians and specialists has the potential to improve communication between primary care providers and specialists and to increase the effectiveness of specialty referrals.
access to care; communication; specialty care