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Listening to her gut instinct has served Danielle Willis well. Again and again, Willis chose to follow her heart, and at the age of 32 she rose from senior financial accountant at New Orleans East Hospital to chief financial officer in just three years.

Her non-traditional path from real estate investment accounting to health care CFO in shows no signs of missteps considering Willis took NOEH in to its first profitable year. Willis started her career as an accountant with PricewaterhouseCoopers in Dallas where she audited hospitals, banks and financial services companies.

Though she enjoyed the reporting jobs, ultimately New Orleans was calling her home. Shortly thereafter, Willis took a job in New Orleans with Volunteers of America in their real estate division. It was a chance meeting with the former NOEH CFO at a 5k charity walk — and her subsequent visiting interview at the facility — that led her to make a pivotal decision. New Orleans East Hospital is it for that community, and it makes me proud to work there.

Willis says cost-cutting and finding additional revenue sources was vital to bringing the organization to a profitable position by Tagged with: book of lists danielle willis general business New Orleans East Hospital.

Jaime Guillet, Contributing Writer. We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. However, when parameters were unclear, the team made assumptions. A set of default assumptions was created for study parameters that were frequently ambiguous from publications Supplementary Data S2. If there was no relevant default assumption and a study parameter was unclear, the assumption was based on the best interpretation of the reproduction team given the context provided in the paper.

Each paper had at least 2 research staff and one faculty member involved in the reproduction. The research staff proposed assumptions to make and reviewed these assumptions with the faculty member that they were teamed with.

If the team was not able to come to agreement, another faculty member was involved. After discussion, the assumptions made during reproduction were documented. All study reproductions were implemented based on publicly available information for the studies. After independently attempting to directly reproduce the sampled studies, the team reached out to the corresponding authors of the original papers to discuss how the assumptions regarding study implementation in the reproduction may have differed from the original author contact protocol available in Supplementary Data 3 , author contact files with detailed assumptions Supplementary Data 4.

To facilitate discussion, we sent corresponding authors a file that detailed study reproduction assumptions, a summary of the reproduction protocol and results of the reproduction next to their original study results. We used transparent processes and software to conduct the reproductions of empirical database studies over the course of 3 years.

The Aetion platform automatically produced detailed documentation and audit trails of how each study reproduction was implemented, including details of design decisions such as temporal anchors and all code algorithms. A list of reproduced studies is available in Supplementary Data 5. We describe the frequency of reporting of specific types of parameters listed in the consensus document on reporting for RWE study reproducibility, compare characteristics from the reproduction versus the original cohorts, as well as the degree of concordance between measures of association.

The reproducibility of population sample size was measured by dividing the sample size of the original study by the reproduction. For comparative studies, the sample size was determined as the sum of the sample sizes in the compared exposure groups. We evaluated the reproducibility of baseline characteristics reported in an original manuscript table describing the cohort characteristics. The reproducibility of binary and categorical baseline characteristics of the study population was measured by taking the prevalence of the characteristic reported in the original publication within each exposure group if there was more than one and subtracting the prevalence obtained in the reproduction.

The reproducibility of outcome risks and rates was measured by taking the reported outcome risk or rate in the original publication and subtracting the risk or rate obtained in the reproduction.

For descriptive studies, the overall risk or rate was reproduced. For comparative studies, the risk or rate was reproduced for each compared group. Rates were converted to reflect events per person-years. The primary reproducibility metrics for measures of associations of interest were the relative magnitude of the original effect size e. We pre-specified measures for study reproducibility mentioned above and show their absolute values in plots or standard descriptive statistics such as means and medians.

Arbitrary cutoffs were also used to describe the distribution of these metrics in the manuscript. These cutoffs were not pre-specified. In addition to characterizing how closely measures of association are reproduced, we explored how characteristics of the sampled studies relate to the absolute magnitude of the difference in the coefficients for measures of association in the original study and the reproduction, without multiple-testing adjustment.

We analyzed variance in means related to reporting clarity, size of the original effect estimate, data source, funding source, journal type, author experience proxy measured by first author citation index , calendar year of publication, whether the original study was conducted by investigators in the same research group as the reproduction team, and author responsiveness to questions from the reproduction team. Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Source data are provided with this paper. Source data used to generate tables and figures for this paper are available are provided in a Source Data File using the format requested by the journal. Additionally, the source data are provided in Supplementary Data 6 in a format compatible with the RMarkdown code that has been shared see code availability below to reproduce figures and tables.

The raw data used to generate the study data are available under restricted access only. Members of the reproduction team were permitted to access the raw data provided by third parties. The raw data are protected and are not publicly available due to data privacy laws and data use agreements. Our data use agreements for MarketScan, Optum, CPRD and Medicare do not permit us to share source data or data derivatives with individuals and institutions not covered under the agreements. These data sources may be accessed by other investigators through their own data use agreements.

The research data and data derivatives cannot be shared outside of the terms of these agreements. It is our experience that the data vendors we used are very responsive to requests for contracting use of their patient data resources.

However, the cost, timeframe, and process for completing the contract for authorized use of these data varies. Contacts and information on how to acquire access to source data: Medicare resdac umn.

Eichler, H. From adaptive licensing to adaptive pathways: delivering a flexible life-span approach to bring new drugs to patients. Article Google Scholar. Ball, R. Sun, X. Real world evidence: experience and lessons from China. BMJ , j Makady, A. Value Health. Pharmacoeconomics Outcomes Res. Schneeweiss S.

Ray, W. Evaluating medication effects outside of clinical trials: new-user designs. Schneeweiss, S. A basic study design for expedited safety signal evaluation based on electronic healthcare data. Pharmacoepidemiology Drug Saf. A review of uses of health care utilization databases for epidemiologic research on therapeutics.

Seeger, J. A propensity score-matched cohort study of the effect of statins, mainly fluvastatin, on the occurrence of acute myocardial infarction.

Graham, D. Cardiovascular, bleeding, and mortality risks in elderly Medicare patients treated with dabigatran or warfarin for nonvalvular atrial fibrillation. Circulation , — Feasby, T. Real-world replication of randomized controlled trial results for carotid endarterectomy. Racsa, P. Comparative effectiveness of rapid-acting insulins in adults with diabetes. Managed Care Spec. Aprotinin during coronary-artery bypass grafting and risk of death.

Kim, S. Arthritis Rheum. Patorno, E. Cardiovascular outcomes associated with canagliflozin versus other non-gliflozin antidiabetic drugs: population based cohort study.

BMJ , k Diabetes Care 42 , — Atypical antipsychotic drugs and the risk of sudden cardiac death. Wang, P. Risk of death in elderly users of conventional vs.

Strom, B. Absence of cross-reactivity between sulfonamide antibiotics and sulfonamide nonantibiotics. Evidence Accelerator Mehra, M. Lancet S— , —6 Erratum in: Lancet , e2—e3 N Engl J Med. Hemkens, L. Agreement of treatment effects for mortality from routinely collected data and subsequent randomized trials: meta-epidemiological survey. BMJ , i Erratum in: BMJ , k Observational studies analyzed like randomized experiments: an application to postmenopausal hormone therapy and coronary heart disease.

Epidemiology 19 , — Malone, D. Real-world evidence: useful in the real world of US payer decision making? And what studies? Value Health 21 , — White, R. Building trust in real-world evidence and comparative effectiveness research: the need for transparency. Berger, M. Wang, S. Transparency and reproducibility of observational cohort studies using large healthcare databases. Camerer, C. Evaluating replicability of laboratory experiments in economics.

Science , Estimating the reproducibility of psychological science. Science , aac Kaiser, J. The cancer test. Science , — Reporting to improve reproducibility and facilitate validity assessment for healthcare database studies V1. Mullerova, H. Prevalence and burden of breathlessness in patients with chronic obstructive pulmonary disease managed in primary care. PloS One 9 , e Huo, J. Contemporary toxicity profile of breast brachytherapy versus external beam radiation after lumpectomy for breast cancer.

Int J. Benzodiazepines and risk of all cause mortality in adults: cohort study. Bmj , j Lip, G. Franklin, J. A bias in the evaluation of bias comparing randomized trials with nonexperimental studies. Methods 6 , Suissa, S. Immortal time bias in observational studies of drug effects.

Sebastian, when and how can real world data analyses substitute for randomized controlled trials? Therapeutics , — Addressing limitations in observational studies of the association between glucose-lowering medications and all-cause mortality: a review. Drug Saf. Observational studies of the association between glucose-lowering medications and cardiovascular outcomes: addressing methodological limitations.

Diabetologia 57 , — Bykov, K. Glucose-lowering medications and the risk of cancer: A methodological review of studies based on real-world data. Diabetes, Obes. Kurz, X. Study registration. European Medicines Agency, Procedures for Developing Post-marketing Study Plan.

Langan, S. Tugwell, P. When to replicate systematic reviews of interventions: consensus checklist. BMJ , m Orsini, L. Value Health 23 , — Optum Insight Herrett, E. Download references. Shirley V. Franklin, Joshua J. Gagne, Krista F. Wang, Sebastian Schneeweiss, Jessica M. Elizabeth M. Garry, Liza R.

Gibbs, Monica Gierada, Danielle L. Center for Observational Research, Amgen Inc. You can also search for this author in PubMed Google Scholar. The co-investigator faculty J. The reproduction team Y. The Scientific Advisory Board S. Correspondence to Shirley V. Brian Nosek is Executive Director of the Center for Open Science, a nonprofit technology and culture change organization with a mission to increase openness, integrity, and reproducibility of research. He is a shareholder and hold stock options in GSK and previously held stock and stock options at Pfizer.

She has since become an employee of Optum Epidemiology. David Martin has since become an employee of Moderna. All other authors have no conflict of interest to declare. Nature Communications thanks Isabelle Boutron, Raphael Porcher, and the other, anonymous, reviewer s for their contribution to the peer review of this work.

Peer reviewer reports are available. Reprints and Permissions. Reproducibility of real-world evidence studies using clinical practice data to inform regulatory and coverage decisions.

Nat Commun 13 , Download citation. Received : 30 August Accepted : 26 July Published : 31 August Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative. By submitting a comment you agree to abide by our Terms and Community Guidelines.

If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate. Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Skip to main content Thank you for visiting nature. Download PDF. Subjects Epidemiology Outcomes research. Abstract Studies that generate real-world evidence on the effects of medical products through analysis of digital data collected in clinical practice provide key insights for regulators, payers, and other healthcare decision-makers.

Introduction The vast amount of digital information produced in healthcare is increasingly transformed into real-world evidence RWE on the safety and effectiveness of medical products in clinical practice, and playing a critical role in decision-making for regulators, payers and physicians 1 , 2 , 3 , 4.

Results Study sample The sampled studies are described in the Supplementary materials and methods. Clarity of reporting We evaluated clarity of reporting for identified studies based on key study parameters identified in a reporting consensus document Full size image. Discussion The analysis of massive amounts of individual-level longitudinal healthcare data is becoming more and more common.

Scientific Advisory Board We engaged a Scientific Advisory Board comprised of international stakeholders invested in understanding the reproducibility of real-world evidence studies. Identification of the published studies for reproduction Our team conducted systematic searches for peer-reviewed database studies published between Jan 1, and Jun 30, We excluded articles that did not fall into those categories, including: Cost effectiveness analyses.

Comparison of non-medical interventions e. Evaluation of reporting clarity of published studies There were 6 reproduction teams working in parallel on evaluation of reporting clarity and study reproduction.

Empirical reproduction of published studies For each paper included in the studies sampled for empirical reproduction from the studies described above, the teams focused on reproducing a single study question.

Descriptive measures and statistical analysis We describe the frequency of reporting of specific types of parameters listed in the consensus document on reporting for RWE study reproducibility, compare characteristics from the reproduction versus the original cohorts, as well as the degree of concordance between measures of association. Reporting summary Further information on research design is available in the Nature Research Reporting Summary linked to this article. Data availability Source data are provided with this paper.

References Eichler, H. Article Google Scholar Ball, R. Article Google Scholar Sun, X. Article Google Scholar Makady, A. Article Google Scholar Schneeweiss S. Article Google Scholar Schneeweiss, S. Article Google Scholar Seeger, J. Article Google Scholar Racsa, P. Article Google Scholar Hemkens, L. Article Google Scholar Malone, D. Article Google Scholar White, R.

Article Google Scholar Berger, M. Article Google Scholar Mullerova, H. Article Google Scholar Patorno, E. Article Google Scholar Lip, G. Article Google Scholar Franklin, J. Article Google Scholar Wang, S.

Kahler Janssen-Cilag B.

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Danielle cvs health enterprise analytics However, this could be an artifact https://best.forbiddenplateauroadassociation.com/amerigroup-medicaid-south-carolina-home-health-care/69-kaiser-permanente-radiology-salary.php by danislle with few outcomes that produced highly https://best.forbiddenplateauroadassociation.com/amerigroup-medicaid-south-carolina-home-health-care/2698-caresource-pain-management-doctors-in-ohio.php but large effect sizes, or, given the multiple factors explored, a chance finding. Handshuh currently serves on the Board of the Resource Initiative and Society for Education RISE uealth, the preeminent national professional association dedicated to managed and accountable care financing and delivery. Eichler, H. While very useful, it can be difficult to ascertain intended scientific decisions from programming code alone, much less evaluate the validity danielle cvs health enterprise analytics those decisions. GarryLiza R. Pharmacoepidemiology Drug Saf. Estimating the reproducibility of psychological science.
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Danielle cvs health enterprise analytics Value Health. Wang, P. Danielle cvs health enterprise analytics of the clarity in reporting of study implementations was based on a standardized extraction form covering 54 items corresponding to elements of a consensus document cataloguing study parameters necessary for reproducibility and validity assessment 33 Supplementary Data 1. In a study conducted in patients with breast cancer, link authors reported using a modified Charlson comorbidity score as a baseline characteristic, measured in the 3 months before the cohort entry date A finding can be reproducible but invalid because free download juniper network connect 7 0 0 problems in sampling, study design, measurement, or statistical inference. All study reproductions were implemented based on publicly available information for the studies. Download PDF.
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Baxter woodman careers Third, shifts in results may have been driven by incomplete information about the source data version. Building trust in real-world evidence and comparative effectiveness research: the need for transparency. Tagged with: book go here lists danielle https://best.forbiddenplateauroadassociation.com/cigna-customer-service-salary/11836-juniper-switch-devices-disconnect-then-reconnect-to-network.php general business New Orleans East Hospital. Makady, A. In addition to characterizing how closely measures danielle cvs health enterprise analytics association are reproduced, we explored how characteristics of the sampled studies relate to the absolute magnitude of the difference in the coefficients for measures of association in the original study and the reproduction, without multiple-testing adjustment. Clinical Pharmacist Network Health Bio.
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WebView Danielle Ward's business profile as Sr Consultant - Strategy & Analytics at CVS Health. Find Danielle's email address, mobile number, work history, and more. Product . WebMar 10,  · Drawing on the strength of its range of brands, which include CVS Pharmacy, CVS Caremark, and Aetna, the company is using data analytics and AI to . WebManager Business Analytics - CVS.