Evidence
2003–2022
What we have done, with which data, by which methods.
Our client work is confidential. What follows is our published record — the studies, the data they used, and the methods behind them — and every method described is one we have executed ourselves.
- Publications, abstracts, and posters
- 50
- Full publications, incl. JAMA and Circulation
- 15
- Therapeutic areas
- 12
- Years of output, 2003–2022
- 20
01Landmark program
mSToPS: three organizations, one trial
A nationwide, direct-to-participant screening trial run by a manufacturer, a research institute and a national health plan together — published in JAMA, and now the model for how much of the industry works.
A pharmaceutical manufacturer, a research institute and a national health plan, on one author list, running one nationwide trial with no study site.
mHealth Screening To Prevent Strokes tested whether a wearable ECG patch, posted to people identified as at risk from their own claims history, would find atrial fibrillation that routine care was missing. The health plan found the population and measured what followed; the research institute designed and ran the trial; the manufacturer funded it and sat on the author list. The population came from Aetna’s own membership, and our principal is named on the papers from both Aetna and Healthagen Outcomes.
Three organizations that had no history of sharing a protocol, an endpoint or a dataset. That was unusual in 2016. It is how much of the industry now works — and we have been inside it from the payer side since the beginning.
- randomized, nationwide, with no study site
- 2,659randomized, nationwide, with no study site
- actively monitored with 12-month follow-up
- 1,738actively monitored with 12-month follow-up
- published outputs we co-authored, 2016–2019
- 7published outputs we co-authored, 2016–2019
Janssen Scientific Affairs
ManufacturerSponsored the trial and sat on the author list, through a research grant to Scripps.
Scripps Translational Science Institute
Research instituteDesigned and ran the trial, and held the grant.
Aetna / Healthagen Outcomes
Health planThe national health plan. Its claims identified who was at risk; its analytics business measured what followed. Our principal is an author from Aetna on the design paper and from Healthagen Outcomes on the trial result.
Inside the manufacturer, we worked with
- Market access
- Commercial
- R&D
- Medical affairs
Four departments that buy evidence differently, on one program.
The program, as published
Supported by a research grant from Janssen Pharmaceuticals to the Scripps Translational Science Institute.
- 2016Rationale and design of the trialAmerican Heart Journal (source, opens in a new tab)
- 2017Digital recruitment of a nationwide cohortACC 2017 (source, opens in a new tab)
- 2017Screening an at-risk population nationwideAmerican Heart Association
- 2018An end-to-end trial inside a health insurance systemACC 2018
- 2018Primary trial resultJAMA (source, opens in a new tab)
- 2019What the recruitment model taught usContemp Clin Trials Commun (source, opens in a new tab)
- 2019Healthcare resource use after screeningACC 2019 (source, opens in a new tab)
Conference abstracts without a permanent online record are listed without a link.
The method the trial demonstrated was then reviewed across the industry in Technology-Enabled Clinical Trials (Circulation, 2019), which our principal co-authored with regulators, sponsors, and academic centers.
Primary result: Steinhubl SR, Waalen J, Edwards AM, Ariniello LM, Mehta RR, et al. JAMA. 2018;320(2):146-155. Read it.
02Selected studies
Four studies, told the way you would assess one
Studies our researchers have presented and published, told the way you would assess one. They come from the public record, not from client engagements, and every figure is quoted as the authors reported it.
- 01Pharmacovigilance
A claims-based sentinel system for drug safety
47,319
indication–drug–outcome combinations, in under 48 hours
Can relationships between indications, drugs, and outcomes be surfaced from routine claims fast enough to direct further study?
Data, method, and finding
- Data
- De-identified claims for five million people over twelve months.
- Method
- Relative risk and chi-square for every combination of 73 drug categories and 39 health outcomes of interest. Indication from ICD-9 claims, exposure from NDC refills, and an outcome counted only if it appeared in months 6–12 and not in months 1–6.
- Finding
- The system produced 47,319 combinations in under 48 hours. At a threshold of at least five patients and a chi-square above 5, 13,094 of them (28%) were flagged for closer inspection — a way of targeting analysis rather than a list of conclusions.
Wei H, Mehta R, Steinberg G. ISPOR 18th Annual International Meeting, 2013.
- 02Infectious disease
Incidence and cost of healthcare-associated infections
$33,626
median total cost per patient with a healthcare-associated infection
What do device- and non-device-related infections actually cost an integrated health system, and how often do they occur?
Data, method, and finding
- Data
- 79,839 admissions from 62,647 adult patients at two urban hospitals, July 2008 to September 2010.
- Method
- Electronic surveillance with every case verified against NHSN definitions by three infection preventionists; clinical, cost, and demographic data drawn from the enterprise data warehouse.
- Finding
- 2,707 infections in 2,080 patients — 3.3% of patients, 8.5 per 1,000 patient-days, with a median stay of 12 days. Nearly half were not device-related, and C. difficile had become the most common microbial cause.
Pombo DJ, Lopansri BK, Keane M, Taylor C, Kleckner R, Sumner S, Mehta RR, Burke JP. IDSA, 2013.
- 03Infectious disease
The under-estimated cost of catheter-associated UTI
1.2% vs 5.6%
of Medicare encounters coded for the infection, against those who actually developed it
When Medicare stopped paying for hospital-acquired infections, did the coded record reflect how often they happened?
Data, method, and finding
- Data
- 56,554 patients with an indwelling catheter at two tertiary hospitals, 2000–2008, including 28,888 Medicare patients.
- Method
- Matched case–control: 277 coded cases matched on sex, facility, surgery, admission year, severity of illness, and DRG.
- Finding
- 382 patients were coded; 1,604 developed the infection. Cases stayed longer (14.2 against 11.0 days) and cost more ($16,913 against $15,553 median per encounter). Cost estimates built on coded cases understate the real burden.
Dascomb K, Mehta RR, Pombo DJ, Burke JP. IDSA 47th Annual Meeting, 2008.
- 04Infectious diseaseNull result — published
Rapid versus overnight bacterial identification
No difference
in length of stay, variable cost or mortality
Would switching to a rapid identification platform deliver the shorter stays and lower costs reported elsewhere?
Data, method, and finding
- Data
- 1,959 inpatients at two hospitals — 653 cases and 1,306 matched controls — January 2002 to August 2003.
- Method
- Retrospective case–control, two controls per case matched on sex, APR-DRG severity and specimen type. Kaplan–Meier analysis of length of stay, adjusted for patients who died.
- Finding
- Turnaround was 61 against 62 hours, median stay 7.2 against 7.7 days, and median variable cost $6,875 against $7,566 — none significant. At day 25, 13% against 16% remained in hospital (log-rank 1.68, not significant).
Mehta RR, Burke JP, Pombo DJ. ICAAC, poster D-697.
Our client work is confidential.
We do not publish client names, and we will not publish an outcome we cannot evidence. Anonymized case material — the question, the data, the method, and what the work enabled — is available under NDA, or we can walk you through comparable engagements on a call.
Ask for anonymized case material03Therapeutic areas
Where our published work is concentrated
One deep specialty in infectious disease and hospital outcomes, then a spread across cardiology, diabetes, respiratory, dermatology, and mental health.
- 01Infectious disease27C. difficile, MRSA, S. pneumoniae, ABSSSI, HAI
- 02Atrial fibrillation7incl. the mSToPS trial, JAMA 2018
- 03Trauma4hospital-associated infection
- 04Asthma3guideline impact and resource use
- 05Type 2 diabetes3Meta-analysis, Diabetes Obes Metab 2021; guideline conformance, J Clin Transl Endocrinol 2020
- 06Pharmacovigilance2US patent 8,744,872; claims-based sentinel
- 07Cardiovascular1Technology-enabled trials, Circulation 2019
- 08Mental health1Pharmacogenetic testing, Depress Anxiety 2018
- 09Psoriasis & PsA1Treatment patterns within a health plan
- 10Opioid utilization1Peri-surgical opioid use
- 11COVID-191Machine learning hospitalization risk
- 12Hemophilia A0Prophylaxis utilization, claims
Bars count entries in our published record below. Our therapeutic experience outside the published literature is broader.
04Data coverage
The real-world data we work in
Payer, provider, and pharmacy data — extracted and analyzed by the same team, so the cohort definition survives contact with the data.
Payer
Enrollment, benefits, and what the plan paid for.
- Medical claims
- Eligibility
- Formulary
Provider
What happened clinically, inside the health system.
- EMR
- EHR
- Registry
Claims & pharmacy
What was dispensed, billed, and tested.
- Pharmacy Rx
- Medical
- External lab
Named sources
We hold direct experience with named payer, PBM, and provider organizations. Naming them publicly is subject to client clearance.
05Published record
Everything we have published, searchable
Fifty publications, abstracts, posters, a patent, and a book chapter authored or co-authored by our team between 2003 and 2022 — in JAMA, Circulation, Diabetes, Obesity and Metabolism, Vaccine and others. Search it, or filter by type.
50 of 50 entries
- 2022Rajesh Mehta, Surya Uppunuthula. Use Machine Learning (ML) Techniques to Identify the Likelihood of Hospitalization for High-Risk Patients Diagnosed with COVID 19. 2022 ISPOR May 18 – May 22.COVID-19PublicationISPOR
- 2022Michele Bennett, PhD, Ewa J. Kleczyk, PhD., Rajesh Mehta, R.Ph., MS. Similarities and Differences between Machine Learning and Traditional Advanced Statistical Modeling in Healthcare Analytics. https://doi.org/10.48550/arXiv.2201.02469, Jan 2022.Publication (source, opens in a new tab)
- 2021Powell RE, Zaccardi F, Beebe C, Chen XM, Crawford A, Cuddeback J, Gabbay RA, Kissela L, Litchman ML, Mehta R, Meneghini L, Pantalone KM, Rajpathak S, Scribner P, Skelley JW, Khunti K. Strategies for overcoming therapeutic inertia in type 2 diabetes: A systematic review and meta-analysis. Diabetes Obes Metab. 2021 Sep;23(9):2137-2154. doi: 10.1111/dom.14455. Epub 2021 Jun 27. PMID: 34180129.Type 2 diabetesPublicationDiabetes Obes Metab (source, opens in a new tab)
- 2019Guillaume Marquis-Gravel, Matthew T. Roe, Mintu P. Turakhia, William Boden, Robert Temple, Abhinav Sharma, Boaz Hirshberg, Paul Slater, Noah Craft, Norman Stockbridge, Bryan McDowell, Joanne Waldstreicher, Ariel Bourla, Sameer Bansilal, Jennifer L. Wong, Claire Meunier, Helina Kassahun, Philip Coran, Lauren Bataille, Bray Patrick-Lake, Brad Hirsch, John Reites, Rajesh Mehta, Evan D. Muse, Karen J. Chandross, Jonathan C. Silverstein, Christina Silcox, J. Marc Overhage, Robert M. Califf, Eric D. Peterson. Technology-Enabled Clinical Trials. Circulation. 2019;140:1426–1436. https://doi.org/10.1161/CIRCULATIONAHA.119.040798. (Publication)PublicationCirculation (source, opens in a new tab)
- 2019Baca-Motes K, Edwards AM, Waalen J, Edmonds S, Mehta RR , Ariniello L, Ebner GS, Talantov D, Fastenau JM, Carter CT, Sarich TC, Felicione E, Topol EJ, Steinhubl SR. Digital recruitment and enrollment in a remote nationwide trial of screening for undiagnosed atrial fibrillation: Lessons from the randomized, controlled mSToPS trial.Contemp Clin Trials Commun. 2019 Jan 7;14:100318. doi: 10.1016/j.conctc.2019.100318. eCollection 2019 Jun.Atrial fibrillationPublicationContemp Clin Trials Commun (source, opens in a new tab)
- 2018Steinhubl SR, Waalen J, Edwards AM, Ariniello LM, Mehta RR , Ebner GS, Carter C, Baca-Motes K, Felicione E, Sarich T, Topol EJ. Continuous ECG Monitoring Patch on Detection of Undiagnosed Atrial Fibrillation: The mSToPS Randomized Clinical Trial. JAMA. 2018 Jul 10;320(2):146-155. doi: 10.1001/jama.2018.8102.Atrial fibrillationPublicationJAMA (source, opens in a new tab)
- 2018Ajay Sharma, Amiee Kang, Arun Tiwari, Rajesh R. Mehta, RPh, Simon Dagenais. Use of opioids before and after common elective surgical procedures: An analysis of Aetna fully insured commercial and Medicare populations. ASHP 2018 (Poster).Opioid utilizationPosterASHP
- 2018Kenneth Snow, Brian Ung, Corey Pelletier, Alison Edwards, Rajesh Mehta , Steve Sample. Patient Characteristics and Treatment Patterns of Psoriasis (PsO) and Psoriatic Arthritis (PsA) Patients Within a Health Plan. AMCP 2018 (Poster)PsoriasisPosterAMCP
Note — selected bibliography of work authored or co-authored by our team, 2003 to 2022. Entries with a DOI, PMID or patent number link to the source.
06Methods
Methods and analytical capability
Every method listed is one we have run ourselves, from study design through to the code.
Study design
- Retrospective observational
- Prospective pragmatic
- Randomized controlled trials
- Epidemiology and burden of illness
- Cohort development
- Risk stratification
- Surveillance and point-prevalence studies
Statistics
- Logistic regression
- ANOVA
- Survival analysis
- Propensity score matching
- Multivariate models
- Machine learning techniques
- Systematic review and meta-analysis
Data engineering
- SQL extraction
- Hadoop
- Teradata
- TOAD
- SAS
- SPSS
- Hierarchical data files
Bring us the question you cannot answer internally.
A 30-minute call with a senior researcher. We will tell you what data it would take, and whether that data exists.