# Implementation of a Novel Multi-Platform Evidence-Based Clinical Decision Support System

> **NIH AHRQ R18** · FEINSTEIN INSTITUTE FOR MEDICAL RESEARCH · 2020 · $376,917

## Abstract

Project Abstract
Northwell Health's Center for Health Innovation and Outcomes Research (CHIOR) has spent a decade
conducting clinical decision support system (CDSS) related research. Our work began with the science of
deriving and validating clinical prediction rules (CPRs). As health information technology improved, our
research focus shifted to the efficient use of the electronic heath record (EHR) as a tool for the dissemination
and implementation of these evidenced-based tools. CPRs are the engines driving complex CDSSs, which
utilize multiple forms of data to calculate patient specific probabilities to inform decision making at the point of
care (we refer to them as integrated CPRs or iCPRs). Our extensive experience in this area sparked an
ultimate vision, to build an EHR agnostic platform from which to implement these tools. This proposal
focuses on the development, testing, and measurement of the impact of a novel, complex, evidence-
based CDSS, built using a service oriented architecture (SOA), that will function across multiple EHR
platforms.
The key innovation of this approach is building a CDSS using a SOA employing a modern, platform-
independent methodology (adhering to HL7 and SMART on FHIR standards where possible) that allows
it to integrate with other open health information technology (HIT) solutions. For the purposes of this
project, the CDSS we develop will operate within Northwell's health information exchange (HIE) environment
and EHRs. The HIE is a data warehouse and exchange which aggregates information across Northwell's HIT
continuum (i.e. EHRs, billing systems, registration systems) to gather multiple types of data (i.e. radiology,
medications, diagnoses, appointments, discharge notes). Building the CDSS using a SOA integrated with the
HIE, as well as with individual EHRs, allows the CDSS to widely and effectively communicate with every
clinical care environment while allowing for customization specific to the needs of each particular micro-
environment with a minimal amount of effort.
Our CDSS will implement two key evidence based CPRs – Wells' Criteria to determine the risk for pulmonary
embolism and IMPROVE Risk Model for venous thromboembolism – and assess their ability to impact care in
two healthcare environments (emergency department care and inpatient medical care) using two EHRs
(Allscripts Sunrise Clinical Manager and Cerner). Specific sets of clinical features will trigger useful and usable
EHR enabled provider alerts, iCPRs, and recommendations. With the ability to continuously monitor patient
records and trigger CDS to the right provider at the most appropriate time, we can infuse and measure the
impact of evidence-based clinical care throughout the health system.

## Key facts

- **NIH application ID:** 9882226
- **Project number:** 5R18HS026196-02
- **Recipient organization:** FEINSTEIN INSTITUTE FOR MEDICAL RESEARCH
- **Principal Investigator:** THOMAS G MCGINN
- **Activity code:** R18 (R01, R21, SBIR, etc.)
- **Funding institute:** AHRQ
- **Fiscal year:** 2020
- **Award amount:** $376,917
- **Award type:** 5
- **Project period:** 2019-03-01 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9882226

## Citation

> US National Institutes of Health, RePORTER application 9882226, Implementation of a Novel Multi-Platform Evidence-Based Clinical Decision Support System (5R18HS026196-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9882226. Licensed CC0.

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