# Presentation: 902598

## Adopting TBPT Tools: DSIC Issues

***The Experience of the Kimmel Cancer Center at Jefferson***

- Jack London, PhD
- Thomas Jefferson University
**May 15, 2007**

## TJU Environment

**Jefferson is organized into two corporations.**
- Several years ago, Thomas Jefferson University (TJU) and Thomas Jefferson University Hospital (TJUH) became two legally separate, but very linked, corporations.
**Thomas Jefferson University ** (TJU) consists of Jefferson Medical College, the College of Graduate Studies, and the College of Allied Health Sciences.  The Medical College was founded in 1824, has awarded 26,000 medical degrees, and has more living graduates than any other U.S. medical school.
-  **Thomas Jefferson University Hospital **(TJUH) is a 957-bed academic medical center, and the flagship institution of the Jefferson Health System, which serves the Philadelphia metropolitan area.
- The **Kimmel Cancer Center at Jefferson** carries out basic and clinical research through TJU, and provides clinical services through TJUH.

## Tools Adopted

**TJU has adopted and deployed TBPT tools.**
- The Kimmel Cancer Center at Jefferson is an adopter of TBPT tools.  Working with the developers, the following tools have been deployed and are being are being integrated into the cancer center work flow.
- cancer Text Information Extraction System (**caTIES**):
- Automatically extracts, concept-codes, and de-identifies information contained in Anatomic Pathology Laboratory reports.  To date, over 50,000 surgical pathology reports processed.
**caTissue Core**:
- Manages information characterizing biospecimens avaialble for research.  Currently, this application is used with three tumor banks, having over 6,000 tissues.
- Adopter activities are currently focused on deploying new application releases, and particularly the integrated **caTissue Suite** application.

## caTIES (cancer Text Information Extraction System)

- caTIES, developed by UPMC, takes Surgical Pathology reports from the Hospital pathology information system, de-identifies and concept codes the report text, and creates both  “private” (PHI) and “public” (non-PHI) data stores.

## Thomas Jefferson University IRB

-  Prior relevant experience existed with the TJU IRB in gaining approval for participation in the Pennsylvania Cancer Alliance Bioinformatics Consortium project for establishing a state-wide biospecimen database.
-   The IRB wanted evidence of TJU IRB/HIPAA training certification of all project staff who might have access to PHI, including programming staff.
-   Expedited approval granted.

## Thomas Jefferson University Hospital

-  AP Lab manager wanted the caTIES servers physically in the lab area, along with his clinical servers (to assure physical security).
-   The Hospital Compliance Office  - a Hospital regulatory office, separate from the University IRB - was initially not comfortable with the replication of PHI on the caTIES server.  However, the AP Lab manager prevailed in his need that the caTIES application’s Private data store be on a separate server.
-   Lab manager only comfortable with the interface to his clinical system being provided by the lab system vendor (Cerner).

## caTissue Core

-   The focus of this tool is the management of research tumor banks, and while it incorporates PHI, it does not interact directly with hospital clinical systems (as caTIES does).
-   The TJU IRB application for caTIES was amended to include caTissue Core, and, looking forward to the integration the these two tools, caTissue Suite.
-   caTissue Core (and eventually Suite) will replace several legacy research tumor bank systems.

## Separate Data Stores vs Firewall Tunnels

- caTIES is designed to maintain two separate data stores:  a server with PHI inside the firewall, primarily for access by honest brokers, and a de-identified data store outside the firewall for researchers.

- AP LIS

- Private Report Data Store

- formatted  (HL7) report transfer

- Public Report Data Store

- automatic report     de-identification

- caTIES

- automatic data extraction

- Researcher

**FIREWALL**

## Separate Data Stores vs Firewall Tunnels

- caTissue Core does not have a separate data store design.  In one scenario, a researcher can “tunnel” through the firewall, and be given access to non-PHI data.

- Tumor Bank Data Store

- caTissue Core

- Researcher

**FIREWALL**

- Honest Broker

## Separate Data Stores vs Firewall Tunnels

- In an alternative scenario, a researcher only has access to a replicate of the tumor bank data store, that has PHI removed.

- Tumor Bank Data Store

- caTissue Core

- Researcher

**FIREWALL**

- Honest Broker

- Tumor Bank Data Store Copy w/o PHI

## Separate Data Stores vs Firewall Tunnels

**Pro’s & Con’s:**
-   “Tunnel” approach is operationally simpler - no de-identified database copies need be periodically made and moved outside the firewall.
-   “Tunnel” approach gives all users a consistent data view:  there is only ONE database.  The replicate alternative maintains TWO databases, the replicate always having “stale” data.
-   Not all situations demand instantaneous updates.  Tumor bank data that is say, 12 hours old,  is satisfactory for researchers.
-    University/Hospital I.T. departments are reluctant to allow tunneling - want proof that there is no viable alternative.
-   IRB’s more comfortable knowing that no PHI even exists outside the University firewall.
-   It is conceivable that either approach can be compromised by faulty software.