Development of a cross institutional database and data management system for research, clinical...

Development of a cross institutional database and data management system for research, clinical management and quality indicators in GI disease Jaroslaw Pillardy Bioinformatics Facility Cornell University Andrew Talal Division of Gastroenterology, Hepatology, and Nutrition University at Buffalo, State University of New York Center for the Study of Hepatitis C Weill Cornell Medical College

Cornell University Bioinformatics Facility Provides bioinformatics state-of-the-art computational resources and analysis tools, and expertise in their applications, to the university community and to outside investigators. Research collaborationResearch collaboration Access to bioinformatics computational resourcesAccess to bioinformatics computational resources Software, database and website developmentSoftware, database and website development Project design and data analysis consultationProject design and data analysis consultation Bioinformatics workshops and trainingBioinformatics workshops and training

Development of a cross institutional database and data management system for research, clinical management and quality indicators in GI disease. The database and data management system was developed initially for Andrew Talal Lab in Weill Cornell Medical College. The system (Datamart) integrated tissue bank data and clinical data. The development started in 2008.

Presentation Overview Overview of the Datamart Current limitations and future development Applications

Overview of the Datamart

What is Datamart? Information Management System (IMS) with Flexible user-defined data structure Integration of existing data from multiple sources Management of Lab data (e.g. tissue bank, sequencing) Web browser access Point-and click interface for all interface functions Data export to file or database Text data mining (in progress)

Datamart components: server Three parts: 1.Web interface ASP.NET C# application. Requires Windows Server. 2.Database MS SQL database. Requires MS SQL Server. Hep C database with 35,299 patients and 33,164,068 labs required 477 GB space (as of 9/3/2013). IRB approval has been obtained to have data on patients examined by WCMC GI division providers. Data from all patients seen by GI providers at Weill Cornell are eligible for inclusion in Datamart.

Sample Repository 3. Repository 2,500 patients with 5,890 blood, liver, plasma, serum, PBMC, and buffy coat samples. We have two separate IRB protocols for samples in which we prospectively consent patients for either blood or liver with or without blood collection. The second consent is given to patients undergoing liver biopsy.

Datamart components: client Four major web browsers are supported: Internet Explorer (7 or newer) Firefox (3 or newer) Safari (5 or newer) Mozilla API based (1 or newer) Most mobile browsers work, we may develop a mobile application to improve mobile content browsing if there is demand The interface refuses to work with incompatible browsers

How is Datamart different? Meta-IMS: Users define how data is stored and what are relations between forms Various data sources: Integrates with hospital clinical databases Internet access:Accessible from any device with web browser Data mining:Convert text based records into numeric records Using previous data:Easy import of previous lab data from Access or Excel repositories

Data Structure defined by the user In a classical system any change in data structure requires programmatic changes in database and interface. In the Datamart, the data layout is defined by authorized users via web interface. Data is stored in forms and fields. Each field may be unrestricted data of a given type (txt, int, dec, etc.) or restricted to a list of values (pulldown).

Data Structure defined by the user.

Database Layout defined by the user

Accessing Data Browsing data with filters Data can be traversed using browsing form, with filters including all form fields. It is also possible display patient information if needed. Advanced search Custom queries, build online using web interface.

Browsing data with filters Data can be traversed using browsing form, with filters including all form fields. It is also possible display patient information if needed.

Advanced search Queries can be built using graphical interface, by choosing forms, fields, filters. Queries can be stored in the server for other users. Resulting data can be exported to a file or a database table.

Datamart advanced search

Entering Data Manually Data can be entered or modified manually if needed. Each record can be edited, linked forms can be edited together. An example is data from the sample repository in which data on liver or blood samples need to be entered. Data import Preferred way of entering data is data import.

Manually entering data

Importing clinical data from hospital database (e.g. EPIC) Data can be imported from various database sources via database queries. Any data source that can be queried in SQL can be imported. Imported data are matched to the existing data and the format converted as appropriate. External data are then added or internal data is updated.

Importing clinical data from hospital database (e.g. EPIC) Data matching is done using multiple fields (e.g. for patients last name, DOB, PAT_ID, MRN, IDX etc). Records with inconsistent match or otherwise inconsistent data are reported to the operator for manual inspection. Import can be stopped and restarted at any time. If an external source does not support incremental export, dump of the previous version of the export can be used to limit the amount of data to process.

Importing clinical data from hospital database (e.g. EPIC) Rules for data matching and conversion are defined by an authorized user via graphical interface. Consistency check is performed during import, any data failing consistency check can be ignored or reported as inconsistent for inspection and correction.

Importing data from other repositories Data collected in other media such as a text file, Access database or Excel spreadsheet can also be imported. This type of import is not automated and requires programming help. MS Access file can be configured as SQL query compatible resource by a server administrator, and then imported the same way as any other external source. Datamart has been initialized with data from Access database which was set up as SQL queryable resource.

Importing data from other repositories Data collected in other media such as a text file, Access database or Excel spreadsheet can also be imported. This type of import is not automated and requires programming help. Excel file can be imported directly using a customized C# script written for this particular file, or the data can be imported into SQL database or Access database and then imported using the standard system

Exporting data to text or database Data can be exported from data browsing or a query. Data can be exported to tab separated text file, which can be further converted into any appropriate format (e.g. SAS) or opened in Excel. database table for further processing This type of data export can be very useful for clinical trials or transferring data between labs. Data can be further processed.

Exporting data to text or database

Datamart security The IMS is protected with passwords and encryption / decryption keys. Every user is assigned to a role that defines the access and modifications rights. Sensitive data (names, DOB, MRN) are encrypted and can be only accessed by users with encryption / decryption keys. Not even database administrators have access to these data.

Datamart security: no key login Multiple slides

Datamart security The users activity in the LIMS is logged, including logins, logouts, data export and import. No data can be physically removed from the database new versions are just visible in front of the old. The IMS has auditing and data recovery procedures. Any data record can examined using auditing page, where all the previous versions can be inspected, and the changes reverted if necessary.

Datamart security: auditing previous record versions

Datamart security Client related security -Encrypted communication enforced -Only selected browser versions are accepted -Page will log out automatically if not used -Client browser caching is switched off -User cannot use back function from the browser

Datamart security Users Access to data can be controlled on multiple levels -allow or deny access to encrypted data -allow or deny access to particular forms -allow or deny access to editing functions -allow or deny access to export/import functions Users can be assigned group rights based on projects.

Datamart data mining Many records from hospital databases contain useful data in free text format This data can be extracted and imported as numerical or categorized data points to other forms This feature is under development.

Datamart data mining First, data is imported as is and stored in the database as free text. Second, data mining procedure is run (via web interface). Data mining procedure finds key phrases and words and extracts data in question (e.g. liver cirrhosis stage). The extracted data is converted into appropriate numerical or dictionary format and stored in another form, or another field in the current (mined) form. This way both formats are preserved: the original free text and extracted data. Data mining may be re-run in the future when improved data mining procedures are available to update extracted data.

Current limitations and future development

Optimization The query design module needs to be further expanded to include more complicated data searching capabilities, including text search inside pre-defined entries and more flexible form joining. The interaction with the database should be optimized taking into account database size, a balance between different types of data, which will result in significant speed increase.

Data import The Datamart is designed to import data form one external source at a time. The import module itself is very flexible and can accept a variety of formats and data source types (any data source supporting SQL queries is compatible), but only one source at a time may be configured and used. This feature is going to be changed to multiple simultaneous sources.

Data import The import module should be generalized to be able to switch between pre-defined sources. Pre-defined import templates for particular EMR systems (in addition to a generic SQL import source) should be available. Some external data sources do not provide incremental data export (e.g. EPIC where it is not possible to export only new data), therefore the entire database needs to be scanned and imported. In such a case it is a challenge to complete the data import quickly. The data import module needs to be optimized for increased data import speed.

Data mining Data mining module is still under development. Limited form of data mining is available for import procedures: data located between two known phrases can be extracted and converted text data can be converted to controlled vocabulary (i.e. pulldown) complicated conversions are handled by built-in functions (e.g. converting ICD9 classes, date formats, height). Scanned documents cannot be queried at present

Applications

Research

Research Accomplishments AASLD 2012-4 presentations 2 Presidential poster of distinction 1 Presidential Plenary EASL 2013-1 poster presentation AASLD 2013-1 abstract submission Manuscripts 2012 to date: 6 published 2012-to date 8 submitted or in preparation 3 active collaborations 1 Gastro paper 1 Clin Proteomics paper 1 submitted manuscript

Translational research Studies performed using data and samples from Datamart

Collaborative Research Research collaborations- Multiple research groups using the same data system, accessible remotely.

Retrospective reviews Resident and fellow studies performed using data from Datamart

Clinical Trials Datamart is a good tool to export data for clinical trials. Data can be extracted using an appropriate queries, then exported in a text form. If further conversion is required, external script or program can be used. Datamart has been used over last 1 year to export data for Gilead clinical study of Hepatitis C (GS-US-321-0101).

GS-US-321-0101 Datamart has been used over last 1 year to export data for Gilead clinical study of Hepatitis C. Lab results and patient data related to the study was first extracted using pre-defined queries.

GS-US-321-0101

The results of the queries where then exported to an external database table for further processing. Exported data was processed by a short C# program (script), that converted Datamart lab results categories and names to Gilead standards, and prepared the input for SAS program to convert exported data to SAS format. The last step was to run SAS program with a set of commands produced by above described C# script which produce SAS formatted file for Gilead. The SAS file was copied to Gilead server using sftp protocol.

GS-US-321-0101 The data was exported every 4 weeks. Initial setup required about 3 days of programmer work. Monthly export took about 10 minutes.

GS-US-321-0101

Clinical Care BGMC Cerner 6 VA UB SMBS ECMC Allscripts Meditech RPCI Allscripts Dent Tower UBMD Allscripts

Clinical Care Datamart is designed to interact with various external data sources. Datamart is capable of importing data from any source compatible with SQL queries. Data is not only copied, but also converted into the Datamart data format and schema. This approach makes the importing module very complicated, and the process of designing import parameters is not fast, but the data imported from the external source is properly verified and usable. Once the import schema and parameters are decided, repeating import process is easy.

Feasibility and Gap Analysis Site to Establish Liver Transplant Program at Buffalo-Aug 4 to 6, 2013 Sukru H. Emre, MD, FACS Professor of Surgery and Pediatrics Director, Yale-New Haven Transplantation Center Chief, Section of Transplantation and Immunology Department of Surgery Yale University School of Medicine Michael Schilsky, MD Medical Director, Adult Liver Transplant Yale New Haven Transplantation Center Weaknesses for establishing liver transplant Lack of an integrated EMR/information system amongst UB affiliated institutions hinders communication, quality of patient care, Reporting responsibilities related to ethical/medical and legal aspects Impedes workflow for regulatory reporting to UNOS, CMS, Joint Commission, and NYS DOH. The Datamart could potentially be used to overcome this issue.

Quality Indicators for CRC Colorectal cancer (CRC) is third most common cancer diagnosed and third leading cause of cancer death in men and women. Cancer screening via colonoscopy is preventative against CRC by removal of precancerous lesions. Colonoscopy requires high quality examination; low quality examinations lead to interval cancer, CRC diagnosed within five years of a negative colonoscopy. Three key quality measures are Adenoma detection rate (ADR)- Detection of one polyp per 100 colonoscopies Proposed ADR is 25% for males and 15% for females Most important endoscopist indicator as higher rate translates into lower incidence of interval cancer development. Cecal intubation rate- # of exams in which cecum is reached per 100 colonoscopies. Should be 95% Follow through with post colonoscopy surveillance recommendations

Importance of CRC Quality Indicators ADR Risk of interval CRC 10-fold higher if endoscopist has ADR < 20% 1 Effected by withdrawal time, quality of prep, and endoscopists experience. Cecal intubation rate More cecal intubation, less cancer 2 1 Kaminski et al, NEJM 2010; 2 Baxter et al, Gastroenterology 2011

Proposed CMS Payment for QI 2014-ADR added to PQRS 2014-18-0.5% Medicare physician reimbursement with continuation of PQRS and Meaningful Use. 2019 physicians can participate in a new Update Incentive Program (UIP). beefed up PQRS and will compare physician performance based on quality metrics developed by societies and other stakeholders. Providers not participating will receive a 3% reimbursement reduction.

How to capture CRC QI? ADR Requires link between endoscopy and pathology databases Requires notation of colonoscopy withdrawal time in endoscopy report. Cecal intubation rate Requires notation in endoscopy report. With potential changes likely to be proposed, require fluid system.

Datamart relationships Datamart Weill/Cornell Epic NYPres Hosp Eclypsis UBMD Allscripts ECMC Allscripts Meditech Kaleida Cerner RPCI Allscripts Medical information Billing information Payroll Hosp RVU Patient keeper Clinical care Research Quality indicators Financial statements/Pay for Performance

Summary and conclusions Datamart permits data linkage from a variety of sources Security can be set as appropriate HIPPA compliance System has variety of applications Research Clinical care Quality indicators Billing

Development of a cross institutional database and data management system for research, clinical...

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