Beate Danielsen, Health Information Solutions Soora Wi, Kaiser Permanente Eileen Walsh, Kaiser Permanente

 Need for customized data collection possibly at different sites connected by an intranet or the internet  SAS foundation technologies available including staff resources familiar with those technologies  Need for customized data reports delivered via an intranet or the internet  Need for flexibility in terms of data collected and reports generated

 Brief introduction to a custom data collection at Kaiser Permanente – Division of Research  Status and challenges 2 years ago  Features of re-designed application  Cost / Benefit considerations  Outlook and future goals

 Neonatal Minimum Data Set (NMDS)  On-line data collection from Kaiser Permanente’s 6 Level III Neonatal Intensive Care Units   18,000 infants screened annually for eligibility   3,000 eligible infants annually  Up to  800 variables collected per infant stay  Data used for monitoring health outcomes, participation in QI initiatives, performing research, and more  On-line reporting

 Web-based application relying on HTML, JavaScript, JSP/Java/JDBC, Tomcat, Oracle, and SAS  Necessity of exporting Oracle tables into SAS  Limited on-line help  Limited real-time error checking  Lack of on-line reporting  Considerable delay between NICU encounter and its abstraction into the database and additional delays to NICU reports  Need of outside programmer for system changes such as addition of new variables or any type of application maintenance  No support of other constituents

Client PC Application Server SAS Base SAS/IntrNet SAS/Graph Unix System Browser sends http request (a completed HTML form) Web Server Apache Unix System broker.cgi Data Web server passes variables in specific format generated via CGI script Runs SAS program and sends result as HTML / XML Web server returns HTML and other generated content such as figures, XML documents, etc. that it received from application server Kaiser DOR Intranet Kaiser DOR Intranet

 Web-based  SAS data sets  DBs fully managed through application  Data integrity checks built into application using JavaScript and comprehensive SAS- based error check

 User-friendly environment with relevant help screens  Multiple levels of access (e.g., review-only user, abstractor, supervisor, DB reports only)  Database activity reports and other custom reports helpful in the abstraction process  Integration of an expanded data collection on a subset of cases (continued)

 Integrated reporting  Ability to populate some of the SAS DBs from other sources  Support DB generation to meet needs of multiple constituents: national and statewide patient outcome registries, payer-sponsored quality benchmarking programs, and regional/local QI initiatives by KP clinical staff (continued)

LEGACY SYSTEM  More complicated set up requiring the maintenance of multiple software products  Limited real-time error checking  Relatively inflexible, data collection only with limited flexibility to add/remove data elements RE-DESIGNED SAS-BASED SYSTEM  Simpler set up requiring SAS only  Real-time error checks  Flexible: Data collection, user management, reporting, support of QI projects built-in  Application built and in production within 6 months  Staff time needed for data entry reduced from 6.0 to 4.0 FTEs  Increased independence of KP staff

 Integration of legacy data into re-designed application  Population of database variables through other KP databases particularly the EMR further reducing abstracting time  Continuous improvement of application interface based on user feedback  Expanded reporting

 SAS/IntrNet only solutions are difficult to maintain  Entirely dependent on the application designer  NMDS implementation makes it easy to find relevant modules (“gatekeeper” macro)  asp.net is a better solution  Only available on Windows-based web servers, therefore not platform independent  Need for ASP programmer

SAS Foundation Technologies combined with basic web techniques provide a powerful tool to institutions vested in SAS to generate completely customized and flexible solutions for data collection and informative reporting.

Beate Danielsen, Health Information Solutions Soora Wi, Kaiser Permanente Eileen Walsh, Kaiser Permanente