Background and Aims:
The Virtual Data Warehouse (VDW) at the Institute for Health Research (IHR) at Kaiser Permanente Colorado (KPCO) is the data source of choice for the IHR analytic team. This ...research ready data source is important for efficient use of analytic team resources. Our aims are to 1) describe the attitudes, methods and processes that lead to high data quality in the VDW at KPCO, and 2) provide examples of improvement successes.
Methods:
The methods used to pursue VDW improvement include the following:
we gathered support from all local interested parties and provided avenues for all interested parties to participate in setting VDW file improvement priorities along with the allocation of available resources to support the process;
we worked to develop relationships with experts in data content areas throughout KPCO’s clinical delivery system and those overseeing legacy source data systems;
we stayed informed of issues concerning the VDW by participating at the national level in committees concerned with VDW development;
we encouraged programmer networking at both the local and national levels;
we created an environment that encouraged detailed file documentation;
we encouraged two way communications between those using data files and those creating data files.
Results:
We found that nurturing a collaborative team spirit encouraged 1) the identification of key individuals best suited to improve specific files, 2) realistic estimates of time necessary to complete the improvement tasks, and 3) the freeing of time for those key individuals to perform these tasks. Engaging content experts outside of the IHR allowed for better understanding of legacy data files and allowed for lead time to respond to data system changes. Engaging programmer networks allowed for the development and sharing of best practices. Enhanced VDW file documentation lessened the chance of misinterpretation or misuse of data. Enhanced communication between those creating the VDW files and those using the files assure continued improvement.
Conclusions:
Good communication among many different parties and a supportive team spirit from local interested parties are necessary to facilitate the building and maintenance of a high quality research data structure.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Background and Aims:
The positive predictive value (PPV) of a hyperkalemia diagnosis in administrative data has not been evaluated and relationships between coded hyperkalemia diagnoses, elevated ...potassium concentrations and clinical signs have not been assessed. The aims of this study were to determine the performance of a coded diagnosis in administrative data at identifying 1) clinically-evident hyperkalemia and 2) patients with potassium >= 6 mmol/liter.
Methods:
This retrospective observational study included 8,722 patients with diabetes newly-initiating ACEi, ARB, or spironolactone therapy. The outcome measure was the first hyperkalemia-associated event comprised of a hospitalization, emergency department visit or death that occurred within 24 hours of a coded hyperkalemia diagnosis and/or potassium >= 6 mmol/liter during the first year of therapy. The medical records of all patients identified from administrative data as having hyperkalemia-associated events were reviewed as were a random sample of records of patients identified as not having hyperkalemia.
Results:
Among the random sample (n = 99) of patients identified from administrative data as not having hyperkalemia, none had hyperkalemia upon record review. Among 64 patients identified from administrative data as having hyperkalemia, all had a hospitalization or emergency department visit associated with a coded hyperkalemia diagnosis (n = 41), potassium >= 6 (n = 9), or coded diagnosis and potassium >= 6 (n = 14). Of the 55 total patients with a coded hyperkalemia diagnosis, 42 (PPV 76%) had clinically-evident hyperkalemia; 32 (PPV 58%) had potassium >= 6. Of the 9 patients identified with potassium >= 6 who had no coded hyperkalemia diagnosis, 7 (PPV 78%) had clinically-evident hyperkalemia. Although 5 of the 64 patients died at the time of the hyperkalemia outcome, none had a coded diagnosis of hyperkalemia-associated death and hyperkalemia was not mentioned on the death certificate of any patient.
Conclusions:
Nearly one-fourth of patients with a coded hyperkalemia diagnosis do not have clinical signs and nearly one-half do not have potassium concentration >= 6 mmol/liter. Because both false positives and negatives occur when using coded hyperkalemia diagnoses to identify hyperkalemia-associated outcomes from administrative and death certificate data, medical record validation of hyperkalemia outcomes is necessary.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Background:
HMORN leadership charged several Workgroups to check and describe Virtual Data Warehouse (VDW) data areas, provide observations on data quality across sites, and recommend needed actions. ...Availability of laboratory (lab) results data in the VDW in a standardized format is desirable, but across HMORN sites, lab content is either incompletely developed or not built at all. Further, there is little consistency across sites with regard to the approach to adding lab content. The work of the VDW Lab Content Area Workgroup (Lab Workgroup) therefore focused on developing a standardized approach to incorporating lab content. We describe development and implementation efforts to create and maintain a standardized lab result content area across HMORN sites.
Methods:
The Lab Workgroup identified priorities:
Establishing standardized naming conventions for variables;
Determining test results to be initially incorporated;
Encouraging site-specific exploration and development of lab information system content as well as lab department contacts;
Developing a lab test reference document;
Serving as content area experts; and
Conducting content quality checks.
A list of possible tests to incorporate was circulated to HMORN sites. The Lab Workgroup wrote code to generate descriptive data and data checks across sites for glycated hemoglobin (HGBA1C) and serum potassium result content. A lab test metadata table was posted for site data managers to complete.
Results:
Incorporation of chemistry tests that were most often requested for research was identified as an initial priority. Microbiology and tumor markers content were other high priority areas. Standardized lab variable naming conventions were determined for the list of initial tests. Results of data checks for HGBA1C and potassium concentration results will focus on describing the extent and quality of these files at sites, as well as identify potential issues to be addressed. Sites were surveyed about the barriers, facilitators, and priority of adding lab content to VDW. Results of all this work as well as an excerpt from the lab test reference document will be presented.
Conclusions:
The availability of lab test results information in the VDW in a standardized, extractable format across HMORN sites is a technological advance in data availability and sharing. The work described here will provide important initial insights into the lab content area potential of the HMORN VDW.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Background/Aims:
The Virtual Data Warehouse (VDW) is the HMO Research Network (HMORN) approach for facilitating multisite research while protecting the privacy of members and proprietary corporate ...information. A valid and sustainable VDW is critical to the success of the HMORN, and is needed for HMORN’s inclusion in many of the most important public health initiatives planned for the next few years.
Methods:
In November 2007 the HMORN Governing Board approved the VDW 5-Year Strategic Plan, including creation of a VDW Operational Committee (VOC), reporting to the Assets Stewardship Committee (ASC) and providing coordinated oversight of the development, maintenance, and enhancement of the VDW. The seven members of the VOC are investigators and analysts representing HMORN’s major consortia projects: CERT, CVRN and CRN.
Results:
In 2008, the VOC accomplished two major short term goals:
Creation of a comprehensive data quality checking system, implemented by seven content area expert Working Groups (WGs) consisting of 23 investigators and 23 programmer\analysts. The content areas of the WGs are enrollment and demographics, pharmacy, utilization, tumor, vital signs, laboratory, and census. The WGs assessed data availability and completeness for their content area and reported findings to the VOC and ASC, including recommendations for changes and enhancements. WG reports will form the basis for ongoing VDW documentation that will be used to standardize HMORN VDW descriptions for grants and proposals;
Development of a budget, staffing plan and priorities for 2009. The 2009 priorities include development of VOC standard operating procedures for creating new data content areas and changing current data areas/definitions, documenting policies for use of the VDW, promoting use of the VDW, and creation of additional WGs for death (new VDW content area), informatics, implementation, and data documentation. The documentation WG will oversee issues such as data dictionaries, data checking documentation, programming resources, a clinical concepts library, user guides, and incorporating updated VDW information in the HMORN Collaboration Toolkit. Looking forward, the VDW 5-year Strategic Plan includes streamlining IRB approval for multisite research and enhancing HMORN informatics capabilities.
Conclusions:
The newly created VOC has made substantial progress in helping make the HMORN VDW an even more valuable and useful resource for the network.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
PDF
