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Jay Fisher has written a series of articles on helping providers implement the AIRS software so that they can improve their data collection and reporting. The article posted below was the original article on data collection for the AIRS software. Since then, he has written other articles dealing with implementation and data collection issues and I have posted these new articles in the following links. There will be more articles coming and I will post those as they become ready for publication. Click HERE for the article on Section 5 Data Quality Tips for Primary Care Providers Click HERE for the article on choosing and customizing data collection forms. Click HERE for the article about getting a handle on lagged data. Data Collection Strategies for Success by Jay Fischer, Ph.D. Health Program Administrator II, Organizational Development, Office of Systems Development Programs face increasing demands for data collection brought about by funding source accountability, accrediting organizations, new automated data collection systems (including AIRS) and internal operations such as program planning and evaluation. While the demands for data collection and its complexity are increasing, many programs have not been able to set aside time to plan an effective data collection strategy to cope with the changing environment. This article will attempt to suggest ways to strengthen the data collection process. The issues discussed here do not address the concepts of data entry and quality control of data once entered. While these are important building blocks of a total data management program, they involve separate issues and perhaps separate resources. You may find that some ideas are more applicable than others or that they serve as a focal point for further discussion among colleagues at the work place. The most successful data collection strategies remain malleable and can be modified to meet the unique organizational climate and system of service delivery within the organization. The first phase of any data collection strategy involves deciding what data to collect. For AIRS, there are three data groupings that need consideration. The first group is data elements required by the software. The required fields have field names in a bold black font. The second is additional data elements required by the section(s) of the AIDS Institute to whom your program reports. You will need to check with the section (s) in question, to learn, what fields, beyond the system requirements, may also be required. The third group is data elements not covered above, that your program wishes to collect. When deciding upon what needs to be collected, items that are required by your section(s) should be given equal weight to those required by the software. Only when data collection strategies are in place for these two groups of data elements, should you move toward collecting the majority of data in AIRS, which is not required. In short, start with reporting requirements and branch out from there. Remember that software required fields along with those required by your section(s), account for significantly less than 50% of all fields in AIRS. The task is really more manageable than it might first appear. Deciding on a data collection form is the next step. We have developed a set of data collection forms that correspond to data entry screens in AIRS and are available from for download from the AIRS web site. Alternatively, you may wish to modify your existing data collection forms already in use in your organization or create new ones, as long as the forms contain the necessary fields. In some of the larger healthcare settings, it may be difficult to modify existing encounter forms so that using our data collection forms be something to seriously consider. When selecting and/or developing data collection forms, try to review existing forms and systems with an eye toward eliminating multiple forms that essentially capture the same information or forms/systems that capture data that is no longer needed. Moreover, make sure that data collection mechanisms exist to capture all the needed data. Where there are gaps, design new data collection mechanisms with appropriate staff input. At least one provider has used this opportunity to create an interdepartmental/interdisciplinary forms committee with good results, which has resulted in the elimination of several unnecessary forms. Some providers have also used the committee approach to include the Medical Records Department, to more fully integrate data collection forms within the patient/client record, making information more accessible to clinicians. Once forms are selected, who will complete them? MOST programs develop an initial approach that mirrors existing lines of authority and job description. An alternative is to identify those individuals, best suited by virtue of patient flow or contact. This can best be done in a workshop format, where staff come together to "brainstorm." Select a neutral staff member to act as facilitator and recorder. Record on a flip chart those persons, who first come to mind as being asked to routinely complete data collection forms, based on current practice. Include instances where data may need to be accessed externally e.g. warehouse, storage files etc. Have the facilitator go around a second time and ask participants to think how patients/clients move around the organization on an average day in terms of staff contact. Record their perceptions on new flip chart pages. Flow diagrams may help. Compare how patients flow within your program, against who might normally be perceived as completing data entry forms to identify gaps in data collection practices. Where possible and practical, gradually work toward eliminating the gaps. Successful data collection is the cornerstone of data management that should reflect both the organization and the pattern of service delivery, if it is to be maximally effective. If you have any question or would like to discuss these strategies in more detail, contact Jay Fischer, Office of Systems Development, Division of HIV Ambulatory Health Care,
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