Automated point of care (POC) documentation closes the loop between the office management systems and the clinical documentation requirements for homecare. Point of care helps bring an agency’s standards into the field and enhances best practice. However, the real power of POC, in my opinion, is yet to be tapped.
Data mining- the automated searching of patterns of information using specific criteria- is now coming into its own for homecare. While it’s mainly an advantage to home health, with the coming standardization of hospice quality data collection, it will not take very long for benchmarking firms to get tools up and running for hospice as well. Home health data mining is based upon the OASIS instrument. Substantial reliability has been demonstrated for the OASIS data set items (Madigan, 2002). It’s about time for the time consuming exercise of performing the OASIS to result in something positive!
Most research on clinical data in homecare has been manual and tedious. Now, data mining tools are available and the effort can be outsourced. OASIS has been around long enough that patterns of information can be compared real time to assessment data, so that predictions of outcomes result. When an agency can identify high risk patients in the start, then beat the odds, preventing re-hospitalization or emergency visits, the statistical evidence is a very powerful marketing tool. Take advantage of proactive data tools and find the gold in them thar hills!
That said, data miners will be digging for fool’s gold if they don’t use additional POC tools to standardize the other aspects of documentation- specifically variance reporting necessary to judge the impact of care (Versel, 2003). Documentation of patient responses to care should be simple and reliable. Otherwise the clinical data warehouse will be full of data, but won’t be worth much. Recall the old saw “healthcare is drowning in data and dying of thirst”. Or, what you thought was a gold mine, turns out to be a data landfill.
For variance charting against care plans, I go for the ultra simple model: met, not met, or not applicable. A numerical value can be assigned to each of these outcomes so that a number of meaningful conclusions can be drawn by patient or by group improvements. Check out Melina Huffman’s (2005) book on how to design a homecare outcomes program. Most modern point of care systems can meet the functional requirements of her recommendations.
References
Huffman, M. (2005). Implementing Outcome-Based Home Care. Sudbury, MA: Jones and Bartlett.
Madigan, E. A. (2002). The scientific dimensions of OASIS for home care outcome measurement. . Home Healthcare Nurse, 20(9), 579-583.
Versel, N. (2003). A beautiful mine. Modern Physician, 7(7), 26.
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