Thursday, April 11, 2013

This Is A Useful Summary Of Where Analytics May Help To Make A Difference.

This appeared a little while ago.

5 ways hospitals can use data analytics

By Kelsey Brimmer, Associate Editor, Healthcare Finance News
Created 02/28/2013
When it comes to healthcare analytics, hospitals and health systems can benefit most from the information if they move towards understanding the analytic discoveries, rather than just focusing on the straight facts.
George Zachariah, a consultant at Dynamics Research Corporation in Andover, Mass., explains the top five ways hospital systems can better use health analytics in order to get the most out of the information.
 1. Use analytics to help cut down on administrative costs.
 “To reduce administrative costs – it’s really one of the biggest challenges we face in the industry,” said Zachariah. “One-fourth of all healthcare budget expenses are going to administrative costs, and that is not a surprise because you need human resources in order to perform.”
Zachariah suggests that hospital systems begin to better utilize and exchange the information they already have by making sure their medical codes are properly used, and thus, the correct reimbursements are received.
“Right now, with electronic medical records, you can see that automated coding can significantly enhance how we can turn healthcare encounters into cash flow by decreasing administrative costs,” he said.
2. Use analytics for clinical decision support.
Zachariah said that having all medical tests, lab reports and prescribed medications for patients on one electronic dashboard can significantly improve the way clinicians make decisions about their patients – while at the same time cutting costs for the organization.
“If all the important information is on one electronic dashboard, clinicians can easily see what needs to get done for a patient, and what has already been done. They can then make clinical decisions right on the spot,” he said. “In addition, clinicians will not be double-prescribing patients certain medications due to the lack of information they have on the patient.”
Read the other three here:
This is a very useful summary of where analytics fit. Well worth a read.
David.

2 comments:

Paul Fitzgerald said...

Another good article on the fact that 80% of healthcare data will be unstructured. Important to have a big data tool that doesn't create a huge data warehouse, and can use unstructured data, as well as structured. It will become more important to discover the unknown unknowns.
http://www.zdnet.com/within-two-years-80-percent-of-medical-data-will-be-unstructured-7000013707/

Terry Hannan said...

This topic is not new. It has been well known for decades the link between CDM and health costs as well as health costs inflation driven by ‘administrative/ business’ health care systems.
Research has also shown that effective CCDSS improve the quality of care and reduce costs.
Recent work by Wennberg and others is also demonstrating our current ‘markers’ of care through Case Mix, DRGs and Activity based Funding are POOR markers of care delivery and are significantly inaccurate(1-5).


1. Johns RJ, Blum BI. The use of clinical information systems to control cost as well as to improve care. Trans Am Clin Climatol Assoc. 1979;90:140-52. Epub 1979/01/01.
2. Tierney WM, Miller ME, Overhage JM, McDonald CJ. Physician inpatient order writing on microcomputer workstations. Effects on resource utilization. JAMA. 1993;269(3):379-83. Epub 1993/01/20.
3. Pestotnik SL, Classen DC, Evans RS, Burke JP. Implementing antibiotic practice guidelines through computer-assisted decision support: clinical and financial outcomes. Ann Intern Med. 1996;124(10):884-90. Epub 1996/05/15.
4. Wennberg J. Wrestling with variation: an interview with Jack Wennberg [interviewed by Fitzhugh Mullan]. Health Aff (Millwood). 2004;Suppl Variation:VAR73-80. Epub 2004/10/09.
5. Woolhandler S, Campbell T, Himmelstein DU. Costs of health care administration in the United States and Canada. N Engl J Med. 2003;349(8):768-75. Epub 2003/08/22.