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Quality in long-term care: from quality assurance to performance improvement.

In long-term care and assisted living facilities there is a need and an opportunity to move from a quality assurance approach to performance improvement. There is a need to focus on clinical measures and outcomes measures, as our customers want affordable quality. We must meet the expectations or lose the customer. The opportunity lies in the current approach taken by the Centers for Medicare and Medicaid Services with their focus on the quality indicators, and the resources furnished to long-term care facilities through the QIO's--quality improvement organizations. The DelMarva Foundation for Medical Care is partnering with facilities in DC, Maryland and Virginia to assist with the quality improvement opportunities.

One of the best definitions of quality is, I believe, customer satisfaction. We all know that we have both internal and external customers, but we might not necessarily think of other aspects of quality. The first is income-oriented quality, which increases income through features that add value to our customers; the second is cost-oriented quality, which reduces cost to the customer and the provider by being free from failures, rework and waste.

In the "old" days, we looked at quality as something we really couldn't measure unless we did an audit, corrected the mistakes and ordered our staff to "fix" things, as some of us believed that poor quality and defects come from people, and if I "could just hire some good employees, I wouldn't have so many problems." And the other--"I am in charge here and I have to watch people all the time or they will make a mistake." With exhortation to goals, a little fear and some monetary incentives, we should be able to get the job done.

Hospitals and long-term care facilities with JCAHO accreditation have known for some time that quality can be improved and that quality is measurable. Long-term care facilities will lose residents and staff unless we learn how to meet and exceed their expectations. We must facilitate the ability of the staff to improve their own work processes and teach staff to find the root cause of problems and to identify solutions. Thus, supervisors and managers become facilitators of workers ideas rather than directors of workers activities.

Measurement and understanding of processes improves quality. Give staff the training and the opportunity to improve and remember Juran's 85/15 rule--that 85 percent of management effort is focused on 15 percent of the problems. One model which might prove useful to us as we look at quality improvement is this: Plan, Do, Study, Act. Or, we could look at a similar model developed by Hospital Corporation of America, which is FOCUS-PDCA:

* Find a process to improve

* Organize a team that knows the process

* Clarify current knowledge

* Understand variation

* Select a potential process improvement

* Plan

* Do

* Check

* Act

Clinical informatics can help improve quality, with using the computer to analyze data and to compile meaningful charts and graphs used in performance improvement. Some statistical tools we could use for data analysis and measuring consist of:

* Cause and Effect or Fishbone Diagrams

* Histograms

* Pareto Charts

* Scatter Diagrams

* Run Charts and Control Charts

In looking at processes in facilities we ask ourselves: What do we want to accomplish? What is the problem? Brainstorming is a tool often used to identify the variables to study. A cause and effect, or fishbone diagram, is often useful to study a problem and identify variables which can lead to a solution or to further study.

Further problem definition could include Pareto analysis. A Pareto chart is a bar chart, with the bars in rank order of occurrence, separating the "vital few" from the "useful many"; i.e., the 80/20 rule is useful, that 80 percent of the gain will come from 20 percent of the categories. Pareto charts can be used to study such variables as reasons for call-ins on a certain day of the week, causes of falls and medication errors, reasons for complaints about the food, or causes for hospital admissions/readmissions.

Histograms can be used to identify the distribution of one variable--identified from our Pareto analysis. We can visualize the central location, spread and shape of our data and make some decisions about whether or not there are patterns that bear further study, as it gives us a comparison of averages and we can see the sequencing and variation of data. Some uses of histograms might be for length of stay, length of time to respond to stat requests for x-rays and the number of diabetics with reduced HgA1c levels.

Scatter diagrams help us look for a cause and effect relationship, as in the amount of a drug given and the subsequent pain rating. Another example could be the rating on a particular question in relationship to overall customer satisfaction.

A final question to ask ourselves after looking at data we have analyzed using one or more of the above tools is: have we designed processes that are stable over time; and are we in compliance with the processes we have set up? Run charts and control charts will give us the answer to these questions and give us powerful tools to analyze variation in processes over time; and even we have special or common cause variation.

Common cause variation is variation which occurs because the process itself is not stable or does not give us consistent data over time. Generally, common cause variation is present when there are seven data points above or below the mean in sequence. Common cause variation means that the process must be studied and redesigned. Using the Plan-Do-Study-Act Model, we would plan and test process changes.

Special cause variation is due to a specific and special circumstance. It can mean that our process is not stable, and therefore needs to be redesigned, or it can mean that our process is stable, and that all we have to do is learn how to identify and prevent the special cause variation. We would not take action without understanding the nature of the variation in the process.

There are many aspects of a performance improvement program; many improvement opportunities to be ranked and studied, such as risk management and safety, infection control, employee health, team productivity, customer satisfaction, and monitoring and learning from sentinel events, which in long-term care, have been identified by CMS as fecal impaction, dehydration and pressure ulcers. Our long-term care quality indicators come from our Resident Assessment Instrument (RAI), or the Minimum Data Set (MDS). This tool forms the basis of quality improvement in the long-term care facility, and the data from the assessments is transmitted to CMS on a regular basis. Quality indicators are available to us, as well as benchmarks with other facilities. This forms the basis for comparisons in real time as to how we compare with like facilities.

The outcome of all the focus on quality tells us that we must become leaders instead of bosses; coaches instead of enforcers. While our goal is always to prevent and eliminate problems in systems and in processes, sometimes, unfortunately, people do have to be counseled or replaced. And entire organization, starting with the Board of Directors, must understand quality improvement concepts. Teamwork, empowerment, process management with statistical tools - are all powerful concepts in helping us focus on the outcomes of care and on communicating and rewarding the truly positive accomplishments of our healthcare teams.


Dana, Bernie (2002). Presentation "Old Way, New Way" Changing the Way We Think

About Quality in Long-term Care. National Association for Healthcare Quality, Nashville, Tennessee Guide to Quality Management, 8th Edition (1998). Published by the National

Association for Healthcare Quality.

Murray, Sandra K. (1999). A Dash Through the Data. Video produced by the National Association of Healthcare Quality and Pfizer Pharmaceuticals.

By, Sandra Clatterbuck, MS, RN, CPHQ

Assistant Administrator, Methodist Home of DC
COPYRIGHT 2003 Capital Area Roundtable on Informatics in Nursing
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2003 Gale, Cengage Learning. All rights reserved.

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Author:Clatterbuck, Sandra
Publication:CARING Newsletter
Geographic Code:1USA
Date:Mar 22, 2003
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