Overview

This section is designed to help when measuring the success of your
program or an intervention. This section will cover:

> I. Steps in Measuring Success
>
> II\. Key Measures
>
> III\. Other Important Measures
>
> IV\. Analyzing the Data

# I. Steps in Measuring Success

There are 4 steps to measuring the success of your program:

## A. Step 1: Define the scope

> The first step in measuring the success of your program is to define
> what you are reviewing. For falls, you will need to develop a
> definition of a fall. The suggested definition of a fall is a sudden,
> uncontrolled, unintentional downward displacement of the body to the
> ground or other object, excluding falls resulting from violent blows
> or other purposeful actions.
>
> When defining a fall, it is important to consider:
>
> *1. Un-witnessed falls (specify that you looked at this type of fall
> when sharing data with staff and leadership)*
>
> *2. Types of "near falls" or "near misses," such as trips or slips*
>
> *You should also define and measure the severity of injuries due to
> falls. The VHA standards for injury severity are as follows:*
>
> 0 = None no injury or disability^2^
>
> 1 = Minor Injury (abrasion, bruise, minor laceration).^1^ Injuries are
> minor in nature, and if they do require any medical intervention, they
> do not extend the patient's hospital stay except for observation or to
> obtain laboratory and/or radiology results.^2^
>
> 2 = Major Injury (hip fracture, head trauma, arm fracture)^1^ Injuries
> which require medical or surgical intervention, increased hospital
> stay, or are disabling and/or disfiguring to a degree that the patient
> will have any degree of permanent lessened function or require
> surgical repair.^2^
>
> 3 = Death^1,2^

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## B. Step 2: Deciding what to measure and how

> The three different types of measurements are outcome, process and
> balancing measures.
>
> Outcome measures help determine if the desired patient goal is being
> achieved. For example are we reducing falls and injuries due to falls?
> You could also examine organizational goals such as "reduce severity
> of fall related injury by 20%\..."
>
> Process measures tell us if we are implementing actions that are
> expected to lead to improvement. For example, you may want to examine
> how many patients are assessed for fall risk or the percentage of
> patients who fell and had all the indicated interventions in place. If
> you find a high percentage of patients who fell did not have all of
> the indicated interventions implemented you may want to focus on
> improving the use of fall prevention interventions. Another process
> measure is the percentage of staff trained in fall prevention.

Balancing measures are factors to monitor while you are improving one
area to ensure that another area of care has not gotten worse. For
example, we recommend measuring restraint use to ensure it does not go
up as you try to reduce your fall rates.

> For examples of each of these measures see the next part.
>
> The measures you use should follow these simple rules:
>
> *1. Contains a numerator and denominator*
>
> *2. Specifies the time in which the information will be collected,
> i.e., monthly, quarterly or annually*
>
> 3\. Specifies the measurement strategy, i.e., observation, random
> checks of patient charts or number of incident reports (Keep in mind
> that if you measure incident reports you're not measuring the actual
> number of incidents, but the level of reporting --- this may skew your
> results.)

## C. Step 3: Collect baseline data

> Once you have chosen your specific measures, such as fall rates, major
> injury rates and restraint use, you will need to collect some baseline
> data. The baseline data is taken prior to the implementation of the
> program or a specific intervention. It is used to determine whether
> there is a change in your measures after the intervention is
> implemented.

Keep in mind that you will need at least five or six baseline data
points in order to ensure accurate data.

## D. Step 4: Collection and analysis of data after implementation

> After implementing the program or specific intervention you will need
> to keep measuring the data. You will need five or six data points
> after the implementation is complete to ensure accurate information.
> For more information on data analysis please see the data analysis
> section.

# 

# II. Key Measures

The measures that are most often used are Fall Rate and Major Injury
Rate. This information is often easiest to show in a run chart. This
will be described in the section on data analysis.

## A. Fall Rate

> The fall rate is a measurement of risk. It tells you how many falls
> you can expect for every 1000 bed days of care (BDOC).
>
> Fall rate = (number of falls/bed days of care) x 1000 BDOC
>
> Note: Bed days of care tells how many days patients were in beds. For
> example, if you have a census of 30 for 30 days this is 900 BDOC. To
> obtain the bed days of care for your unit or facility you should
> contact the health information department.
>
> Example of Fall Rate*\**:
>
> Your facility has had 4 falls in the last month. The health
> information department reports that you had 900 bed days of care last
> month. Thus your fall rate for last month was:
>
> Fall Rate = (Number of Falls/Bed Days of Care) x 1000BDOC = (4/900) x
> 1000 = 4.44 per 1000 BDOC
>
> Interpretation:

For every 1000 bed days of care you can expect to have about 4 falls.

## B. Injury Rates

> Injury rate = (number of injuries/number of falls) x 100
>
> The injury rate tells you how many injuries per 100 falls. It is
> important to separate the injuries based on their severity, using the
> severity index described in the previous section. Depending on the
> intervention you are implementing you may want to measure both the
> major and minor injury rates. For instance if you were implementing
> hip protectors you would want to see a decrease in the major injury
> rate but you may see an increase in the minor injury rate as a result.
>
> Example of Injury Rates^3^:
>
> Your facility has had 80 falls in the last month. Of the 80 falls, 5
> falls resulted in a minor injury, 3 falls resulted in a major injury,
> such as a hip fracture, and the remainder resulted in no injury.
>
> Minor Injury Rate = (5/80) x 100 = 6.25 per 100 falls (6.25%)
>
> Major Injury Rate = (3/80) x 100 = 3.75 per 100 falls (3.75%)
>
> Interpretation:
>
> 6.25% of the falls last month resulted in minor injuries and 3.75%
> resulted in major injuries.

# III. Other Important Measures

When aggregating fall data look for trends such as falls related to
toileting or repeat fallers. This can lead to focusing on reducing
particular types of falls. To do this you may want to keep track of:

> *1. Where a fall occurred (e.g., a specific unit or a place like a
> bathroom or hallway).*
>
> *2. What the patient was doing, or attempting to do, at the time of
> the fall.*
>
> *3. The shift that the fall occurred on (e.g., first, second or third
> shift).*
>
> This information is categorical and the easiest way to analyze it is
> by using a Pareto chart or bar graph.

To aid aggregate review teams and target future interventions you should
keep track of factors that related to each fall, such as communication
issues, assistive devices and environmental factors. For more
information on this and other ways to measure success, please see the
CD-ROM or Web site.

# IV. Analyzing the Data

Once you have collected the data you will need to analyze it. There are
two easy ways to look at your data: run charts or Pareto charts. For
other ways to analyze the data, please see the Web site or CD-ROM.

## A. Run Charts

> Run charts are used to track data over time. They are most often used
> to track data like fall rates or injury rates. It is important to
> clearly mark on the graph the months that the interventions were
> implemented. To show a difference you will want to take the average
> fall rate for the months prior to the interventions.
>
> Example*\** --- The fall rates per 1000 BDOC at a facility for the
> last year are:

  -------------------- ------------ ---- ----------------------- ---------
  Fall Rate per 1000                                             
  BDOC                                                           

  January              10.5              July                    9.9

  February             11                August                  8.7

  March                12                September               6.3

  April                11.3              October                 5.3

  May                  12.4              November                5.6

  June                 10                December                4.5
  -------------------- ------------ ---- ----------------------- ---------

> In May an education program was implemented and in June a program to
> reduce repeat fallers was implemented. The run chart for this is
> below:
>
> ![](media/image1.wmf){width="4.5125in" height="3.317361111111111in"}
>
> To see if the interventions are working you will want to take the
> average fall rate prior to the interventions and after the
> interventions.
>
> In this case, the average fall rate for January through June is:
>
> ((10+11+15+13+13+11)/(950+1000+1250+1150+1050+1100)) x 1000 =
> (73/6500) x 1000 =11.2 per 1000 BDOC
>
> The average fall rate for the months after the intervention
> (July-December) is:
>
> ((10+10+8+6+6+4)/(1010+1150+1275+1130+1080+975)) x 1000 = (44/6620) x
> 1000 = 6.6 per 1000 BDOC

This means that prior to the intervention the average fall rate was 11.2
and after the interventions the fall rate decreased to 6.6.

> **Prior** to the interventions the facility could expect 11.2 falls
> per 1000 BDOC.
>
> **After** the interventions the facility could expect 6.6 falls per
> 1000 BDOC.
>
> If you want to analyze this further you could take the variance of the
> data or do a statistical means test. Both of these can be done using
> functions in Excel. For more information on this, please see the
> CD-ROM or Web site.
>
> **B. Bar Graphs**
>
> Bar graphs are used to visualize categorical data, like the location
> of patient falls or what the patient was trying to accomplish at the
> time of the fall. They can be used to target interventions where there
> is the highest risk. For instance if most of the falls are occurring
> while the patient is toileting then instituting a toileting schedules
> for at-risk patients may be an option. The bar graph is sorted with
> the largest category first going to the smallest category. It may be
> helpful to separate the data into separate charts --- such as falls by
> location or shift.
>
> Example*\**:
>
> A facility tracked what the patients were attempting to do at the time
> of a fall. They found that the falls broke down into the following
> categories:

  ------------------------------------------------------------ ----------
  Toileting                                                    28

  Transferring                                                 25

  Walking to Bathroom                                          20

  Transferring from Chair                                      14

  Walking in Hallway                                           9

  Rolled out of Bed                                            5
  ------------------------------------------------------------ ----------

> The data graphed into the following bar graph:
>
> ![](media/image2.wmf){width="4.257638888888889in"
> height="3.6215277777777777in"}
>
> Bar graphs can also be used to show the incidence of certain factors
> before and after an intervention. For instance, after implementing a
> frequent toileting schedule for incontinent patients and patients with
> urgency, they found that the incidence of falls were:
>
> ![](media/image3.wmf){width="3.865972222222222in"
> height="3.9756944444444446in"}
>
> As you can see there appears to be a difference before and after the
> toileting schedule was implemented. To find out more information on
> how to show that there is a statistical difference, see the Web site
> or the CD-ROM.

*^1^ VHA National Center for Patient Safety. Patient Personal Freedoms
and Security. Fall Prevention and Management. October 2001
http://www.patientsafety.gov/FallPrev/howtostart.html) and DVA. (1996).
Clinical Practice Guidelines: The Prevention and Management of Patient
Falls).*

*^2^ Severity of Injury Level Scale, 35.07, M-2, Part 1, Chapter 35*

*\*Data in the examples are not real; they are examples to show the
process of looking at the data, not guide any interventions.*