Ashbec LLC - Treatment Optimization for Patient Safety (TOPS)
 

Defining a Report

Report Type: Graph or Table?

Graphs show data about facility performance over a longer timeframe for a smaller number of facilities. Line graphs provide an excellent way to see overall trends and comparisons between facilities over time. Tables show the same type of data for more facilities over a shorter timeframe. Tables also make it easier to see precise percentile rankings. More specifically, graphs allows for the comparison of up to seven facilities over 20 quarters. Tables provide precise data for up to 20 facilities over the previous eight quarters.

Reports can include national percentile rankings for an unlimited number of performance metrics. Each metric will appear on a separate page. However, the form of the report will be uniform. In other words, while you can select a large number of metrics to be ranked in a single report, they must all appear as graphs or all as tables. They cannot be mixed.

Data contained in the report

All types of data represent percentile rankings for all medical facilities in the United States that have provided sufficient information to the Center for Medicare and Medicaid Services (CMS). The data appearing in a graph or table on a particular page of the report can be either a percentile ranking of an individual metric from the CMS Hospital Compare data sets or a client defined aggregation of groups of those metrics. (Aggregates are discussed in more detail below.)

The individual metrics currently available for use in reports are listed here. (This list will be updated approximately every three months.) Clients can request the addition of any other data available on the CMS Hospital Compare website but adding it to the reporting database will require payment of a setup fee. The currently available metrics are as follows:

COMP_HIP_KNEE
Rate of complications for hip/knee replacement patients
HAI_1_SIR
Central line-associated bloodstream infections
HAI_2_SIR
Catheter-associated urinary tract infections
HAI_3_SIR
Surgical Site Infection from colon surgery
HAI_4_SIR
Surgical Site Infection from abdominal hysterectomy
HAI_5_SIR
Methicillin-resistant Staphylococcus aureus (or MRSA) blood laboratory-identified events (bloodstream infections)
HAI_6_SIR
Clostridium difficile (C.diff.) laboratory identified events (intestinal infections)
MORT_30_AMI
Death rate for heart attack patients
MORT_30_CABG
Death rate for Coronary Artery Bypass Graft (CABG) surgery patients
MORT_30_COPD
Death rate for chronic obstructive pulmonary disease (COPD) patients
MORT_30_HF
Death rate for heart failure patients
MORT_30_PN
Death rate for pneumonia patients
MORT_30_STK
Death rate for stroke patients
PSI_10_POST_KIDNEY
Kidney and diabetic complications after surgery
PSI_11_POST_RESP
Respiratory failure after surgery
PSI_12_POSTOP_PULMEMB_DVT
Serious blood clots after surgery
PSI_13_POST_SEPSIS
Blood stream infection after surgery
PSI_14_POSTOP_DEHIS
A wound that splits open after surgery on the abdomen or pelvis
PSI_15_ACC_LAC
Accidental cuts and tears from medical treatment
PSI_3_ULCER
Pressure sores
PSI_6_IAT_PTX
Collapsed lung due to medical treatment
PSI_8_POST_HIP
Broken hip from a fall after surgery
PSI_9_POST_HEM
Bleeding or bruising during surgery
READM_30_AMI
Rate of readmission for heart attack patients
READM_30_CABG
Rate of readmission for Coronary Artery Bypass Graft (CABG) surgery patients
READM_30_COPD
Rate of readmission for chronic obstructive pulmonary disease (COPD) patients
READM_30_HF
Rate of readmission for heart failure patients
READM_30_HIP_KNEE
Rate of readmission after hip/knee surgery
READM_30_HOSP_WIDE
Rate of readmission after discharge from hospital (hospital-wide)
READM_30_PN
Rate of readmission for pneumonia patients

For more detailed descriptions of these metrics and other data available on the CMS Hospital Compare website, see the CMS Hospital Compare data dictionary.

Defining Aggregates

What is an aggregate?

Aggregates are used to paint a broader picture of patient safety in a particular situation. For example, Ashbec has defined sample aggregates for overall patient safety, cardiac patient safety, orthopedic patient safety and pulmonary patient safety. Ashbec's overall patient safety metric is an example aggregate made up of two groups. The first group is a collection of metrics related to the frequency of patient injuries. The second group is a collection of metrics related to the frequency of patient mortality. Each group is assigned a weighting factor. In this example, the mortality group is weighted as heavily as the injury related group.

Each group contains a set of metrics. If those metrics are available for a particular facility in a particular quarter, they will be included in the quarter's group score for that facility. Each group is also assigned a minimum number of metrics that must be available. For example, the group may be defined as containing 10 possible metrics. Let's assume that the minimum for the group is 4. For a particular facility to have a group score it must have reported at least four of the 10 possible metrics. If the facility has not reported the minimum number, it will not receive a group score for the quarter and consequently, it will not receive an aggregate score for that quarter either. Note that this can result in gaps in the line graphs and empty cells in tables. If there are no scores for a facility across all of the reporting quarters, the facility will not be included on that page of the report.

There is also a second requirement for a facility to receive a group score in a particular quarter. When you define the list of individual metrics that make up the group, you can indicate that certain specific metrics are required. If the facility did not report that particular metric in that quarter, it will not receive a group/aggregate score.

What do you want the aggregate to measure?

When you are defining an aggregate the first thing you need to focus on is what you are trying to measure. For example, when Ashbec's cardiac patient safety aggregate was defined, the objective was to provide a measure (albeit an imperfect measure) that could provide an indication of how safe a particular hospital was for cardiac patients in general. A measure was desired that would allow the safety of two different facilities to be compared for standard procedures like a coronary artery bypass without penalizing one hospital because they did not perform heart transplants while the other facility did. However, it was important not to rank hospitals that did not provide cardiac care at all.

The first step is to select the individual measures that are relevant for the aggregate measure you wish to define. Now examined that list and identify which measures are more important than the others. Break the list into two groups to show the difference. Adjust the weighting factor of each group to compensate for their relative importance. Now within each group, determine if any of the individual measures are critically important to the aggregate. Mark those measures as required. Now decide for each group how many of the individual measures should be reported for this facility to be considered comparable to other facilities. That number should be recorded as a minimum number of individual measures required for the group. That would complete the aggregate definition.