Healthcare Analytics

Uncovering the Value in the Data: Analytics Help Drive Quality Improvements at Atlantic Health System

Introduction 2

Transitioning to McKesson Explorer 3

Making Information Usable 5

Assuring Data Quality 7

Improving Patient Care 8

Next Steps for Atlantic Health System 9

Contact Us 10

Care Providers–Hospitals and Healthcare Organizations

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Three years ago, Thomas Carlough, a former lead pharmacist and pharmacy informaticist who is now the Coordinator of Pharmacy Data Services at Atlantic Health System, began working on data analysis for a study on the safe and effective use of insulin. The study, led by the Joint Commission Center for Transforming Health Care, explored a basic question: Why do some patients who successfully managed their blood glucose level at home become hyperglycemic when they are a hospital patient? In Six Sigma terminology, the Joint Commission probed for hospital processes that could contribute to a patient’s defect status by identifying where data differed between groups.

The variety of data points and data sources was complex, taking into account not only glucose levels but also the timing of meals, size of meals, which parts of the meal were eaten, timing of insulin, amount of insulin, and other variables that might impact the measurement of glucose. The tools that were available for Carlough to process this data were

simple. An executive report writer and SQL queries from flat files could produce a printed sheet of numbers and simple aggregations, but there was no easy way to attach different data sources to each other and find value in them.

“I was pulling huge data sets, but

creating a cohesive picture from all

that information required a lot of

manual labor.”

The first stage of the project was a success—reflecting a 30 percent drop in the defect rate—but processing the data was cumbersome and time-consuming. When Atlantic Health System began a new and wider-reaching medication safety initiative, a more powerful data tool was needed.

Introduction

Atlantic Health SystemMorristown, New Jersey

• Five hospitals providing care in the New Jersey, Pennsylvania and the greater New York metropolitan area, with more than 600 community-based affiliated health care providers

• Named Hospitals and Health Networks magazine’s Most Wired health organization six years in a row, 2010-2015

• Named one of Fortune magazine’s 100 Best Companies to Work For seven years in a row, 2009-2015

Critical Issues• Complex medication safety initiatives required a level

of data analysis not available in previously used report writing systems

• Accessing and validating data could be cumbersome and slow

• Flat reports did not include the reasons behind the numbers, preventing a full understanding by key users

Solution Spotlight• McKesson Analytics Explorer™

• McKesson Performance Analytics™

Results• Combining multiple streams of data into one accessible

source empowered users to make new connections among disparate elements of patient records

• Data visualization drove discovery of root causes for gaps between performance goals and actual outcomes

• In-house control of the data increased both accuracy and confidence in data quality

• Provided data transparency and easy access via customized dashboards to directly improve quality

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Transitioning to McKesson Analytics Explorer™

Atlantic Health System has a tradition of quality and employs several adverse drug event (ADE) reporting tools and surveillance technologies to safeguard its patients. As Atlantic Health System looked to expand its surveillance from reported ADEs to event indicators, it was clear that conventional tools would prove inadequate. Atlantic Health System began using McKesson Analytics Explorer, McKesson’s data visualization solution, to build medication safety dashboards that would track six types of event indicators and instances of a patient going into defect status, according to different types of medication:

• Opiate rescue

• Anticoagulant bleed

• Insulin hyperglycemia

• Oral therapy hyperglycemia

• Anticoagulant Heparin dosing

• Anticoagulant Warfarin dosing

To make the most of available data streams, Atlantic Health System leveraged McKesson Analytics Explorer to combine clinical, administrative and financial data. Creation of the med safety dashboards

drew information from multiple sources:

• Encounters

• Lab results

• Diagnoses

• Medication administration

Carlough joined the core team to build the dashboards. He quickly saw the difference a comprehensive analytics and visualization solution could make. Atlantic Health System used specialized software for each individual department or service line. As a result, the data didn’t yet exist in one common data warehouse.

# Indicator ID ADE Alert Event Denominator

1 Opiate RescueNaloxone w/in 72 hrs of narcotic adminCounted each time one follows the other.

Monthly Patients withNarcotics Admin

2 AC BleedAnticoagulant admin with non-POA hemorrhagerelated Dx. Event shown in Month of Discharge.

Monthly Patients withAnticoagulant Admin

3 Insulin HyperglycGlucose > 300 post SC Insulin Admin. Count eachhigh Glucose Result 3 hrs after previous.

Monthly Patients with SCInsulin Admin (Exclude POA DKA)

4 Oral TX HyperglycGlucose > 300 post SC Insulin Admin. Count eachhigh Glucose Result preceeded by Admin and 3 hrsafter previous.

Monthly Patients with oral Hypoglycemic Admin

5 AC Heparin Dosing Count Each PPT > 100 post IV Heparin IV Monthly Patients IV withHeparin Days

6 AC Warfarin Dosing Count Each INR > 4; 48 hrs post Warfarin Admin Monthly Warfarin Days 48 hrspost 1st Admin

“One exciting part of this

project was the complexity

of the data and the number

of data sources used to pull

information. McKesson was

able to add clinical data to the

administrative and financial

data already in use.”

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Transitioning to McKesson Analytics Explorer™

Combining into one source: In the Inpatient Glycemic Control project, the report writer created simple totals and averages. McKesson Analytics Explorer allowed a wide range of possibilities, combining data from different sources and connecting it in different ways.

“I no longer had 16 different flat

files. I could load them all into

McKesson Analytics Explorer and

choose the connections I wanted to

make between them.”

Reducing manual labor: With real-time connections to data sources and business insight subsets, users could spend less time on data input and more time on finding value in the data.

Visualizing to cue further actions: Visual representation of the data made it easier to find opportunities for intervention. For example, the new medication safety dashboard not only showed the gap between the target rate for ADEs and the actual rate, but also allowed users to explore the reasons behind the gap. Atlantic Health System found that distinguishing between the patient rate and the event rate – the number of glucose measurements over 180, and not simply the number of patients who exceeded a glucose level of 180 – allowed them to identify an important quality measure for patient care. A bar graph next to the tabular view of the data made it easier to understand the size of the performance gap, compare performance among facilities or, by using red or green color cues, highlight the severity of the gap.

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During the Inpatient Glycemic Control project, Carlough’s primary means of sharing information was to create individual reports for each nursing unit, including them in a document and emailing them to each manager one at a time. With the new dashboards, not only can reports be more easily automated, but users can also access the information themselves at any time.

“McKesson Analytics Explorer

helped get the data where I

needed it to be and helped us do

more significant analysis. The

greatest fruit that it is going to

bear, however, is giving managers

access to that information at their

fingertips.”

With medication safety dashboards drawing from data within McKesson Performance Analytics, McKesson’s healthcare analytics solution, managers

can determine at a glance how they are doing on each of the ADE measures, by weeks or months. By simply switching to different views, users can make comparisons by facility, department, service line, and diagnosis-related group (DRG). Units can assess how they are performing comparatively and see whether they are improving over time.

Making Information Usable

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Using color-coded tree maps, Carlough also created visualizations that show the different locations in a hospital at a glance. Users can see how well they are doing compared to each other, to the hospital average, or to a stated goal on a given measure. When nursing managers log into the dashboard, they see a series of measures with visual cues. A measure in red shows an area needing improvement, while green bars indicate the unit is performing well. The dashboard also gives users the ability to drill down and identify the factors driving the performance measure. For example, the data may show that a unit is holding too much basal insulin. From the dashboard, a user can drill down to identify individual

practitioners who aren’t performing according to benchmark practices and work with them to improve.

“The number is less important

than the impact it has. We are able

to get to the reasons behind the

data and take appropriate action.

Accessible data can also point toward opportunities for further exploration. In the case of anticoagulant bleed, the collected data showed that the difference in the length of stay between a patient who bled and a patient who did not was 11 days — a significant divergence. Additional analysis of those cases may clarify the relationship between an anticoagulant bleed and length of stay. That in turn could dramatically affect both the quality of patient care and the eventual cost of individual hospital stays.

Making Information Usable

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Assuring Data Quality

As Atlantic Health System integrated a new system with the data streams already in place, transparency, quality assurance and data confidence were top priorities. Although some debate was inevitable, ultimately working through the process of building new reports and dashboards led to data that was considered trustworthy and usable.

Data definitions A key factor in building data confidence was standardizing the definitions behind it—and understanding when those definitions needed to be customized. Often an element of data will have different definitions depending on the context. When disparate data streams are combined, conflicts can arise. Through discussions with multiple stakeholders, Atlantic Health System built consensus on data definitions that ensured the accuracy of the results.

Visualizing problems Being able to visualize the data also ensures that the numbers add up. Drilling into the data through the detail screen allowed Atlantic Health System to ensure categorization remained consistent,

by including data that may have been previously overlooked.

“Not only is McKesson Analytics

Explorer great for creating

visualizations for the end users,

but it also makes developing

analysis simpler. Because of the

detailed drill downs, you can do

your own quality assurance as you

build it out. The software really

made it as easy as possible.”

Confirming accuracy The immediate availability of data provided by using McKesson Analytics Explorer made locating conflicts in the data simpler and faster.

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Improving Patient Care

Data visualization isn’t just the latest tech buzzword. When put into practice, it means seeing old problems in new ways that lead to new solutions.

For Atlantic Health System, that meant moving into the next phase of its medication safety projects with a more robust system for collecting, processing and utilizing data. Beyond measuring improvements in outcomes, they were able to measure process statistics, such as the number of times basal insulin was held, or the timing of an insulin dose with respect to a meal. Atlantic Health System is creating visualizations that highlight any gaps between individual practitioners’ insulin management and the current benchmark practices in their discipline.

The capacity to keep adding new data sources continues to expand possibilities. Data from hospitalist groups has recently been added to the mix to allow comparisons among hospital units. Seeing the difference in patient outcomes drives discovery of root causes.

In the case of the Inpatient Glycemic Control project, such root causes could be outdated methods of using insulin that are no longer the health system’s standard for care. Giving this information to the hospitalist groups helps them to push for concrete changes in physician practices.

Adopting McKesson Analytics Explorer also led to combining elements of data that had not been connected previously. For example, while ICD-9 codes were present in the billing systems and encounter data, they were not included in the clinical database for the Inpatient Glycemic Control project. Connecting these data sources allowed Atlantic

Health System to distinguish between patients based on diagnosis. Looking at the blood glucose level of diabetic and non-diabetic patients separately, the analysis verified that both patient groups showed a decline in blood glucose day over day while in the hospital, into the normal range. As raw numbers, the blood glucose measures look very different —165 for diabetic patients vs. 110 for non-diabetic — but when put into context they tell a consistent story about the effectiveness of Atlantic Health System’ insulin management

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“The medication safety initiative was a nice project to show the value of the solution, but the sky is the limit.”

To capitalize on the enhanced availability of their data resources, Atlantic Health System created a new pharmacy position to perform data analysis. Soon, Pharmacy Services and other Atlantic Health System service lines and departments hope to roll out more dashboards to influencers in the organization—hospitalist groups, nursing management, certain PCUs—who can take action based on visualized information. According to Carlough, “We would like to get it in the hands of those who can affect change. Then we can advance more quality improvements and watch these metrics move.”

Next Steps for Atlantic Health

Atlantic Health System has planned and initiated new projects to take advantage of their upgraded analytic and visualization capabilities:

• A dashboard allowing users to follow the path of medication around the hospital, from the pharmacy to the floor

• Coordination of data in the financial and clinical systems, using data visualization to find points of conflict between data sets

• An audit of ADEs

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