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The IT team at Texas Children’s Hospital, Houston, used to spend weeks and sometimes months developing reports for physicians and others involved in quality and operational improvement efforts. Needless to say, hospital staff became frustrated with the time delays and, sometimes, the inadequacy of the information.
To improve its reporting capabilities, the 622-bed hospital used a two-pronged approach, incorporating both technology and teamwork. To improve the data gathering process and quality of reporting, Texas Children’s implemented an enterprise data warehouse (EDW) and data analytics. The hospital also created interdisciplinary teams to foster collaboration between those who request the data—physicians—and those who gather it—IT staff.
Over a one-year period, Texas Children’s has realized direct benefits of $4.5 million from the new approach. The benefits come mainly in IT labor, which can be shifted to focus on more detailed data analytics, such as helping physicians identify improvement opportunities in care processes that could lead to better quality care and cost savings.
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Obtaining Better Data, Faster
When Texas Children’s implemented an electronic health record (EHR) in 2008, the hope was that the tool would help arm the organization with the data necessary to make quality and operational improvements as the industry shifts from a volume- to a value-based payment model.
Although the EHR accumulated vast amounts of raw clinical and financial data, the data did not lend itself to analysis for identifying trends in patient care. The need to combine EHR data with data from disparate hospital information systems, such as enterprise resource planning applications, also complicated the data gathering and reporting processes.
Insufficient data and delays in reporting, however, were impeding clinician efforts to pinpoint exact problem areas. For example, physicians would request the number of C-sections that were performed at the hospital in the previous year or the number of patients who presented in the emergency department with chronic asthma for a particular time period. Analysts spent an average of 97 hours to build a report; clinicians required an average of nine additional reports to get their required information.
The problem was that EHR-generated reports, such as daily patient volume lists, provided only one-dimensional views of the data. Physicians needed more detailed information to guide improvements in care. Consequently, physicians sometimes bypassed the use of business analysts by requesting data, and then creating their own spreadsheets to try to determine patterns and trends, according to John Henderson, director of enterprise systems at Texas Children’s.
The EDW, in contrast, enables clinicians to get a more comprehensive picture of a disease. Implemented in September 2011, the EDW automatically aggregates clinical, financial, and patient account data from siloed hospital information systems, enabling Texas Children’s to eliminate the inefficient manual gathering of data needed for improvement efforts.
This has resulted in a 25 percent faster turnaround of reports and a 75 percent reduction in time to build reports. “We can generate data directly from the EDW in a manner of probably minutes as opposed to the previous process where it would have taken hours, or even days to generate that data,” Henderson says.
The automated process enables analysts to focus on discovering patterns in the data that could identify where changes in care processes and operations are necessary. Advanced analytic applications are used to provide more detailed dashboard-type information, prioritize initiatives, and track improvements, Henderson says.
The labor cost involved in building a report from the EDW is, on average, 67 percent less than the cost to build a report through the EHR. Previously, Texas Children’s had generated about 1,300 reports annually at a cost of $4,832 per report. According to Henderson, one EDW-generated report provides as much information as 10 EHR-generated reports. “So you are getting more capabilities from the enterprise data warehouse with less time to deliver results than you would by traditional reporting means,” he says.
One of the challenges in achieving effective reporting for Texas Children’s was the inherent disconnect between those requesting and those developing reports. Physicians would request a report, find the data insufficient, and request multiple additional reports, causing frustration for both themselves and IT staff.
To initiate collaboration not just between physicians and IT but across the enterprise, Texas Children’s worked with its EDW vendor to create integrated workgroup teams made up of physicians, nurses, and representatives from patient safety, quality improvement, finance, and IT. These teams focus on specific conditions such as asthma, diabetes, and pneumonia, as well as procedures, such as appendectomy and spine surgery, to uncover root causes of variation and identify opportunities for improvement in care processes. Each team defines improvement targets and takes full responsibility for reaching those targets, Henderson says.
Incorporating IT staff has been a pivotal benefit because analysts are able to understand how their work can directly affect patient care processes.
“Typically, on the technology side, the team doesn’t get that opportunity. With this effort, they’re embedded with these teams, so they get firsthand knowledge of how they’re able to identify and present data to the clinicians in a way that helps them treat the patient in a more effective manner,” Henderson says.
Quality improvement goals at Texas Children’s focus on increasing standardization and removing waste in care processes for specific patient populations, especially those with costly chronic conditions such as asthma.
The integrated care teams have used the EDW-generated data to standardize care processes and generate efficiencies in operations.
Asthma. In 2011, Texas Children’s had 3,000 emergency department (ED) visits and 800 hospital admissions related to asthma. An analysis identified the hospital’s asthma program as an area with wide variation in care processes and a high level of resource use.
The workgroup team then assessed how the hospital managed acute asthma from a patient’s time of arrival in the ED to discharge. Using dashboard data generated from the EDW and analytical tools to drill down into the data, the team found that physicians were ordering chest X-rays for 65 percent of their patients, while evidence-based practice called for an X-ray in just 5 percent of cases. The high volume of X-rays, which translated into unnecessary and unsafe testing, was traced to a faulty order set in the EHR. After the order set was rewritten, the number of chest X-rays ordered for asthma patients declined by 35 percent over the course of a year.
Pediatric radiology. To improve efficiency, physicians wanted to understand the timeline from the ordering of a radiology test to the time the test has been administered, the results read, and the diagnosis rendered. “We’ve been able to demonstrate and provide that information so they can determine where the options are for improving workflow of that entire process,” Henderson says.
In addition to efficiency benefits, improving the timeliness of orders helps drive more responsive patient care and provider satisfaction, he says.
By using EDW-generated data, IT staff were able to more quickly and efficiently generate a report, for estimated annual savings of $150,000.
“It’s helped us target very specific process improvement to that cycle time,” Henderson says. The data showed where the bottlenecks were occurring, so managers could align staffing with volume.
Labor productivity. Incorporating data generated by the EDW, a productivity dashboard was created using siloed data from disparate hospital information systems. The dashboard application provides a global view across the hospital’s cost centers enabling financial managers to gain a better understanding of volume, FTE budgeting, and premium pay, Henderson says.
The productivity tool enables financial managers to compare actual labor costs to budgeted costs and worked hours per unit of service. If labor use outpaces production, managers can drill down into the data to understand labor use at the job code level and the proportion that represents premium labor, such as overtime and temporary hours. Managers can then determine whether premium pay is correlated with actual higher volumes or whether it reflects inadequate forecasting, Henderson says.
A dashboard for operating room (OR) productivity, for example, as shown in the exhibit below, includes data on targeted versus actual worked hours per unit of service, OR hours versus paid hours (showing such detail as regular, overtime, and nonproductive hours for staff and temporary workers), and OR hours versus flex time.
By using automated rather than manual data gathering and integration, Texas Children’s is saving an estimated $120,000 annually on productivity reporting. Because the data is near real time, as opposed to a month old, department managers can make timely staffing and budgeting decisions. Henderson says the hospital is also realizing actual labor cost savings but has not yet measured these improvements.
Additional dashboards are being used to improve performance in other key operational areas, such as length of stay.
Automated data aggregation and sophisticated analytics have been instrumental in the hospital’s ability to achieve improvements in care programs and operations. However, the integrated effort, especially the pairing of physicians and IT staff, has provided the expertise needed to achieve improvements that combine improved practices in care delivery and operations with financial benefits required in an increasingly value-based environment.
What was especially important, Henderson says, was the governance structure that was put in place through these integrated care teams.
“That group determines what you are really trying to accomplish first, and keeps the focus on that,” Henderson says. “In the absence of that, you try to be all things to everyone and you really wind up serving no one effectively at all.
All the times we failed previously in this effort, it was because we were trying to serve everyone and we didn’t have the governance structure in place.”
Karen Wagner is a freelance healthcare writer in Forest Lake, Ill., and a member of HFMA’s First Illinois Chapter.
Interviewed for this article: John Henderson, director of enterprise systems, Texas Children’s Hospital, Houston.
Publication Date: Thursday, December 12, 2013
TriMedx helps health systems control costs and uncover savings opportunities by optimizing the clinical engineering function.
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Health care is a dynamic mergers and acquisitions market with numerous hospitals and health systems contemplating or pursuing formal arrangements with other entities. These relationships often pose a strategic benefit, such as enhancing competencies across the continuum, facilitating economies of scale, or giving the participants a competitive advantage in a crowded market. Underpinning any profitable acquisition is a robust capital planning strategy that ensures an organization reserves sufficient funds and efficiently onboards partners that advance the enterprise mission and values.
The success of healthcare mergers, acquisitions, and other affiliations is predicated in part on available capital, and the need for and sources of funding are considerations present throughout the partnering process, from choosing a partner to evaluating an arrangement’s capital needs to selecting an integration model to finding the right money source to finance the deal. This whitepaper offers several strategies that health system leaders have used to assess and manage capital needs for their growing networks.
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