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| Deborah Bulger |
With the growing focus on regulatory reporting and transparency, it is easy for health care organizations to become so focused on data collection that they fail to see the big picture. Few hospitals know how much time or money they spend on collecting and analyzing data. In a CareScience study, a sample of providers spent between 50 and 90 hours a month to collect data for Joint Commission core measures for acute myocardial infarction, congestive heart failure and pneumonia, and another 23 hours a month to analyze the data. The associated costs ran up to $100,000 a year.
The intended result of reporting and transparency is quality improvement, but many providers have few resources left over after collecting the data for implementing practices to systematically achieve and sustain meaningful progress. Adopting an automated data collection and analysis tool may allow clinicians and executives to re-focus their efforts on process redesign, education and other activities that can help eliminate care variation and produce desired outcomes. Surgical care is an optimal target for this type of intervention.
Building the Right Warehouse
Health care organizations increasingly are recognizing the value of the information that flows through the various clinical information systems used to provide patient care. For example, surgical management and emergency care systems capture valuable data about how patients are processed through those settings, including the caregivers’ names, the treatment provided and the time required. Bar-code scanning and charting systems provide detailed information on medication administration, nursing and other interventions, along with their reasons and timing. But these thousands of data points may never be used again.
An automated approach takes advantage of time-stamped data produced as a byproduct of patient care rather than relying on a secondary--usually manual--data collection process. Data from disparate sources are electronically integrated into a clinical analytics application, or health care-specific data warehouse, where it is transformed into usable information and distributed through a Web-based scorecard application. The warehouse can collect and normalize data from virtually any clinical, financial and departmental transaction system as well as external data such as patient satisfaction results, risk and case management solutions, and public benchmarks. In an area such as surgical care, well-known best practices can be added to the mix. This creates the valuable data necessary to analyze multiple aspects of care and drive improvement.
Simplifying SCIP
The Surgical Care Improvement Project (SCIP) is a national partnership of 34 organizations committed to improving the safety of surgical care by reducing postoperative complications by 25 percent by 2010. In December 2006, the Institute for Healthcare Improvement recommended SCIP evidence-based guidelines as one of six new interventions in its 5 Million Lives Campaign, which seeks to reduce medically induced patient harm during the next two years.
Specifically, SCIP comprises a bundle of interventions that, when reliably executed, are proven to result in far lower infection rates than when even a single element is omitted. The interventions fall into four main areas:
- Surgical site infection prevention
- Beta blockers for patients who are on them before admission
- Venous thromboembolism prophylaxis
- Ventilator-associated pneumonia prevention
Measurement of SCIP guidelines began in July 2006 and currently requires collection and reporting of data against nine metrics. The SCIP population comprises eight strata representing 1,156 principal procedures.
If a hospital chooses to participate, it must include roughly 10 percent of procedures in each stratum. Even with sampling, this represents significant effort on behalf of the hospital to manage information in a timely, efficient, accurate manner. Further, a truly comprehensive approach to managing the care of surgical patients should include measures of resource utilization, throughput and cost--metrics not currently included in the basic SCIP measurement approach.
The first guideline alone comprises four interventions, including reliable delivery of the correct perioperative antibiotics within one hour of incision and discontinuation within a specified period depending on surgery type. This can be tracked using time-stamped data on medication administration and incision and close time from the surgical management system. Antibiotic discontinuation data can then be captured from the bar-code point-of-care medication administration and clinical documentation systems on the nursing unit.
To improve care in real time, a daily scorecard can alert the risk manager about any non-compliance that puts a patient at risk for postoperative infection. The med-surg nurse assigned to care for the patient also can benefit from this knowledge. Guidelines can be further reinforced throughout the patient stay in two ways: first, via standard order sets tied to SCIP in computerized provider order entry systems with clinical decision support, and second, through assessment-driven charting that reinforces surgery-specific protocols related to the other guidelines, with alerts to remind clinicians when required documentation is missing.
For retrospective, population-level analysis, these elements are then fed along with UB92 claims data into the clinical analytics system to determine how consistently each intervention is being followed over time and the effect on outcomes--by tracking length of stay, readmission rates, total cost of care, and even complications by payer and patient satisfaction. This information is distributed regularly via customized scorecards to appropriate stakeholders, from board members and executives to patient safety officers, case managers, departmental managers and frontline caregivers, enabling them to quickly identify variances and drill down to determine the cause with little or no analytical training.
Three Reporting Styles
While manually reporting to multiple regulatory, quality and payer organizations is difficult, how data are aggregated can further tax resources and muddy the performance picture. Most Joint Commission core measures, for example, look at groups of individual measures to assess care for AMI, CHF and pneumonia. There are three basic ways that performance against multiple related measures can be calculated, with widely varying results.
Item-by-item measurement looks at performance on each separate element as a percentage of the total sample population who received each intervention. Providers receive full credit for good performance on any measure, regardless of whether outcomes are compromised due to poor performance on related measures for the same condition.
Composite measurement calculates a percentage based on all the care that was given to a sample population for a condition compared with all the care that should have been given for that condition based on performance metrics. It gives only partial credit for incomplete care.
All-or-none measurement is the least forgiving standard. It calculates performance on all elements in, for example, the nine-metric SCIP bundle and gives credit only if all nine were performed well. This may seem harsh, but the point of bundled interventions is to ensure that all patients with a given condition receive all of the care deemed necessary to optimize their outcomes when it is provided together and in the right sequence. The all-or-none standard, endorsed by IHI President and CEO Donald Berwick, M.D., among others, may not be far from reality. In the 8th Scope of Work, the Centers for Medicare & Medicaid Services’ national healthcare vision for 2005-2008, performance measurement has shifted to this approach.
Data to Support Goals
Needless to say, the analytical power needed to compete in an all-or-none, consumer-directed or pay-for-performance environment is beyond human capacity. Clinical analytics systems transform source data into actionable information so management can head off errors and institute process improvements. Properly designed scorecards focus attention on only the most meaningful metrics for stakeholders at each level of the organization. The result may be fewer surgical complications, increased capacity and patient throughput, higher service line profitability or another goal--the answer is in the data.
Deborah Bulger is vice president, performance management solutions, at McKesson Provider Technologies, Atlanta.
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This article first appeared on April 4, 2007 in HHN's Magazine online site.
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