• Using Data and Analytics to Improve Clinical and Financial Performance

    A column by Walter W. Morrissey, Robert W. Pryor, and Anand Krishnaswamy, Kaufman, Hall & Associates, LLC Nov 17, 2016

    Access to data and to robust analytics helps provider organizations target areas of unwarranted variation in care and craft a strategy to deal with the issue.

    Data and analytics are no longer nice-to-have tools. Instead they underpin an organization's ability to achieve high-valuecare, which we define as patient-centric care with improved quality and outcomes, at lower costs. Because healthcare reform--particularly Medicare payment reform under the Medicare Access and CHIP Reauthorization Act--puts all providers at risk financially if they fail to improve value, data and meaningful analytics are critical elements of the cost of doing business. With such tools, hospitals and health systems can drive the performance improvement needed to succeed in a value-based environment.

    For most hospitals and health systems, unwarranted variation in care is a significant source of suboptimal patient outcomes and unnecessarily high costs. Such variation is present in clinical practice when there is a gap between the desired best practice and current practice. An analysis that excludes outliers and is risk- and severity-adjusted can indicate when quality outcomes and/or costs differ significantly by physician or other care provider. This apples-to-apples analysis produces actionable data that can be used to eliminate or decrease the performance gap.

    Causes of unwarranted or inappropriate variation may include:

    • Suboptimal clinical practices or processes (e.g., not implementing an accelerated mobilization protocol, which is a practice expected of care providers for patients following hip or knee replacements, except in rare cases)a
    • Overuse of supply-sensitive care, (e.g., higher use of specialists in regions where more specialists practice, such as by obtaining cardiology consults for all patients with chest pain)
    • Misuse of preference-sensitive care (e.g., use of a high-cost orthopedic prosthesis or drug when a lower-cost version would be equally effective or appropriate for a particular patient)
    • Underuse of proven effective care (e.g., not using prophylaxis for deep venous thrombosis with surgical patients)
    • Provision of services or procedures that are not clinically indicated (e.g., unnecessary diagnostic testing)

    Challenges to reducing unwarranted variation include gaps in clinicians' knowledge, lack of economic incentives to drive desired clinical behaviors, concerns about malpractice risk, physicians' desire for the ability to go with personal preferences, and inadequate decision-support tools.b

    Hospitals and physicians typically have been compensated for the care they provide even if such care creates unwarranted variation in quality or cost. The value mandate from both private and public purchasers and payers is rapidly changing this situation, putting a high-intensity spotlight on unwarranted variation in care and providing incentives to reduce such variation.

    Ensuring Credible Data

    An organization-wide approach to reducing clinical variation must be supported by a commitment from the leadership team to aggregate, analyze, and disseminate credible data related to quality, outcomes, and cost. Benchmark data and advanced analytics that use such data enable the organization's leadership and quality teams to compare performance against a variety of factors:

    Historical trend performance and/or performance targets. This assessment looks at the performance of the hospital or health system using the organization's own data, either overall or by hospital, department, physician, treatment type, patient diagnosis, or other considerations.

    Peer group comparisons. Data from public and commercial sources enable comparison of the organization's performance with that of an appropriate peer group, defined as of similar type with like functions, services, operating revenue, or other factors.

    Using benchmark-based reports and scorecards, hospital executives and managers are able to observe patterns of performance based on factors such as diagnosis, comorbidities, treatment type, department, and physician. Areas of undesirable variation can be explored and targeted for improvement.

    Determining Early Areas of Focus: Case Study

    One health system with three hospitals and approximately 300 affiliated and employed physicians sought an assessment of its performance compared to peer organizations on selected measures of utilization, quality, cost, and patient safety. The goal of the assessment was to enable the health system to identify areas where it should focus early efforts to reduce clinical variation.

    The health system used data from its own performance records and from public and proprietary databases. It obtained a robust analytic platform with more than 2,000 performance indicators, which enabled a view of how the system performed internally over time and comparatively with other organizations regionally and nationally (peer organizations were selected from among more than 5,000 hospitals nationwide). Measures included length of stay (LOS), mortality rate, critical care utilization, emergency department admissions, hospital-acquired conditions, and cost.

    Length-of-Stay (LOS) Variance

    Length-of-stay (LOS) variance for one health system.

    Based on all-payer data for the most recent 12-month period, the organization was performing below the 50th percentile in LOS (see the exhibit above) and mortality rates and below the 25th percentile in critical care utilization compared with all hospitals and with a regional community hospital subset nationwide (the data were severity- and risk-adjusted). Analytics identified the sources of the greatest performance variance by department, clinical condition, and physician.

    Data credibility is the essential foundation for driving behavioral change. Physicians who receive reliable data with evidence of unwarranted variation in their own care--whether related to quality, outcomes, or cost--typically need no further inducement to bring their practices in line with their colleagues.

    Where to Start

    Building a sustainable program to eliminate unwarranted clinical variation can be undertaken one step at a time. The focus initially may be on an individual DRG or on use of a certain drug, device, test, procedure, condition, work process, clinical program, or other element of patient care. Prioritization of which areas to tackle first can be based on a number of factors, including likelihood of early success, magnitude of the benefit or opportunity, resources required to effect change, and expected implementation timing.

    Following such a prioritization exercise, the organization can focus on the categories of data or measurement that typically reflect the most significant opportunities to reduce unwarranted care variation. For example, some of the major categories of resource utilization are:

    • Medical/surgical supplies: Physician preference items often have high cost differentials.
    • Pharmacy: Brand-name drugs, as opposed to generic drugs, and drugs for certain therapies have high cost differentials--and sometimes may be no more effective.
    • Accommodation: LOS can indicate physician and staff practice patterns and processes that positively or negatively affect how patients move through the hospital and discharge.
    • Laboratory and pathology: Standing orders for daily tests, as an example, may or may not be needed or appropriate.
    • Imaging: The physician's choice of imaging options, including MRI, CT, ultrasound, and X-ray, has a large impact on cost.

    Charges and Costs Detail

    The size of the improvement opportunity in resource utilization by one health system.

    For one $3 billion hospital system, benchmark data of a peer group of large hospitals in the Northeast indicated the size of the improvement opportunity in these and other categories (see the exhibit above). For the top five categories, the hospital system's costs were approximately $135 million higher than those of its peers.

    Looking at its own data across the top five measure categories and overall, the organization was able to identify which physicians had the most significant opportunities to reduce variations in care. All Patients Refined DRG data were severity-adjusted, and outliers were excluded.

    When compared with their peers, three physicians in different specialties accounted for nearly $2 million in potentially unwarranted care variation. This variation represented 10 to 20 percent of the total variation and spend in each of their service lines. The opportunities to reduce variation and costs in medical/surgical supplies and imaging were particularly notable. Further assessment of spending by category indicated specific products that might be adding unnecessary cost or varying from patient protocols.

    Physician 1, for example, used more anesthesiology supplies per minute than did his peers--and the highest-cost surgical mesh. As was the case in this instance, often physicians simply are unaware of the cost of the items, tests, or drugs they order and can shift their ordering behavior without affecting their patients.

    Drilling Deeper

    Even more powerful analytic work looks at the relationship between care quality, patient satisfaction, and cost indicators by hospital and physician. For example, reducing unwarranted variation in knee and hip joint replacements presents an important area of organizational focus in the current regulatory environment. Effective April 1, 2016, the Centers for Medicare & Medicaid Services rolled out a mandatory bundled payment program in 67 markets. Known as the Comprehensive Care for Joint Replacement, it involves approximately 800 hospitals. By making hospitals responsible for all charges within 90 days of discharge, the program incentivizes hospitals to optimize inpatient care, streamline postoperative care, and discharge patients to lower-cost settings or directly to home when appropriate.

    In the context of knee joint replacement, a best-practice analysis for one multihospital system identified the best-performing hospital in the system based on indicators including length of stay; total cost; a risk-adjusted patient safety index including pressure ulcer rates, postoperative infections, and other measures; the hospital-acquired condition rate; and a patient satisfaction rating. The benchmark was based on all-payer data for short-term acute care facilities nationwide.

    Best-Practice Analysis: Knee Replacement by Physician

    Column-2-Exhibit-Best-Practice-Analysis

    Drilling down within the best-performing hospital, the analysis identified the best-performing operating physician for knee joint replacement using the same indicators. Based on data covering a two-year period, the top exhibit of the two above shows the results for 10 physicians, highlighting that Physician 1 performed above the national all-payer benchmark on all dimensions.

    Further analysis established what the improvement opportunity might look like if the lowest-performing physicians performed at the level of Physician 1. The bottom of the two exhibits above shows those results, which would bring a cost-reduction opportunity of nearly $10 million.

    The health system's chartered clinical improvement team closely studied the clinical practices of Physician 1 to learn specific means by which he was able to ensure patient safety and quality while reducing surgical and related hospital costs. Directed by physicians with participation from nurses and other clinical team members, this is the hard work that needs to be done to reduce unwarranted clinical variation in hospitals and other facilities nationwide. The benchmark data and analytics identified the target and set the stage for the work that followed.

    It's All in the Tools

    Hospital leaders need access to credible and accurately attributed data and analytics that enable them to identify both significant opportunities to improve financial and clinical performance and the root causes of suboptimal performance that require corrective action. Armed with the ability to simultaneously access data on utilization, quality, patient satisfaction, and cost, and benchmarks of internal and external best-practice care, executives can quickly identify underperforming areas to which attention should be directed.


    Walter W. Morrissey, MD, is managing director, Kaufman, Hall & Associates, LLC; Robert W. Pryor, MD, is senior vice president, Strategic and Financial Planning practice, Kaufman, Hall & Associates, LLC; Anand Krishnaswamy is vice president, Strategic and Financial Planning practice, Kaufman, Hall & Associates, LLC.

    Footnotes

    a. Soni, S.M., Giboney, P., and Yee, H.F., “Development and Implementation of Expected Practices to Reduce Inappropriate Variations in Clinical Practice,” JAMA, May 24/31, 2016.

    b. Ibid.


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