Page 29 of 36
Previous Page     Next Page        Smaller fonts | Larger fonts     Go back to the flash version
HMT1005 MedCurrent


Radiology decisions
lead to cost savings

Point-of-order clinical decision-support solutions assure that
medically appropriate procedures are given the highest priority.
By Stephen Herman

While research varies, studies report that up to 25 percent of imaging procedures are unnecessary, inappropriate or duplicative. Many health plans have instituted requirements for physicians to provide prior notification or to secure prior authorization. The process is telephone-based and, in many instances, administered by a third-party utilization-management company. In this model, a physician’s office places a call to determine if an advanced study, such as an MRI, CT, PET or nuclear cardiology scan, will be covered for a patient’s specific situation. Most require a preauthorization code in order to be reimbursed.
For both radiologists and their referring physicians, frustration can occur with these types of third-party pre-authorization processes. Doctors bear the financial overhead to acquire authorization for procedures, and must live with inefficiencies in the system. In many instances, physicians are given an inadequate explanation when approval is denied.
The Centers for Medicare and Medicaid Services is conducting a number of bundled payment pilots, and the ability to appropriately manage costs at the point of service could be required under future reimbursement systems. Pay-for-performance metrics are under consideration for increased Medicare reimbursement, with a requirement to utilize decision support in the patient’s care. In some geographic areas, payers are incentivizing providers to use decision-support tools by waiving the preauthorization and paying claims for physicians whose orders fall within a specific range of compliance with the appropriateness criteria.
A clinical decision-support solution should ensure that the most medically appropriate procedures are given the highest priority and performed in the most-efficient way possible. Essentially, information technology helps each doctor order the right test, at the right time and for the right reason. The system should be available in the physician’s office to provide support at the time care is being discussed with the patient and prior to ordering imaging procedures, especially advanced procedures.
The system should allow physicians to easily and logically enter patient history information and a chosen procedure and then immediately receive feedback about the appropriateness of the exam. The ordering physician should be able to secure an understanding of the clinical reasoning based on standards set by the American College of Radiology, and be able to understand the reasoning behind the feedback being offered.
The system should use technology to expedite and improve transmission of traditional paper- or telephone-based requests from physicians to specialists and specialized health facilities. Radiologists and imaging facilities should be notified when an order is placed, and when preauthorization is obtained.
These clinicians should have ready access to appropriate protocols for the specific patient’s study. Imaging providers can eliminate the ordering and scheduling of inappropriate procedures before the patients are in the system and, subsequently, reduce claim denials and appeals. Patient care is improved because appropriate tests are ordered and administered.
A clinical decision-support system can automate the processes involved with securing pre-authorizations from insurers. For payers, this can help minimize the expense of establishing and maintaining a call center, and the work involved with telephone-based approval processes. Additionally, payers can overcome the perception that preauthorization decisions may be based on financial variables. A payer that uses a clinically based medical appropriateness decision-support system may be more readily perceived as a clinical partner in care decision making.
Models for deploying clinical decision-support systems are expanding, including recent availability of cloud-based software-as-a-service options and systems that readily embed into electronic medical records and portal environments. Yet, most current systems lack a fluid process for review, refinement and customization of rules that drive the system.
The system should utilize rule sets that are continually enriched and expanded for improved outcomes. Efficient updating should be possible based on ongoing procurement of new medical knowledge, including use of the system itself to gather and analyze the data it collects. Additionally, the system should allow individual users to create and submit rules that fit individual needs, and use them based on appropriate review and approval.
In a comprehensive project done in Minnesota in 2007, more than 2,300 of the state’s providers participated in a pilot, using point-of-service decision-support criteria to order high-technology diagnostic imaging studies. Researchers saw claims for advanced imaging procedures among five health plans drop by 3 percent in 2007 versus 2006. Based on the previous four-year trend line, the reduction in claims was estimated at 9 percent.
A March 2010 study by researchers at the University of Washington’s Harborview Medical Center in Seattle showed that more than 25 percent of outpatient CT and MR exams ordered by primary-care physicians at a hospital in Washington were inappropriate. The authors reviewed medical records from elective outpatient CT and MR examinations.
Of the 459 exams, 341 (74 percent) were considered appropriate, and 118 (26 percent) were not considered appropriate. Fifty-eight percent of the appropriate studies had positive results and affected subsequent management, whereas only 24 percent of inappropriate studies had positive results and affected management.
The researchers concluded that these results suggest a need for tools to help primary-care physicians improve the quality of imaging decision requests. “In the current environment, which stresses cost containment and comparative effectiveness,” they state, “traditional radiology benefit-management tools are being challenged by clinical decision support, with an emphasis on provider education coupled with electronic order-entry systems.”
Another study published in the February 2010 issue of The American Journal of Managed Care evaluated the effects of providing appropriateness criteria for advanced imaging procedures through guideline-based electronic health record decision support. Chart audits were performed on a random sample of adult primary care orders for CT, MRI of the head and MRI of the lumbar spine. Decision support was associated with a 20 percent to 36 percent drop in two of the three procedures. Results for the three procedures showed that a larger proportion of studies ordered after implementing decision support fit appropriateness criteria, and more post-implementation studies had the highest utility rating.
Systems designed to help clinicians identify and avoid unnecessary imaging procedures could bring annual savings of $35 billion to the nation’s healthcare system. A clinical decision-support system designed with enough fluidity can be readily adapted for use beyond imaging, in specialities where established appropriateness criteria exist. HMT


A medical appropriateness decision-support solution presents information and patient-specific appropriateness criteria in a user-friendly environment, allowing physicians to make the best clinical judgment and avoid unnecessary procedures or referrals.

Stephen Herman, M.D., has served for more than 25 years as a radiologist at Toronto’s University Health Network (UHN) and Mount Sinai Hospital. For more information on Medcurrent solutions: www.rsleads.com/005ht-206


Leverage business and clinical intelligence
By Rose Higgins
Market consolidation has left payers with legacies of multiple, disparate systems and inconsistent data sets. Many plans have systems that exist in separate silos for various business functions; the systems are unable to routinely communicate essential data between them. This is evident in claims systems that were not designed to receive clinical information.
Business-intelligence technology platforms that are infused with clinical and healthcare expertise provide integrated business and clinical intelligence that make possible linking the right people with the right information to make faster decisions about coverage, treatment and plan design. Analytics with outward-facing capabilities to engage stakeholders – employers, clinicians and members – are also needed so they, too, can make data-driven decisions that are both medically sound and cost-effective. Future business intelligence systems will:
Offer true enterprise-wide solutions: One central source of business intelligence is needed for the whole organization. This data should be easy to use and readily available. Stakeholders throughout an organization should be able to query and receive up-to-date metrics for their programs.
Performance metrics should be accessible for all providers. Solutions also should be customizable to reflect the culture and specific needs of an organization. Most of all, they should be robust enough to provide actionable analyses.
Use right-time data: Next-generation analytics will include the most-current data and methodologies. Claims completion factor data, for example, might reveal an early spike in costs that is projected to exceed the expected variance for a certain procedure. Drilling down further into the data, a medical director might find the cause and be able to address it quickly. If, for example, costs for total knee replacement were up because of many clotting complications in one physician group, the medical director could direct that group to guidelines on the proper use of prophylactic anticoagulation. Plans need tools that depict a situation in as close to real-time as possible – and analyses that produce actionable results.
Incorporate clinical and claims data, with capability for preset alerts: When a newly enrolled patient is found to be diabetic, that clinical data should immediately trigger an alert to the plan. This would prompt nurse managers to quickly introduce disease management or other services aimed at keeping the patient healthy and out of the hospital. Similarly, a plan should be able to monitor, for example, the number of emergency department visits for acute respiratory distress. If those visits spike among pediatric patients, plan managers should be able to drill down through the data to see the cause of the problem.
Integrate evidence-based medicine: Clinical rules and clinical intelligence need to be integrated with business analytics. The rapid incorporation of claims and clinical data provides an opportunity for cost-effective care and improved outcomes.
If data creates a more-complete profile of a specific population, plans can design targeted benefits. If a system includes regional and national guidelines and quality benchmarks, a plan is able to meet requirements for regulatory and quality reporting more readily. All of these uses have a measureable return on investment.

Rose Higgins is vice president of care-management solutions at McKesson Health Solutions. For more information on McKesson solutions:
www.rsleads.com/005ht-205
Previous arrowPrevious Page     Next PageNext arrow        Smaller fonts | Larger fonts     Go back to the flash version
1  |  2  |  3  |  4  |  5  |  6  |  7  |  8  |  9  |  10  |  11  |  12  |  13  |  14  |  15  |  16  |  17  |  18  |  19  |  20  |  21  |  22  |  23  |  24  |  25  |  26  |  27  |  28  |  29  |  30  |  31  |  32  |  33  |  34  |  35  |  36