ASHA Short Course Outcomes Measurement in Long-Term Care (LTC) Bill Goulding, MS/CCC-SLP November 19, 2012
How Do We Show Value? Easy to measure! Not so easy! V $$$ A L Impact? Cost U Benefit E
What do Outcomes Show Us? $2500 or 19 days in Tx Cost V A L U E??? Benefit
What do Outcomes Show Us? $2500 or 19 days in Tx Cost V A L U E 45% more I and safe w Swallowing Benefit
What do Outcomes Show Us? Dollars Days Cost V A L U E Indep BOC Benefit
The Rise of the Value Equation The Centers for Medicare and Medicaid Services (CMS) initiated this movement in LTC in the early 1980s by introducing a Prospective Payment System (PPS) because they wanted patients to move into the Post-Acute Care (PAC) part of the continuum ASAP, due to the expense of treating patients in the Acute setting. As a result, PAC settings such as Inpatient Rehab (IRF), Home Health (HHA) & Skilled Nursing (SNF) began receiving patients quicker and sicker. But, no such payment reform was in place in any of those settings at the time!
The Rise of the Value Equation Patients PPS dams force patient flow further down the treatment river Acute IRF SNF HHA Patients
The Rise of the Value Equation D R G Patients PPS dams force patient flow further down the treatment river Acute IRF SNF HHA Patients
The Rise of the Value Equation D R G Patients PPS dams force patient flow further down the treatment river 65% Acute IRF SNF HHA Patients
The Rise of the Value Equation D R G Patients PPS dams force patient flow further down the treatment river 65% R U G Acute IRF SNF HHA Patients
CMS - From P4P to VBR 1990s Pay for Performance 2000s Value-Based Reimbursement 2006 Transmittal 63 2008 PAC Payment Reform Project 2008 DOTPA: Developing Outpatient Therapy Payment Alternatives 2011 Accountable Care Organizations (ACO)
Transmittal 63 (12/29/06) Importance of Outcomes in Justifying M/N Objective measurements are required to document the patient s condition and progress during treatment. Indicate a measurable physical function in all records. Certain tools are recommended but not required (NOMS, OPTIMAL, FOTO, AMPAC). Other measurement tools, both commercial and clinic-generated, may be appropriate.
Transmittal 63 (12/29/06) Importance of Outcomes in Justifying M/N Good therapeutic outcomes are identified by better than typical improvement (effectiveness) with less than typical amount of treatment (efficiency) compared to patients with similar conditions. Value Equation
Reimbursement Model? Study by FOTO for CMS Pay Scenario Results Payment Enhanced Effectiveness (Outcomes better than predicted) 1 Enhanced Efficiency Visits less than predicted +10% 2 Predicted Efficiency Visits equal to predicted +5% 3 Decreased Efficiency Visits more than predicted +5% Predicted Effectiveness (Outcomes equal to predicted) 4 Enhanced Efficiency Visits less than predicted Standard 5 Predicted Efficiency Visits equal to predicted Standard 6 Decreased Efficiency Visits more than predicted Standard Decreased Effectiveness (Outcomes less than predicted) 7 Enhanced Efficiency Visits less than predicted -5% 8 Predicted Efficiency Visits equal to predicted -5% 9 Decreased Efficiency Visits more than predicted -10%
What do Outcomes Show Us? $$$ LOS Cost V A L U E Indep BOC Benefit
What do Outcomes Show Us? Inefficient & Ineffective Efficient Cost V A L U E Benefit Effective
What do Outcomes Show Us? Efficient & Effective Cost Efficient V A L U E Effective Benefit
Reimbursement Model? Pay Scenario Results Payment Enhanced Effectiveness (Outcomes better than predicted) Visits less than predicted +10% Visits equal to predicted +5% Visits more than predicted +5% Predicted Effectiveness (Outcomes equal to predicted) Visits less than predicted Standard Visits equal to predicted Standard Visits more than predicted Standard Decreased Effectiveness (Outcomes less than predicted) Visits less than predicted -5% Visits equal to predicted -5% Visits more than predicted -10%
CMS Initiatives to Define Value According to CMS Roadmap for Implementing Value Driven Healthcare in the Traditional Medicare Fee-for- Service Program (CMS, 2009) the agency has begun to transform itself from a passive payer of services into an active purchaser of higher quality, affordable care. Further future efforts to link payment to the quality and efficiency of care provided would shift Medicare away from paying providers based solely on their volume of services. The catalyst for such change would be grounded in the creation of appropriate incentives encouraging all healthcare providers to deliver higher quality care at lower total costs.
Post Acute Care (PAC) Payment Reform 2008: CMS Contracted with the Research Triangle Institute (RTI) to develop of a standardized patient assessment tool for use at the acute hospital discharge and at all PAC settings admission and discharge. This tool, the Continuity Assessment Record and Evaluation (CARE) tool, would measure the health and functional status of Medicare acute discharges and measure changes in severity and other outcomes for Medicare patients across the various settings that a patient may utilize. The tool is designed to controll for factors that affect outcomes, such as cognitive impairments & social/ environmental factors. The CARE tool is being developed to eventually replace similar items on the existing Medicare assessment forms, including the OASIS (Home Health), MDS (SNF), and IRF PAI (IRF) tools.
DOTPA (Outpatient Therapy) Recent CMS studies, MedPAC reports, GAO reports, and the current national healthcare debate indicate a trend towards an emphasis on the measurement and reporting of key clinical indicators that represent measures of quality and/or outcomes. There is no single current patient reporting tool for outpatient therapy services that has been identified that could serve these purposes. One of the objectives of the CMS DOTPA project is to develop such a tool...
The Future: Predictive Modeling Those that pay for LTC services prefer to have the financial commitment determined prospectively. In order for a provider of skilled therapy services to compete for patient access, they will need to employ a statistical methodology called predictive modeling that will allow them to predict the expected outcome & cost to achieve that outcome with sufficient certainty to obtain approval for services. That prediction is most often based upon some form of regression analysis, in which unknown values are predicted based on known values of one or more variables. For example, the PPS model for LTC is based upon gathering a minimum data set of information regarding the patient and using that to predict what resources the patient will utilize during an upcoming period of time.
The Future: Predictive Modeling Not an especially new analytic approach, some form of it has been used by actuaries in the insurance industry, financial services, pharmacy and even other healthcare fields for decades. However, its application is relatively new within the LTC rehabilitation world due to the relative paucity of foundational data that are available. It is difficult to do the sort of data mining that is necessary to make cost vs. benefit predictions when there is relatively little data to be mined. Growing foundation of outcomes research in LTC rehabilitation and the even larger foundation of collected outcomes via commercial tools and industry instruments such as the MDS in SNF facilities has allowed for several stakeholders to begin to reliably predict the value equation (cost vs. benefit) that payers and providers will need going forward.
Shared Risk & Care Coordination = ACO Another trend: Movement towards shared risk. One such endeavor falls under the umbrella that is sometimes referred to as an Accountable Care Organization (ACO). ACOs are essentially collaborations between physicians, hospitals, and other providers (such as rehabilitation specialists) that are held clinically and financially accountable for healthcare delivery for a given group of patients. Collaborators have a common goal to improve quality and decrease costs across episodes of care. The reason that they have this goal in common is that they will share extra profit for care that is more efficient and results in cost savings to the payer. Conversely, they also share the risk that care could be more expensive than expected. It is easy to see how those entities that have reliable predictive analytics will be better able to participate as a member of such collaborative efforts.
Conclusion The lessons for the LTC rehabilitation practitioner are clear. To be an efficient and effective provider for your patients, you will need to: Know the costs of providing care to various patient types. Know how to predict outcomes and costs by patient types, (i.e., by diagnostic group) and account for the impact of comorbidities (risk adjustment). Know your clinical capabilities (i.e. what treatment areas can you reliably address and still provide meaningful outcomes?) Be able to advocate for those individuals who do not have a sufficient voice in the discussion to advocate for themselves.