September 2009

1. September 2009 Towards a Value Driven System Measurement as a first step

2. Overview Goals of health care Definitions –quality, cost, efficiency, value What can we measure now? What COULD we measure in full EHR environment in organized systems (?with right incentives) Moving forward incrementally

3. If you can’t determine (measure) where you are, where you have been, and where you want to go- it is difficult to get there

4. It’s easy to oversimplify an answer to this question System should do more than make you better System should prevent illness, diagnose early, etc. System should work for everyone to keep them to the left Explain chart Note where we’re spending all our money That’s not a system based on value It’s easy to oversimplify an answer to this question System should do more than make you better System should prevent illness, diagnose early, etc. System should work for everyone to keep them to the left Explain chart Note where we’re spending all our money That’s not a system based on value

5. The Critical Aims of Health Care  IOM Safe Timely Effective Efficient Equitable Patient Centered

6. Definitions-towards the practical Value in health care: A SUBJECTIVE assessment of the net benefits (benefits-risks) of health care in relationships to the costs relative to other goods and services Depends on who is doing the “valuing” (patient, consumer, purchaser, “society”) Based on variable amount of objective information Value= (benefits-risks)/costs Difficult to measure benefits, risks and costs directly (at least right now)

7. Definitions-towards the practical Efficiency: The physical relation between resources used and health outcome…when the maximum set of possible improvements is obtained from a set of resource inputs (resources-cost). Palmer & Torgerson, BMJ 1999 Measureable Efficiency: An objective assessment of quality relative to the costs (resources used and/or price paid)

8. Definitions Quality: The degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge. Measureable quality: reliable and valid assessment of the structures, processes and outcomes related to provision of health care related to the aims of care that is safe, timely, effective, efficient, equitable and patient centered

9. Current to Ideal Quality & Cost Measurement 

10. So where are we now? Quality measures Underuse- ample number of measures Overuse-misuse- a few useful measures mostly for medications Outcomes- best related to patient experience (CAHPS), few clinical intermediate outcomes Appropriateness (relative benefit-risk) virtually no measures Cost-resources use Commercial (complex defined episode based-specific costs) NCQA RRU measures (time episode based total costs)

11. So what to do now to “define” value? Use (where possible) NQF endorsed measures-preferably those used in PQRI and/or Hospital incentive program Quality HEDIS-MD specified Physician consortium for Performance Improvement PCPI (selected) Cost-Resource use (NQF review late 2009) HEDIS RRU (used at plan level 2007-09) Episode of care –commercial, ABMS (2010)

12. Complex episode of care measures Positives Widely used by health plans Focused on specific procedure or claims defined episode of care allows drill down Negatives Nearly all products use some sophisticated (and non transparent) set of conventions to sort costs into discrete episodes and to risk adjust Need for large numbers to get valid results (400 plus episodes) Questionable use for public reporting given variation and difficulty in summarizing The more episodes created the lower the apparent cost Is not sensitive to the appropriateness of what was done

13. Population Resource Use Approach Positives Publically available specifications with public domain risk adjustment Measures resource use of care for groups of patients with index condition over time –sensitive to effects of in appropriate care Negatives Does not look at disease or procedure specific costs Only limited drill down potential (best if coupled with internal episode measures)

14. The Good NewsIt CAN be doneQuality and Resource UseHEDIS- 2007-08-09

15. NCQA Population RRU Measures Total yearly relative resource use over for people with COPD (08) Cardiac Conditions (08) Hypertension, uncomplicated (08) Diabetes (07 & 08) Asthma (07 & 08) Condition, episode delimited resource use for people with Acute low back pain (07 & 08) Cost Service Categories Inpatient Facility Surgery & Procedure Evaluation & Management Pharmacy, ambulatory Utilization Service Categories Inpatient Discharges ED Discharges MRI (low back pain only)

16. Features of NCQA RRU Measurement Transparent-anyone can “look inside” Uses same population as HEDIS Quality Measures in same disease-so can be reported together Simple risk adjustment Age & Gender Disease severity (Type 1 v Type 2 diabetes) Presence of co-morbidities (yes-no) Exclusions of other dominant conditions Active cancer, HIV/AIDS, ESRD, etc. Member cost capped if exceeds specified amount Adjusted for enrollment and pharmacy benefit status (medical and pharmacy member months) Standardized Fee Schedule—weighted resource use Cost differentiates between a more intense and less intense service—e.g., amputation & office visit As you can see the common principles met our goals. Because of this, we did have to restrict the services that could be reliably and consistently captured across many health plans.As you can see the common principles met our goals. Because of this, we did have to restrict the services that could be reliably and consistently captured across many health plans.

17. Resource Use and Quality Results This is an overview of RRU results shown along with quality. How would you interpret these results? How would you assess quality versus resource use? What data elements seem confusing? What data elements seem particularly interesting?This is an overview of RRU results shown along with quality. How would you interpret these results? How would you assess quality versus resource use? What data elements seem confusing? What data elements seem particularly interesting?

18. Resource Use and Quality Results

19. Resource Use and Quality Results This is another view of rolled-up resource use plotted against quality. Imagine that you are selecting from Plans A, B, C, D and E. Would you: Review this type of data as you evaluate procurement options? Work with plans in “worse” quadrants on quality/resource-based performance guarantees? Consider working only with plans in “better” quadrants? Make this information available in any format to employees when announcing plan options (as rationale for why particular plans are offered)?This is another view of rolled-up resource use plotted against quality. Imagine that you are selecting from Plans A, B, C, D and E. Would you: Review this type of data as you evaluate procurement options? Work with plans in “worse” quadrants on quality/resource-based performance guarantees? Consider working only with plans in “better” quadrants? Make this information available in any format to employees when announcing plan options (as rationale for why particular plans are offered)?

20. And now the bad newsResource Use Measures Even though transparent-resource use measures are complex Due to inherent wide variation of costs in patient groups, need very large sample sizes (>400) at least for public reporting Data incompleteness and lack of standardization is rampant Bundling of services Missing data (losing data in reporting cost-resource use makes you look better)

21. More bad newsComparison with Quality No consistent relationship between resource use-cost and quality Weak correlations Higher quality with higher pharmacy and outpt E&M Lower quality with higher in-patient and surgery-procedures Too few or too weak quality measures to link in most diseases (diabetes, CV, asthma, hypertension exceptions) Most KEY quality measures still require manual chart review (paper AND some EMR’s)-so nearly impossible to measure at individual MD level

22. But a bright futureSome promising developments Creation of standardization of measures in EMR and EHR environments Limitations of EMR measurement (physician versus patient focus) Measures building on EHR capabilities Measurement of Appropriateness-overuse (relative risk- benefit) measures-towards a real VALUE measurement

23. Standardization of measures in EHRs Stampede of activity related to ARRA and 35 plus Billion Multiple standard setting organizations racing to create protocols for specifying and embedding measures, extracting data and reporting in EMR-EHRs Definition of “meaningful use” for 2011, 2013, and 2015 Likely to have profound effects on EMR’s, EHRs and measures (project to create standard specifications for EMR measures launched)

24. New Measures for EHRs

25. Advances using E-data Measures linked to guidelines and clinical decision support (concurrent measurement) Adherence to guidelines-exceptions and rapid cycle learning Overall CV risk reduction (verses single measures) Appropriateness- relative risk benefit (more to come) Measures of outcomes of clinical care Reduction of CV risk (Archimedes)-real time and in follow-up Functional status over time Intensification of treatment and exceptions Coordination of care

26. Advances in other realms Patient experience of care More sophisticated surveys (medical home related) More sophisticated data collection Email-webased-time of encounter Incorporation into quality improvement- payment driven

27. Major GAPAbility to Measure Relative Benefit and Risk DirectlyAHRQ-NQF-NCQA-PCPI Conference

28. Relative Benefit Risk (?and cost) There are virtually NO measures of quality related to many of the big ticket items driving cost Areas identified by NPP as critical Surgical procedures (by pass surgery) Other procedures (endoscopy) Diagnostic imaging (PET, MRI, CT scans) Screening (excess pap smears, mammograms etc)

29. Why this gap? For these interventions, it is difficult to judge quality without dealing with the relative benefit and risks of applying procedure to a given set of patients Example of problem Excellent “quality” score -but patients had a low probability of getting any benefit from the procedure Fair quality score – but all patients really had high probability of benefiting from the procedure

30. Barriers Technical-scientific Weakness of evidence and analysis of evidence (including efficacy and effectiveness) Paucity of consensus, evidenced based guidelines Need for clinically rich data to determine appropriateness Range in expert consensus based on specialty and weighting of evidence

31. Barriers Political-cultural Lack of funding for development (evidence, analysis or application) Overuse encouraged by fee for service reimbursement (one persons overuse is another’s income) Belief that doing something is better than nothing Public belief in technical solutions to health problems Legal concerns (populations versus individual outcomes) Strong push within organized medicine to use predicted clinical effectiveness ONLY for decision support or feedback

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33. Low Hanging Fruit Overuse: Application of an otherwise effective intervention to patients for whom the benefits are small or negative relative to the risks AND/OR costs “Currently definable overuse”: overuse in groups of patients that can be defined using currently available data (claims, age, gender etc)

34. Priorities for Overuse Interventions with high variation and high cost (NPP defined areas) Imaging, Procedures Screening Look where existing criteria or guidelines have been developed indicating lack of benefit US Preventive Services Task Force-”D” recommendations American College of Cardiology-American College of Radiology Look for specific areas where “overuse” could be defined by existing claims or demographic data (duplication of services, hospital readmissions, ambulatory sensitive readmissions)

35. Currently definable overuse projects(initial focus of PCPI and NCQA work) Imaging Cardiac Sinusitis Procedures GI (endoscopy) Angioplasty, Angiography, By-Pass Surgery Induction of labor Low back pain (surgery, injection) Screening (over screening) Other related measures under development (possibly waste-overuse) Readmissions Ambulatory sensitive or avoidable admissions

36. BUT- reducing overuse using existing datais only a first stepNext: Begin research and collaboration with others to create framework to address full range of benefit risk measurement

37. Uses of relative benefit- risk “scores” Use in Clinical Decision Support Real time “academic detailing” to reduce low benefit use (MGH) Peer review of clinicians who do a high risk, low benefit procedure Comparison to actual outcomes (learning) Use as Performance Measures Overall performance based feedback to individual clinicians (7.5 versus 4.5) Review by group leaders or by Boards (MOC) Substitute for utilization review Linked to payment

38. Work to date on Relative Risk Benefit RAND studies (Appropriateness) American College of Cardiology Have developed Criteria for CV PET scanning, Percutaneous Coronary Interventions, others American College of Radiology “Relative Clinical Utility” criteria for >30 imaging procedures Mass General has developed computer based ordering decision support (Radiology Order Entry) Very little beyond these –and above were done either for research or within the professional organizations for QI only purposes

39. Conclusion: Critical area to pursue BUTDifficult and expensive to create measuresRequires full electronic health record system Likely to be controversial

40. Path Beyond Need for further technical –methodological work How best to create criteria and measures of relative risk benefit ? How to build interface with Effectiveness research Computer modeling of effectiveness Clinical decision support (patient and provider) Focus would be from start on development of benefit-risk measures for use in EHRs since detailed clinical data in electronic formats needed to To identify eligible populations To calculate benefit/risk scores To link to concurrent clinical decision support

41. Sooo- in Conclusion We are making progress-but a lot slower than we would like to do in creating evidence for VALUE determinations Limited at present by data, data collection, payment system and a lot more Some help is on the way-but uncertain how much or when So-ON WISCONSIN (except when playing Penn State)