Post on 22-Jan-2016
description
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Patient Welfare and Selective Contracting in Kidney Transplantation
David H. HowardDepartment of Health Policy and Management
Emory University
Funding by NIDDK/NIH
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…patients should be free to seek out the providers with the best track records given their unique circumstances. In the current environment, where patients' treatments are determined by the networks they are in, network providers are all but guaranteed.
Michael E. Porter and Elizabeth Olmsted TeisbergHarvard Business Review
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Why lies at the core of consumers’ complaints about managed care? To my mind, the answer is clear. Today’s well-educated, assertive consumers want choice and control.
Regina Herzlinger, J Health Politics Policy and Law 1999
In health care there is increasing control over access to medical services. Insurance companies disallow patient free choice of physicians, clinics and hospitals outside their approved network. If there is a solution to this problem, it will take the form of changing the incentive structure: empowering the consumer by channeling third-party payment allowances through the patients or students who are choosing and consuming the service.
Vernon Smith, Wall St. Journal 2006
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CIGNA LIFESOURCE Transplant NetworkMS
The nation's leading transplant program
Each facility in our network is carefully chosen and must continue to meet our stringent quality standards. We assess several factors, including:
•patient outcomes; •staff training and experience; •number of transplants performed; •waiting periods; •availability of housing arrangements and transportation for patients' families; •geographic location and accessibility; and •availability of transplant organs in the geographic area of the facility.
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What is the Blue Quality Centers for Transplant (BQCT) Program?
The Blue Quality Centers for Transplant (BQCT) is a centers of excellence bone marrow and organ transplant program offered through participating Blue Cross Blue Shield Plans. All institutions selected as BQCT centers of excellence must meet stringent Program criteria. BQCT includes for covered transplants seven individual networks: heart; lung; heart/lung; liver, lung, simultaneous kidney-pancreas; pancreas and bone marrow (autologous and allogeneic).
How do you select and credential facilities?
Institutions are selected for the Blue Quality Centers for Transplant (BQCT) Program based on their ability to meet defined clinical criteria that are unique for each type of transplant. Panels of transplant surgeons and physicians advise the Blue Cross and Blue Shield Association on selection criteria, which are updated in response to medical advances.
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Humana has authorized the National Transplant Network (NTN) Site Selection Committee to establish guidelines by which the NTN is to be developed and maintained.
•Transplant programs must be in continuous operation for a minimum of one year, and ideally, for four years from the date of the first transplant. •Transplant team members should be in place and working together for a minimum of one year. •Transplant programs must meet volume guidelines for the previous year or average of previous two years. (see below) •Outcomes for a solid organ transplant program will be compared to United Network for Organ Sharing (UNOS) or US Transplant, whichever is most current, and must not be significantly below the expected patient and graft survival at one year or three years. Transplant programs must meet Medicare minimum patient survival outcomes, as defined in the Federal Register for a specific solid organ transplant.
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• Direct method: Compare quality between in- and out-of-network providers (Gaskin et al. 2002; Mukamel et al. 2002, Lindrooth et al. 2002).
• Indirect method: Infer the role of quality in contracting decisions from patient flows. (Escarce et al. 1999; Chernew et al. 1998; Feldman and Sharfstein 2000).
• Very indirect method: Examine how the impact of hospital competition on quality varies by payer type. (Kessler and McClellan 2000; Gowrisankaran and Town 2003).
Three approaches to studying the role of quality in selective contracting:
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• Obtain network lists from for Beechstreet, Aetna, Humana, United Health, Cigna
• Merge with a list of all hospitals offering kidney transplant services w/ outcome data for each center
• Compare outcomes between in-network and out-of-network facilities
Direct method - Overview
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Quality at in-network and out-of-network transplant centers for five health plans
Health plan % In-network In-network Out-of-network Diff. T-stat
BeechStreet 21% 0.90 -0.58 1.47 1.66United 33% 1.39 -1.19 2.58 4.00Cigna 29% 0.50 -0.92 1.42 1.96Humana 35% 1.40 -1.14 2.54 3.69Aetna 38% 0.74 -1.28 2.02 3.16
Quality: O-E graft survival
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• Use data on registrations for patients added to the kidney transplant waiting list
• Create patient-level choice sets
• Merge with data on transplant center location and outcomes
• Compare impact of outcomes on choice between patients with private insurance and Medicare
Indirect method - Overview
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Sample construction
• 28,364 non-elderly adult (age 18-64) kidney transplant registrants.
• Registered on the wait list between January 1, 2000 and October 31, 2002.
• With private insurance or Medicare (no Medicaid).
• Note that the choice of transplant center is made at the time of registration, not the time of transplant.
• The database includes the universe of candidates for deceased donor
transplants in the United States and 30 percent of living-donor transplant recipients.
• Choice sets were constructed using distance and historical registration patterns.
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Conditional logit model: fully interact
transplant center attributes patient characteristics -quality -age-distance -sex
-race -health status -education -insurance
Statistical analysis
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Conditional logit model: fully interact
transplant center attributes patient characteristics -quality -age-distance -sex
-race -health status -education -insurance
Statistical analysis
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Conditional logit model: fully interact
transplant center attributes patient characteristics -quality -age-distance -sex
-race -health status -education -insurance
Statistical analysis
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InsurancePrivate Medicare
Age 48 47Male 59% 59%White 57% 38%On dialysis 70% 95%Diabetic 35% 41%Cardiac condition 15% 19%ADL limitation 12% 17%Education: HS degree 56% 62%Education: College degree 20% 8%Education: Unknown 22% 21%Employed 55% 21%
N 15,906 12,458
Differences between privately-insured registrants and Medicare beneficiaries
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Variable Quality Distance
Level 1.6671 (1.2792) -0.9509 (0.0152)*Age -0.0161 (0.0165) 0.0000 (0.0000) Male 0.0417 (0.3444) 0.0017 (0.0005)*White 1.3929 (0.3596)* -0.0011 (0.0005)*On dialysis 0.0646 (0.4932) 0.0010 (0.0006) Diabetic -0.2809 (0.3753) -0.0021 (0.0005)*Cardiac condition -0.2267 (0.4314) -0.0013 (0.0006)*ADL limitation 1.7232 (0.5084)* 0.0061 (0.0008)*Education: HS degree -1.3803 (0.8673) 0.0026 (0.0008)*Education: College degree 1.0463 (0.9872) 0.0033 (0.0010)*Education: Unknown -1.2771 (0.8987) 0.0022 (0.0009)*Employed -0.5976 (0.3913) -0.0026 (0.0005)*Private insurance 3.0534 (0.3822)* 0.0035 (0.0005)*
*P < 0.05Standard errors are in parentheses.
Center attributes
Estimates from the conditional logit model
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Variable Quality Distance
Level 1.6671 (1.2792) -0.9509 (0.0152)*Age -0.0161 (0.0165) 0.0000 (0.0000) Male 0.0417 (0.3444) 0.0017 (0.0005)*White 1.3929 (0.3596)* -0.0011 (0.0005)*On dialysis 0.0646 (0.4932) 0.0010 (0.0006) Diabetic -0.2809 (0.3753) -0.0021 (0.0005)*Cardiac condition -0.2267 (0.4314) -0.0013 (0.0006)*ADL limitation 1.7232 (0.5084)* 0.0061 (0.0008)*Education: HS degree -1.3803 (0.8673) 0.0026 (0.0008)*Education: College degree 1.0463 (0.9872) 0.0033 (0.0010)*Education: Unknown -1.2771 (0.8987) 0.0022 (0.0009)*Employed -0.5976 (0.3913) -0.0026 (0.0005)*Private insurance 3.0534 (0.3822)* 0.0035 (0.0005)*
*P < 0.05Standard errors are in parentheses.
Center attributes
Estimates from the conditional logit model
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Variable Quality Distance
Level 1.6671 (1.2792) -0.9509 (0.0152)*Age -0.0161 (0.0165) 0.0000 (0.0000) Male 0.0417 (0.3444) 0.0017 (0.0005)*White 1.3929 (0.3596)* -0.0011 (0.0005)*On dialysis 0.0646 (0.4932) 0.0010 (0.0006) Diabetic -0.2809 (0.3753) -0.0021 (0.0005)*Cardiac condition -0.2267 (0.4314) -0.0013 (0.0006)*ADL limitation 1.7232 (0.5084)* 0.0061 (0.0008)*Education: HS degree -1.3803 (0.8673) 0.0026 (0.0008)*Education: College degree 1.0463 (0.9872) 0.0033 (0.0010)*Education: Unknown -1.2771 (0.8987) 0.0022 (0.0009)*Employed -0.5976 (0.3913) -0.0026 (0.0005)*Private insurance 3.0534 (0.3822)* 0.0035 (0.0005)*
*P < 0.05Standard errors are in parentheses.
Center attributes
Estimates from the conditional logit model
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Actual: 0.14 [95% CI: -0.21,- 0.07].
One-standard deviation increase in graft failure rate for a hospital 7% decline in registrations
If all registrants were privately insured: -0.22 [95% CI: -0.29, -0.15].
One-standard deviation increase in graft failure rate 11% decline in registrations
If all registrants were in Medicare: -0.03 [95% CI: -0.10, 0.04].
One-standard deviation increase in graft failure rate 2% decline in registrations
Quality-choice elasticity estimates
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To sum up: evidence is consistent with plans’ claims.
Caveats
No data on prices
Endogeneity?
Only observe static effects-dynamic effects may be more important
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Porter & Teisberg’s Ingredients for Change
No Restrictions to Competition and Choice • No preapprovals for referrals or treatments • No network restrictions • Strict antitrust enforcement against collusion, excessive concentration, and unfair practices • Meaningful co-payments and medical savings accounts with high deductibles, all of which will give consumers incentives to seek good value
Accessible Information • Appropriate information on treatments and alternatives is formally collected and widely disseminated. • Information about providers‘ experience in treating particular diseases and conditions is made available immediately. • Risk-adjusted outcome data are developed and continually enhanced. • Some information is standardized nationally to enable comparisons.
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Porter & Teisberg’s Ingredients for Change
No Restrictions to Competition and Choice • No preapprovals for referrals or treatments • No network restrictions • Strict antitrust enforcement against collusion, excessive concentration, and unfair practices • Meaningful co-payments and medical savings accounts with high deductibles, all of which will give consumers incentives to seek good value
Accessible Information • Appropriate information on treatments and alternatives is formally collected and widely disseminated. • Information about providers‘ experience in treating particular diseases and conditions is made available immediately. • Risk-adjusted outcome data are developed and continually enhanced. • Some information is standardized nationally to enable comparisons.
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Porter & Teisberg’s Ingredients for Change
No Restrictions to Competition and Choice • No preapprovals for referrals or treatments • No network restrictions • Strict antitrust enforcement against collusion, excessive concentration, and unfair practices • Meaningful co-payments and medical savings accounts with high deductibles, all of which will give consumers incentives to seek good value
Accessible Information • Appropriate information on treatments and alternatives is formally collected and widely disseminated. • Information about providers‘ experience in treating particular diseases and conditions is made available immediately. • Risk-adjusted outcome data are developed and continually enhanced. • Some information is standardized nationally to enable comparisons.