Continuation of Research on Consumer Directed Health Plans: Does Access to Transparent Provider Quality and Cost Information Affect Health Care Cost and Utilization of Preventive Services?. Results

12/15/2008

Our first step to complete the empirical analysis was to generate the provider portfolio ratings. We weighted the portfolio ratings by three different patient and year-specific variables: the unique number of provider visits of a patient, the allowed charge amount for the patient, and the out-of-pocket expenditures of the patient. Table 2 provides the results of these ranking methodologies. The first set of variables in the table corresponds to the second-year portfolio score by each of three methods used. Note that both firms have average scores above 1 (the lowest value), except the out-of-pocket expenditure weighted score for firm #2. The second set of rows in Table 2 is the change between year 1 and year 2 in provider portfolio ratings. Note that the visit weighted portfolio decreased slightly for Firm #1. The last set of rows in the table is associated with the variable we use in our multivariate analysis. Here we measure a 0/1 variable for whether a person’s provider portfolio improved from one year to the next. Although the out-of-pocket expenditure weighing method is associated with the greatest improvement in portfolio rankings, we choose the median method in terms of impact – weighting by allowed charges.

Variables Firm 1 Firm 2

Table 2 – Provider Portfolio Rankings by Weighting Type

Average Values

Year 2 Portfolio Score
Visit Weigted 1.405 1.299
Allowed Charges Weighted 1.347 1.280
Out-of-pocket Expenditure Weighted 1.033 0.867
Year 2 - Year 1 Portfolio Rating Delta
Visit Weigted -0.004 0.010
Allowed Charges Weighted 0.001 0.031
Out-of-pocket Expenditure Weighted 0.942 0.397
Positive Change in Score = 1, else 0
Visit Weigted 0.323 0.249
Allowed Charges Weighted 0.335 0.264
Out-of-pocket Expenditure Weighted 0.655 0.423

In Table 3, we present the bivariate results associated with a change in provider portfolio ratings on expenditures and preventive care use. The two firms experienced a major change in benefit design where there was a full replacement of a PPO design for a CDHP design. As noted above, we use the change in portfolio from an allowed charges weighting method to identify the impact of the ranking system at each firm.4 In the case of Firm #1, total expenditures increased from $2,359 to $3,483 for patients with a negative or neutral provider portfolio change, but decreased from $4,894 to $4,087 for those with a positive provider portfolio change. Similar patterns were observed in Firm #2, with increases from $1,948 to $2,100 for patients with a negative or neutral provider portfolio change, and decreases from $4,020 to $2,989 for those with a positive provider portfolio change. Patients with positive changes had higher baseline spending in both firms – an indication of the need to control for baseline illness burden and other factors that determine the level of spending across patients.

Out-of-pocket medical expenditures have different patterns compared with overall expenditures. Out-of-pocket spending increased for both types of patients in both firms. This is due, most likely, to the changes in health plans in both firms in 2006. Similar patterns were observed for consumer out-of-pocket pharmacy spending.

With respect to preventive visits, patients in both firms with positive provider portfolio changes had fewer colonoscopies in year 2 than in year 1. Other changes in preventive visits and colonoscopies were not statistically significant.

  Negative or Neutral Provider Portfolio Change Positive Provider Portfolio Change  
  Firm 1     Firm 2     Firm 1     Firm 2    
  Year 1 Year 2   Year 1 Year 2   Year 1 Year 2   Year 1 Year 2  

Table 3 – Bivariate Provider Portfolio Ratings Changes with Cost and Preventive Use

Total Expenditures $2359.22 $3483.18 *** $1947.77 $2100.32 *** $4893.98 $4087.08 *** $4019.60 $2989.08 ***
Consumer Medical Expenditures $ 86 $ 344 *** $ 256 $ 486 *** $ 144 $ 445 *** $ 557 $ 714 ***
Consumer Pharmacy Expenditures $ 48 $ 240 *** $ 145 $ 176 *** $ 70 $ 365 *** $ 290 $ 407 ***
Preventive Visits 0.291 0.273   0.106 0.105   0.425 0.446   0.248 0.255  
Colonoscopy Screenings 0.204 0.240   0.128 0.107   0.267 0.187 ** 0.251 0.123 ***
*** p<=.001, ** p<=.01, *P<=.05

The attributes associated with positive changes in provider portfolios are described in Table 4. Here we look at the results of three logistic regressions, each using a different weighting strategy for identifying a positive change in the provider portfolio. The middle set of results that is boxed represents the weighted by allowed charges strategy we use for this analysis. The table is useful to identify the attributes of patients associated with positive changes in provider portfolios. Across all methodologies we see a positive relationship with female gender. Age has a positive relationship for visits and allowed charge weighted portfolio scores and a negative relationship with out-of-pocket expenditure weighted portfolio scores. Those who are more ill, either due to a higher illness burden or a catastrophic medical event, have greater likelihood of improving their provider portfolio. In all weighting methodologies, spouses and dependents have less improvement in their provider portfolio than the insurance contract holder.

Variable Visit All Allowed $$$ Out-of-Pocket $$
  Coefficient Pr>ChiSq Coefficient Pr>ChiSq Coefficient Pr > ChiSq

Table 4 –Attributes Associated with Positive Changes in Provider Portfolios

Provider Rating Portfolio Weighting Methodology

Intercept -1.0281 <.0001 -0.9209 <.0001 0.3397 <.0001
Age (years) 0.0046 0.0032 0.0026 0.0913 -0.0096 <.0001
Female=1, else 0 0.0951 0.0024 0.0863 0.0054 0.1449 <.0001
Baseline Illness Burden 0.1055 <.0001 0.1122 <.0001 0.1736 <.0001
Catastrophic Shock=1, else 0 0.1355 0.0002 0.0730 0.0476 0.1157 0.0024
Year 2=1, else Year 1 0.0039 0.9196 0.0021 0.9549 0.0009 0.9808
Firm 2=1, else 0 -0.0894 0.0513 -0.0750 0.0981 -0.4872 <.0001
Firm 2 & Year 2 interaction -0.0339 0.5949 -0.0327 0.6038 -0.0284 0.6442
Enrollee is spouse=1, else 0 -0.0139 0.7124 -0.0166 0.6593 -0.0765 0.0466
Dependent enrollee=1, else 0 -0.1687 0.009 -0.1707 0.0075 -0.6324 <.0001

In Tables 5 through 7, we present two models of the effects of a positive change in provider portfolio on expenditure. Model 1 uses a ’dummy’ variable defined as 1 if there was a positive change in the patient’s provider portfolio between year 1 and year 2, and 0 if there was not a positive change. Model 2 includes an interaction term between the illness burden metric and the dummy variable indicating a positive change in provider portfolio. In Table 5, we examine the effect of the change in provider portfolio on the change in total expenditure. In model 1, the effect is largely negative and statistically significant, suggesting an overall cost savings from provider portfolio improvement. In model 2, the portfolio change variable is now positive and insignificant. However, the interaction of illness burden and provider portfolio change is negative and significant. This suggests patients with a greater illness burden have lower expenditures if they receive care from a set of providers where there was improvement in the provider portfolio. As expected, age and the presence of a catastrophic illness shock have statistically significant and positive effects on the change in total expenditures.

  Model 1 Model 2
  Coefficient Pr > |t| Coefficient Pr > |t|

Table 5 – Impact of a Positive Change in Provider Portfolio on Change in Total Expenditures

Change in Total Expenditures

Intercept 804.954 0.227 89.754 0.894
Age (years) 15.353 0.226 21.021 0.097
Female=1, else 0 192.379 0.458 121.538 0.638
Baseline Illness Burden -370.544 <.0001 -176.619 0.005
Catastrophic Shock=1, else 0 3323.816 <.0001 3293.081 <.0001
Firm 2=1, else 0 -927.401 0.001 -874.774 0.001
Enrollee is spouse=1, else 0 593.991 0.065 540.374 0.092
Enrollee is dependent=1, else 0 -316.554 0.545 -155.532 0.766
Provider Portfolio improvement=1, else 0 -1593.317 <.0001 709.520 0.145
Portfolio Change & Illness Burden   -642.657 <.0001
Adjusted R-Square 0.047 0.055  

Tables 6 and 7 look at the effect of a positive change in provider portfolio on the change in consumer out-of-pocket expenditures for medical care and pharmaceuticals, respectively. We find different impacts of the provider portfolio change on these two types of spending. For out-of-pocket medical expenditures, there is a negative impact from the portfolio change variable interacted with the illness burden of the patient in model 2. In model 1, the effect of provider portfolio improvement is also negative but not statistically significant at the p<.05 level. The catastrophic shock variable is associated with the largest positive impact on the change in out-of-pocket medical expenditures.

 

Model 1

Model 2

  Coefficient Pr > |t| Coefficient Pr > |t|

Table 6 – Impact of a Positive Change in Provider Portfolio on Change in Medical OOP Expenditure

Change in Consumer Out-of-Pocket Medical Expenditures

Intercept 362.619 <.0001 323.352 <.0001
Age (years) -1.612 0.112 -1.300 0.200
Female=1, else 0 64.858 0.002 60.968 0.003
Baseline Illness Burden -16.422 0.000 -5.774 0.253
Catastrophic Shock=1, else 0 353.670 <.0001 351.982 <.0001
Firm 2=1, else 0 -65.964 0.002 -63.075 0.003
Enrollee is spouse=1, else 0 -20.570 0.423 -23.513 0.359
Enrollee is dependent=1, else 0 -226.746 <.0001 -217.905 <.0001
Provider Portfolio improvement=1, else 0 -30.728 0.177 95.706 0.014
Portfolio Change & Illness Burden     -35.284 <.0001
Adjusted R-Square 0.063   0.067  

For pharmaceutical services, the effect is quite different. In Table 7 there is a positive and significant effect of provider portfolio change in model 1. In model 2, the interaction of illness burden and change in provider portfolio is small and statistically insignificant. This suggests that for pharmaceutical services, there may be less value in changing to providers who have a higher star rating.

  Model 1 Model 2
  Coefficient Pr > |t| Coefficient Pr > |t|

Table 7 – Impact of a Positive Change in Provider Portfolio on Change in Drug OOP Expenditure

Change in Consumer Out-of-Pocket Pharmacy Expenditures

Intercept 77.289 0.004 76.935 0.005
Age (years) 2.632 <.0001 2.634 <.0001
Female=1, else 0 22.760 0.030 22.725 0.031
Baseline Illness Burden 18.363 <.0001 18.459 <.0001
Catastrophic Shock=1, else 0 -19.260 0.128 -19.276 0.128
Firm 2=1, else 0 -152.306 <.0001 -152.280 <.0001
Enrollee is spouse=1, else 0 -27.280 0.036 -27.307 0.036
Enrollee is dependent=1, else 0 -55.067 0.010 -54.987 0.010
Provider Portfolio improvement=1, else 0 51.635 <.0001 52.776 0.008
Portfolio Change & Illness Burden     -0.319 0.944

Adjusted R-Square

0.134   0.134  

In Tables 8 and 9, we examine the effect of a change in provider portfolio on the change in use of preventive services. In Table 8, the portfolio change variable shows a positive and significant relationship with the change in preventive visits, after accounting for age, gender and health status. However, for colonoscopy screening the result is quite different. As seen in Table 9, a positive change in provider portfolio is associated with a substantial decrease in colonoscopy screening and the result is statistically significant at the p<.001 level.

  Coefficient Pr > |t|

Table 8 – Impact of a Positive Change in Provider Portfolio on Change in Preventive Visits

Any Preventive Visits

Intercept 0.031 0.385
Age (years) 0.000 0.903
Female=1, else 0 0.006 0.667
Baseline Illness Burden -0.017 <.0001
Catastrophic Shock=1, else 0 0.007 0.666
Firm 2=1, else 0 -0.001 0.949
Enrollee is spouse=1, else 0 -0.006 0.735
Enrollee is dependent=1, else 0 0.010 0.727
Provider Portfolio improvement=1, else 0 0.050 0.001
Adjusted R-Square 0.010  
  Coefficient Pr > |t|

Table 9 – Impact of a Positive Change in Provider Portfolio on Change in Colonoscopy Screening

Change in Colonoscopy Screening

Intercept 0.384 0.002
Age (years) -0.005 0.024
Female=1, else 0 -0.001 0.982
Baseline Illness Burden -0.019 0.001
Catastrophic Shock=1, else 0 -0.004 0.894
Firm 2=1, else 0 -0.074 0.014
Enrollee is spouse=1, else 0 0.007 0.803
Provider Portfolio improvement=1, else 0 -0.112 <.0001
Adjusted R-Square 0.029  

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