This data brief compares average state-level prices against quality measures for asthma, diabetes and hypertension care and finds that higher prices for medical services are not always indicative of higher quality of care

Eric Barrette

Kevin Kennedy

English

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1  www.healthcostinstitute.org    Data Brief #3 April 2016 KEY FINDINGS Health care quality is largely unrelated to health care price Four of the five price-quality correlation coefficients were between –0.45 and 0.00, suggesting a negative or null rela-tionship between price and quality. Prices for health care services are gen-erally related, while quality measures are not All ten price correlations were larger than 0.50 and nine of the ten quality measure correlations were less than 0.35, suggesting states may be character-ized as high or low priced, but the level of quality may vary within a state. The Price-Quality Paradox in Health Care  the quality will be the same; and, thus, are not correlated. We calculated the correlation between the state-level quality measures and prices to address the question “is higher quality asso-ciated with higher prices?” The correlation coefficients are presented in Table 1. A posi-tive correlation implies higher quality measures occur where prices are higher. A negative correlation implies the quality measures are relatively lower where prices are higher and higher quality occurs where there are lower prices. Furthermore, the magnitude of the correlation coefficient sug-gests how strong the relationship is between price and quality. A correlation of 1.00 im-plies for every unit increase in price, quality increases proportionally (a –1.00 correlation implies price and quality move in opposite directions). On the other hand, a correlation coefficient of 0.00 implies there is no con-sistent relationship between the two measures.  The results suggest that higher prices are not indicative of better quality of care. Of the five price-quality correlations, only hemoglo-bin A1C test had a weakly positive correla-The recent push for greater transpar-ency in health care has often focused on making prices more accessible and useful to all health care stakehold-ers—consumers, payers, employers, etc. Yet, with only price information, stakeholders have no way to deter-mine if paying a higher price is war-ranted. Public information about the quality of health care services needs to be provided alongside prices if health care transparency efforts have any chance of reducing costs while im-proving health outcomes. This data brief examines how the quality of health care services is related to pric-es. The Health Care Cost Institute (HCCI) calculated quality of care measures with the same claims data used to esti-mate the average prices of common health care services, publically availa-ble on guroo.com. Like the price esti-mates, these quality measures are re-ported at the local, state, and national levels. Quality and price of five measures are discussed in this brief; one related to asthma (asthma evaluation), two re-lated diabetes (diabetes evaluation and hemoglobin A1C test), and two related to hypertension (hypertension evaluation and creatinine test). Higher measure values imply higher quality of care. (See “Data and Methods” for ad-ditional details.) Table 1 presents the mean and stand-ard deviation of the five state-level  quality measures and their compara-ble price estimates, which were re-portable for 42 states and D.C.1 The results show that there are significant differences in the provision of recom-mended care across quality measures. While nearly every diabetes patient receives an annual evaluation (97%), only about half of the individuals with asthma have an annual physician visit related to their condition.  There is no consistent relationship between quality measures and prices Figures 1-5 are scatter plots showing the relationship between the state-level quality and relative price measures. Quality is measured along the horizontal axis with quality meas-ure values increasing left to right. The vertical axis is a normalized price measure, calculated as the ratio of each state-level price divided by the national average price for the same service. Thus, the vertical axis shows to what extent a state-level price is above (>1.0) or below (<1.0) the na-tional average price.  The red dot on each graph represents the intersection of the national aver-age price and national average quality level for each measure. Among the negatively correlated measures, asth-ma and hypertension evaluation, most of the state-level points are in the up-per left and lower right quadrants of the graph. This indicates higher quali-ty in states with lower relative prices and lower quality in states with higher relative prices.  The hemoglobin eval-uation measure graph depicts an op-posite distribution—higher quality where there are higher prices. The creatinine measure points are scat-tered evenly across the graph, sug-gesting no relationship between price and quality. The points on the diabe-tes evaluation measure graph are highly concentrated around the quali-ty average, but have a wide range of prices. This suggests that no matter the price of the diabetes evaluation, Higher prices for medical services are not always indicative of higher quality of care  2 www.healthcostinstitute.org    tion of 0.18. Creatinine tests had a weak but negative correlation coefficient of -0.11. The quality measures for asthma evaluation and hypertension evaluation were both negatively correlated with their corresponding prices and the mag-nitudes were moderately high; -0.37 and -0.45 respectively. No relationship be-tween diabetes evaluation quality and price was found—the correlation was 0.00.  A higher quality measure for one health care service does not guarantee higher quality for another We also tested the correlation between the five quality measures, the resulting matrix of correlations is presented in Table 2. Positive correlations between the different measures suggests similar patterns in quality across different ser-vices. While one would expect a highly positive correlation between the ser-vices related to the same underlying condition, the results did not support this expectation. Hemoglobin testing and diabetes evaluation were only mod-erately correlated (0.34) and the creati-nine testing-hypertension evaluation correlation was even weaker at 0.16.  There was a strong, positive correlation between hemoglobin A1C testing and creatinine testing (0.84). Hypertension evaluation was moderately correlated with diabetes (0.34) and asthma (0.37) evaluations. The remaining quality pair-ings had weak to no correlation.  Higher price levels for one health care serivce suggest prices may be higher for other services Finally, we examined the relationship between the prices of the corresponding medical procedures. Unlike the quality measure relationships, all of the price correlations were positive and greater than 0.50 (Table 3). The results suggest that health care prices are related even where prices and quality for the same services are not. The correlation of dia-betes evaluation and hemoglobin A1C testing prices, both of which are related to treatment for diabetes, was 0.89. Sim-ilarly, the correlation of prices for treat-ments of hypertension, hypertension evaluation and creatinine testing, was 0.70.  Among all 10 state-level price-to-price pairings, the lowest correlation (0.55) was among two different categories of health care services (creatinine testing and asthma evaluation). However, the nearly perfect correlation of 0.97, was also between different service catego-ries (asthma and diabetes evaluations).  Conclusion Although stakeholders need more  information about the costs of health care serivces, they are limited in how they can use that information without knowing what to expect for a given price. The results of this evaluation of the relationship between state-level quality and price measures demonstrate how price alone may not be sufficent for identifing quality. In some cases, it appears that higher prices are acutally associated with lower quality. If policy makers and health care industry leaders expect transparency efforts to have real impacts on the health care system, making quality information more accessible and useable by stakeholders is also necessary.  Limitations Both the price and quality measures used in this analysis were calculated at a state level and may differ from a partic-ular provider’s prices or quality. The measures reflect the average for the state allowing for nationwide analysis. Additionally, the quality measures were calculated from claims data and reflect a measure of quality of care based on whether recommended services were provided. A provider’s treatment may differ from the recommended care for many reasons and there are numerous other ways to evaluate quality. The qual-ity measures do provide a sense of whether particular patient populations are receiving the types of services asso-ciated with improved outcomes.  Data and Methods HCCI's data set includes de-identified, HIPPA compliant health insurance claims from multiple national health insurers, representing over 50 million covered lives. The membership and claims data include details such as zip codes, diagnostic codes, procedure codes, actual amounts paid by the insurer as well as the  copayments, deductibles, and coinsurance paid by the insured. Both individual and employer sponsored insurance claims were included in the analyses.  The quality measures were calculated with person-level claims data using Symmetry EBM Connect software version 9.0.2 The person-level results were aggregated to local, state, and national levels for reporting and analysis. The quality measures assess whether patients with a specific diagnosis received recommended health care services, which are known to improve health outcomes. The measures are reported as the percentage of patients who received the recommended care.  The price measures included in the analysis were the most comparable to the services for which quality measures were calculated.  For additional details on the average price estimates and reporting requirements see guroo.com.3  Endnotes 1. HCCI data are insufficient for reporting prices in Alabama, Idaho, Hawaii, Michigan, Montana, South Dakota, Vermont, and Wyoming.  2. Additional details are available at: https://www.optum.com/government/fed/analytics-hit/population-analytics/measuring-value-understanding-costs/symmetry-ebm-connect.html. 3. Additional details are available at: http://www.guroo.com/#!terms-and-conditions. 3  www.healthcostinstitute.org    Table 1. Summary Statistics and Quality-Price Correlations  Quality Measure Description Price Measure  Description Price Mean (SD) Quality Mean (SD) Quality—Price Correlation Asthma  Evaluation People with asthma should have regular doctor visits to monitor and review control of their asthma, treat-ment plan, and medications. This measure reports the percentage of people with asthma who had an office visit for asthma care within the last 6 months. For this measure, a higher score is better.  Four visits with a primary care physician to evaluate your asthma and determine the best course of treatment $734.47 (190.14) 54.85 (1.83) -0.37 Diabetes  Evaluation People with diabetes should receive regular medical care. At a minimum, an annual doctor visit is recom-mended. This measure reports the percentage of people with diabetes who had at least 1 visit during the last 12 months. For this measure, a higher score is better.  Two visits with a specialist for a detailed evaluation and treatment of your diabetes $353.65 (99.60) 97.57 (0.88) 0.00 Hemoglobin A1c Test Hemoglobin A1c (HbA1c) testing should be performed routinely for all people with diabetes. HbA1c testing is recommended at least 2 times per year. This meas-ure reports the percentage of people who had at least 1 HbA1C test in the last 6 months. For this measure, a higher score is better.  HbA1c test is a blood test used to diagnose or check for diabetes $183.91 (62.53) 79.70 (2.73) 0.18 Hypertension Evaluation People being treated for hypertension should have a minimum of one doctor visit per year to assess their adherence to the treatment and changes in target organ function. This measure reports the percentage of people with hypertension who had a visit for a hypertension assessment within the last 12 months. For this measure, a higher score is better.  One visit with a primary care physician to evaluate your blood pressure and determine the best course of treatment $17.30 (9.53) 58.17 (5.54) -0.45 Creatinine Test At least one serum creatinine test per year is recom-mended for people being treated for hypertension. This measure reports the percentage of people with hypertension that had a serum creatinine test in last 12 months. For this measure, a higher score is better.  Creatinine test to check the level of creatinine in the blood system $13.35 (5.49) 68.31 (3.75) -0.11 Source: HCCI, 2016. Notes: All reported correlations are Pearson product moment correlation coefficients, which measure the linear correlation between variables. The standard deviation is listed in parentheses.  4 www.healthcostinstitute.org    Source: HCCI, 2016. Notes: All reported correlations are Pearson product moment correlation coefficients, which measure the linear correlation between variables.  Table 2. Quality to Quality Correlation    Asthma Diabetes Hemoglobin  Hypertension Creatinine Asthma Evaluation 1.00         Diabetes Evaluation 0.05 1.00       Hemoglobin A1c Test  -0.03 0.35 1.00     Hypertension Evaluation 0.37 0.34  -0.03 1.00   Creatinine Test -0.02 0.21 0.84 0.16 1.00 Table 3. Price to Price Correlation    Asthma Diabetes Hemoglobin  Hypertension Creatinine Asthma Evaluation 1.00         Diabetes Evaluation 0.97 1.00       Hemoglobin A1c Test  0.81  0.89  1.00     Hypertension Evaluation 0.90 0.97 0.92 1.00   Creatinine Test 0.55 0.62 0.64 0.70 1.00 Source: HCCI, 2016. Notes: All reported correlations are Pearson product moment correlation coefficients, which measure the linear correlation between variables.  5  www.healthcostinstitute.org    Figure 2. Diabetes Evaluation Price—Quality Relationship (n=43) Source: HCCI, 2016. Source: HCCI, 2016. Figure 1. Asthma Evaluation Price—Quality Relationship (n=43) 6  www.healthcostinstitute.org    Figure 4. Hypertension Evaluation Price—Quality Relationship (n=43) Source: HCCI, 2016. Source: HCCI, 2016. Figure 3. Hemoglobin A1C Price—Quality Relationship (n=43) 7  www.healthcostinstitute.org    Source: HCCI, 2016. Figure 5. Creatinine Test Price—Quality Relationship (n=43) Authors Eric Barrette and Kevin Kennedy ebarrette@healthcostinstitute.org   571-257-1584  Copyright 2016 Health Care Cost Institute, Inc. Unless explicitly noted, the content of this report is licensed under a Creative Commons Attribution Non-Commercial No Derivatives 4.0 License  Health Care Cost Institute, Inc. 1100 G Street NW, Suite 600 Washington, DC 20005 202-803-5200 

The Price-Quality Paradox in Healthcare

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The Price-Quality Paradox in Healthcare

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