VA Center for Medication Safety, Hines VA

Center for Health Equity Research and Promotion, VA

: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

: Sherrie L. Aspinall, PharmD, MSc, VA Pittsburgh Healthcare System, Center for Health Equity Research and Promotion (151C-H), 7180 Highland Dr, Pittsburgh, PA 15206. E-mail: 

2. Karter AJ, Parker MM, Moffet HH, et al

. Longitudinal study of new and prevalent use of self-monitoring of blood glucose. 

4. Davidson MB, Castellanos M, Kain D, Duran P

. The effect of self monitoring of blood glucose concentrations on glycated hemoglobin levels in diabetic patients not taking insulin: a blinded, randomized trial. 

: LifeScan, A Johnson and Johnson Company.

: The authors (SLT, MEM) are employees of IMS, a company that provides contracted research consulting to LifeScan.

: Sandra L. Tunis, PhD, Health Economics and Outcomes Research, IMS Consulting Services, 14701 Cumberland Rd, Ste 107, Nobelsville, IN 46060. E-mail: 

. Self-monitoring of blood glucose in type 2 diabetes: cost-effectiveness in the United States. 

3. Centers for Disease Control and Prevention, National Center for Health Statistics

. National Nutrition and Health Examination Survey (NHANES) data. Hyattsville, MD: US Department of Health and Human Services; 2000.

Articles

LETTERS TO THE EDITORS

Cost-Effectiveness of Blood Glucose Monitoring Is Controversial

: To describe adherence with statin treatment in a usual practice setting and to investigate potential determinants of better adherence. 

: Retrospective cohort study using administrative claims data.

: Study patients were 47,680 individuals enrolled in the Central District of Clalit Health Services HMO in Israel who filled at least 1 prescription for statins between January 1, 1999, and December 31, 2006. Data were retrieved on patientsâ€™ sex, year of birth and immigration, socioeconomic status, and whether they had diabetes mellitus, hypertension, and other cardiovascular diseases.

: Mean age at the beginning of treatment was 61.3 Â± 11.8 years; 53.3% of the study patients were women. The proportion with at least 1 chronic disease before starting statins was 40.1%; and 38.9%, 21.8%, and 9.6% of the patients were continuously adherent after 1, 3, and 6 years, respectively. Risk of discontinuation was highest among new immigrants (hazard ratio [HR] = 1.20; 95% confidence interval [CI] = 1.14, 1.27). Adherence was higher in patients having a chronic disease before starting statins (HR = 0.88; 95% CI = 0.84, 0.94) or after starting statins (HR = 0.90; 95% CI = 0.86, 0.95). Patients age <50 or >79 years had lower adherence rates. Low socioeconomic state did not affect adherence.

: Adherence with statin therapy was poor, though adherence rates were better in patients with accompanying chronic diseases. Of particular concern was the low level of adherence in new immigrants. Intervention programs are needed and should target all patient groups. 

Adherence with statin therapy in a usual care setting (Israelâ€™s largest HMO) was poor.

The low rate of adherence in new immigrants was of particular concern. 

The adherence rates in patients with cardiovascular diseases or with cardiovascular risk factors were higher but were still unacceptably low.

Our results suggest that intervention programs are needed and should target all groups of patients.

The study was conducted in the Central District of Clalit Health Services HMO (the largest HMO in Israel, with more than 50% of Israel&#8217;s population being members). All HMO members over 25 years of age in the central district on January 1, 1998, who were still members and alive on December 31, 2006, and filled at least 1 prescription of statins were included. The overall annual rate of leaving our health plan is less than 1%.

 Patients who dropped out of our health plan during follow-up were not included in the study cohort.

All community pharmacies in use by the HMO are computerized and report to a central repository. All prescriptions of all brands of statins, which were filled by the study population through HMO-related pharmacies, were documented. This HMO dispenses medications with nominal and almost equal copayments (between $3 and $8 for a monthly dosage), which ensures that all prescriptions were documented.

From the HMO&#8217;s central register of patients with chronic diseases,

 we retrieved data to determine whether the patients had diabetes mellitus or cardiovascular diseases, and the date of the diagnosis. For each participant we retrieved sociodemographic data from the HMO database, including sex, place of residence, year of birth, country of origin, and year of immigration to Israel. A patient was defined as having low socioeconomic status if he or she had an exemption from paying his monthly National Insurance contribution. Patients with low socioeconomic status have a copayment discount.

A patient was defined as a new immigrant if he or she came to Israel after 1990. We choose the year 1990 as a cutoff point because in this year (as in many of the years in the early 1990s), there was a large wave of immigrants to Israel, especially from the former Soviet Union.

The collection of data for the study was done anonymously and in conformity with all country laws and the Helsinki Declaration.

We identified 47,680 patients who met the inclusion criteria. 

 shows the population characteristics at entry. The number of new patients treated with statins every year increased rapidly during the study period from 4576 new patients in 1999 to 8787 in 2005.

Using the definition of 80% adherence, 61.1% of the patients stopped treatment during the first year. In the years to follow, treatment discontinuation continued. After 3 and 6 years, only 21.8% and 9.6% of the patients, respectively, were still on statins.

 presents the HRs of treatment discontinuation associated with potential predictors (an HR <1 means better adherence with statins compared with the reference group). The risk of discontinuation was higher in new immigrants who came to Israel after 1990 (HR = 1.20; 95% confidence interval [CI] = 1.14, 1.27) and immigrants from Ethiopia (HR = 1.22; 95% CI = 1.16, 1.29) compared with others. The adherence was higher in patients who had chronic diseases before starting statins (HR = 0.88; 95% CI = 0.84, 0.94), or when chronic disease was diagnosed during the course of treatment for hyperlipidemia (HR = 0.90; 95% CI = 0.86, 0.95).

Patients younger than age 50 or older than 79 had lower adherence rates than the other patients. Place of residence and sex had a statistically significant but a very small effect on adherence rates, while low socioeconomic status did not have any effect on adherence rates.

The current study was of current routine care of community patients. We found that the number of patients beginning statins between 2003 and 2005 increased 32%. although statins clearly have become a cornerstone in the management of  cardiovascular risk, both for primary and secondary prevention, the adherence rates are very disappointing. In the vast majority of cases, statins are lifelong medications. To the best of our knowledge, this large-scale, retrospective, longitudinal study is the longest follow-up reported in a routine clinical care setting.

The rate of discontinuation during the first year was very high: 61.1%. This rate is much higher than that previously reported in clinical trials.

It is much higher than the 26% reported by Caspard et al

 and similar to the 57% reported by Schultz et al

We were able to identify determinants of adherence to statin therapy. Adherence rates were higher for secondary prevention than for primary prevention. This finding, which was consistent across the entire spectrum of cardiovascular risk factors that we evaluated, is not surprising and is in concordance with previous studies that had shorter follow-up periods.

However, even in this high-risk population, adherence rates were disappointing. We must search for better ways to increase adherence in this group of patients by educational, medical, and administrative interventions.

Sociodemographic characteristics affect adherence. Low income did not predict a lower adherence rate in our patients, possibly because of the relatively low copayment, which is even lower for low-income patients. This low copayment may be unique to the Israeli health system and not generalizable to other health systems. 

However, we were able to determine other demographic characteristics of patients with low adherence. Low rates of adherence were found in new immigrants, who may have come from cultures with different health beliefs (equivalent to minorities in other studies).

They may have difficulties in the immigration process that influence adherence as well as many other health indicators, and we should focus on this population in this vulnerable period.

There are several strengths to our study. Use of pharmacy claims allows assessment of long-term adherence in a large population. Patients and physicians were unaware that adherence would be assessed; thus, behavior was not altered by adherence measurements, a common flaw of studies based on self-report or pill count. Our ability to link documentation of the onset of chronic diseases, accurate sociodemographic data, and pharmacy claims gave us the opportunity to eliminate possible confounders.

The study has a few limitations. The setting may not be representative of usual care in populations and health systems in other parts of the world. But the very large sample and the confounders entered into the statistical model enable readers to make the needed adaptations. We may have missed clinical correlations when we used pharmacy claims. It may be that therapy was discontinued for clinically appropriate reasons such as adverse drug events or conversion to other therapies, or because LDL-C target levels were reached by weight reduction, change in diet, and exercise. However, statins are very safe, and conversion from statins to nonstatin agents is rare.

 The possibility that medications were stopped because patients achieved target levels of LDL-C deserves further study. There is no way to verify that those who purchased a prescription actually consumed the pills. But this surrogate fits for large epidemiologic studies.

To evaluate adherence, we considered all brands and dosages together. More potent statins or a higher dosage might indicate more severe disease, and better stratification of the cohort might have resulted if these factors had been considered. However, as we are dealt with an extended follow-up period, we presumed that dosage and brand were not constant for the whole period in many patients. We chose, therefore, stratification according to primary versus secondary prevention only.

Our criterion for adherence was 1 year of at least 80% adherence, but patients who experienced breaks in statin treatment because they were out of the country or had an extended hospitalization could have been falsely labeled as discontinuers. However, in our HMO, a patient leaving the country can get 3 months of chronic medications in advance. Also, we presumed that only a small minority of the cohort had hospitalizations longer than 2 months, and only a small number of discontinuations could be explained this way.

: From the Department of Family Medicine, Tel Aviv University, Tel Aviv Israel (SV, MS); and Clalit Health Services, Rishon LeZion, Israel (SV, MS, TB, AE).

: Dr Vinker had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. The authors (SV, MS, TB, AE) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

: Concept and design (SV, AE); acquisition of data (SV, TB); analysis and interpretation of data (SV, MS, TB); drafting of the manuscript (SV, MS, TB, AE); critical revision of the manuscript for important intellectual content (MS, AE); statistical analysis (SV, MS, TB); provision of study materials or patients (TB, AE); and administrative, technical, or logistic support (SV, AE).

: Shlomo Vinker, MD, Department of Family Medicine, Tel Aviv University, POB 14238, Ashdod 77042, Israel. Email: 

. Heart Disease and Stroke Statistics- 2003 Update. Dallas, TX: American Heart Association, 2003. 

http://www.americanheart.org/downloadable/heart/1040391091015HDS_Stats_03.pdf

3. Expert Panel on Detection Evaluation,Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III

). Executive summary of the third report of the National Cholesterol Education Program (NCEP). 

5. Pearson TA, Laurora I, Chu H, Kafonek S

.The lipid treatment assessment project (L-TAP): a multicenter survey to evaluate the percentages of dyslipidemic patients receiving lipid-lowering therapy and achieving low-density lipoprotein cholesterol goals. 

7. Benner JS, Glynn RJ, Mogun H, Neumann PJ,Weinstein MC, Avorn J

. Long-term persistence in use of statin therapy in elderly patients. 

9. Ford ES, Mokdad AH, Giles WH, Mensah GA

. Serum total cholesterol concentrations and awareness, treatment, and control of hypercholesterolemia among US adults. Findings from the National Health And Nutrition Examination Survey, 1999 to 2000. 

. Compliance with a statin treatment in a usual care setting: retrospective database analysis over 3 years after treatment initiation in health maintenance organization enrollees with dyslipidemia. 

13. Walley T, Folino-Gallo P, Stephens P, Van Ganse E

. Trends in prescribing and utilization of statins and other lipid lowering drugs across Europe 1997-2003. 

. Analysis of factors associated with statin adherence in a hierarchical model considering physician, pharmacy, patient, and prescription characteristics. 

. Estimating medication persistency using administrative claims data. 

. Prevalence of selected chronic diseases in Israel. 

21. Downs JR, Clearfield M,Weis S, et al, and Air Force/Texas Coronary Atherosclerosis Prevention Study

. Primary prevention of acute coronary events with lovastatin in men and women with average cholesterol levels: results of AFCAPS/TexCAPS. 

23. Kaplan RC, Bhalodkar NC, Brown EJ Jr, White J, Brown DL

. Race, ethnicity, and sociocultural characteristics predict noncompliance with lipid-lowering medications. 

25. Grant RW, O'Leary KM, Weilburg JB, Singer DE, Meigs JB

. Impact of concurrent medication use on statin adherence and refill persistence. 

POLICY

Adherence with statins over 8 years among members of Israel's largest HMO was found to be poor, especially among new immigrants.

Adherence With Statins Over 8 Years in a Usual Care Setting

Self-management of chronic disease is crucial for optimal health. In the March 2008 issue, Tunis and Minshall evaluated the cost-effectiveness of self-monitoring of blood glucose (SMBG) in patients with type 2 diabetes on oral diabetes medicines.

 They concluded that self-monitoring is a good value, with costs per quality-adjusted life-year (QALY) below $30,000 even over horizons as short as 5 years.

Patients&#8217; time is essential for medical care, especially self-management. The Panel on Cost-Effectiveness in Health and Medicine recommended that patients&#8217; time be recognized as a cost in cost-effectiveness analysis,2 but it rarely is and Tunis and Minshall did not include it. Often the stated reason is lack of data, but a published estimate of the time required for SMBG, made by a group of diabetes educators, is available: 3 minutes per monitoring episode for experienced patients with type 2 diabetes controlled by oral agents,3 likely a conservative estimate for Tunis and Minshall&#8217;s &#8220;new users.&#8221; Three minutes does not sound like much, but repeated daily for a year it amounts to 18.25 hours, which, valued at the average 2006 hourly wage in private nonagricultural industry ($16.76),4 is $306 per patient per year. Self-monitoring 3 times daily requires time worth $918 per patient per year.

We used these values to recalculate the incremental cost-effectiveness ratios Tunis and Minshall reported for their 3 time horizons: 40 years/lifetime, 5 years, and 10 years (see the 

). We used the same 3% discount rate and conservatively assumed that 95% of the remaining cohort survived each year, a rate consistent with the validation of the CORE model used by Palmer et al in Figure 7 of their article.

The incremental cost-effectiveness ratios are much higher when patients&#8217; time is included. The increases are greatest for the shorter time horizons that may be of most interest to providers. For example, Tunis and Minshall estimated that, over a 5-year horizon, self-monitoring once daily would cost $23,380 per QALY gained. When patients&#8217; time is included, that cost rises to $76,340 per QALY gained.

Some may think the average wage is not appropriate for these patients, many of whom are retired, but retired people still value their time and have other uses for it. The average wage allows us to gain an appreciation for the magnitude of patients&#8217; time relative to the other resources required for self-monitoring. How individual patients respond to the time required will depend on their own valuation of their time; some may value it less highly than the average wage, others more highly. Note that the time valuation does not include the effort required to schedule being near the SMBG equipment at the right times, especially important when patients test 3 times daily.

We suggest that providers may want to consider the time requirements of self-management activities to better understand when and why patients follow their advice, and when and why they do not. Time is very much a cost to patients and influences their willingness and ability to comply with self-management recommendations with the regularity required to achieve the best results. The recalculated results show that it is a substantial cost.

Institute for Health, Health Care Policy, & Aging Research

.Time requirements for diabetes self-management: too much for many? 

. Validation of the CORE diabetes model against epidemiological and clinical studies. 

The Importance of Recognizing Patients' Time as a Cost of Self-Management

: To examine the current state of quality monitoring and management activities of US health plans.

: We surveyed medical directors of 252 commercial HMOs (96% response rate) drawn from 41 nationally representative markets in the United States. We randomly sampled healthcare markets with at least 100,000 HMO enrollees. The markets in our sampling frame include an estimated 91% of US HMO enrollees and represent 78% of the metropolitan population.

: There was near-universal collection of data at the health plan level for each of the 7 outpatient measures we examined (ranging from 92.1% of health plans that collect data on hypertension control and cholesterol management (see p. 379) to 99.2% that collect data on patient satisfaction). There also was substantial data collection at the level of the individual provider or physician group (ranging from 50.4% for hypertension control to 81.4% for diabetes care); this was more common in health plans that primarily use capitation to reimburse primary care physicians. Health plans that collected data typically fed these data back to physician groups, but public reporting to enrollees was infrequent.

: Almost all health plans measured their performance on multiple indicators of quality. The majority of health plans also collected data at the level of the individual physician or group and used these data in quality improvement activities, but not in public reporting. Thus, adoption of physicianlevel performance measurement and reporting by the Centers for Medicare & Medicaid Services will likely entail a major change for individual physicians.

This survey of a nationally representative sample of HMOs indicated that almost all health plans measure their performance on multiple indicators of quality.

The majority of health plans collect data at the level of the individual physician or group and use these data in quality improvement activities, but not in public reporting. 

Collection and use of performance data are more prevalent among health plans that predominantly use capitation.

These findings document the substantial changes health plans have made in data collection and quality management, and foreshadow the controversy ahead as we likely move to broad-scale public reporting on individual physicians.

The spread of capitation within the managed care sector during the early 1990s intensified concerns about quality of care as a major potential problem for the US healthcare system.

 Until that point, the vast majority of US physicians had been compensated using fee-for-service (FFS) payments, which, if anything, were believed to lead to overprovision of services.

 Under capitation, however, physicians and other providers of care had financial incentives to provide fewer services, leading to fears that physicians would skimp on care.

 These concerns contributed to the development and promulgation of the multiple quality measures and measurement activities that are common today.

Over the past 15 years, quality monitoring has become commonplace, and there has been increased interest in harnessing the organizational capabilities of health plans and hospitals to improve the quality of care.

 Most organizational efforts have included systematic collection and examination of clinical data, and use a variety of strategies such as physician and/or patient education, physician- and patient-specific feedback, public release of data, and financial incentives designed to improve adherence with accepted standards of care. Managed care plans occupy a unique place within the healthcare system, affording them the opportunity to access a variety of clinical and financial data that can be used in quality improvement activities.

Despite the importance of organizational efforts to monitor and improve quality of care, few data exist that describe the actual quality management practices of health plans.

The data that do exist are a decade old. In the interim, there have been tremendous advances in information systems and other electronic capabilities that can enhance the capacity of health plans to engage in medical management activities. In this study we examined the current state of quality management activities of a nationally representative sample of commercial HMOs, particularly those activities related to the collection and use of clinical data. We hypothesized that health plans that primarily use capitation rather than FFS to compensate primary care physicians (PCPs) would have more highly developed quality management programs.

We conducted a survey of a national sample of HMOs about their quality management activities (hereafter, we interchangeably use the terms &#8220;health plan&#8221; and HMO). We chose to focus on HMOs because among all types of health plans, they have the most advanced quality management infrastructure. There are currently more than 70 million enrollees in HMOs nationally.

 We estimated the prevalence of specific quality management activities using a set of representative quality indicators related to chronic disease management and prevention selected from the Health Plan Employers Data and Information Set (HEDIS). We previously reported on a subset of these data that focus on pay for performance (P4P).

The survey instrument elicited information related to the organizational characteristics of the health plan, its products and purchaser contracts, provider contracting, quality improvement activities, and &#8220;member-centric&#8221; health improvement efforts. Unless otherwise noted below, the frame of reference for the survey was 2005. Cognitive testing of a draft instrument was conducted with 5 health plans that were not in our sample prior to finalizing the questionnaire.

We first elicited information about the numbers of enrollees in the sampled market, the use of primary care gatekeeping, accreditation by the National Committee for Quality Assurance (NCQA), and ownership (for profit, not for profit). Next, we asked about the degree to which the plan relied on salary, capitation, and FFS payment for compensating PCP services. We were not able to distinguish between primary care payment arrangements with organizational entities such as large medical groups versus those with individual physicians, so individual physicians belonging to large medical groups might not be paid directly by capitation payments  themselves in instances when the health plan used capitation payments for PCP services.

We then asked a series of questions about data collection programs at the level of the health plan as a whole, as well as at the level of physicians or groups of physicians within the plan. For these questions, we selected 7 tracer measures from HEDIS in the areas of patient satisfaction (1 measure), prevention (1 measure), mental health (1 measure), and other chronic disease management (4 measures) that we thought would be most important to an employed population. The measures were patient satisfaction, breast cancer screening, antidepressant medication management, hypertension control, use of appropriate medications for asthma, comprehensive diabetes care (including assessment and control of glycosylated hemoglobin, cholesterol assessment and control, retinal eye exams, and nephropathy screening), and cholesterol management after heart disease (defined as achieving a low-density lipoprotein cholesterol level <100 mg/dL). For ease of presentation, we focused our presentation of regression analyses on 4 of these measures, including 1 each in the areas of satisfaction, prevention, mental health, and other chronic disease management. The results for the other 3 quality indicators were qualitatively similar.

At the health plan level, we asked if the plan collected information on the measure, used the information obtained to target quality improvement efforts, or had demonstrated improvements in quality. At the physician/group level, we asked if the plan collected information, provided this information to the physicians/groups, used the information in a report card for enrollees, or used the information in a P4P program. We also inquired into 2 patient-specific uses of data: whether the plan sent patient-specific feedback to the responsible physician and whether the plan sent specific reminders directly to patients (eg, for a flu shot).

Finally, we also elicited information on the collection and use of hospital performance data. For these questions, we inquired into the collection of data regarding the Leapfrog standards (eg, intensive-care&#8211;unit staffing, physician order entry, procedure volume),

 National Quality Forum Safe Practices, Joint Commission on the Accreditation of Healthcare Organizations core measures,

 nurse staffing ratios, complication rates,

 We then asked whether these data were used to define hospital tiers (eg, with varying copayment levels) or to provide increased payments.

Among 309 health plans we initially identified, 57 were found to be ineligible because they no longer offered a commercial HMO product in the relevant market (n = 36), had closed entirely (n = 11), or were duplicates (n = 10). Of the 252 eligible plans, 242 completed the survey (96% response rate). The overall item response rate was more than 90%.

Of the 242 health plans, 77 (32%) primarily compensated PCPs via some form of capitation, and the remainder used FFS (63%) or salary (5%) (

). Capitated and salary plans were more commonly located in the West (53% and 42%, respectively, compared with 16% of FFS plans; overall P <.001) and less commonly located in the South (17% and 25%, respectively, compared with 42% of FFS plans; overall 

 = .015). The vast majority of plans were network or IPA model plans, and about two thirds were for profit. Most health plans required the use of a gatekeeper.

Although not as universal as at the health plan level, substantial data collection activities also were reported at the level of individual providers or physician group, ranging from a low of 50.4% for hypertension control to 81.4% for diabetes care. Moreover, most health plans that collected individuallevel or group-level data also fed these data back for use by the physicians or physician organizations in their quality improvement efforts. Fewer health plans used these measures in P4P programs. The most frequently used measure in P4P programs was diabetes care (used by 40.5% of plans), whereas relatively few plans used the hypertension control or antidepressant medication management measures in this way (14.5% and 17.4%, respectively). Twenty-five percent or fewer of the health plans reported data to enrollees in report cards (ranging from 13.6% for antidepressant medication management to 25.2% for diabetes care).

Collection and Use of Hospital Performance Data

Most health plans collected a variety of performance data about hospitals in their network, including 76.4% that examined data on standards promulgated by the Leapfrog group and 63.6% that examined data from the Hospital Quality Alliance (

). Few health plans used these data to define hospital tiers with differential copayments or to provide extra payments to hospitals. For instance, approximately 20% of health plans used any hospital performance data to provide extra payments to hospitals and slightly fewer used these data to define hospital tiers.

Data Collection and Use in Capitated and Fee-for-Service Health Plans

), there were relatively few differences in the collection and use of performance indicators between capitated and FFS health plans in both unadjusted and adjusted analyses. In general, capitated plans almost universally collected data on performance measures in each domain (100% for all measures except antidepressant medication management) and targeted these measures for improvement. Although FFS plans collected data almost as frequently, the measures were targeted for improvement less frequently. For instance, in adjusted analyses, although 98.8% of FFS plans collected satisfaction data, 90.2% targeted this measure for improvement, compared with 99.0% of capitated plans that targeted this measure for improvement (

 = .03). In unadjusted analyses, capitated health plans reported more success in actually improving care. These differences were no longer significant after adjustment for other health plan characteristics.

Use of Patient-Level Data Health plans also used their data to remind patients about needed care and to provide patient-specific reminders for physicians (

). Both capitated and FFS health plans commonly reported sending patient reminders, with rates of about 90% for mammography and diabetes care reminders. Physician reminders, although also common, were used somewhat more frequently by capitated health plans than by FFS health plans.

. Contractual arrangements between HMOs and primary care physicians: three-tiered HMOs and risk pools. 

4. Pauly M, Eisenberg J, Radany M, Erder M, Feldman R, Schwartz J.

Paying Physicians: Options for Controlling Cost, Volume, and Intensity of Services

. Ann Arbor, MI: Health Administration Press; 1992. 

6. US Department of Health and Human Services

. Hospital Compare: a quality tool for adults, including people with Medicare. 

8. National Committee for Quality Assurance (NCQA).

10. Newhouse J, Buchanan J, Bailit H, et al

. Does managed care mean more hassle for physicians? 

14. The Henry J. Kaiser Family Foundation

. State health facts: total HMO enrollment, July 2006. 

http://www.statehealthfacts.org/comparemaptable.jsp?ind=348&cat=7

16. US Census Bureau. Census 2000 summary file 1

http://www.census.gov/Press-Release/www/2001/sumfile1.html

http://www.leapfroggroup.org/for_hospitals/leapfrog_hospital_quality_and_safety_survey_copy/leapfrog_safety_practices

. Relationship between Medicareâ€™s Hospital Compare performance measures and mortality rates. 

22. Fisher E,Wennberg D, Stukel T, Gottieb D, Lucas F, Pinder E

. The implications of regional variations in Medicare spending, part 1: the content, quality, and accessibility of care. 

26. Centers for Medicare and Medicaid Services

http://www.medicare.gov/MPPF/Include/DataSection/Questions/Welcome.asp?version=default&browser=Firefox%7C1%7CW

27. Centers for Medicare and Medicaid Serv

http://www.cms.hhs.gov/HospitalQualityInits/

29. Landon B, Normand S, Blumenthal D, Daley J

. Physician clinical performance assessment: prospects and barriers. 

31. Rosenthal M, Frank R, Buchanan J, Epstein A

. Scale and structure of capitated physician organizations in California. 

This survey of 252 HMOs found that almost all measure their performance on multiple indicators of quality and most use these data in quality improvement activities.

Quality Monitoring and Management in Commercial Health Plans

: To examine the extent to which numeracy predicts consumer-directed health plan (CDHP) comprehension and health plan choice. Also, to test whether comprehension can be improved using different presentation approaches.

: We conducted an experimental laboratory study in which 303 adults viewed information about a hypothetical CDHP and a hypothetical preferred provider organization (PPO) presented in several different ways. Participants were randomized to view plan comparisons in a side-by-side or a common/unique format, and whether or not to view a framework.

: Participants completed a survey that included comprehension items, numeracy and literacy assessments, and sociodemographics. Multivariate regression models were developed to examine the independent effects of numeracy and presentation approach on CDHP comprehension and choice. Interactions between numeracy and presentation approaches were tested.

: Although less numerate consumers understood less about CDHPs, they were substantially more likely to select the CDHP. Providing an overarching framework to highlight the differences between the CDHP and PPO boosted comprehension on items related to the framework message. However, it reduced comprehension on items that were not related to the framework, particularly among the less numerate. Participants reported that the common/unique presentation of comparative information was easier to understand, yet there was a trend toward less comprehension using that presentation approach.

: This study highlights the difficulty many consumers have in understanding comparative plan information and in making informed healthcare choices. Findings also indicate that some presentation strategies may help the less skilled understand choices better.

Comparing consumer-directed health plans with preferred provider organizations is challenging for consumers, particularly those with low numeracy skills. These findings highlight the complexity of supporting informed choices among consumers and the need to develop and test presentation formats.

Frameworks that emphasize key conceptual information can improve comprehension across numeracy levels. However, frameworks should be used cautiously, because they may result in reduced comprehension of information not included in the framework.

Information providers should not rely on consumersâ€™ assessment of how easy information is to understand, as this assessment is not necessarily predictive of comprehension.

Consumer-directed health plans (CDHPs), which were introduced in 2000, enrolled 10% of covered employees in 2007.

 CDHPs are high-deductible health plans with an accompanying savings account. They were designed to provide enrollees with financial incentives to contain their own healthcare costs. Enrollees in CDHPs pay for their medical care with account funds or out of their own pocket until they reach the deductible level, at which point standard insurance coverage begins.

With greater exposure to healthcare costs, CDHP enrollees are expected to make more cost-effective healthcare choices, like comparison shopping for healthcare and reducing unnecessary medical care visits. Unspent funds in the savings account may be rolled over for use in future years, providing an incentive to conserve on healthcare. Because CDHPs typically have lower premiums than traditional insurance,

 some policymakers view them as a vehicle for reducing the number of uninsured.

 Medicaid agencies also are starting to pilot a version of CDHPs with low out-of-pocket costs, called Health Opportunity Accounts.

Critics have raised a number of concerns over CDHPs. These include the plans&#8217; complexity, the potential for consumers to cut back on &#8220;essential&#8221; medical services, their role in segmenting the risk pool, and the fact that CDHPs are not designed to reduce healthcare costs for those with the highest utilization.

 Some have raised the question of how vulnerable populations, such as low-income persons and racial minorities, will fare with CDHPs, due to their having less discretionary income, lower literacy skills, and more limited access to Internet-based information.

This paper focuses on consumers&#8217; understanding of CDHP design among a largely low-income population. Because CDHPs potentially require greater out-of-pocket spending than traditional health insurance, it is important for consumers to understand differences in plan design when selecting health plans. CDHPs also are more complex than other forms of health insurance once consumers are enrolled. Depending on enrollees&#8217; needs for healthcare, they may experience up to 4 different stages of coverage within a CDHP. In the first stage, consumers can pay for healthcare costs using the savings account (or they may opt to save the account funds for the future by paying out-of-pocket). In the second stage, which occurs if the account is exhausted, healthcare costs are not covered and must be paid out-of-pocket. In the third stage, once the high deductible is met (typically $1500-$2000 for individuals),

 healthcare costs are covered by a health plan with cost-sharing. Finally, in the fourth stage, if an out-of-pocket maximum is reached, all healthcare costs are covered by the health plan. Enrollees are expected to use informational resources to make cost-effective decisions. This complexity may be more difficult for consumers with lower education and numeracy levels.

To date, little research has examined consumers&#8217; understanding of CDHPs. One study found that fewer than half of enrollees in a CDHP said they knew &#8220;a lot&#8221; about the plan prior to enrollment, though CDHP enrollees reported being more knowledgeable than those not selecting the CDHP.

 Another study found that the CDHP plan selection process differed considerably between salaried and hourly employees.

 Although some salaried employees described using computer spreadsheet programs to compare likely out-of-pocket costs in preferred provider organizations (PPOs) and CDHPs prior to enrollment, hourly enrollees more often described confusion about selecting the plan and how CDHPs work.

Two bodies of literature are related to the question of consumers&#8217; understanding of CDHPs. The first focuses on consumer literacy (reading skills) and numeracy (numeric literacy). In the United States, many more people have low literacy and numeracy skills than in other industrialized countries.

 Based on the National Assessment of Adult Literacy, only 13% of Americans have the skills to comprehend lengthy prose or to synthesize multiple pieces of information in complex documents.

 We hypothesized that these skills, in particular numeracy, will be predictive of understanding the differences between CDHPs and conventional health plans. Prior research has found that literacy, numeracy, or a measure of health literacy combining the 2 are positively associated with similar types of health-related tasks, including consumers&#8217; ability to extract quality information from comparative tables and confidence in making health coverage decisions.

Emerging literature has sought to improve consumer comprehension and informed decision making by simplifying the presentation of comparative information. Experimental studies have documented that simpler displays of information&#8212; those containing less information and that require less synthesis&#8212;are in general easier for consumers to comprehend. A recent study, for example, found that when consumers were provided with quality indicators along with hospital characteristics (eg, the number of hospital beds), only 40% selected the highest-quality hospital. However, when only quality indicators were provided, simplifying the data display and reducing the number of factors to consider, 62% of consumers selected the highest-performing hospitals.

 Two other techniques to simplify information presentation (listing health providers by quality rankings rather than alphabetically, and framing indicators so that higher numeric scores indicate better performance) also substantially improved comprehension and informed decision making.

There is evidence that information presentation may not have the same influence on all consumers. Peters and colleagues found that using a traffic light symbol helped highly numerate consumers select better-quality hospitals. However, it reduced the ability of less numerate consumers to select the best-quality hospital.

 The present study  builds upon this emerging area of study.

This study&#8217;s first goal was to examine the effect of numeracy on comprehension of CDHP design and informed decision making among a largely low-income population. The second goal was to test whether comprehension could be improved by varying the way the information was presented. We randomized consumers to view different presentations of the same comparative plan information to test the impact of presentation across all respondents and for those with high and low numeracy skills.

We first tested whether presenting common/unique plan attributes influenced comprehension and decision making compared with listing plan attributes side by side. Our hypothesis was that the common/unique presentation approach would require consumers to synthesize less information, and therefore would result in higher comprehension levels across all levels of ability.

We also tested the influence on comprehension and decision making of a framework that details the advantages and disadvantages of a CDHP relative to a conventional PPO. Educational theory suggests that if we provide consumers with a framework for understanding a concept or the &#8220;big ideas,&#8221; they will be more likely to understand the &#8220;little ideas&#8221; and integrate new pieces of information into the framework.

 Because using a framework increases the amount of information that is presented, which may be difficult for those with lower numeracy skills, we opted to test longer and shorter versions of the framework.

To test these questions, we used an experimental study design with a convenience sample of 303 adults age 18-64 years in Oregon. To ensure variation in numeracy and literacy skills, we recruited our sample so that approximately half of the participants would have lower levels of education (a high school diploma or less). Participants were randomly assigned to view 1 of the following 6 formats comparing the same 2 hypothetical health plans:

1. Long framework, information side by side.

3. No framework, information side by side.

5. Short framework, common/unique information.

2. Which plan is better for a person who needs very little healthcare?

4. How much would it cost with Plan B to go to an urgent care facility?

6. What would be the out-of-pocket maximum cost per year for a single person with individual coverage under Plan B?

Each question was followed by 2-4 response options, one of which was correct. For some analyses, we also used 2 subindices of comprehension: one that included the 3 questions that directly related to the key framework messages (questions 1-3), and one that included questions that did not directly relate to the framework information (questions 4-6).

The plan choice question asked participants which plan they would be more likely to choose for themselves. The easeof- understanding question asked participants to self-report &#8220;how easy or difficult it was to understand the information about the 2 health plans&#8221; using a 7-point scale (&#8211;3 = very difficult to +3 = very easy).

All participants completed numeracy and literacy assessments. The numeracy assessment included the 11 items from Lipkus and colleagues,

This study highlights the difficulty many consumers have in understanding comparative plan information. It also suggests that presentation strategies may help consumers understand choices better.

June 2008

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