 To verify the gastroprotective agent (GPA) rate assumption used in cost-effectiveness models for cyclo-oxygenase 2 inhibitors (COX-2s) and to re-estimate model outcomes using GPA rates from actual practice.

 Prescription and medical claims data obtained from January 1, 1999, through May 31, 2001, from a large preferred provider organization in the Midwest, were used to estimate GPA rates within 3 groups of patients aged at least 18 years who were new to nonselective nonsteroidal anti-inflammatory drugs (NSAIDs) and COX-2 therapy: all new NSAID users, new NSAID users with a diagnosis of rheumatoid arthritis (RA) or osteoarthritis (OA), and a matched cohort of new NSAID users.

 Of the more than 319 000 members with at least 1 day of eligibility, 1900 met the study inclusion criteria for new NSAID users, 289 had a diagnosis of OA or RA, and 1232 were included in the matched cohort. Gastroprotective agent estimates for nonselective NSAID and COX-2 users were consistent across all 3 samples (all new NSAID users, new NSAID users with a diagnosis of OA or RA, and the matched cohort), with COX-2 GPA rates of 22%, 21%, and 20%, and nonselective NSAID GPA rates of 15%, 15%, and 18%, respectively. Re-estimation of the cost-effectiveness model increased the cost per year of life saved for COX-2s from $18 614 to more than $100 000.

 Contrary to COX-2 cost-effectiveness model assumptions, the rate of GPA use is positive and marginally higher among COX-2 users than among nonselective NSAID users. These findings call into question the use of expert opinion in estimating practice pattern model inputs prior to a product's use in clinical practice. A re-evaluation of COX-2 cost-effectiveness models is warranted. 

Decision makers have said that for pharmacoeconomic information to be useful it should, among other things, be presented in a timely manner, include head-to-head comparisons with relevant comparators, and consist of reliable data.

 The dilemma for researchers is that meeting all of these criteria is practically impossible. If the pharmacoeconomic information is to be presented in a timely manner, typically when a product comes to market, often the only available data come from the randomized controlled trials used to establish safety and efficacy of the product compared with placebo. At the time of product launch, studies comparing the new product with existing similar products are rarely available. Another difficulty faced by researchers is that data important to the economic evaluation of the therapy may not be available at the time of product launch, such as practice patterns reflecting real-world use, costs, resource utilization, and utilities. To provide decision makers with information in a timely manner, including use of relevant comparators, researchers utilize decision analysis techniques, relying on the best data available for model inputs. When such data are not available, expert opinion and consensus are often used to obtain estimates.

 Rarely, however, are these assumptions verified once actual practice data become available. 

A case in point is cost-effectiveness evaluations of cyclo-oxygenase 2 inhibitor (COX-2) therapy. Both nonselective nonsteroidal anti-inflammatory drugs (NSAIDs) and COX-2s are equally effective in treating pain. However, nonselective NSAIDs have a significantly higher rate of gastrointestinal (GI) adverse events. To reduce the risk of GI adverse events with NSAIDs, several guidelines have recommended that physicians co-prescribe gastroprotective agents (GPAs), such as proton pump inhibitors (PPIs) or misoprostol to those patients at high risk of adverse GI events.

 Given the cost associated with GPA use and the extent of GPA co-prescribing among nonselective NSAID users, estimated to be from 17% to 34%,

 failure to include these costs in economic evaluations of these products could underestimate the true cost of NSAID therapy.

Cost-effectiveness models comparing COX-2s with nonselective NSAIDs have been published for celecoxib

 Because no differences have been noted between the efficacy of nonselective NSAIDs and that of COX-2s, these studies evaluated whether the added cost of COX-2 therapy is worth the benefit gained through reductions in GI adverse events among arthritis patients. These models have all concluded that COX- 2s provide cost savings or that the benefits gained, in terms of years of life saved, is worth the added cost. Each study made use of decision analysis, but differed in study methods, inclusion of model inputs, perspectives, patient populations (i.e., patients diagnosed with osteoarthritis [OA] or rheumatoid arthritis [RA]), treatment alternatives, and decision pathways (

). Each model assumed that a proportion of nonselective NSAID users would be prescribed a GPA. Because no empirical data were available at the time the studies were conducted to estimate the GPA rate among those on COX-2 therapy, and given clinical trial evidence supporting a more favorable GI side effect profile with COX-2s, all models assumed that the need for GPAs would be reduced or completely eliminated for COX-2 users. 

In 3 cost-effectiveness studies of rofecoxib (Vioxx), based on usage patterns in the United Kingdom,

 the authors use published estimates of GPA rates for nonselective NSAIDs of 20%, 23%, and 25.5%, respectively. Estimates of the GPA rate for patients treated with rofecoxib were derived from an expert panel in 2 of the studies.

 The expert panel, comprising gastroenterologists, rheumatologists, and general practitioners, estimated the GPA co-medication rate for rofecoxib to be 75% less than the base rate for nonselective NSAIDs. In the Canadian study,

 the GPA rate was assumed to be 90% less than the nonselective NSAID rate, or 2.3%. No explanation was given as to how researchers arrived at this estimate. All rofecoxib models tested model sensitivity to variation in the base case GPA rate for nonselective NSAIDs and the percent reduction in GPA use for rofecoxib. In 2 of the 3 rofecoxib models,

results were sensitive to the GPA co-medication rate. 

In the arthritis cost consequence evaluation system (ACCES) model, developed to compare celecoxib (Celebrex) with nonselective NSAIDs, the costs and GI consequences of celecoxib use were compared against 5 nonselective NSAID therapy alternatives: nonselective NSAID monotherapy, nonselective NSAID plus a PPI, nonselective NSAID plus an H2 receptor antagonist (H2), nonselective NSAID plus misoprostol, and Arthrotec, a combination product containing diclofenac sodium and misoprostol.

 The ACCES model assumed no GPA co-medication with celecoxib. The model allows for variation in the overall GPA rate for nonselective NSAIDs depending on the sample population being modeled. For example, in an application of the model using Norwegian data, the distribution of nonselective NSAID patients included 20% taking a nonselective NSAID plus a PPI, 15% taking a nonselective NSAID plus H2, and 10% taking Arthrotec.

In another cost-effectiveness model evaluating celecoxib, the assumption was again a zero GPA rate among celecoxib users.

 No discussion was provided in any of the celecoxib models as to why a 0% GPA rate assumption was made. In addition, model sensitivity to variation in nonselective NSAID GPA rates was not evaluated. 

Given evidence of model sensitivity to the GPA assumption, the use of expert opinion to estimate COX-2 GPA rates (when estimated), lack of documentation to support a 0% COX-2 GPA rate assumption and evidence contrary to these assumptions,

 and the high cost of GPA therapy relative to NSAIDs, the purpose of this study was to verify this assumption using actual practice data. We also replicated the COX-2 cost-effectiveness model developed by Pellissier and colleagues

 to re-estimate model outcomes based on observed GPA rates. We selected this model because it is the only COX-2 cost-effectiveness model to represent a US perspective, which was the perspective of our analysis. 

Pharmacy and medical claims data for a 320,000- member preferred provider organization located in the Midwest were used to identify new NSAID users. The pharmacy benefit design for plan members varied; however, more than 90% of sample members had a 3-tier benefit structure with first-tier co-pays ranging from $8 to $10, second-tier co-pays from $15 to $20, and third-tier co-pays from $25 to $30. Cyclo-oxygenase 2 inhibitors were on the third tier, and no other restrictions regarding their use were in place during the time of evaluation (i.e., step therapy or prior approval). New NSAID users were defined as individuals with an NSAID claim within an index window from January 1, 2000, through May 31, 2000, and with no NSAID claim in the previous 12 months. Other inclusion criteria were that the individuals obtained a supply for 30 days or more for an NSAID during the 1-year follow-up; were at least 18 years of age; and were continuously eligible for the entire study period. Patients taking disease-modifying agents (i.e., methotrexate, gold compounds) during the 1-year follow-up were excluded due to indications of greater disease severity. 

From the first NSAID claim in the index window (i.e., index prescription), patients' prescription claim activity was followed for 365 days. Use of NSAIDs was identified from the generic product identifier (GPI; First Databank [Medispan], Indianapolis, Ind.) number beginning "661000" (nonselective NSAID) or "661005" (COX-2). Gastroprotective agent usage was identified using the GPI code for H2 receptor antagonists (GPI beginning "4920"), PPIs (GPI beginning "4927"), misoprostol (GPI beginning "4925"), sucralfate (GPI beginning "4930"), and ulcer therapy combinations (e.g., ulcer anti-infective with bismuth combinations or PPIs, or H2 antagonists-antacid combinations, GPI beginning "4999"). Gastroprotective agent usage was defined as use of any of the above-listed agents on 1 or more days during the 365-day follow-up. 

Three GPA rates were estimated-one for new NSAID users regardless of diagnoses, the second among new NSAID users with a diagnosis of RA or OA, and the third among a cohort of new NSAID users matched for GI risk and length of NSAID therapy. The matched cohort was included to control for differences in the GI risk across COX-2 and nonselective NSAID users, due to recent findings indicating channeling of patients at risk for GI events to COX-2s.

 Matching for GI risk was based on the Standardized Calculator Of Risk for Events (SCORE) criteria. Although not a fully validated instrument, SCORE is a self-assessment instrument to quantify the risk of serious NSAID-related GI toxicity (e.g., stomach ulcer or bleeding ulcer) and is based on 6 criteria: age, self-reported health status, diagnosis of RA, use of oral corticosteroids, hospitalization for a stomach or intestinal problem or prior history of stomach ulcer, and history of gastrointestinal side effects (heartburn, stomach pain, nausea, vomiting) when taking NSAIDs. SCORE was developed by researchers at Stanford University and based on data from the Arthritis, Rheumatism, and Aging Medical Information System (ARAMIS) database.

 ARAMIS is a database that has followed more than 36,000 patients with rheumatic diseases, collecting data on health status, clinical outcomes, drug side effects, and resource utilization. We selected the SCORE criteria because it was the only algorithm available to assess NSAID-induced GI risk that combined several documented risk factors into a single score for each individual, thereby adding a level of specificity beyond a simple "yes/no" indication of risk. 

Using medical and pharmacy claims data, a SCORE value was calculated for each patient using 5 of the 6 criteria, the exception being self-reported health status (

). Whereas SCORE was designed to be administered by patients or physicians, the estimation of SCORE criteria using medical and pharmacy claims data has been documented.

 For the SCORE criteria of GI side effects when taking NSAIDs, a proxy was used. We chose this method because the study criteria excluded individuals with prior use of NSAID therapy and because prior use of NSAID therapy could have occurred earlier than 365 days before the index prescription. This proxy measure included a diagnosis of any of the following conditions: gastritis, esophagitis, ulcer-related symptoms (i.e., dyspepsia), gastroesophageal reflux disease (GERD) damage, and GERD-related symptoms. Using the scoring algorithm for the 5 SCORE criteria, a summed value was generated for each member of the sample. Values could range from 0 to a maximum of 35. 

Nonselective NSAID and COX-2 users were also matched for length of NSAID use, with length of therapy calculated as the summed value of the days supply field from the index prescription 365 days forward. Length of NSAID therapy was included as a match criterion due to findings of significantly greater length of therapy for individuals whose index prescription was a COX-2 and the likelihood that this would inflate the GPA rate among COX-2 users. For matching purposes, days supply was categorized into 20th percentiles. 

Results are presented by the pattern of switching between selective and nonselective NSAIDs during the 365 days of follow-up (i.e., COX-2 users only, nonselective NSAID users only, switch from nonselective NSAID to COX-2, and switch from COX-2 to nonselective NSAID). 

We replicated the cost-effectiveness model of Pellissier and colleagues

 using Microsoft Excel 97. The COX-2 and nonselective NSAID GPA rates from this study were then used to re-estimate the cost per day of therapy, the cost offset per day, cost per GI event avoided, and cost per year of life saved. The only input not provided by Pellissier was the market share of the individual GPA agents. Requests for this information were made but not obtained. Therefore, using our own data as a reference point, we modified market share values slightly until we were able to exactly replicate Pellissier's cost offset per day. The market share used to replicate Pellissier's model was 74% omeprazole, 5% misoprostol, and 21% H2s. Finally, several sensitivity analyses were conducted to evaluate the robustness of our results to variations in other model assumptions in addition to GPA rate assumptions. The first involved using actual days supply of GPA and NSAID therapy rather than full compliance, as assumed by Pellissier. The second varied which GPA agents were included in the analysis.

A total of 319,263 members had at least 1 day of enrollment during the index window with 17,300 having an NSAID in the index window. A total of 9,611 members were excluded for non-continuous eligibility during the 29-month study period and 612 were excluded because they were younger than 18 years. An additional 3685 members were excluded because of prior NSAID use, and 25 were excluded due to use of disease-modifying agents. Finally, 1,467 members were excluded for having less than a 30-days' supply of NSAID during the 1-year follow-up. The final sample for the analysis of new NSAID users regardless of diagnosis was 1,900. From this sample, 1611 had no evidence of OA or RA in the 365 days prior to or 120 days after the index prescription, leaving a sample of 289 for the evaluation of new NSAID users with a diagnosis of OA or RA. Other diagnoses associated with the use of NSAIDs indicated many and varied musculoskeletal conditions (e.g., low back pain, 20.6%; joint pain, 9.7%; knee or other joint derangement, 7.4%; sprains and strains of joints and adjacent muscles, 3.2%; dysmenorrhea, <1%; etc) and other pain-related conditions (e.g., hospitalization, organ transplant, headache, etc). Approximately 26% had no documented condition that could be attributed to NSAID use. 

Finally, using the sample of 1,900 new NSAID users, 668 were excluded during the matching process for a final sample size of 1,232 for the matched cohort analysis (616 nonselective NSAID and 616 COX-2 users). 

presents the demographics and NSAID use pattern across the 3 samples. The average age of sample subjects was 47 years (SD = 12), with 57% female. This demographic profile was not significantly different across samples with respect to percent female (&#967;

= .618). However, Bonferroni paired comparison tests indicated significant differences in age across samples at the ¦Á = 0.01 level. The average SCORE value for the matched cohort was 8.5 (SD = 2.98). 

The pattern of use and switching among those who begin on nonselective NSAIDs and COX-2s varied across the 3 samples (Table 3). For the overall sample of new NSAID users (n = 1900), approximately 60% had as their index prescription a nonselective NSAID. Among those with a diagnosis of OA or RA (n = 289), the proportion with a COX-2 as their index prescription (51%) was significantly higher compared to the overall sample (&#967;

Across all 3 samples, from 18% to 19% of patients had evidence of GPA use during the 1-year follow-up. Across all 3 samples, the GPA rates for those who began therapy on a nonselective NSAID were lower compared with individuals who began with COX-2 therapy. However, these rates were significantly different only in the overall sample of NSAID users (15% vs. 22%, for nonselective NSAID vs. COX-2 users, respectively; &#967;

To evaluate whether GPA use began during the follow-up period or represented continuation of therapy, the date GPA therapy began relative to the index prescription was captured. Among persons with GPA use during the follow-up period, 70%, 77%, and 68% of those whose first prescription was a COX-2 had evidence of GPA therapy prior to beginning their COX-2, within the sample of total new NSAID users, OA/RA patients, and the matched cohort. These same percentages for those whose first prescription was a nonselective NSAID are 53%, 43%, and 54%, respectively. These rates of prior GPA use among GPA users in the follow-up period were all significantly different at the &#945; = 0.05 level (&#967;2 = 10.73, 

profiles the outcomes replicated using Pellissier's base case assumptions14 and re-estimated using GPA rates from our study sample. The model was exactly replicated for the outcomes of expected cost per day for nonselective NSAIDs and cost offset per day and estimated to within $0.01 for expected cost per day for rofecoxib. The model was replicated to within 4% for cost per perforation, ulceration, and bleeding (PUB) avoided and cost per year of life saved. We believe that an error in the calculation or reporting of cost per death avoided may have occurred in Pellissier's table contributing to the 11% difference in replicated estimates. 

The Pellissier model was re-estimated using GPA rates from the matched cohort, which had the smallest difference in GPA rates across nonselective NSAID and COX-2 users of 18% and 20%, respectively. Using these GPA rates, the base case expected costs per day for rofecoxib and nonselective NSAIDs were estimated to be $3.29 and $2.49, respectively. Separating these costs into NSAID drug cost and GI-related costs (i.e., GPA and other GI medical costs), the GI-related expected cost per day for rofecoxib increased from $0.44 to $0.87 and decreased for nonselective NSAIDs from $1.26 to $1.02. The difference in the GI-related costs between nonselective NSAIDs and rofecoxib represent the expected daily cost offset for rofecoxib. Pellissier's base case cost offset per day was estimated as $0.81, substantially higher than the $0.15 from the re-estimated model using GPA rates from actual practice. These findings are presented in the 

together with the Pellissier data, which tested model sensitivity to changes in the base case nonselective NSAID GPA rate and varied the GPA co-medication reduction with rofecoxib.

Using total cost estimates (i.e., NSAID drug costs and GI-related medical costs) for a cohort of 10,000 patients over 1 year, Pellissier estimated the cost per PUB avoided at $4,738 and the cost per death avoided at $274,749. Assuming a difference of 2 deaths due to GI adverse events between rofecoxib and nonselective NSAIDs, and a loss of 18.6 years for each death discounted at 3%, Pellissier estimated a cost per year of life saved for rofecoxib of $18,614. Re-estimating the model using GPA rates from actual practice increases the cost per PUB avoided to $29,636 and the cost per death avoided increases to approximately $1.5 million. Using the same assumptions regarding life years lost, the marginal cost per year of life saved for rofecoxib exceeds $100,000. 

Another assumption made by Pellissier that could not be confirmed from actual practice data was full compliance during the 1-year period. Using the matched cohort, the number of days on GPA therapy by index prescription was 35 and 28 days for COX-2 and nonselective NSAID users, respectively. The number of days on NSAID therapy by index prescription was 108 and 99 days for COX-2 and nonselective NSAID, respectively. Changing the number of days on GPA therapy in the model changed our original results only slightly, from a cost offset per day for COX-2s of $0.15 to $0.19; the cost per PUB avoided decreased to $27,850; the cost per death avoided decreased to $1,392,508; and cost per year of life saved decreased by less than $5,000 to $101,323. The results were more favorable for COX-2s even though the days on GPA for COX-2s are greater. This result is because GPA costs represent a larger proportion of total GI-related costs for COX-2s than for nonselective NSAIDs. When both days on nonselective NSAID and GPA therapy are modified using actual practice data, the cost per year of life saved for COX-2s increased to more than $200,000 per year of life gained. 

We also varied the inclusion of specific GPA agents. Our initial choice of GPA agents was based on the agents used by Pellissier. Re-estimating GPA rates excluding H2s decreased the GPA rate within the matched cohort to 14% and 11%, respectively, for COX-2 and nonselective NSAID users. Using these GPA rates, the cost offset per day for COX-2s decreased slightly from our base estimates of $0.15 to $0.13; the cost per PUB avoided increased to $29,783; the cost per death avoided increased to $1,489,135; and the cost per year of life saved increased to $108,354. 

This study failed to verify the GPA co-medication rate assumption made in COX-2 cost-effectiveness studies. Contrary to estimates provided by expert opinion and assumptions made by study authors, the GPA rate among COX-2 users is positive and marginally higher than the rate among nonselective NSAID users. Using the GPA estimates from our sample to re-estimate Pellissier's model, the cost per year of life saved goes beyond that considered economically acceptable using the threshold of $50,000/year. 

Recent findings would appear to provide support for this conclusion.

 In a study comparing the effect of a drug policy restricting and not restricting use of COX-2 therapy among long-term NSAID users, researchers found an incremental cost of $31,900 and $56,700 for the nonrestrictive versus restrictive policy in preventing symptomatic and complicated ulcers, respectively. This incremental cost is greater than the incremental cost to prevent PUB in our replicated model ($29,188). At this rate, the cost per life year gained would likely fall outside of the accepted threshold, as it did in our estimates. 

Several study limitations may limit generalizability of the study findings. The data represent only one plan's experience, and GPA prescribing patterns could vary depending on numerous factors including physician practice style and plan design. In estimating the GPA rate, we fully recognize the limitations in using medical claims data to identify specific diagnoses, such as that used in the matching process.

 Prior history of NSAID-related GI risk or diagnoses may have been missed because of undercoding. This can be due to lack of documentation or the fact that these diagnoses were secondary to other conditions for which the patient was being seen and not captured in the primary, secondary, or tertiary ICD-9 fields. Additionally, the time during which we evaluated individual history of GI events was limited to 365 days. A GI event could have occurred prior to this look-back period. While we recognize these factors as limitations in the matching of patients using the SCORE method, results were consistent regardless of the sample used. In addition, because calculation of the GPA rate relied primarily on prescription claims data, which studies have shown to be a reliable and valid source of data,

 we believe that these limitations are minimized with respect to GPA estimates. 

Gastroprotective agent estimates in this study did not include use of over-the-counter (OTC) GPA agents, including OTC H2 receptor antagonists or antacids, as other estimates have.

 Failure to capture OTC GPA usage may underestimate the true GPA rate among NSAID users. However, OTC use typically would not be used in economic evaluations conducted from a third-party payer perspective. 

These findings call into question the use of expert opinion in estimating model inputs for pharmacoeconomic evaluation, particularly when estimating practice patterns prior to the product's use in a real world setting. When compared with clinical trial data documenting GI adverse events associated with use of COX- 2s and nonselective NSAIDs, these assumptions fail even the most basic test of validity, face validity. Two large trials have compared the risk of gastrointestinal complications between COX-2s and nonselective NSAIDs, the Vioxx Gastrointestinal Outcomes Research (VIGOR) trial and the Celecoxib Long-Term Arthritis Safety Study (CLASS) trial.

 In the VIGOR trial, the incidence of complicated confirmed upper GI events was 1.22% in the naproxen group and 0.52% in the rofecoxib group (

< .005). The CLASS trial found no statistically significant difference between celecoxib and nonselective NSAID users in the incidence of the primary endpoint of ulcer perforation, gastric-outlet obstruction, or upper GI bleeding (0.8% vs. 1.5%, respectively; 

= .09). Both rofecoxib and celecoxib have been found to significantly reduce mild-to-moderate GI adverse events (rofecoxib compared with naproxen = 23.5% vs. 25.5%, 

; and celecoxib compared with nonselective NSAIDs = 31.4% vs. 36.8%, 

 a reduction of 8% to 15%, respectively. Taken together, these differences would not support the expert panel's estimate of a 75% reduction in GPA use among COX-2 users, nor the assumption that COX-2 users would not be prescribed a GPA. 

We do not contend that our results are the definitive answer to the cost effectiveness of COX-2s. We do believe, however, that the cost effectiveness of COX-2s should be revisited. Sufficient data are now available to evaluate practice patterns that would affect total costs (i.e., GPA use and switching). Newly developed studies should take into consideration the effect of GI risk on the cost effectiveness of COX-2s and compare relevant treatment alternatives (e.g., nonselective NSAIDs plus PPI vs. COX-2s vs. COX-2s plus PPI) among high-risk patients. Additionally, not all models evaluate other patterns reflecting actual practice; these include days supply of NSAID therapy and switching, either due to lack of efficacy or side effects. 

The error of unsubstantiated assumptions had been documented as a criticism of pharmacoeconomic evaluations. 

 Although Pellissier and colleagues concluded that rofecoxib is cost effective compared with nonselective NSAIDs, they also acknowledged the need for further evaluation, stating that "it is too early to tell if the economic benefits of rofecoxib versus nonselective NSAIDs will be realized in clinical practice. However, until clinical GI outcomes data becomes available from a mature marketplace, this research provides insight into the potential cost-effectiveness of rofecoxib in the management of OA.

" This study demonstrates that GI clinical outcomes are not the only data that need to be verified using data from a mature marketplace in assessing the economic benefit of rofecoxib. 

However, some would argue that the critics of decision analysis modeling in healthcare

 are naive as to the purpose of modeling and that the cost of waiting until perfect evidence is available would paralyze the practice of medicine.

 Weinstein and colleagues contended that we must balance the costs and consequences of obtaining and waiting for better data against the costs and consequences of permitting a synthesis of the available evidence.

 Perhaps some believe that errors in economic modeling may not be viewed with the same degree of concern as errors in establishing clinical efficacy or safety. 

The harm from incorrect assumptions, such as those found in the cost-effectiveness evaluations of COX-2s, is that they undermine the ultimate goal of pharmacoeconomics, that is, the efficient allocation of scarce healthcare resources. Whether more harm than good resulted from an invalid COX-2 cost-effectiveness model will require further examination. In the mean time, greater efforts at verifying unsubstantiated model assumptions is a critical step to undertake in order to increase the usefulness of and confidence in pharmacoeconomic information. 

The authors thank Kathleen Fairman, MA, for helpful comments on the study's analysis, and Bryce Sutton, PhD, for assistance in cost-effectiveness model replication.

Pharmacy benefit management: enhancing the applicability of pharmacoeconomics for optimal decision making. 

The use of consensus methods and expert panels in pharmacoeconomic studies: practical applications and methodological shortcomings. 

3. Hochberg MC, Altman RD, Brandt KD, et al. 

Guidelines for the medical management of osteoarthritis. Part I. Osteoarthritis of the hip. American College of Rheumatology. 

4. Hochberg MC, Altman RD, Brandt KD, et al. 

Guidelines for the medical management of osteoarthritis. Part II. Osteoarthritis of the knee. American College of Rheumatology. 

A guideline for the treatment and prevention of NSAID-induced ulcers. 

Prevention and treatment of gastrointestinal symptoms and complications due to NSAIDs. 

The effect of nonsteroidal antiinflammatory drugs on the use of gastroprotective medication in people with arthritis. 

8. Simon LS, Zhao SZ, Arguelles LM, et al. 

Economic and gastrointestinal safety comparisons of etodolac, nabumetone, and oxaprozin from insurance claims data from patients with arthritis. 

Recent considerations in non-steroidal anti-inflammatory drug gastropathy. 

Articles

CLINICAL

Verification of a Decision Analytic Model Assumption Using Real-World Practice Data: Implications for the Cost Effectiveness of Cyclo-oxygenase 2 Inhibitors (COX-2s)

 To examine whether it matters, in terms of quality improvement initiatives and access to commercial networks, whether states contract with Medicaid-dominant or commercial managed care plans

 A 2001 telephone survey of Medicaid managed care plans in 11 states that together account for about half of the national Medicaid managed care enrollment. 

 The survey was developed in consultation with a panel of individuals knowledgeable about Medicaid managed care. Information on plan characteristics and network design was obtained from the plan CEO or person most knowledgeable about the topics. The rest of the data were obtained from the person the CEO named as most knowledgeable about quality improvement initiatives.

 Surveyed plans reported an extensive array of quality improvement initiatives. Programs are in many ways similar across Medicaid-dominant and commercial plans. Medicaid-dominant plans tend to specialize more in conditions of greatest priority to Medicaid beneficiaries. Commercial plans tend to develop programs for accreditation by the National Committee for Quality Assurance, and to limit measurement specific to the Medicaid population. They draw on their commercial networks to support the Medicaid product line, but how much they expand provider access is not clear. Both types of programs face barriers that limit the effectiveness of the plansâ€™ initiatives.

 This study shows extensive development of quality initiatives in Medicaid managed care plans, with limited differences across Medicaid-dominant and commercial plans.

Managed care has become the dominant form of health care for many Medicaid beneficiaries. Fifty-six percent of Medicaid beneficiaries, predominantly low-income children and their parents, received care under a managed care arrangement in 2001.

 States moving to managed care have diverse goals.

 Improved provider access and healthcare quality typically are among them. Ensuring adequate provider participation and access to care have long been outstanding challenges in state Medicaid programs.

 In moving to managed care, states hope to expand physician participation and also to use the network-based structure of managed care to improve accountability and quality of care. 

Policymakers disagree fundamentally about whether Medicaid beneficiaries should be directed toward managed care plans specializing in serving Medicaid enrollees or whether it is better to attract plans with substantial commercial enrollments.

 Theoretical arguments exist for both perspectives. Specifically, to the extent Medicaid enrollees have characteristics and needs distinct from those in commercial managed care, Medicaid-focused managed care may provide better quality through specialization. Alternatively, the discipline of the private market that polices commercial plans could be used to maintain quality in commercial plans so Medicaid beneficiaries would be less likely to be taken advantage of. Many commercial plans may be unwilling to participate in Medicaid under the conditions states currently set for their participation and payment, but policy concern remains over the potential inequity of having different plans serve Medicaid and commercial enrollees. 

In the context of this debate, there are few empirical data on how plan characteristics influence the quality of care Medicaid enrollees actually receive in managed care. Most studies focus on state policies, not plan practices

 or are highly specific to individual plans and states.

 An exception is a 1998 study of managed care plans in 11 states and the District of Columbia that found similarities in programs sponsored by Medicaid-dominant and commercial plans, but limitations in each.

 That survey showed 78% of Medicaid-dominant and 72% of commercial plans had programs in place for high-risk pregnancy; 66% and 68%, respectively, had programs for pediatric asthma. Medicaid-dominant plans were considerably more likely to have in place specialized programs targeting particular needs of the Medicaid population (e.g., lack of telephone, illiteracy). Similar data that reflect the recent growth in managed care and changes in plan sponsorship would be valuable. 

To address this need, this paper examines quality improvement structures in Medicaid-participating capitated plans in 2001. Although the review looks at self-reported practices rather than audited outcomes, the survey captured specific details of practice and provided insight into plan strategy, infrastructure, and what plans say they are doing to promote quality of care. 

This paper is based on data from capitated Medicaid participating plans in 11 states with major Medicaid managed care programs: California, Pennsylvania, Michigan, New York, Florida, New Jersey, Arizona, Maryland, Texas, Washington and Missouri.

 In California we limited plans to those under contract in Los Angeles and Orange County because the state is large and experience varies substantially by county. To best target available resources, we excluded all plans with fewer than 5000 patients in combined Medicaid/State Children's Health Insurance Program (SCHIP) enrollment, but surveyed all of the rest. Although surveyed plans may not necessarily be nationally representative, they capture the experience of participating plans and enrollees representing about half of the risk-based enrollment of Medicaid and SCHIP plans nationwide in 2000.

A total of 155 plans were surveyed, of whom 133 ultimately proved eligible for the survey. Overall, 109 plans responded to the survey for a response rate of 82%. Response rates varied by state from a high of 100% in New Jersey, Texas, and Washington to a low of 50% in Florida. Otherwise, plans with different characteristics had relatively similar response rates.1 Of the 102 plans participating in Medicaid, 101 responded to the quality improvement component of the survey. The data reported here refer to these 101 plans. Plans were asked to respond for Medicaid (rather than SCHIP) even if they participated in both programs because managed care has been in place longer for Medicaid, allowing plans more time to develop, and amass data on, quality improvement initiatives. Item response rates are shown in the tables. 

Data were captured via a telephone survey developed in consultation with an expert panel of individuals knowledgeable about Medicaid managed care in various states. The main body of the survey focused on plan participation and provider networks and was answered by the plan CEO or the person most knowledgeable about the topics. The information presented here on plan characteristics and provider network design comes from that part of the survey. The rest of the data reported come from a parallel instrument on quality improvement initiatives that was answered by the person the CEO named as most knowledgeable about quality improvement initiatives. 

Interviews with quality improvement staff averaged 20 minutes and had 2 purposes. The first was to determine whether plans were pursuing for Medicaid patients any or all of 17 specific health improvement initiatives (e.g., diabetes, asthma). These initiatives might or might not include non-Medicaid enrollees as well. Interviewees then were asked to complete and return a worksheet and include specific information on the design of and experience with up to 5 initiatives. Plans were automatically asked about any initiatives they offered for pregnancy, lead screening, sickle cell anemia screening, and general well-child screening or early periodic screening, diagnosis, and testing (EPSDT). Plans were asked to select the remaining initiatives from those that were most extensive and included Medicaid members. The second purpose of the quality interviews was to ask in considerable detail about operational pregnancy programs in place for Medicaid members and about well-child care. We selected these conditions for more intensive study because our advisory panel believed these types of care were particularly important given the demographics of enrollees in Medicaid managed care. The findings are limited because plans might not have viewed answers in the same light (e.g., what constitutes a "yes") and because they are based on self-reports. However, the survey provides relatively detailed data on practices in the Medicaid program. 

The analysis distinguishes between health plans for whom Medicaid/SCHIP enrollment accounts for 75% or more of plan enrollment ("Medicaid dominant") and others (which we defined as "commercial"). (Though SCHIP enrollment is included in the definition, Medicaid enrollment drives the classification because Medicaid is a much bigger program. For example, 34% of participating plans had fewer than 5000 SCHIP enrollees and 12% had fewer than 10000 SCHIP enrollees. In contrast, only 3% and 15% of surveyed plans had Medicaid enrollments this low.

) The distinction between Medicaid-dominant and commercial plans is consistent with earlier research

 and builds on Medicaid requirements that until recently stated that no more than 75% of a Medicaid-participating health plan's enrollment could come from that program.

 In the survey used here, 64% of responding plans were Medicaid dominant and 36% were commercial.

summarizes the characteristics of these plans. Though many similarities exist, Medicaid-dominant plans were more likely to be provider sponsored and public sponsorship is unique to this type of plan. In contrast, commercial plans tended to be larger but to have a smaller Medicaid enrollment base. That means commercial plans have a larger enrollment base upon which to spread any fixed costs, but may have less incentive to modify their systems to accommodate specific requirements of Medicaid, which constitutes a typically small share of enrollment. Reflecting their commercial base, these plans also were much more likely to be accredited by the National Committee for Quality Assurance (NCQA) because many large employers require it.

 Accreditation means the organization has undergone a rigorous external survey and meets specified standards on clinical and administrative systems in the area of patient safety, confidentiality, consumer protection, access, service, and continuous improvement. Medicaid is less likely than commercial payers to require such accreditation, though Medicaid agencies may impose similar standards for plans participating in their programs. 

The analysis used in the paper is descriptive, showing for the most part the proportion of plans reporting a particular practice. In comparing Medicaid-dominant and commercial plans, we calculated the chi-square statistic to provide evidence of the likelihood the differences were by chance. We show significance at both the conventional 0.05 level and at a more expansive 0.10 level and identify in the text statistically significant findings. Though few differences are statistically significant (the survey size is small), we noted patterns that appear consistent and substantively large, a practice we believe appropriate, particularly because we were dealing with a census of all qualified plans in the 11 states, not a sample. Although most of the findings are reported in tables, we include additional information in the text to elaborate or provide context. 

Quality Improvement Initiatives by Plan Type 

More than three quarters of the surveyed plans had initiatives targeting asthma, immunizations, pregnancy, well-child screenings/EPSDT, diabetes, and breast and cervical cancer screening (

). At least half had initiatives on tobacco cessation, prevention of HIV or other sexually transmitted diseases (STDs), depression, and nutrition counseling. Ninety-five percent of plans with lead screening programs said the state required those plans, as did 93% of plans with well-child/ EPSDT programs and 89% of plans with pregnancy programs (data not shown). This was much less likely to be the case for immunizations, asthma, diabetes, and sickle cell screenings. 

Among the 17 health improvement initiatives, the mean number offered was 12 per plan, a figure that differed little between Medicaid-dominant and commercial plans (12 versus 11). The top 7 conditions most frequently addressed for Medicaid enrollees were the same in both types of plans: immunizations, asthma, well-child screenings/EPSDT, pregnancy, diabetes, breast cancer screening, and cervical cancer screening. Commercial plans were more likely to have programs targeting diabetes, tobacco cessation, congestive heart failure, coronary artery disease, depression, and nutrition counseling. Medicaid-dominant plans were more likely to have programs targeting asthma, violence prevention, HIV or other STD prevention, lead screenings, and sickle cell anemia screenings. Most of these differences were small and not statistically significant, but they were consistent with differences in plan membership. Enrollees with employment-based coverage made up the majority in commercial plans, and these members spanned the income and age spectrum; dealing with chronic disease associated with aging is an important need of this population. Though these conditions also are relevant to Medicaid, the Medicaid population is younger and poorer; well-child screenings, pregnancy, and health problems associated with poverty dominate care needs. 

The surveyed plans completed worksheets that provided more detail on specific quality initiatives. The worksheets reported on up to 5 types of programs (for a total of 453 programs across the plans). Though plan reports of practices were not audited, the worksheet data provided supporting evidence to indicate that initiatives are "real." Plans said that 65% of initiatives have been fully implemented, 25% are in the process of being implemented and 10% are still in the design stage (

). Medicaid-dominant and commercial plans have similar shares of fully implemented programs (64% vs. 67%). Statistically significant differences by type of plan were seen only in diabetes programs. 

Measuring quality before and after an initiative has been implemented is central to continuous quality improvement. Plan performance on this indicator was mixed (

). The vast majority (97%) of plans reported being able to show improvement in the quality of care for at least 1 of the programs about which they provided information. The ability to show improvement was most likely for immunizations (100%) and least likely for diabetes (63%) (data not shown). 

To draw clinicians more closely into quality improvement initiatives, some plans provide them with feedback on performance and use financial incentives to promote improvements in quality (

). About a third (32%-41%) of plans provide feedback to clinicians on the 5 types of programs most commonly reported on the worksheets. Plans typically give feedback to individual clinicians or a practice rather than a larger aggregation of physicians (data not shown). Commercial and Medicaid-dominant plans did not differ dramatically in their use of clinical feedback (see Table 4). 

Financial incentives to improve quality were used less often than feedback. They were most common for well-child/ EPSDT care and for immunizations. This probably reflects the fact that plans use these incentives to encourage physicians to submit data needed to construct Health Plan Employer Data and Information Set (HEDIS) indicators for these conditions, as findings we report later show. 

Virtually all plans (99%) have a fully implemented pregnancy program that includes Medicaid members. Most programs (76%) serve all pregnant enrollees, or they have a component that does so (

). Forty-two percent of the programs have at least 1 component that is targeted to 1 or more specific subgroups of pregnant women&#8776; typically subgroups whose characteristics mean they may be at higher risk. Though commercial plans were no more likely than Medicaid-dominant plans to have targeted programs, when they did they were more likely than Medicaid plans to target by geographic area or provider. (Service areas for Medicaid-dominant plans probably are targeted already by the plan's design.) 

The pregnancy programs of Medicaid-dominant and commercial plans differ in some other respects, though few of these differences are statistically significant. Medicaid-dominant plans much more frequently offer incentives for prenatal and postnatal visits, and they more often offer free or discounted childbirth and parenting classes. They also put more emphasis on the case management component of their programs. Although three quarters or more of both commercial and Medicaid-dominant plans reported being able to show improvement in the past 24 months, only 53% of commercial plans (versus 66% of Medicaid-dominant plans) could show improvement specifically for the Medicaid population. 

Member characteristics and behaviors were most often cited by plans as the top 2 substantial barriers to improvements in pregnancy care (these factors account for two thirds of the barriers cited by plans surveyed; data not shown). Failure to seek care early in pregnancy was a particular concern that plans attributed to lack of awareness or education regarding the value of prenatal care, or inability to see the value of prenatal care relative to other priorities in patients' lives. Other concerns included the absence of babysitting and transportation to support care seeking, population mobility, and enrollees' young age, cultural values, or substance abuse, leading to poorer outcomes. 

Data limitations also serve as barriers to achieving better outcomes (accounting for 36 of 181 factors mentioned; data not shown). The most typical problems were that plans did not have correct address or telephone information for enrollees and that they had difficulty identifying pregnant women. Seventy-seven percent of plans found it difficult or very difficult to identify pregnant plan members early enough in pregnancy so that they could benefit substantially from the program. Thirty-seven percent reported global billing for pregnancy as a barrier to timely identification of pregnant women, and 88% reported other significant problems (e.g., women not seeking care early enough in their pregnancy or not enrolling in the plan until late in the pregnancy). Medicaid-dominant plans were more likely than commercial plans to use pharmacy and claims or encounter data to identify pregnant women (52% of Medicaid-dominant plans used pharmacy data and 84% used claims data, versus 31% and 63% of commercial plans). 

Virtually all (96%) of surveyed plans had a well-child initiative targeted to Medicaid enrollees. All include childhood immunizations, and almost all included EPSDT (see 

). Lead screening and an adolescent immunization component also were common, whereas fewer included a sickle cell anemia screening component. Almost all the well-child programs included educating providers on the importance of well-child screening and EPSDT, sending newsletters to parents that include well-child immunization schedules, and sending personalized reminders to parents about age-appropriate immunization schedules. Medicaid-dominant plans were more likely to provide feedback to clinicians on when patients are due for a visit. Commercial plans were more likely to send personalized reminders to parents, though the differences were not statistically significant. 

Eighty-eight percent of the plans reported the ability to show improvement over the past 24 months. Though the differences were not statistically significant, Medicaid-dominant plans were somewhat less likely than commercial plans to have shown improvement for their program as a whole (85% versus 94%), but only 63% of commercial plans could show improvement in well-child care specifically for the Medicaid population. 

As with pregnancy care, enrollee characteristics were cited most commonly as the major barrier to improving well-child care (accounting for 113 of 179 factors mentioned; data not shown). Many plans reported that enrollees are not aware of the importance of well-child care and that socioeconomic factors are important barriers, or simply stated that parents do not comply with the schedule for well-child care. Sixteen plans specifically cited a lack of transportation or babysitters as important barriers. Data issues also create barriers (37 mentions). The most common data problem stems from the fragmentation of care, with difficulties obtaining data from the public health department or schools and the absence of a central registry for care. Getting encounter data from doctors and coding problems also were mentioned. 

Because we anticipated the latter kind of problem, we probed for additional information on it. Almost half (44%) of plans said they receive complete data for fewer than half of the well-child visits of their enrollees, with this problem more prevalent for Medicaid-dominant than commercial plans (47% vs. 37%). Medicaid-dominant plans that receive complete data frequently have a payment method or other financial incentive for clinician to accurately code and report on well-child visits (57%); only 25% of commercial plans do. 

In the context of the Medicaid program, there is a history of assuming that commercial enrollment is, by its nature, associated with higher quality of care because consumer demand for quality is viewed as more effective in the commercial sector, where many privately insured people have higher incomes, more education, and more options than those on Medicaid. This argument is behind the historical federal requirement (subject to waivers and now defunct) that no more than 75% of the patients in health plans participating in Medicaid be Medicaid enrollees. Commercial plans, some believe, benefit Medicaid enrollees because they have a broader network of providers who might otherwise be unwilling to treat Medicaid beneficiaries. Conversely, however, some are concerned about whether such providers will be familiar with the special needs of the Medicaid population and about how their involvement affects the traditional safety net of providers that serve low-income people, whether on Medicaid or off it. 

The survey provides insight on how provider networks differ between Medicaid-dominant and commercial plans on both these dimensions. Within a commercial plan, Medicaid enrollees do not necessarily have access to the same providers as commercial enrollees (data not shown). Only 19% of the commercial plans surveyed (n = 37) require that providers in their commercial products participate in Medicaid, with 57% including providers in the Medicaid network that are not in the commercial network. Most plans say these outside providers render a "little" (40%) or "some" (55%) of care, not most (5%) or all (none). These findings mean that attracting commercial plans to Medicaid may increase the number of providers willing to treat Medicaid patients, but this outcome is not as effective as commercial plans bringing entire commercial networks to the Medicaid product. 

In establishing the provider network for the Medicaid product, 29% of the surveyed commercial plans said they give strong preference to providers experienced in serving Medicaid, 33% expressed a mild preference, and 38% expressed no preference. The most common reasons given for using providers outside the commercial network were maintaining existing care arrangements for Medicaid enrollees, making care geographically accessible, including safety net providers that traditional served the Medicaid population, or ensuring cultural/linguistic competency. However, some commercial plans said they use outside providers because there are not enough providers in the commercial network to serve both. Some also go outside the commercial network for Medicaid because the state requires it, there are needs for specific specialty types, or a Medicaid beneficiary requests a specific provider type. 

Medicaid-dominant plans that consider themselves safety net plans (85% of plans that are both Medicaid dominant and provider sponsored) also make use of providers from outside the organization.

 On average, such providers account for 56% of the network in such plans. Provider-sponsored plans say they go outside their system to build a provider network to ensure sufficient providers, provide geographic accessibility, meet state requirements, respond to member demands, and compete with other plans. 

More detail on provider participation and on payment is provided elsewhere.

 Unfortunately, the survey was unable to capture information important to assessing access to providers, such as the share of patients treated by diverse kinds of providers or the size of networks. 

The survey provides encouragement for states seeking to use managed care to improve quality of care for low-income beneficiaries. We have no data on initiatives under the traditional Medicaid program. However, without the infrastructure of managed care, such initiatives are extremely challenging to create, suggesting that managed care has the potential to enhance care delivery. 

States considering how to structure their Medicaid managed care programs and what emphasis to place on attracting different kinds of plans can take some comfort in the findings of this study. They show that both Medicaid-dominant and commercial plans can and do mount an extensive array of quality improvement initiatives. Medicaid-dominant plans have the advantage of being able to specialize in programs tailored to the needs of Medicaid enrollees. Commercial plans have the advantage of the quality structure (and resources) available on the commercial side to support quality improvement. Though commercial plans do not bring their entire provider network to the Medicaid product line, there is some evidence that contracting with a commercial plan could bring in some additional providers. Further, at least some commercial plans appear willing to modify their systems to address specific needs and requirements of Medicaid, though such requirements may limit participation by other plans. 

The survey also highlights quality improvement challenges. When care is fragmented among multiple providers, data are particularly important for quality improvement but may be difficult to secure. Facing many demands, individuals served by public programs often are noncompliant with preventive services guidelines. To be successful, plans participating in Medicaid may require outreach, education, and support beyond that provided in the commercial network. More research into this problem is warranted to provide insight on data collection techniques, tools, and information systems that work. 

Absent true outcomes data, this study cannot determine whether the apparently greater Medicaid specialization in Medicaid-dominant plans results in better or worse quality of care for Medicaid beneficiaries than they would receive in a commercial plan. The results support flexibility for states contracting to accommodate differences in the managed care markets. They also highlight the barriers and challenges both commercial and Medicaid-dominant plans face in developing quality improvement initiatives to improve health outcomes for Medicaid beneficiaries. 

The authors gratefully thank Jessica Mittler, MPP; Debra Draper, PhD; Julie Ingels, BA; Michael Sinclair, PhD; and Miriam Loewenberg, AB of Mathematica, who worked along with the authors to develop, implement, and analyze the survey on which the paper is based.

POLICY

Do Quality Improvement Strategies for Medicaid Enrollees Differ in Medicaid-Dominant Versus Commercial Managed Care Organizations?

This activity is designed for physicians, pharmacists, and managed care organization medical directors and administrators.

To identify symptoms, diagnosis, and treatment of celiac disease, a systemic illness with varied manifestations and serious complications if untreated.

Upon successful completion of this educational activity, participants should be able to:

1. Describe risk factors for and clinical presentation of celiac disease.

2. Explain the rationale for early diagnosis of celiac disease.

3. Describe methods of screening and diagnosing celiac disease.

4. Discuss treatment modalities and resources for patients with celiac disease.

The University of Pennsylvania School of Medicine is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

The University of Pennsylvania School of Medicine designates this educational activity for a maximum of 1 category 1 credit toward the AMA Physicianâ€™s Recognition Award. Each physician should claim only those credits that he/she actually spent in the activity.

To receive credit for your completion of this educational activity, you should read and review the material contained in this article, correctly answer the posttest questions, and complete the evaluation and request for credit information. All requests for credit must be submitted to the University of Pennsylvania School of Medicine Office of Continuing Medical Education within the term of approval for this activity and a score of at least 80% correct achieved on the posttest in order to receive CME credit.

The estimated time to complete this activity is 1 hour.

This CME activity was produced under the supervision of Katrina Armstrong, MD, MSc, Assistant Professor of Medicine and Clinical Epidemiology and Senior Scholar, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine.

The authors have disclosed no significant financial interests or other relationships with commercial entities related directly or indirectly to this educational activity. The authors have indicated that this article does not reference unlabeled/unapproved uses of drugs or devices.

Daniel Leffler and Sumona Saha are Clinical Fellows in Medicine and Richard J. Farrell is Assistant Professor of Medicine, all at Harvard Medical School, Boston, Mass. Dr. Farrell is also Associate Physician, Gastroenterology Division, Beth Israel Deaconess Medical Center, Boston, Mass.

Program reviewed and released December 15, 2003; program expires December 15, 2004. Celiac disease, a systemic illness characterized by an abnormal T-cell response to gluten, is more prevalent than previously thought. Because of its varied clinical manifestations and the serious complications that can occur if the condition is untreated, diagnosis is important but can be difficult. Recently developed, accurate serologic tests and the gold standard for diagnosing celiac disease, endoscopic small bowel biopsy, can lead to early detection. Besides a lifetime commitment to a gluten-free diet, management of celiac disease may include dietary supplementation, bone mineral density measurements, intravenous corticosteroid therapy, or other immunosuppressant agents. Symptoms, diagnosis, and treatment of celiac disease are presented.

Celiac disease, also known as celiac sprue or gluten-sensitive enteropathy, is a multifactorial systemic disorder with its central component being an abnormal T-cell response to gluten in predisposed individuals.

Although this disease has been recognized for more than a century, recent advances have improved our understanding of its prevalence, pathogenesis, and complications. There is a growing awareness in the general population, as well as in the medical community, that celiac disease may be more common than previously suspected. With the advent of highly sensitive and specific serologic tests for celiac disease comes the possibility of prompt accurate diagnosis and treatment, leading to symptomatic relief and possible mitigation of the risk of a number of associated disorders such as cancer and osteoporosis.  

In the past, celiac disease was considered to be a rare disorder in the United States, with a prevalence ranging from 1 in 3000

 and teachings in many American medical schools tended to reflect this belief. Although celiac disease is still considered to be uncommon among some Asian and African populations,

 in recent years the prevalence of celiac disease in the United States has been estimated at between 1 in 133

 which is similar to prevalence rates reported in western Europe.

 Further, populations with a prevalence of celiac disease similar to or greater than these rates have been found across the globe.

 Consistent reports of the high prevalence of celiac disease, together with new means of diagnosis and the recognition of the potentially severe consequences of untreated celiac disease, has led a number of European countries to consider national screening programs. While this tactic has not yet been adopted in the United States, a broad, up-to-date understanding of the wide spectrum of celiac disease is needed by all physicians. 

Outside the general population, certain groups have markedly elevated risks of celiac disease. It has long been known that individuals with first-degree relatives diagnosed with celiac disease have a 10% to 20% risk of developing celiac disease.

Additional populations known to have a high prevalence of celiac disease include those with Down's syndrome

 and patients with autoimmune disorders such as type 1 diabetes mellitus, 

The familial clustering of celiac disease along with its association with autoimmune disorders has contributed to the current understanding of the disease's pathophysiology as a primary immune disorder. Gluten is the major protein constituent of many grains. The pivotal step of gluten sensitivity appears to be the alteration of  the gliadin peptides in gluten by tissue transglutaminase.

 These altered gliadin peptides are then presented to local intestinal T cells and recognized as foreign, thereby stimulating an immune response.

 The gliadin peptides are preferentially presented by a limited number of human leukocyte antigen (HLA) haplotypes, with more than 90% of patients with celiac disease sharing the HLA DQ2 haplotype (DQA1*0501, DQB1*0201 heterodimer) and most of the remainder carrying DQ (alpha 1*0301, beta 1*0302) (DQ8).

 Along with abnormal antigen presentation of gliadin, predisposition to developing celiac disease and a number of related autoimmune phenomena appears to be mediated by T cells,

 although the mechanisms behind this T-cell mediation are not well understood. A combination of genetic and environmental factors likely leads to the immune reaction to gliadin peptides, causing inflammation with characteristic intestinal histology and systemic changes. 

The clinical manifestations of celiac disease are extremely varied and, in many cases, differentiating these manifestations from those of associated disorders can be difficult. Clinical manifestations of celiac disease tend to differ by age group. Infants and children with celiac disease typically present with gastrointestinal manifestations including diarrhea, abdominal distention, or symptoms of malnutrition such as short stature, anemia, defects in dentition, failure to thrive, or developmental delay.

 Extraintestinal manifestations are less common in this patient group. For adults, nonspecific gastrointestinal complaints are common and include abdominal pain, flatulence, diarrhea, and, in severe cases, steatorrhea. Nevertheless, most adults with celiac disease present with extraintestinal features. 

One of the most common extraintestinal features among adults is fatigue and malaise, which may occur independently of anemia. Anemia has also been shown to be a strong predictor of celiac disease in all populations, leading some to argue that celiac testing is indicated for anyone with anemia of unknown origin.

 Although anemia in celiac disease may be due to a number of factors including folate or vitamin B12 deficiency or chronic disease, iron deficiency is the most common cause. Iron deficiency anemia in celiac disease may be compounded by bleeding from the gastrointestinal tract, as almost half of patients in 1 study were found to have positive fecal occult blood tests.

Osteoporosis and increased risk of fractures are also common among patients with undiagnosed or subclinical celiac disease.

 The etiology of increased osteopenia in celiac disease relates to impaired calcium and vitamin D malabsorption from the small intestine. Interestingly, celiac-related osteopenia in some individuals appears to be caused by an anti-bone immune process with antibodies targeting a number of normal skeletal constitutes.

 Skin lesions, most commonly dermatitis herpetiformis, occur in approximately 10% of patients with celiac disease.

 Additional clinical presentations of celiac disease are varied and include psychosis, 

The association between celiac disease and malignancy is of special concern because of the potential to prevent the development of cancer through maintenance of a gluten-free diet. The incidence of malignancies, which may occur either before or after the diagnosis of celiac disease is made, are significantly increased.

 Malignancies that have been reported with higher frequency in patients with celiac disease include small bowel lymphoma and small bowel adenocarcinoma,

 primary liver cancer, both Hodgkin's and non-Hodgkin's lymphoma, and oropharyngeal, esophageal, and large intestine carcinoma.

 Further, there is some evidence that maintenance of a gluten-free diet can, over time, return the risk of malignancy in patients with celiac disease to baseline.

A specific manifestation of celiac disease worth mention is refractory sprue, also known as intractable celiac disease. This condition is defined as symptomatic, severe villous atrophy of the small intestine with increased intraepithelial lymphocytes despite maintenance of a strict gluten-free diet.

 The prevalence of the condition in patients with celiac disease has been estimated to be between 7% and 30%.

 Refractory sprue is by definition resistant to treatment and has been associated in the past with a number of entities including ulcerative jejunoileitis, lymphoma, and collagenous sprue.

 Poorly understood for many years, refractory celiac disease has been convincingly linked by recent studies to an abnormal clonal proliferation of intraepithelial T-cell population, the likely precursor to enteropathy-associated T-cell lymphoma.

Accurate serologic tests are now available for the diagnosis of celiac disease. Whereas multiple tests have been introduced, 3 main categories of antibodies are currently available for diagnostic tests: anti-endomysial antibody (EMA), anti-tissue transglutaminase antibody (tTG), and anti-gliadin antibody (AGA). These tests differ in their sensitivity and specificity and in their average cost (

). The IgA anti-endomysial antibody assay is 85% to 98% sensitive and 96% to 100% specific.

December 2003

Verification of a Decision Analytic Model Assumption Using Real-World Practice Data: Implications for the Cost Effectiveness of Cyclo-oxygenase 2 Inhibitors (COX-2s)

Do Quality Improvement Strategies for Medicaid Enrollees Differ in Medicaid-Dominant Versus Commercial Managed Care Organizations?

Celiac Disease

Insights Into Problems Obtaining Care Believed Necessary as Measured by the Medicaid Consumer Assessment of Health Plans Survey (CAHPS)

Availability of Nutrition Services for Medicaid Recipients in the Northeastern United States: Lack of Uniformity and the Positive Effect of Managed Care