Objective: To assess variation in the content of Medicare's localmedical review policies.
Study Design: Six case studies to compare differences in coveragepolicies by diagnosis codes, procedure codes, and indicationsfor use.
Methods: All carrier policies from 48 carrier contracts (n = 5213)posted to the Centers for Medicare & Medicaid Services Web sitewere downloaded on May 31, 2001. All policies in the data setwere coded based on a typology: new technology (NT), extensionsof new technology (TE), and utilization management (UM) of widelyused procedures. We identified policies addressing the sameprocedure or technology. We required at least 20 separate policiesin each case study to allow meaningful comparisons. We randomlyselected 1 case study of a diagnostic and 1 for a treatmentmodality from each policy type (NT, TE, and UM).
Results: Given previous research on local carriers, we expectedto find variations among policies in each case study. We foundsubstantial similarity, however, among policies covering the NTand TE types. We found significantly more variation among ourUM-type case studies.
Conclusions: Medicare legislation has called for greater coveragepolicy consistency in Medicare. This analysis on variation inpolicy content, part of a larger study on variation in Medicare'slocal coverage process, provides data on policy content differences.Policy reform should reflect the nature of and reasons forpolicy variation as suggested by the findings of this research.
(Am J Manag Care. 2005;11:181-187)
Local and regional variations in healthcare havebeen well documented and raise important issuesabout quality of care in the system.1 A payer'scoverage policies are intended to define whether a particularservice or technology will be offered and, if so,set forth the conditions of use. There is growing interestamong payers, providers, and policy makers about theuse of scientific and economic evidence in healthcarecoverage decision making to encourage more appropriateuse and reduce variation.2,3
Managed care organizations have a strong interest inunderstanding practice variations and encouragingappropriate use to improve outcomes and reduce costs.They have an additional interest in regional variationwithin the Medicare program because the calculation ofthe Medicare Advantage premium is tied to fee-for-serviceadjusted average per capita costs. Regional variationstrongly influences the amount of a Medicare Advantagepremium. Because Medicare Advantage plans must followthe coverage policy in the county where a beneficiaryresides, plans offering services over a largegeographic region or nationally face operational challengeswhen Medicare coverage policies differ.Moreover, recently enacted Medicare provisions aremoving the program toward new regional models, raisingadditional concerns about the implications of policyvariations and practice patterns on participating healthplans.4
Although Tunis5 has recently described efforts toenhance Medicare's national coverage process, mostMedicare coverage decisions are decentralized.Medicare relies on a patchwork of nearly 50 local contractingorganizations (called for Part B andfor Part A) that develop thousandsof local medical review policies (LMRPs) applicable onlywithin their own jurisdictions. The 1965 Medicarestatute authorized local contractors to process claimsas a buffer between providers and government.6 Contractorssubsequently acquired the coverage policymaking function through administrative action in the1990s.
The Medicare Payment Advisory Commission andthe US General Accounting Office have recommendedelimination of Medicare's local coverage process,7,8 andthe 2003 Medicare Prescription Drug Improvement andModernization Act directs the Centers for Medicare &Medicaid Services to work to achieve greater coveragepolicy consistency. However, little empirical work hasbeen done to examine the extent of, reasons for, or consequencesof variation in local coverage.
Our research team has been involved in a multiyearstudy of Medicare's local coverage processes. The variationsin the size, resources, and stability of the diversecontracting organizations have been reported elsewhere.9 Significant variations in contractor productivity(number of policies each contractor posted), use ofevidence (based on evidence cites in LMRPs), and effectivedates of policies among local contractors have alsobeen found.10 These findings document variation acrossa wide range of variables.
There has been no systematic analysis of variation inpolicy content, to our knowledge. For example, whilewe know when local policies covering deep brain stimulation(DBS) were issued, how those policies differ inspecific detail one from another has not been analyzed.What can the analysis tell us about variation that wouldinform payers, providers, and policy makers? To answerthese questions, we developed 6 case studies that revealpatterns of policy variation with important implicationsfor Medicare.
Medicare carriers are required to post LMRPs on theCenters for Medicare & Medicaid Services Web site withprescribed data fields.11 We downloaded all LMRPs onMay 31, 2001. We observed that all LMRPs are not thesame. We identified 3 types of LMRPs: "new technology"(NT), "technology extension"(TE), and "utilizationmanagement"(UM) of widely diffused interventions,defined as follows: NT policies provide guidance for, andlimitations on, the use of new clinical interventions; TEpolicies focus on new uses of procedures or technologiesalready covered for other uses; and UM policies focus onwidely diffused procedures to avoid misuse or overuse.Two physician consultants coded all policies in ourdatabase. More than 85% of LMRPs focus on widely diffusedtechnologies (UM); the rest (< 15%) evaluate newtechnologies (NT) or extensions of technologies (TE). Acomplete discussion of the coding methods has beenpublished previously.10
For our case studies, we established the following criteria:(1) We chose only policies from among 48 carrierfiles (n = 5213) because carriers are more active policymakers than fiscal intermediaries and their regions aremore specifically drawn. A complete discussion of thecomplex structure of Medicare contracting organizationshas been previously published.9 (2) We selected onlycases in which our physician consultants agreed on thecoding by type. (3) To enable meaningful comparisons,we selected only case studies with at least 20 postedpolicies.
Using these criteria, we selected 6 case studies froma pool of 80 cases that met our criteria. We selected 2case studies from each of our 3 policy types, 1 diagnosticand 1 treatment or procedure in each type. The 6case studies represent a detailed analysis of 195 separatecoverage policies. Although additional case studiesmight confirm or challenge our findings, the clear patternswe found suggest that our results will be replicatedwith further research. The case descriptions aredrawn from posted policies on the Centers for Medicare& Medicaid Services Web site.11
Deep Brain Stimulation (NT, Treatment).
Deep brainstimulation is a neurosurgical procedure that uses electricalstimulation of subcortical structures (the thalamusor the basal ganglia) to control tremors.
Helicobacter pylori Breath Test (NT, Diagnostic).is a gram-negative rod that has beencausally linked to chronic gastritis, peptic ulcers, gastriccancer, and gastric lymphoma. breath tests are noninvasive diagnostic procedures todetermine the presence of active infection.
Urethral Stents (TE, Treatment).
Male urethral obstructionsmay result from infections, an enlargedprostate, prostate cancer, prostatitis with fibrosis, andother constrictions. Elimination of the obstructionincludes medical and surgical options. Urethral stentingis an extension of the growing use of stents to hold openoccluded vessels.
Transesophageal Echocardiography (TE, Diagnostic).
Transesophageal echocardiography (TEE) appliesan ultrasound generator to the exterior chest wall or inthe esophagus to obtain additional cardiovascular information.The instrumentation is invasive with potentialfor serious complications.
Toenail Debridement (UM, Treatment).
Toenail debridementinvolves the reduction of a thickened dystrophicnail resulting from mycosis or a severe systemiccondition using specialized equipment, such as forcepsor a rotary drill.
Cardiovascular Stress Test (UM, Diagnostic).
Cardiovascularstress testing uses cardiac physiologicalmonitoring during and after stress, with or without subsequentcardiac imaging. A diseased heart respondsabnormally, allowing a diagnostic determination.
The case studies include 36 DBS policies, 39 breath test policies, 33 urethral stent policies, 33TEE policies, 23 toenail debridement policies, and31 stress test policies. There were 41 foot care policies,but only 23 of them addressed toenail debridementand other toenail problems exclusively,while 18 embedded debridement with several otherfoot care procedures.Similarly, we identified43 policies coveringtransesophagealechocardiography; ofthose, 33 focusedspecifically on TEE,and 10 included TEEwithin a wider range ofechocardiography. Weexcluded the broaderpolicies from theanalysis because wecould not clearly identifywhich componentsin the policy applied tothe specific procedureand which referred tothe broader conditions.Coding all datapoints would artificiallyinflate the diversityof the policies.
Our policy contentcomparisons focus on 3areas: diagnosis codes,procedure codes, andindications.
Diagnosis Code Concentration
Classification of Diseases, Ninth Revision,
One key measure of variation among policies is thearray of diagnosis codes in each policy. The is the principal system for codingpatient diagnoses and conditions. Local medical reviewpolicies specify which diagnosis codes are required forcoverage. We found substantial variation in the waysthat carriers cited diagnosis codes. Some policies listedcodes as ranges (ie, 427.0-427.9); others listed all codesseparately. We coded all ranges as including the mostcomprehensive range; we coded single diagnosis codesseparately.
The scattergrams in Figures 1, 2, and 3 illustratedegrees of uniformity or concentration by policy type.Each point on the x-axis reflects 1 carrier; the y-axisshows the frequency of specific codes cited. Figure 1demonstrates the concentration in our 2 NT case studies,DBS and the breath test. Of the 36 DBSpolicies, all contain 2 codes, idiopathic Parkinson diseaseand essential tremor. Only 2 carriers include 3additional codes, all of which refer to more generalizedspasmodic conditions. In other words, 34 of the 36 carriershave identical diagnosis codes; only 2 are marginallymore inclusive.
There is also considerable consistency among NTpolicies applicable to the breath test. There are24 different codes cited across all 39 policies. Fourappear in all policies (gastric ulcer, duodenal ulcer, gastrojejunalulcer, and gastric ulcer), 32 policies includethe diagnosis code for peptic ulcer, 29 cover infection and general abdominal pain, followed by a fewother abdominal disorders.
Figure 2 shows significant concentration in our 2 TEcases, urethral stent and TEE. Of the 33 LMRPs for urethralstent, there are only 7 cited codes or code ranges.All the policies include a code range that includes differenturethral strictures (eg, unspecified infection ortrauma). Twenty-three policies cover stents for benignprostatic hypertrophy, and only 2 cover strictures dueto shistosomiasis, syphilis, or gonococcal infection.Therefore, for the wide variety of strictures, the policiesare similar. However, in some jurisdictions, other specificstrictures can be treated with stenting.
Transesophageal echocardiography includes 130 differentdiagnosis codes or code ranges. The mean numberof codes or code ranges per policy is 39.9. Figure 2shows that there is high concentration for many codes,but there is variation among policies for a wide range ofother cardiac disorders.
Finally, Figure 3 demonstrates significant variationamong UM policies covering toenail debridement andstress testing. These are widely used procedures in theconventional medical arsenal. The UM policies tend toemerge when carriersidentify overuse or misusein their claims dataand want to set clearerlimits. Because there issubstantial variation inpractice patterns acrossregions, it is not surprisingto find thesecorresponding variationsin UM policies.12
The HealthcareCommon ProceduralCoding System specifieswhich provider activitieswill be reimbursedas part of the coveredservice. There are 3levels of codes: Level IHealthcareCommon ProceduralCoding Systemnational codes for servicesand supplies notincluded in the and local codesif no national code isyet available. Typically,policies listed discreteprocedure codes; occasionally,related codeswere listed in ranges.The Table demonstratesthat patterns ofconcentration amongprocedures (Healthcare Common Procedural CodingSystem) vary from those related to diagnosis codes. Theconcentration is measured by the percentage of policiesthat included the 5 most commonly cited codes. Whilethere are several ways to measure concentration (eg,the Herfindahl index), we used the percentage of policiesciting the most commonly cited codes because it isthe most straightforward method and is not confoundedwith the number of procedures cited. A high percentageof policies citing the 5 most common procedure codesindicates a high degree of homogeneity among policies.
We found highest levels of concentration in TE, withsignificant but somewhat lower levels of concentrationin NT. On closer examination,we found thatNT variation was relatedto new procedures. Forexample, the variationin the DBS policies maybe explained by thepresence of temporary(E) codes in some policiesand by variation inthe listing of ancillaryprocedures, such assubcortical mapping orpreliminary monitoring.These variations do notappear to affect beneficiaryaccess to the coreprocedure but mightaffect total providerreimbursement.
Some of this incidentalvariation presumablywill ameliorate asNT procedures proliferate,temporary codesbecome permanentcodes, and policies arerevised to reflect evolvingpatterns of use. Theconcentration in procedurecodes for TE policiesprobably reflects agreater understandingof a technology beingextended to a new use.
By contrast, the classicUM policy in ourcase study, stress testing,presents a significantlack of concentration.Stress testing is an importantdiagnostic, but carriers vary considerablyon what proceduresthey accept for payment.Because these policies arise fromreview of claims data, it is notsurprising that some carriershave tried to manage use withcareful specification of acceptableprocedure codes.
Another interesting anomaly isthe high degree of concentrationof procedure codes for toenaildebridement. In part, this occurs because there areonly a few procedures to treat the condition. The policyvariations are more likely to occur among permissiblediagnoses or allowable indications. Use concernshave been widespread for this common condition.Concerned carriers have worked together to develop acommon template for toenail debridement (KathleenBrooks, MD, Carrier Medical Director for WisconsinPhysician Services; oral communication; SeventhAnnual Minnesota Health Services Research Conference;March 4, 2003; Minneapolis). As a result, carriers haveadopted a more uniform set of allowable codes thanmight have been expected otherwise.
Concentration by Indications
Each policy includes sections labeled "Indicationsand Limitations of Coverage"and "Reasons for Denial"that provide the clinical, procedural, and administrativeguidelines that determine reimbursement. We allocatedall indications as "for inclusion"or "for exclusion"toprevent redundancy in coding. Criteria for inclusiondocument who or what is covered; criteria for exclusionrecord who or what is not covered. In this analysis, weuse criteria for inclusion as the measure of comparison.
We found that DBS indications are concentrated,with the first and second most cited indications appearingin 100% and 91%, respectively, of all DBS policies.The third DBS indication, appearing in only 60% of policies,warns providers about the seriousness of the procedure.This type of "admonitory"policy should havelittle or no effect on beneficiary access.
There appears to be less consistency among the breath test LMRPs. Of the 21 cited indications, thefirst and second most cited appeared in only 76% ofthe policies. On further examination, however, it wasclear that many indications were variations on atheme, such as recounting symptoms, levels of symptomseverity, or plans for or timing of endoscopy. Allfocused on careful evaluation of the patient before performingthe procedure.
The TE policies for urethral stent and TEE also areconcentrated, with the top 3 indications appearing in90% and 97%, respectively, of all the policies. By contrast,the UM policies show substantial variation acrossthe indications. For example, the most frequentlycited indication for stress testing appeared in 58% ofthe policies. Some policies stated indications generally;others included specific lists of complications. Thetoenail debridement policies exhibited similar variation,with the most cited indication appearing 77% ofthe time and the second most cited indication appearing43% of the time. The indications seek to controlunnecessary use, with requirements that the medicalrecord contain proof of medical necessity in the formof laboratory tests and dated photographs. Other policiesincluded lists of required findings consistent withthe diagnosis and indicative of severe peripheralinvolvement. These UM policy variations demonstrateefforts by specific carriers to control problem use arisingin their regions.
We would expect some variation across all policytypes based on the differences among carriers in termsof resources, size, and output. The results confirmedour hypothesis that NT and TE policies would be mostsimilar, given the limited scientific and clinical dataavailable for evaluation of new technologies. By contrast,we assumed that UM policies were more likely tovary. The UM policies come to the attention of carriersas they review their claims data. Variations in practicepatterns are likely to trigger different responses fromlocal carriers. Therefore, if a carrier wants to controloveruse of stress tests, it will draft a policy to do so; ifthere are no perceived abuses, there is less incentive fora carrier to develop a policy or to address any unobservedmisuse.
Generalizations from 6 case studies should bemade with caution. There are many unique characteristicsof medical technologies. Although we randomlyselected different interventions, additionalcase studies can confirm or qualify our conclusions.However, the consistency of the variation patterns weidentified in our cases suggests a strong likelihoodthat further studies will be consistent with our findings.More research is also necessary to determinewhether and how variations in coverage policiesmight affect clinical practice. We are looking at therelationship between local policies and Medicareclaims data, but these issues are beyond the scope ofthis case study analysis.
Because there is little variation in policy content inour NT and TE case studies, we suggest that these policytypes are not likely to encourage practice variations.However, the decentralized policy environment meansthat there is significant variation in effective dates ofthese policies. The DBS policies, for example, took morethan 21/2 years from the 1st policy to the 36th policy. Adetailed aggregate analysis of the timing of policies hasbeen published previously.10 Some carriers never issuepolicies; their absence is also a sign of variation. Thesedifferences mean that access will vary depending onwhether a policy is in place. Are these variations allclinically important? We have commented on thevariations we found in our cases. However, it is worthnoting that clinical importance is in the eye of the carrier;we must assume that, if carriers include specificcodes in their policies, they must view them as relevantor important. Clinicians may have opinions aboutthe importance of some variations in specificinstances, but conclusions on this point are beyondthe scope of this study.
Why allow multiple carriers to engage in numerousassessments of the same technologies when they reachnearly identical results? This duplicative process isinefficient. There are issues regarding quality of theassessments as well. Carriers often lack the resourcesand expertise to perform formal technology assessments.Therefore, the policies may be technicallyflawed and inefficiently developed.
Most LMRPs are UM policies. The UM policies respondto local conditions. Given disparate practice patternsacross the country, it is not surprising to havelocal policies reflect different use issues. In fact, policyvariations may encourage greater conformance toaccepted practices. One carrier may require specificcontrols to prevent misuse, another may not observemisuse and require no policy, and a third might identifywholly different practice issues calling for an alternativepolicy response. All may lead to similar useresults. A more flexible and responsive local carrier isperhaps better suited to adapt policies to local needsrather than rely on a national policy that might notaddress specific local problems. Carriers also consultlocal practitioners, and policies may reflect local concerns.Although one could argue for greater standardizationin policies embodying best practice in theory,we must balance the value of standard utilization managementapproaches against creative, locally craftedpolicy responses.
Medicare's decentralized local coverage processresults in a complex array of organizations engaged inthe development of multiple policies. The patchworkpolicy environment presents challenges for providersand beneficiaries in the delivery of care. It also presentschallenges to managed care organizations that offerplans subject to policies developed by multiple carriers.The objective of this study was to look carefully at howLMRPs vary in content and to assess the implications ofthat variation on the Medicare program. From a policyperspective, our research suggests that there is roomfor more policy consistency through greater use of thenational process and closer collaboration among carriers.However, reform efforts should reflect the nature ofand reasons for policy variation to most effectivelyaddress practice variations across the country.
From the Division of Health Services Research and Policy, School of Public Health,University of Minnesota, Minneapolis.
This study was supported by Changes in Health Care Finance and Organization project042086 from The Robert Wood Johnson Foundation, Princeton, NJ.
Address correspondence to: Susan Bartlett Foote, JD, Division of Health ServicesResearch and Policy, School of Public Health, University of Minnesota, 420 DelawareStreet SE, MMC 729, Minneapolis, MN 55455. E-mail: email@example.com.
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