Centers for medicare and medicaid mission statement scholarly articles

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The legislation that established Medicare and Medicaid declared that the Federal Government would not interfere in clinical medicine. Despite the original intent, Medicare and Medicaid have had tremendous influence on medical practice.

In this article, we focus on four policy areas that illustrate the influence of CMS and its predecessor agencies on medical practice. We discuss the implications of the relationship between CMS and clinical medicine and how this relationship has changed over time. We conclude with thoughts about potential future efforts at CMS. Notwithstanding what Congress wrote in , the Medicare and Medicaid Programs have enormous influence over the practice of medicine.

The evolution of medical care, its financing, and the expectations of the American population for high-quality care and rational use of public funds have linked, irreversibly, CMS to clinical medicine. As with other payers, CMS must answer to both the beneficiaries it serves and the investors taxpayers ; in addition, CMS must address the concerns of an array of political constituents, including Congress, presidential administrations, and groups representing the health care industry.

To balance these competing interests and pursue evolving policy goals, CMS has had no choice but to become engaged in the practice of medicine and the delivery of health care services. Now, 40 years into the life of Medicare and Medicaid, we reflect on how clinical medicine has become intertwined with CMS by highlighting four key policy areas that illustrate this changing relationship: 1 the end-stage renal disease ESRD program, 2 the quality improvement organizations and the effectiveness initiative, 3 financing of graduate medical education, and 4 State Medicaid activities.

We discuss these policy initiatives, not as an exhaustive listing, but to demonstrate both the broad range of activities that CMS engages in and how those activities have evolved over time as CMS' influence over clinical medicine has increased.

CMS' influence stems from both regulatory decisions by the policymakers in the agency and from legislative decisions made by the Congress. Both avenues of influence are important and are exemplified in this article. The article concludes with thoughts about the future of CMS' relationship with medical practice.

Organized medicine staunchly opposed the passage of Medicare, in part to keep government out of clinical medicine. The American Medical Association AMA , reversing its initial supportive stance, declared its opposition to compulsory health insurance in and in subsequent decades became a powerful lobby against enactment of universal health insurance and its political legacy, Medicare Oberlander, Precisely because of the opposition to national health insurance, political realities forced policymakers to focus on insuring the elderly and minimizing the regulatory role of Medicare in medical practice.

Without conceding to the AMA and limiting the program's regulatory authority, Federal policymakers would have found it much more difficult to gain the medical profession's cooperation in implementing Medicare.

Yet this limitation on regulation became untenable within just 5 years of Medicare's introduction; since that time, Federal policymakers have become increasingly involved and influential in clinical medicine. Because of the weakness of regulatory oversight and the use of unfettered fee-for-service payment in the program's early years, Medicare quickly proved to be a blank check for the health care industry.

This payment structure was not unique to the Federal programs since private health insurance plans generally used similarly inflationary arrangements. Medicare's aim was to finance access for the elderly to mainstream medicine and, in , the mainstream of American medicine showed little concern for cost control or quality oversight.

Indeed, before the s, U. Physicians enjoyed virtually unchallenged clinical autonomy. The number of visits or lengths of hospital stays were generally not influenced by the payer; rather, they were determined at the discretion of physicians. This financing policy did not hold physicians or hospitals accountable for decisions made in patient care and no clear standard for over- or underutilization of health services existed.

Not surprisingly, then, the use of health services and expenditures skyrocketed in Medicare's and Medicaid's early years. As a result, policymakers' attention quickly turned to reforms that would reign in government spending on health care though decisive action was slower to take hold. Evidence suggests that Medicare and Medicaid successfully enhanced access to medical care for low-income and elderly Americans Davis and Schoen, But it is unclear whether the expansion of health care utilization in the first few years of Medicare and Medicaid could be attributed mostly to increasing access to and utilization of needed services or to unregulated overuse of health care.

Likewise, it is unclear whether Medicare and Medicaid predominantly increased use of inappropriate health care services or, instead, increased, in substantial amounts, both appropriate and inappropriate use.

If the latter, one could not argue that Medicare and Medicaid actually changed the practice of clinical medicine, but rather that the programs simply expanded its availability. Regardless, subsequent policy decisions changed the course of Medicare and Medicaid and undoubtedly influenced medical practice. We turn now to four policy areas that exemplify CMS' evolving relationship with clinical medicine. The medical procedure enabling chronic hemodialysis was invented in and pressure soon grew for Federal funding to insure access to the life-saving treatment; the National Kidney Foundation and a small group of physician kidney specialists spearheaded the lobbying campaign.

Long advocated catastrophic health insurance as an alternative to comprehensive national health insurance, and saw ESRD as a demonstration of and prelude to a universal coverage system based on catastrophic insurance Nissenson and Rettig, ; Schreiner, ; and Oberlander, When national health insurance, through catastrophic coverage or any other model, failed to materialize, ESRD remained in Medicare as the Federal Government's only universal, disease-specific coverage program.

ESRD's contribution to health care is obvious: the program has clearly saved hundreds of thousands of lives. With the rapid increase in the prevalence of type II diabetes and the aging of the population, the annual number of new patients entering the ESRD program is expected to increase from , in to , in Collins et al. Beyond the effect of initiating coverage for ESRD, program developments reveal the close relationship between Medicare and what actually happens in the clinical care of patients on dialysis.

Early in the experience of the ESRD program, administrators realized the potential high costs of the program and began to design strategies to contain those costs. For example, outpatient dialysis has been capitated since , and CMS has included more and more services within the capitated payment Nissenson and Rettig, As such, dialysis centers have had to become more efficient over time and have used such cost-saving techniques as reusing dialysis filters and using less well trained technicians to administer dialysis National Kidney Foundation, Although these steps have been frequently debated, dialysis filter reuse does not appear to increase the risk of adverse outcomes Port et al.

As payment to dialysis centers over time has stayed level or decreased, the importance of ongoing quality monitoring of dialysis care has increased Institute of Medicine Committee for the Study of the Medicare End-Stage Renal Disease Program, Another example of CMS' effect on clinical medicine was the decision to deny payment for erythropoietin EPO if a patient's hematocrit was greater than EPO is a naturally occurring protein produced by the kidneys that triggers the production of red blood cells; it improves survival and quality of life among dialysis patients Eschbach, Target hematocrit for patients on dialysis is 33 to 36, so it was thought reasonable to stop administration of EPO when the hematocrit was above this range.

However, the policy actually led to more frequent episodes of a hematocrit below 33 as physicians were concerned about reimbursement denial and more likely to withhold EPO therapy for patients in the higher range Berns et al.

As such, many ESRD patients were not receiving optimal care for their disease. CMS subsequently changed the policy to a cut-point of Through these policies, CMS inserted itself into the patient-specific clinical decisions of physicians.

This also illustrates how data and analysis can help to inform policy as CMS was able to increase the cut-point based on effectiveness studies Berns et al. At the same time as they adjusted the payment rules for dialysis providers, CMS strengthened its oversight and management of dialysis providers and began to pay closer attention to the quality of care provided for ESRD patients. In , Congress approved the creation of ESRD networks that served to collect data related to the care provided within the network and to initiate quality improvement Social Security Amendments of Public Law The networks meet at a national forum each year to share data and ideas for improving quality of care nationally.

Additionally, the improvements made through the ESRD networks have reduced racial disparities in adequacy of hemodialysis Sehgal, By recognizing the relationship between financing and quality of care and then creating a framework for improvement, CMS has participated in improving the clinical care of hundreds of thousands of ESRD patients.

In light of skyrocketing costs in Medicare and Medicaid, as well as concerns over fraud and abuse, Congress decided by the early s that closer oversight of the medical care system was necessary.

The concern was that excess budgetary costs were related to overuse of medical services, driven by uncontrolled financial incentive systems built into the original legislation. These organizations reviewed health service use in an effort to improve the quality of care. Interestingly, the AMA involved itself in the development of the PSROs because they recognized the potential threat of such organizations to physicians' clinical autonomy Oberlander, In the end, Congress agreed with the AMA that physicians should perform the reviews, as they were uniquely suited for the role, but decided that State medical societies would not retain the right to provide this service Oberlander, In fact, PSROs were held accountable by Congress and their contracts could be terminated if they were not fulfilling their role adequately.

By the early s, continued frustration with rising program costs led to the development of new payment and monitoring systems that expanded CMS' regulatory authority and influence. A key response to escalating costs was to change regulatory tools, both in terms of payment and clinical oversight. This change was spurred by congressional action in slowing Medicare spending in the context of rising budget deficits.

The prospective payment system PPS , enacted by Congress in , sought to control hospitalization costs by paying hospitals a fixed rate based on the patient's diagnosis during admission payment was based on diagnosis-related groups Social Security Amendments of Public Law Prior to prospective payment, hospitals and physicians did not have strong financial incentives to provide efficient care.

By implementing this strategy, CMS attempted to relate clinical compensation to the resources needed for patient care. The PPS provided a strong incentive for hospitals to provide fewer services during an admission and shorten the length of stay. The role of CMS as regulatory agency became even more important: it had to monitor for both overuse and underuse of appropriate medical care. Structurally, the PROs differed in that they were consolidated into State level regions.

Functionally, they still relied on retrospective review of cases and, consequently, delayed education or correction of outlying providers. Physicians often maintained an adversarial relationship with the PROs. Nor did the PROs offer much in the way of tangible results: they did not achieve substantial cost savings or quality improvements Oberlander, The most important paradigm shift in Federal policy regarding quality of care began in the contract period starting in Taking advantage of quality improvement knowledge from other industries, CMS charged the PROs to develop prospective quality improvement initiatives.

This model required a change in the relationship between PROs and the physicians and hospitals they served. The PROs had to develop a cooperative relationship and move away from an adversarial culture Bradley et al. The idea was to focus on process improvement and systems based thinking rather than isolating unusual errors Jencks and Wilensky, In , better reflecting the evolution of their mission, the PROs were renamed as quality improvement organizations QIOs.

Recent studies have come to differing conclusions regarding the effectiveness of QIOs at improving care Jencks, Huff, and Cuerdon, ; Snyder and Anderson, ; Gaul, ; Bradley et al. The question of QIO effectiveness has remained elusive because of the difficulty of conducting rigorous studies that demonstrate cause and effect Jencks, Huff, and Cuerdon, ; Snyder and Anderson, QIOs clearly give CMS an important tool to influence quality outcomes, and ongoing evaluation of their effectiveness and improvement of that effectiveness is warranted.

In , CMS launched the effectiveness initiative to evaluate and improve the practice of medicine Roper et al. Because of the enormous potential for the use of data from large populations to study medical effectiveness, CMS committed itself to refining its data system and to linking with clinical researchers to better understand and analyze the data. As a result, CMS could offer clearer information on the health outcomes achieved from health services in regular practice.

CMS has also used the effectiveness initiative to improve the work of the QIOs by helping to inform quality improvement through analysis and interpretation of outcomes data. Through understanding the effects of care and its variation, CMS was in a much better position to educate care providers on quality than it had been previously. Through activities like the effectiveness initiative and advances in data management, CMS can begin to address the enormous variation in care according to geography Wennberg, Fisher, and Skinner, Such variation, which is not associated with differences in outcomes, represents a tremendous opportunity for CMS to control costs.

By understanding the patterns of care that yield the best outcomes at the least cost, CMS can begin to use its influence to get physicians to adopt the most efficient models. Although the process began as a regulatory model, it has evolved into a quality improvement function with the goal of changing how medicine is practiced. This reflects the evolution of Medicare administration from an initial charge of financing care to its current mission that incorporates concerns of improving the quality of care delivered to program beneficiaries as well as cost control.

As such, CMS helps to shape the quality and size of the workforce of future physicians. Additionally, CMS policy changes have substantial effects on the financial health of America's teaching hospitals. Before the s, Medicare allowed teaching hospitals to be reimbursed for their reasonable costs, including the cost of GME. In the early s, along with the PPS, Medicare began making direct and indirect medical education payments to teaching hospitals.

Direct medical education DME payments are intended to offset the actual cost of employing a resident. The indirect medical education IME payments offset the higher cost of care at teaching hospitals because of the higher technology, increased testing, and increased severity of illness.

Contemporaneous with these payments, residency programs grew. The policy rationale for the indirect payments has been hotly debated, and many believe it should include compensation to hospitals for the greater severity of unmeasured case-mix associated with hospitals with teaching programs.

The number of residents nationally totaled 61, in and 98, in At the same time, Congress began to reign in the IME budget by substantially reducing the additional payment to teaching hospitals. Congress has modified the formulas determining the levels of DME and IME support several times over the past decade, attempting to reduce any fiscal incentives to increase the number of training slots.

Additional reduction in slots reimbursed and further cuts in IME levels have been considered; such possibilities raise great concern for the fiscal health of academic medical centers at a time when the U.

The multiple incentives to use residents to provide clinical services include their low cost, high motivation, and skill levels; their work capacity, despite recently being reduced to 80 hours per week, is still far greater than that likely to be realized from any replacement physician or mid-level provider. The pressures that reductions in GME subsidies generate may influence the quality of education of future physicians. In this case, physicians argue that Congress, through CMS policy, substantially influences the direction of our workforce and the financial health of the institutions that drive innovation in medical care.

Immediately after the legislative changes, several prominent teaching institutions had substantial financial losses Coughlan et al. Since then, teaching hospitals have had increasing difficulty maintaining positive operating margins, which can be partially attributed to the reduction in IME payments Phillips et al.

Because of the reduced funding of residency positions, as well as the diminished attractiveness of primary care specialties, some programs have closed, Phillips et al. Teaching faculty are often encouraged to participate in activities that are revenue generating rather than focusing on their role as educators for tomorrow's physicians.

The Medicare Payment Advisory Commission has issued recommendations to consider GME funding from a purely economic argument to allow more market-driven changes in GME Newhouse and Wilensky, , but the proposed market-driven approach may undermine the professional ethos of medicine Gbadebo and Reinhardt, GME financing has substantial influence on the nature of future medical care.

By altering GME payment structures or physician fee rates, CMS can dramatically change the medical education of future physicians. The immediate effects relate to actual patient care practices in teaching hospitals by altering the balance of teaching and medical care by the faculty.

Long-term effects on the size of the workforce and specialty choice are both inevitable and difficult to predict given past problems in projecting workforce needs, as well as the multiple financial and clinical influences changing the staffing and clinical activities of the nation's academic medical centers.

On the Federal level, Medicare has received much more attention than Medicaid over the past 40 years, a consequence of Medicaid's decentralized administrative structure that gives States primary responsibility for its operations. However, within individual States, Medicaid initiatives have had specific influence on the practice of medicine. We focus here on North Carolina to illustrate how initiatives aimed at improving quality in Medicaid are pursued at the State level. CMMI has identified data collection processes as an important enabler of widespread equity advancement.

In future models, the center could consider several initiatives that stakeholders could prepare for:. CMMI may consider integrating incentives and stakeholder education to address barriers to adoption, while also using health equity tools that have demonstrated success in equity-focused programs.

Current CMMI models, state programs, and private-payer and provider initiatives provide a set of potential design choices that could better promote health equity. Several of these approaches have reduced disparities for specific populations; some have improved cost of care performance as well.

Such approaches include provision of various social supports and wraparound services 9 9. Review of evidence for health-related social needs interventions , Commonwealth Fund, July In its strategy refresh, CMMI communicated its intent to incorporate patient experience measures and patient-reported outcomes in performance measurement of future models. This new priority closely mirrors the doubled weight of member or patient experience in the Medicare Advantage Stars program that begins in rating year Based on our primary research with ACO participants, providers may have mixed reactions to the integration of patient experience into performance measurement.

Such integration can create beneficial competitive opportunities but may also require investments in performance improvement plans. Our primary research indicates that providers would find such support valuable to their care management programs since gaps in longitudinal patient data are a meaningful obstacle to succeeding in ACO models, particularly in management of the highest-risk beneficiaries for whom quality and equity of care is also a challenge.

Because of the open network of Medicare FFS, most of the ACO executives we have interviewed said they struggle to capture more than two-thirds of patient encounter data. This dynamic creates discontinuities in management of attributed lives, which in turn can result in care gaps and missed intervention opportunities, worsened patient experience and care quality, and financial losses for the ACO.

A more exhaustive and native source of real-time patient data could create substantial value for patient care and ACO performance. Providers under MA contracts often receive such measures from plans within 72 hours via web-based portals. CMMI could take a similar approach in the future. The second objective is to improve affordability for beneficiaries by reducing out-of-pocket OOP costs, with the ultimate goal of increasing access to care.

In , approximately one-quarter of all Medicare beneficiaries spent 20 percent or more of their income on medical care. High OOP costs can cause beneficiaries to forgo necessary care and prescription drugs. Transitioning to percent accountable care enrollment by could create cost reductions for beneficiaries, but the overall level of relief depends substantially on ACO savings performance and the extent to which these efficiencies are passed on to consumers. Given the limits to influencing affordability purely via ACO efficiencies and the particular tradeoffs to doing so via MA, CMMI has indicated that it is considering broader opportunities to reduce the average beneficiary cost burden.

For instance, targeting price rather than quantity may be an effective approach to lowering overall healthcare costs; several studies have found that price differences could drive a majority of differences in health spending between the United States and peer countries.

Gerard F. Partnerships with organizations beyond demonstration participants may facilitate the scaling of accountable care, particularly partnerships that ease barriers to model participation and collaboration.

CMMI partnerships with public- and private-sector stakeholders would provide different strategic value to demonstration participants. Case studies of prior partnership strategies may serve as a guide for future partnerships.

It has helped spur trends including an emphasis on population health, investments in primary care, and increases in home health.

In particular, the broadened aspirations of this vision convey the heightened importance of newer areas such as care innovation and health equity, and a movement from primary care into a focus on specialty care. These new imperatives create new opportunities. In the wake of the COVID pandemic, consumer expectations and behaviors have evolved, some permanently.

Providers, payers, and innovators can adapt their models to deliver and pay for care that meets top-down signals from the federal government and bottom-up expectations from their own patient populations.

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These findings reinforce the importance of obtaining corresponding Medicare claims of dual enrollees in studies using Medicaid data, even if limited to a non-elder adult population [ 11 , 15 ].

We examined two crude markers of apparent diagnostic miscoding i. While reassuring, this finding does not eliminate the need to formally evaluate the validity and performance metrics of specific health outcomes of interest.

We are unaware of a single standard approach to examine the general validity of a health services database. Therefore, we selected metrics that were broadly applicable, intuitively appealing, easy to measure, and easy to interpret. This is consistent with our prior work in this area [ 15 ] and in alignment with fit-for-use quality assessment components described by Kahn et al.

While other researchers have examined some broad measures of CMS data quality [ 30 , 31 ], their datasets under study were from the s and predated the current model by which CMS prepares data for and provides data to researchers. Big data is a large part of the future of healthcare [ 32 ].

Medicaid data available from CMS have tremendous potential utility for research that will ultimately improve the health of the public. Performing exploratory data analyses, such as that conducted herein, is an important first step in using administrative databases.

Of course, failure to identify problems in the course of such analyses is no guarantee that the data are valid and complete—especially when selected quality metrics represent a tiny fraction of metrics that could be examined e. In conclusion, we broadly examined the quality of thirteen file years of Medicaid and Medicare data from five large states obtained via CMS and its contractors.

Researchers using Medicaid data to study hospital outcomes should obtain supplementary Medicare data on dual enrollees for studies of persons age 45 years and above. US government claims databases. Chichester: Wiley-Blackwell; Chapter Google Scholar.

Studying prescription drug use and outcomes with Medicaid claims data: strengths, limitations, and strategies. Med Care. Ray WA. Policy and program analysis using administrative databases. Ann Intern Med. Frequently asked questions. Accessed 21 Apr Active Projects Report. Medicaid policy brief: guide to MAX data. Math Policy Res Brief. Google Scholar. Validity of pharmacoepidemiologic drug and diagnosis data.

Barosso G. Conducting research with Medicaid claims data videos. Kaiser Family Foundation. Medicaid enrollment by gender. State Health Facts web site.

Research Data Assistance Center. RIF Medicare claims. RIF Medicare claims web site. Descriptive analyses of the integrity of a US medicaid claims database. Pharmacoepidemiol Drug Saf. Article PubMed Google Scholar.

Ohio Medicaid basics The Center for Health Affairs. The evolution of Medicaid managed care in Ohio. Mathematica Policy Research. The Henry J. Dual Eligibles. Dual Eligibles Tutorial web site. Prevalence of diagnosed chronic hepatitis B infection among U. Medicaid enrollees, — Ann Epidemiol. Validity of maternal and infant outcomes within nationwide Medicaid data. Field methods in medical record abstraction: assessing the properties of comparative effectiveness estimates.

Medicare claims can be used to identify US hospitals with higher rates of surgical site infection following vascular surgery.

Use of Medicare claims to identify US hospitals with a high rate of surgical site infection after hip arthroplasty. Infect Control Hosp Epidemiol. Predictive value of Medicare claims data for identifying revision of index hip replacement was modest.

J Clin Epidemiol. Validation of diagnostic codes for outpatient-originating sudden cardiac death and ventricular arrhythmia in Medicaid and Medicare claims data. Safety of saxagliptin: rationale for and design of a series of postmarketing observational studies. Am J Med. Anti-infectives and the risk of severe hypoglycemia in users of glipizide or glyburide.

Clin Pharmacol Ther. A pragmatic framework for single-site and multisite data quality assessment in electronic health record-based clinical research. Data quality assessment for comparative effectiveness research in distributed data networks.

Internal validation of Medicare claims data. Use of Medicaid data for pharmacoepidemiology. Am J Epidemiol. Better big data. Expert Rev Pharmacoecon Outcomes Res. Cai L, Zhu Y. The challenges of data quality and data quality assessment in the big data era. Data Sci J. Article Google Scholar. Download references. The authors wish to thank the following biostatistics and computer programming staff from the University of Pennsylvania for their assistance on this project: Qing Liu, Min Du, and Craig W.

The federal funders had no role in the study beyond comments received during the grant review process. Data that support the findings of this study are available from CMS. Restrictions apply to the availability of these data—used under a data use agreement between the Trustees of the University of Pennsylvania and CMS for the current study—and therefore are not publically available.

However, data may be available from the authors upon a reasonable request and with permission from CMS. CEL and SH formulated the research question. CEL and SH designed the study. SH acquired the data. All authors were involved in data interpretation. CEL drafted the manuscript.

All authors critically revised the manuscript. All authors read and approved the final manuscript. SH secured funding for the study. He has published on topics such as sudden cardiac arrest, drug interactions, drug-induced renal disease, drug-induced respiratory disease, the genetics of drug metabolism, instrumental variable techniques, and the hybrid ecologic-epidemiologic trend-in-trend research design, among others. WBB has consulted for Janssen on an unrelated topic. Access to Medicaid and Medicare claims used herein was permitted by CMS and governed by a data use agreement.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Charles E. Leonard, Colleen M. Bilker, Margaret J. You can also search for this author in PubMed Google Scholar. We were able to use identifiers provided in the data to track unique beneficiaries longitudinally. We then determined the proportion of such beneficiaries without a gap in Medicaid enrollment in each subsequent file year.

This served to quantify the persistence of Medicaid enrollment in beneficiaries over long periods of time. We then graphically summarized several important parameters to assess data completeness and validity. Because our principal use of these data is for pharmacoepidemiologic research, we first looked for unexplained variation in the number of dispensed prescriptions per quarter in each state, which might suggest incomplete prescription data for certain time periods [ 11 ].

We also plotted the ratio of hospitalizations to beneficiary population size in each state, stratified by age group. To avoid double-counting hospitalizations recorded in both Medicaid and Medicare, we included only one hospitalization per beneficiary per day. Finally, we compared quarterly counts of claims with a diagnosis of prostate cancer ICDCM: , Among 15,, beneficiaries identified in file year , 12,, Table 1 presents proportions for interim time points and also for beneficiaries newly-identified as having a full year of continuous enrollment post Raw counts of beneficiaries are presented in Additional file 1 : Table S1.

Figure 1 depicts quarterly prescriptions dispensed per state. Dispensed prescriptions generally increased consistently over time, except for Ohio in which they decreased then plateaued during — see Discussion. The proportion of dispensed prescriptions in which a claim NDC matched a record in Lexicon Plus was See Additional file 1 : Figure S1 for state-specific trends. Figure 2 depicts the annual rate of hospitalization in each state, stratified by age group and federal benefit, considering Medicaid as primary and Medicare as supplemental.

As expected, many hospitalizations in older adults would have been missed if one relied exclusively on Medicaid data. Surprisingly, many hospitalizations in the 45—65 year age group would have been missed if one relied exclusively on Medicaid data. There was a nearly monotonic increase in the rate of hospitalization by age, beginning with the 6—14 year age group. Ratio of number of claims for an inpatient hospitalization to the size of the enrollee population, stratified by age group and state Additional file 1 : Figures S2 and S3 depict quarterly counts of claims with a diagnosis of Complications of Pregnancy, Childbirth, and Puerperium and with a diagnosis of prostate cancer, respectively.

Instances of apparent miscoding were less common in inpatient than outpatient claims 0. Medicaid and Medicare data provided by CMS and its contractors are widely utilized in epidemiologic, policy, and health services research. However, errors in data can lead to incorrect scientific inferences and evaluations of public policy.

Encouragingly, the CMS dataset under study appeared to be of high quality. This dataset provides one an ability to follow a surprisingly large number of beneficiaries without gaps in Medicaid enrollment over long periods of time, despite a large proportion of beneficiaries under study having at least some period of disenrollment.

This is important to researchers wishing to study long-term effects of medical products or policy decisions, for example. Further, dispensed prescriptions generally increased steadily and consistently over time, suggesting that these claims from the Medicaid programs and file years under study may be complete.

During this time, pharmacy benefits in Ohio were carved-in to managed care and the state was undergoing their Medicaid Management Information System replacement project [ 14 ]. Therefore, such claims were not reported to CMS. That being said, researchers interested in identifying non-drug products e. The pattern of hospitalization rates by age group within Medicaid claims alone is similar to prior findings [ 11 , 15 ], in which the apparent rate increases up to age 64, then declines at age Notably, reliance on Medicaid claims alone would have also missed a substantive number of hospitalizations in non-elders, especially among persons age 45— These findings reinforce the importance of obtaining corresponding Medicare claims of dual enrollees in studies using Medicaid data, even if limited to a non-elder adult population [ 11 , 15 ].

We examined two crude markers of apparent diagnostic miscoding i. While reassuring, this finding does not eliminate the need to formally evaluate the validity and performance metrics of specific health outcomes of interest. We are unaware of a single standard approach to examine the general validity of a health services database.

Therefore, we selected metrics that were broadly applicable, intuitively appealing, easy to measure, and easy to interpret. This is consistent with our prior work in this area [ 15 ] and in alignment with fit-for-use quality assessment components described by Kahn et al. While other researchers have examined some broad measures of CMS data quality [ 30 , 31 ], their datasets under study were from the s and predated the current model by which CMS prepares data for and provides data to researchers.

Big data is a large part of the future of healthcare [ 32 ]. Medicaid data available from CMS have tremendous potential utility for research that will ultimately improve the health of the public. Performing exploratory data analyses, such as that conducted herein, is an important first step in using administrative databases. Of course, failure to identify problems in the course of such analyses is no guarantee that the data are valid and complete—especially when selected quality metrics represent a tiny fraction of metrics that could be examined e.

In conclusion, we broadly examined the quality of thirteen file years of Medicaid and Medicare data from five large states obtained via CMS and its contractors.

Researchers using Medicaid data to study hospital outcomes should obtain supplementary Medicare data on dual enrollees for studies of persons age 45 years and above. US government claims databases. Chichester: Wiley-Blackwell; Chapter Google Scholar. Studying prescription drug use and outcomes with Medicaid claims data: strengths, limitations, and strategies.

Med Care. Ray WA. Policy and program analysis using administrative databases. Ann Intern Med. Frequently asked questions. Accessed 21 Apr Active Projects Report. Medicaid policy brief: guide to MAX data.

Math Policy Res Brief. Google Scholar. Validity of pharmacoepidemiologic drug and diagnosis data. Barosso G. Conducting research with Medicaid claims data videos. Kaiser Family Foundation. Medicaid enrollment by gender. State Health Facts web site. Research Data Assistance Center. RIF Medicare claims. RIF Medicare claims web site. Descriptive analyses of the integrity of a US medicaid claims database. Pharmacoepidemiol Drug Saf. Article PubMed Google Scholar. Ohio Medicaid basics The Center for Health Affairs.

The evolution of Medicaid managed care in Ohio. Mathematica Policy Research. The Henry J. Dual Eligibles. Dual Eligibles Tutorial web site. Prevalence of diagnosed chronic hepatitis B infection among U. Medicaid enrollees, — Ann Epidemiol. Validity of maternal and infant outcomes within nationwide Medicaid data. Field methods in medical record abstraction: assessing the properties of comparative effectiveness estimates.

Medicare claims can be used to identify US hospitals with higher rates of surgical site infection following vascular surgery. Use of Medicare claims to identify US hospitals with a high rate of surgical site infection after hip arthroplasty. Infect Control Hosp Epidemiol. Predictive value of Medicare claims data for identifying revision of index hip replacement was modest. J Clin Epidemiol.

Validation of diagnostic codes for outpatient-originating sudden cardiac death and ventricular arrhythmia in Medicaid and Medicare claims data. Safety of saxagliptin: rationale for and design of a series of postmarketing observational studies.

Am J Med. Anti-infectives and the risk of severe hypoglycemia in users of glipizide or glyburide. Clin Pharmacol Ther.

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That being said, researchers interested in identifying non-drug products e. The pattern of hospitalization rates by age group within Medicaid claims alone is similar to prior findings [ 11 , 15 ], in which the apparent rate increases up to age 64, then declines at age Notably, reliance on Medicaid claims alone would have also missed a substantive number of hospitalizations in non-elders, especially among persons age 45— These findings reinforce the importance of obtaining corresponding Medicare claims of dual enrollees in studies using Medicaid data, even if limited to a non-elder adult population [ 11 , 15 ].

We examined two crude markers of apparent diagnostic miscoding i. While reassuring, this finding does not eliminate the need to formally evaluate the validity and performance metrics of specific health outcomes of interest.

We are unaware of a single standard approach to examine the general validity of a health services database. Therefore, we selected metrics that were broadly applicable, intuitively appealing, easy to measure, and easy to interpret.

This is consistent with our prior work in this area [ 15 ] and in alignment with fit-for-use quality assessment components described by Kahn et al. While other researchers have examined some broad measures of CMS data quality [ 30 , 31 ], their datasets under study were from the s and predated the current model by which CMS prepares data for and provides data to researchers. Big data is a large part of the future of healthcare [ 32 ]. Medicaid data available from CMS have tremendous potential utility for research that will ultimately improve the health of the public.

Performing exploratory data analyses, such as that conducted herein, is an important first step in using administrative databases. Of course, failure to identify problems in the course of such analyses is no guarantee that the data are valid and complete—especially when selected quality metrics represent a tiny fraction of metrics that could be examined e. In conclusion, we broadly examined the quality of thirteen file years of Medicaid and Medicare data from five large states obtained via CMS and its contractors.

Researchers using Medicaid data to study hospital outcomes should obtain supplementary Medicare data on dual enrollees for studies of persons age 45 years and above.

US government claims databases. Chichester: Wiley-Blackwell; Chapter Google Scholar. Studying prescription drug use and outcomes with Medicaid claims data: strengths, limitations, and strategies.

Med Care. Ray WA. Policy and program analysis using administrative databases. Ann Intern Med. Frequently asked questions. Accessed 21 Apr Active Projects Report. Medicaid policy brief: guide to MAX data. Math Policy Res Brief. Google Scholar. Validity of pharmacoepidemiologic drug and diagnosis data. Barosso G. Conducting research with Medicaid claims data videos. Kaiser Family Foundation. Medicaid enrollment by gender. State Health Facts web site. Research Data Assistance Center.

RIF Medicare claims. RIF Medicare claims web site. Descriptive analyses of the integrity of a US medicaid claims database. Pharmacoepidemiol Drug Saf. Article PubMed Google Scholar. Ohio Medicaid basics The Center for Health Affairs. The evolution of Medicaid managed care in Ohio. Mathematica Policy Research. The Henry J. Dual Eligibles. Dual Eligibles Tutorial web site. Prevalence of diagnosed chronic hepatitis B infection among U. Medicaid enrollees, — Ann Epidemiol. Validity of maternal and infant outcomes within nationwide Medicaid data.

Field methods in medical record abstraction: assessing the properties of comparative effectiveness estimates. Medicare claims can be used to identify US hospitals with higher rates of surgical site infection following vascular surgery. Use of Medicare claims to identify US hospitals with a high rate of surgical site infection after hip arthroplasty. Infect Control Hosp Epidemiol.

Predictive value of Medicare claims data for identifying revision of index hip replacement was modest. J Clin Epidemiol. Validation of diagnostic codes for outpatient-originating sudden cardiac death and ventricular arrhythmia in Medicaid and Medicare claims data. Safety of saxagliptin: rationale for and design of a series of postmarketing observational studies.

Am J Med. Anti-infectives and the risk of severe hypoglycemia in users of glipizide or glyburide. Clin Pharmacol Ther. A pragmatic framework for single-site and multisite data quality assessment in electronic health record-based clinical research. Data quality assessment for comparative effectiveness research in distributed data networks.

Internal validation of Medicare claims data. Use of Medicaid data for pharmacoepidemiology. Am J Epidemiol. Better big data. Expert Rev Pharmacoecon Outcomes Res. Cai L, Zhu Y. The challenges of data quality and data quality assessment in the big data era. Data Sci J. Article Google Scholar. Download references. The authors wish to thank the following biostatistics and computer programming staff from the University of Pennsylvania for their assistance on this project: Qing Liu, Min Du, and Craig W.

The federal funders had no role in the study beyond comments received during the grant review process. Data that support the findings of this study are available from CMS.

Restrictions apply to the availability of these data—used under a data use agreement between the Trustees of the University of Pennsylvania and CMS for the current study—and therefore are not publically available. However, data may be available from the authors upon a reasonable request and with permission from CMS. CEL and SH formulated the research question. CEL and SH designed the study. SH acquired the data. All authors were involved in data interpretation.

CEL drafted the manuscript. All authors critically revised the manuscript. All authors read and approved the final manuscript. SH secured funding for the study. He has published on topics such as sudden cardiac arrest, drug interactions, drug-induced renal disease, drug-induced respiratory disease, the genetics of drug metabolism, instrumental variable techniques, and the hybrid ecologic-epidemiologic trend-in-trend research design, among others.

WBB has consulted for Janssen on an unrelated topic. Access to Medicaid and Medicare claims used herein was permitted by CMS and governed by a data use agreement. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Charles E. This is important to researchers wishing to study long-term effects of medical products or policy decisions, for example.

Further, dispensed prescriptions generally increased steadily and consistently over time, suggesting that these claims from the Medicaid programs and file years under study may be complete. During this time, pharmacy benefits in Ohio were carved-in to managed care and the state was undergoing their Medicaid Management Information System replacement project [ 14 ].

Therefore, such claims were not reported to CMS. That being said, researchers interested in identifying non-drug products e. The pattern of hospitalization rates by age group within Medicaid claims alone is similar to prior findings [ 11 , 15 ], in which the apparent rate increases up to age 64, then declines at age Notably, reliance on Medicaid claims alone would have also missed a substantive number of hospitalizations in non-elders, especially among persons age 45— These findings reinforce the importance of obtaining corresponding Medicare claims of dual enrollees in studies using Medicaid data, even if limited to a non-elder adult population [ 11 , 15 ].

We examined two crude markers of apparent diagnostic miscoding i. While reassuring, this finding does not eliminate the need to formally evaluate the validity and performance metrics of specific health outcomes of interest. We are unaware of a single standard approach to examine the general validity of a health services database. Therefore, we selected metrics that were broadly applicable, intuitively appealing, easy to measure, and easy to interpret. This is consistent with our prior work in this area [ 15 ] and in alignment with fit-for-use quality assessment components described by Kahn et al.

While other researchers have examined some broad measures of CMS data quality [ 30 , 31 ], their datasets under study were from the s and predated the current model by which CMS prepares data for and provides data to researchers. Big data is a large part of the future of healthcare [ 32 ]. Medicaid data available from CMS have tremendous potential utility for research that will ultimately improve the health of the public.

Performing exploratory data analyses, such as that conducted herein, is an important first step in using administrative databases. Of course, failure to identify problems in the course of such analyses is no guarantee that the data are valid and complete—especially when selected quality metrics represent a tiny fraction of metrics that could be examined e.

In conclusion, we broadly examined the quality of thirteen file years of Medicaid and Medicare data from five large states obtained via CMS and its contractors. Researchers using Medicaid data to study hospital outcomes should obtain supplementary Medicare data on dual enrollees for studies of persons age 45 years and above.

US government claims databases. Chichester: Wiley-Blackwell; Chapter Google Scholar. Studying prescription drug use and outcomes with Medicaid claims data: strengths, limitations, and strategies.

Med Care. Ray WA. Policy and program analysis using administrative databases. Ann Intern Med. Frequently asked questions. Accessed 21 Apr Active Projects Report. Medicaid policy brief: guide to MAX data. Math Policy Res Brief. Google Scholar. Validity of pharmacoepidemiologic drug and diagnosis data.

Barosso G. Conducting research with Medicaid claims data videos. Kaiser Family Foundation. Medicaid enrollment by gender. State Health Facts web site. Research Data Assistance Center. RIF Medicare claims. RIF Medicare claims web site. Descriptive analyses of the integrity of a US medicaid claims database. Pharmacoepidemiol Drug Saf. Article PubMed Google Scholar. Ohio Medicaid basics The Center for Health Affairs.

The evolution of Medicaid managed care in Ohio. Mathematica Policy Research. The Henry J. Dual Eligibles. Dual Eligibles Tutorial web site. Prevalence of diagnosed chronic hepatitis B infection among U. Medicaid enrollees, — Ann Epidemiol. Validity of maternal and infant outcomes within nationwide Medicaid data. Field methods in medical record abstraction: assessing the properties of comparative effectiveness estimates.

Medicare claims can be used to identify US hospitals with higher rates of surgical site infection following vascular surgery. Use of Medicare claims to identify US hospitals with a high rate of surgical site infection after hip arthroplasty. Infect Control Hosp Epidemiol. Predictive value of Medicare claims data for identifying revision of index hip replacement was modest.

J Clin Epidemiol. Validation of diagnostic codes for outpatient-originating sudden cardiac death and ventricular arrhythmia in Medicaid and Medicare claims data.

Safety of saxagliptin: rationale for and design of a series of postmarketing observational studies. Am J Med. Anti-infectives and the risk of severe hypoglycemia in users of glipizide or glyburide. Clin Pharmacol Ther. A pragmatic framework for single-site and multisite data quality assessment in electronic health record-based clinical research.

Data quality assessment for comparative effectiveness research in distributed data networks. Internal validation of Medicare claims data. Use of Medicaid data for pharmacoepidemiology. Am J Epidemiol. Better big data. Expert Rev Pharmacoecon Outcomes Res. Cai L, Zhu Y. The challenges of data quality and data quality assessment in the big data era. Data Sci J. Article Google Scholar. Download references.

The authors wish to thank the following biostatistics and computer programming staff from the University of Pennsylvania for their assistance on this project: Qing Liu, Min Du, and Craig W.

The federal funders had no role in the study beyond comments received during the grant review process. Data that support the findings of this study are available from CMS. Restrictions apply to the availability of these data—used under a data use agreement between the Trustees of the University of Pennsylvania and CMS for the current study—and therefore are not publically available.

However, data may be available from the authors upon a reasonable request and with permission from CMS. CEL and SH formulated the research question. CEL and SH designed the study. SH acquired the data. All authors were involved in data interpretation.

CEL drafted the manuscript. All authors critically revised the manuscript. All authors read and approved the final manuscript. SH secured funding for the study. He has published on topics such as sudden cardiac arrest, drug interactions, drug-induced renal disease, drug-induced respiratory disease, the genetics of drug metabolism, instrumental variable techniques, and the hybrid ecologic-epidemiologic trend-in-trend research design, among others.