Concept: Health Insurance Portability and Accountability Act
Forty years ago, Shenkin and Warner argued that giving patients their medical records “would lead to more appropriate utilization of physicians and a greater ability of patients to participate in their own care.”(1) At that time, patients in most states could obtain their records only through litigation, but the rules gradually changed, and in 1996 the Health Insurance Portability and Accountability Act entitled virtually all patients to obtain their records on request. Today, we’re on the verge of eliminating such requests by simply providing patients online access. Thanks in part to federal financial incentives,(2) electronic medical records are becoming the . . .
The International Classification of Diseases-10 (ICD-10) is a new system that is a federally mandated change affecting all payers and providers, and is expected to exceed both the Health Insurance Portability and Accountability Act (HIPAA) and Y2K in terms of costs and risks. In 2003, HIPAA named ICD-9 as the code set for supporting diagnoses and procedures in electronic administrative transactions. However, on 16 January 2009, the Department of Health and Human Services published a regulation requiring the replacement of ICD-9 with ICD-10 as of 1 October 2013. While ICD-9 and ICD-10 have a similar type of hierarchy in their structures, ICD-10 is more complex and incorporates numerous changes. Overall, ICD-10 contains more than 141 000 codes, a whopping 712% increase over the <20 000 codes in ICD-9, creating enormous complexities, confusion and expense. Published statistics illustrate that there are instances where a single ICD-9 code can map to more than 50 distinct ICD-10 codes. Also, there are multiple instances where a single ICD-10 code can map to more than one ICD-9 code. Proponents of the new ICD-10 system argue that the granularity should lead to improvements in the quality of healthcare whereas detractors of the system see the same granularity as burdensome. The estimated cost per physician is projected to range from $25 000 to $50 000.
Mobile health (mHealth) technology has facilitated the transition of care beyond the traditional hospital setting to the homes of patients. Yet few studies have evaluated the legal implications of the expansion of mHealth applications, or “apps.” Such apps are affected by a patchwork of policies related to medical licensure, privacy and security protection, and malpractice liability. For example, the privacy protections of the Health Insurance Portability and Accountability Act (HIPAA) of 1996 may apply to only some uses of the apps. Similarly, it is not clear what a doctor’s malpractice liability would be if he or she injured a patient as the result of inaccurate information supplied by the patient’s self-monitoring health app. This article examines the legal issues related to the oversight of health apps, discusses current federal regulations, and suggests strategies to improve the oversight of these apps.
Health information technology (IT) offers promising tools for improving care coordination. We assessed the feasibility and acceptability of 6 proposed care coordination objectives for stage 3 of the Centers for Medicare and Medicaid Services electronic health record incentive program (Meaningful Use) related to referrals, notification of care from other facilities, patient clinical summaries, and patient dashboards.
There has been concern that an increase in billing for high-intensity emergency care is due to changes in coding practices facilitated by electronic health records. We sought to characterise the trends in billing for high-intensity emergency care among Medicare beneficiaries and to examine the degree to which trends in high-intensity billing are explained by changes in patient characteristics and services provided in the emergency department (ED).
Given the potential wealth of insights in personal data the big databases can provide, many organizations aim to share data while protecting privacy by sharing de-identified data, but are concerned because various demonstrations show such data can be re-identified. Yet these investigations focus on how attacks can be perpetrated, not the likelihood they will be realized. This paper introduces a game theoretic framework that enables a publisher to balance re-identification risk with the value of sharing data, leveraging a natural assumption that a recipient only attempts re-identification if its potential gains outweigh the costs. We apply the framework to a real case study, where the value of the data to the publisher is the actual grant funding dollar amounts from a national sponsor and the re-identification gain of the recipient is the fine paid to a regulator for violation of federal privacy rules. There are three notable findings: 1) it is possible to achieve zero risk, in that the recipient never gains from re-identification, while sharing almost as much data as the optimal solution that allows for a small amount of risk; 2) the zero-risk solution enables sharing much more data than a commonly invoked de-identification policy of the U.S. Health Insurance Portability and Accountability Act (HIPAA); and 3) a sensitivity analysis demonstrates these findings are robust to order-of-magnitude changes in player losses and gains. In combination, these findings provide support that such a framework can enable pragmatic policy decisions about de-identified data sharing.
With ongoing interest in rising Medicare Advantage enrollment, we examined whether the growth in enrollment between 2006 and 2011 was mainly due to new beneficiaries choosing Medicare Advantage when they first become eligible for Medicare. We also examined the extent to which beneficiaries in traditional Medicare switched to Medicare Advantage, and vice versa. We found that 22 percent of new Medicare beneficiaries elected Medicare Advantage over traditional Medicare in 2011; they accounted for 48 percent of new Medicare Advantage enrollees that year. People ages 65-69 switched from traditional Medicare to Medicare Advantage at higher-than-average rates. Dual eligibles (people eligible for both Medicare and Medicaid) and beneficiaries younger than age sixty-five with disabilities disenrolled from Medicare Advantage at higher-than-average rates. On average, in each year of the study period we found that fewer than 5 percent of traditional Medicare beneficiaries switched to Medicare Advantage, and a similar percentage of Medicare Advantage enrollees switched to traditional Medicare. These results suggest that initial coverage decisions have long-lasting effects.
Randomized controlled trials have traditionally been the gold standard against which all other sources of clinical evidence are measured. However, the cost of conducting these trials can be prohibitive. In addition, evidence from the trials frequently rests on narrow patient-inclusion criteria and thus may not generalize well to real clinical situations. Given the increasing availability of comprehensive clinical data in electronic health records (EHRs), some health system leaders are now advocating for a shift away from traditional trials and toward large-scale retrospective studies, which can use practice-based evidence that is generated as a by-product of clinical processes. Other thought leaders in clinical research suggest that EHRs should be used to lower the cost of trials by integrating point-of-care randomization and data capture into clinical processes. We believe that a successful learning health care system will require both approaches, and we suggest a model that resolves this escalating tension: a “green button” function within EHRs to help clinicians leverage aggregate patient data for decision making at the point of care. Giving clinicians such a tool would support patient care decisions in the absence of gold-standard evidence and would help prioritize clinical questions for which EHR-enabled randomization should be carried out. The privacy rule in the Health Insurance Portability and Accountability Act (HIPAA) of 1996 may require revision to support this novel use of patient data.
The passage of the Affordable Care Act saw the creation of Accountable Care Organizations (ACOs), a new approach to healthcare delivery moving from fee-for-service toward population health. This paper presents a case study of the Memorial Hermann ACO (MHACO), launched in response to the Medicare Shared Savings Program, with goals to align physician and hospital incentives, practice evidence-based medicine, develop care coordination, and increase efficiency. Building blocks included an affiliated primary care network, a clinical integration program (involving shared electronic medical record platforms and quality data reporting), and significant investments in information technology. Presented is the approach taken to form MHACO; the management structure, technology developed, and a 2-year experience. Incorporated in July 2012, the MHACO involved 22 000 Medicare patients. In 2015, Centers for Medicare and Medicaid Services released data showing a composite quality score between 80 and 85 (from a maximum 100) and nearly $53 million in total savings (or 11% of expected expenditure), making MHACO one of the most successful nationally.1 In fewer than 5 years, almost 500 ACOs have developed, and by some estimates, a quarter of Medicare patients are currently enrolled in an ACO. Although ACOs to date have focused on primary care, the future will increasingly involve specialists. At Memorial Hermann, neurosurgeons took an early role in forming collaborative partnerships with the hospital, and started programs that served as precursors to the ACO model. This paper ends with an overview of ACO development, likely changes going forward, and a discussion of the role of specialists in general, and of neurosurgeons in particular.
Building a Rapid Learning Health Care System for Oncology: Why CancerLinQ Collects Identifiable Health Information to Achieve Its Vision
- Journal of clinical oncology : official journal of the American Society of Clinical Oncology
- Published over 4 years ago
The ever-increasing volume of scientific discoveries, clinical knowledge, novel diagnostic tools, and treatment options juxtaposed with rising costs in health care challenge physicians to identify, prioritize, and use new information rapidly to deliver efficient and high-quality care to a growing and aging patient population. CancerLinQ, a rapid learning health care system in oncology, is an initiative of the American Society of Clinical Oncology and its Institute for Quality that addresses these challenges by collecting information from the electronic health records of large numbers of patients with cancer. CancerLinQ is first and foremost a quality measurement and reporting system through which oncologists can harness the depth and power of their patients' clinical records and other data to assess, monitor, and improve the care they deliver. However, in light of privacy and security concerns with regard to collection, use, and disclosure of patient information, this article addresses the need to collect protected health information as defined under the Health Insurance Portability and Accountability Act of 1996 to drive rapid learning through CancerLinQ.