New and Persistent Controlled Substance Use Among Patients Undergoing Mastectomy and Reconstructive Surgery

PurposeProlonged use of controlled substances can place patients at increased risk of dependence and complications. Women who have mastectomy and reconstructive surgery (M+R) may be vulnerable to becoming new persistent users (NPUs) of opioid and sedative-hypnotic medications.MethodsUsing the MarketScan health care claims database, we identified opioid- and sedative-hypnotic-naïve women who had M+R from 2008-2017. Women who filled ≥1 peri-operative prescription and ≥2 post-operative prescriptions within one year after surgery were classified as NPUs. Univariate and multivariable logistic regression analyses were used to estimate rates of new persistent use and predictive factors. Risk summary scores were created based on the sum of associated factors.ResultsWe evaluated 25,270 opioid-naïve women and 27,651 sedative-hypnotic-naïve women.We found that 18,931 opioid-naïve women filled a peri-operative opioid prescription, and of those, 3,315 (17.5%) became opioid NPUs post-operatively. Additionally, 10,781 sedative-hypnotic-naïve women filled a peri-operative sedative-hypnotic prescription, and of those, 1,837 (17.0%) became sedative-hypnotic NPUs. Development of new persistent sedative-hypnotic use was associated with age ≤49 (OR 1.79 [95% CI 1.43–2.25]) and age 50-64 (1.65 [1.31-2.07]) compared to age ≥65; Medicaid insurance (1.92 [1.23–2.98]); southern residence (1.38 [1.20–1.59]); breast cancer diagnosis (1.78 [1.09–2.91]); and chemotherapy (2.24 [2.02–2.49]). Risk of NPU increased with higher risk score. Women with ≥3 of these risk factors were three times more likely to become sedative-hypnotic NPUs than patients with 0 or 1 factors (3.03 [2.60–3.53]). Comparable findings were seen regarding new persistent opioid use.ConclusionWomen who have M+R are at risk of developing both new persistent opioid and new persistent sedative-hypnotic use. A patient’s risk of becoming an NPU increases as their number of risk factors increases. Non-pharmacologic strategies are needed to manage pain and anxiety following cancer-related surgery.

Combating Health Care Fraud and Abuse: Conceptualization and Prototyping Study of a Blockchain Antifraud Framework

Background An estimated US $2.6 billion loss is attributed to health care fraud and abuse. With traditional health care claims verification and reimbursement, the health care provider submits a claim after rendering services to a patient, which is then verified and reimbursed by the payer. However, this process leaves out a critical stakeholder: the patient for whom the services are actually rendered. This lack of patient participation introduces a risk of fraud and abuse. Blockchain technology enables secure data management with transparency, which could mitigate this risk of health care fraud and abuse. Objective The aim of this study is to develop a framework using blockchain to record claims data and transactions in an immutable format and to enable the patient to act as a validating node to help detect and prevent health care fraud and abuse. Methods We developed a health care fraud and abuse blockchain technical framework and prototype using key blockchain tools and application layers including consensus algorithms, smart contracts, tokens, and governance based on digital identity on the Ethereum platform (Ethereum Foundation). Results Our technical framework maps to the claims adjudication process and focuses on Medicare claims, with the US Centers for Medicare and Medicaid Services (CMS) as the central authority. A prototype of the framework system was developed using the blockchain platform Ethereum (Ethereum Foundation), with its design features, workflow, smart contract functions, system architecture, and software implementation outlined. The software stack used to build the system consisted of a front-end user interface framework, a back-end processing server, and a blockchain network. React was used for the user interface framework, and NodeJS and an Express server were used for the back-end processing server; Solidity was the smart contract language used to interact with a local Ethereum blockchain network. Conclusions The proposed framework and the initial prototype have the potential to improve the health care claims process by using blockchain technology for secure data storage and consensus mechanisms, which make the claims adjudication process more patient-centric for the purposes of identifying and preventing health care fraud and abuse. Future work will focus on the use of synthetic or historic CMS claims data to assess the real-world viability of the framework.

Sources of Geographic Variation in Health Care Spending Among Individuals With Employer Sponsored Insurance

We use health care claims data from the Health Care Cost Institute to estimate the share of geographic variation in health care spending attributable to person-specific (demand) and place-specific (supply) factors. We exploit patient migration across 112 metropolitan areas between 2012 and 2016. Using an event study approach, we find that moving to an area with 10% higher (lower) spending leads to a 4.2% increase (decrease) in individual medical spending. Our estimate implies that 42% of variation in health care spending among the commercially insured is attributable to place-specific factors. We show that variation in both price and utilization jointly determine the place-specific impact on individual spending. All else equal, we find that moving to an area with 10% higher (lower) prices, on average leads to a 5% increase (decrease) in spending, while moving to an area with 10% higher (lower) utilization leads to a 3.6% increase (decrease).

Combating Health Care Fraud and Abuse: Conceptualization and Prototyping Study of a Blockchain Antifraud Framework (Preprint)

BACKGROUND An estimated US $2.6 billion loss is attributed to health care fraud and abuse. With traditional health care claims verification and reimbursement, the health care provider submits a claim after rendering services to a patient, which is then verified and reimbursed by the payer. However, this process leaves out a critical stakeholder: the patient for whom the services are actually rendered. This lack of patient participation introduces a risk of fraud and abuse. Blockchain technology enables secure data management with transparency, which could mitigate this risk of health care fraud and abuse. OBJECTIVE The aim of this study is to develop a framework using blockchain to record claims data and transactions in an immutable format and to enable the patient to act as a validating node to help detect and prevent health care fraud and abuse. METHODS We developed a health care fraud and abuse blockchain technical framework and prototype using key blockchain tools and application layers including consensus algorithms, smart contracts, tokens, and governance based on digital identity on the Ethereum platform (Ethereum Foundation). RESULTS Our technical framework maps to the claims adjudication process and focuses on Medicare claims, with the US Centers for Medicare and Medicaid Services (CMS) as the central authority. A prototype of the framework system was developed using the blockchain platform Ethereum (Ethereum Foundation), with its design features, workflow, smart contract functions, system architecture, and software implementation outlined. The software stack used to build the system consisted of a front-end user interface framework, a back-end processing server, and a blockchain network. React was used for the user interface framework, and NodeJS and an Express server were used for the back-end processing server; Solidity was the smart contract language used to interact with a local Ethereum blockchain network. CONCLUSIONS The proposed framework and the initial prototype have the potential to improve the health care claims process by using blockchain technology for secure data storage and consensus mechanisms, which make the claims adjudication process more patient-centric for the purposes of identifying and preventing health care fraud and abuse. Future work will focus on the use of synthetic or historic CMS claims data to assess the real-world viability of the framework.

Genetic testing utilization for patients with neurologic disease and the limitations of claims data

ObjectiveTo determine the utilization of genetic testing in patients seen by a neurologist within a large private insurance population.MethodsUsing the Optum health care claims database, we identified a cross-sectional cohort of patients who had been evaluated by a neurologist no more than 30 days before initial genetic testing. Within this group, we then categorized genetic testing between 2014 and 2016 on the basis of the Current Procedural Terminology (CPT) codes related to molecular and genetic testing. We also evaluated the International Classification of Disease Version 9 Clinical Code Classifications (ICD-9 CCS) associated with testing.ResultsFrom 2014 to 2016, a total of 45,014 claims were placed for 29,951 patients who had been evaluated by a neurologist within the preceding 30 days. Of these, 29,926 (66.5%) were associated with codes that were too nonspecific to infer what test was actually performed. Among those claims where the test was clearly identifiable, 7,307 (16.2%) were likely obtained for purposes of neurologic diagnosis, whereas the remainder (17.2%) was obtained for non-neurological purposes. An additional 3,793 claims (8.4%) wherein the test ordered could not be clearly identified were associated with a neurology-related ICD-9 CCS.ConclusionsAccurate assessment of genetic testing utilization using claims data is not possible given the high prevalence of nonspecific codes. Reducing the ambiguity surrounding the CPT codes and the actual testing performed will become even more important as more genetic tests become available.