Appropriately framing maternal request caesarean section

In their paper, ‘How to reach trustworthy decisions for caesarean sections on maternal request: a call for beneficial power’, Eide and Bærøe present maternal request caesarean sections (MRCS) as a site of conflict in obstetrics because birthing people are seeking access to a treatment ‘without any anticipated medical benefit’. While I agree with the conclusions of their paper -that there is a need to reform the approach to MRCS counselling to ensure that the structural vulnerability of pregnant people making birth decisions is addressed—I disagree with the framing of MRCS as having ‘no anticipated medical benefit’. I argue that MRCS is often inappropriately presented as unduly risky,without supporting empirical evidence,and that MRCS is most often sought by birthing people on the basis of a clinical need. I argue that there needs to be open conversation and frank willingness to acknowledge the values that are currently underpinning the presentation of MRCS as ‘clinically unnecessary’; specifically there needs to be more discussion of where and why the benefits of MRCS that are recognised by individual birthing people are not recognised by clinicians. This is important to ensure access to MRCS for birthing people that need it.

Need-Based and Optimized Health Insurance Package Using Clustering Algorithm

The paper presents a novel methodology based on machine learning to optimize medical benefits in healthcare settings, i.e., corporate, private, public or statutory. The optimization is applied to design healthcare insurance packages based on the employee healthcare record. Moreover, with the advancement in the insurance industry, it is rapidly adapting mathematical and machine learning models to enhance insurance services like funds prediction, customer management and get better revenue from their businesses. However, conventional computing insurance packages and premium methods are time-consuming, designation specific, and not cost-effective. During the design of insurance packages, an employee’s needs should be given more importance than his/her designation or position in an organization. The design of insurance packages in healthcare is a non-trivial task due to the employees’ changing healthcare needs; therefore, using the proposed technique employees can be moved from their existing package to another depending upon his/her need. This provides the motivation to propose a methodology in which we applied machine learning concepts for designing need-based health insurance packages rather than professional tagging. By the design of need-based packages, medical benefit optimization which is the core goal of our proposed methodology is effectively achieved. Our proposed methodology derives insurance packages that are need-based and optimal based on our defined criteria. We achieved this by first applying the clustering technique to historical medical records. Subsequently, medical benefit optimization is achieved from these packages by applying a probability distribution model on five years employees’ insurance records. The designed technique is validated on real employees’ insurance records from a large enterprise.The proposed design provides 25% optimization on medical benefit amount compared to current medical benefits amount therefore, gives better healthcare to all the employees.

A Stepwise Framework for Shared Decision Making in Pediatrics

It is poorly understood when and how to use shared decision making (SDM) in pediatrics. To address this gap, this chapter presents a practical stepwise framework for putting SDM into practice in pediatrics. This framework includes four steps. The first three steps pose a question to the physician, with the answers directing the physician further along the framework: Step 1 (Medical Reasonableness): Does the decision include more than one medically reasonable option? Step 2 (Benefit-Burden): Does one option have a favorable medical benefit–burden ratio compared to other options? Step 3 (Preference Sensitivity): How preference sensitive are the options? Step 4 (Calibration): This step provides direction on the specific SDM approach to use for the decision under consideration based on the answers to Steps 1 through 3 as well as other decisional characteristics present. For each step, we expound on its rationale, application, and potential issues.

Five Mitigations for the 10 Toxicities

Throughout the text we have discussed the necessity of sound and comprehensive medical benefit-risk assessment of digital health tools and have introduced the 10 Toxicities: privacy, security, misinformation, charlatanism, cybersecurity, overdiagnosis, cyberchondria, medical device deregulation, and user error. To many, these hazards appear new, evolving, and, possibly, overstated. The truth is, however, that there is preexisting precedent and numerous examples for all of them. This chapter presents five mitigations for these toxicities including awareness and education, a new regulatory paradigm, professionalism and workforce development, and new models of collaboration between health care and law enforcement. Fortunately, it is not too late to get ahead of the hazards of digital health and ensure optimized benefits and minimized risks.

A proactive medical necessity review program reduces revenue loss associated with outpatient medical benefit drugs

Purpose A common denial trend that occurs with “outpatient medical benefit drugs” (ie, medications covered by a medical benefit plan and administered in an outpatient visit) is payers not requiring or permitting prior authorization (PA) proactively, yet denying the drug after administration for medical necessity. In this situation, a preemptive strategy of complying with payer-mandated requirements is critical for revenue protection. To address this need, our institution incorporated a medical necessity review into its existing closed-loop, pharmacy-managed precertification and denials management program. Summary Referrals for targeted payers and high-cost medical benefit drugs not eligible for PA and deemed high risk for denial were incorporated into the review. Payer medical policies were evaluated and clinical documentation assessed to confirm alignment. This descriptive report outlines the medical necessity workflow as a component of the larger precertification process, details the decision-making process when performing the review, and delineates the roles and responsibilities for involved team members. A total of 526 drug orders were evaluated from September 2018 to August 2019, with 146 interventions completed. Of the 761 individual claims affected by proactive medical necessity review, 99.2% resulted in payment and less than 1% resulted in revenue loss, safeguarding more than $5.3 million in annual institutional drug reimbursement. At the time of analysis, there were only 3 cases of revenue loss. Conclusion Our institution’s pharmacy-managed medical necessity review program for high-cost outpatient drugs safeguards reimbursement for therapies not eligible for payer PA. It is a revenue cycle best practice that can be replicated at other institutions.

Participatory and responsive governance in universal health coverage: an analysis of legislative provisions in Thailand

Participatory and responsive governance in universal health coverage (UHC) systems synergistically ensure the needs of citizens are protected and met. In Thailand, UHC constitutes of three public insurance schemes: Civil Servant Medical Benefit Scheme, Social Health Insurance and Universal Coverage Scheme. Each scheme is governed through individual laws. This study aimed to identify, analyse and compare the legislative provisions related to participatory and responsive governance within the three public health insurance schemes and draw lessons that can be useful for other low-income and middle-income countries in their legislative process for UHC. The legislative provisions in each policy document were analysed using a conceptual framework derived from key literature. The results found that overall the UHC legislative provisions promote citizen representation and involvement in UHC governance, implementation and management, support citizens’ ability to voice concerns and improve UHC, protect citizens’ access to information as well as ensure access to and provision of quality care. Participatory governance is legislated in 33 sections, of which 23 are in the Universal Coverage Scheme, 4 in the Social Health Insurance and none in the Civil Servant Medical Benefit Scheme. Responsive governance is legislated in 24 sections, of which 18 are in the Universal Coverage Scheme, 2 in the Social Health Insurance and 4 in the Civil Servant Medical Benefit Scheme. Therefore, while several legislative provisions on both participatory and responsive governance exist in the Thai UHC, not all schemes equally bolster citizen participation and government responsiveness. In addition, as legislations are merely enabling factors, adequate implementation capacity and commitment to the legislative provisions are equally important.