EMRs have been full of data being put in by healthcare organizations for years, resulting in a lot of data, and most likely an inaccurate problem list. There are certain concepts to be followed for the HCC risk adjustment model, and having an accurate problem list is one of them. Reporting a complete picture of the risk adjustment factor increases the accuracy of the patient score and ideally reduces the need to request medical records or audit providers’ claims. According to the ‘American Academy of Family Physicians, “hierarchical condition category coding helps communicate patient complexity and paint a picture of the whole patient,” helping to appropriately measure quality and cost performance. Healthy patients have a below-average RAF score so revenue from the insurance premium is transferred from healthy patients to patients with an above-average RAF score. The HCC model assigns a Risk Adjustment Factor (RAF) score to each patient basis patient’s demographics and diagnoses, which is a relative measure of how costly that patient is anticipated to be. This article walks through the basics of the risk adjustment model and how the provider can ensure accuracy in documentation and HCC coding to achieve swift and maximal reimbursements. With the rising number of beneficiaries enrolled in Health insurance Advantage plans, it’s more important than ever for healthcare organizations to pay attention to this model and make sure physicians are coding diagnoses appropriately to ensure fair compensation. Inaccurate HCC coding not only affects the patients and payers but also has an impact on healthcare organizations’ reimbursement. Recommendations for the successful implementation of MFMs included wide consultation with food-service and DHB staff, the need to provide evidence on the success of MFMs and alternatives, consideration of the wider food environment, and provision of dietitian support for the food service.The Hierarchical Condition Category (HCC) risk adjustment model is an integral element within the medical coding world. Qualitative analysis of the interviews and open-ended questions of the survey identified four key themes (1) ‘Change and choice’, MFMs’ impact on personal choice and resistance to changing eating habits (2) ‘Getting it right-product and price’, food quality, appearance, nutritional balance, and the impact of an MFM policy on customer retention and sales (3) ‘Human and planetary health’, the co-benefits of MFMs and hospitals as leaders in healthy, sustainable diets (4) ‘Implementation success’, including consultation, communications, and education, for a successful MFM policy and maintaining staff wellbeing. Of those surveyed, 59% were positive towards MFMs, and 31% were negative. Of those surveyed, 51% were actively cutting back on meat, mainly for health and environmental concerns and enjoyment of plant-based dishes. The online survey received 194 responses (105 from Auckland and 89 from Nelson and Marlborough). We conducted an online staff survey at two DHBs and eleven semi-structured interviews with food-service managers, café managers, and sustainability managers. We conducted a mixed-methods investigation at these District Health Boards along with Auckland (who were not considering an MFM policy) of the attitudes of DHB staff and managers towards MFMs and the implementation barriers and enablers. In 2020, Nelson Marlborough District Health Board (DHB) introduced an MFM policy at their staff and guest cafes, and Northland DHB trialled an MFM policy for two months. Meat-Free Mondays (MFM) is a global campaign to reduce meat consumption by 15% to improve human and planetary health. Reducing human meat intake contributes to a reduction in environmental degradation and non-communicable diseases, but meat-reduction policy interventions are limited, and globally, meat intake remains high.
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