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PURPOSE: Identification and mitigation of obesity-related risks to staff and healthcare organisations can occur using patient obesity data; however, a 2017/18 audit of obesity data accuracy was assessed to be poor. This study investigates the results of an intervention to improve obesity data recording and coding accuracy at an Australian hospital. BACKGROUND: Increasing population obesity rates result in increased organisational and financial risks to hospitals. Australian obesity prevalence has steadily increased since 1995, and 42% of the Australian population is predicted to be obese in 2035. To reduce risks to healthcare staff who care for obese patients, complete and accurate obesity recording is required. METHODS: Following a previous audit of obesity recording and coding accuracy of patients admitted to hospital with Type II diabetes, a 12-month intervention was undertaken, comprising staff education, introduction of tape measures and obesity decision-making tools, recording of patient volunteered height, regular reinforcement of obesity recording requirements and enhanced clinical coding of obesity. A re-audit was subsequently conducted to determine if the intervention impacted obesity recording and coding at the previously audited site. RESULTS: Improved recording of obesity-related measures and obesity data accuracy were observed, including increased patient BMI, impacted by increased patient height measurements and increased patient weight measurements. Obesity recording accuracy increased due to the intervention, including increased sensitivity, increased negative predictive values and reduced false negatives. CONCLUSION: The obesity recording intervention was successful; however, as hospitals increasingly use electronic health records, improvement opportunities should be considered such as compulsory recording of patient weight and height, embedded BMI calculators and "check boxes" for recording impacts of obesity conditions on treatment. Immediate improvement of obesity recording in manual patient files can be achieved in the meantime by implementing targets of 100% weight, height and BMI recording, introducing education programs and auditing compliance.
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PURPOSE: Pressure on Australia's healthcare system is increasing annually due to corresponding increases in chronic diseases such as obesity and rapidly ageing population growth across Australia, resulting in requirements for increased funding. This study investigates the financial impact to hospitals due to inaccurate obese patient recording and coding. BACKGROUND: Australian healthcare organisations receive Activity-Based Funding (ABF) which provides reimbursement of costs relating to the type of patient care delivered and the resources required for the patient treatment. Accurate healthcare data are essential to ensure accuracy of ABF and appropriate reimbursement of costs incurred by hospitals that manage obese patients. Managing obese patients results in operational funding requirements such as increased staffing and purchasing of equipment such as hoists, bariatric wheelchairs and bariatric beds, and hospitals must ensure that these clinical requirements are documented accurately in order to be reimbursed of these costs by way of ABF. METHODS: This study identifies the financial implications of inaccurate obesity data within the Western Australian Country Health Service (WACHS) and examines factors that may affect obesity data recording accuracy. The study involves 85 cases of identified obesity data recording inaccuracy that were adjusted by entering corrected obesity codes, which then adjusted Diagnosis-related Groups, National Weighted Activity Units and Activity-Based Funding results. RESULTS: The study demonstrated estimated annual lost funding opportunities of $2.23 million due to obesity coding inaccuracy. An annual average of 616 cases of obesity data inaccuracy was calculated with an average lost funding opportunity of $3625 per case. CONCLUSION: Improvements are required in the clinical recording and coding of patient obesity, such as mandatory recording of patient weight and height data and automated BMI calculations within electronic patient records. Enhanced obesity recording and coding accuracy will result in increased funding opportunities and reduced cost burdens that hospitals currently experience when required to fund obesity-related clinical and safety requirements within operational budgets.
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This literature review explores obesity risks to healthcare staff and organizations that manage and caring for obese (bariatric) patients. These risks are anticipated to increase due to Australian population obesity rate projections increasing from 31% in 2018 to 42% by the year 2035, which will result in increased hospital admissions of patients with obesity. Literature searches were conducted through the Cumulative Index to Nursing and Allied Health Literature (CINAHL), MEDLINE, Scopus, and Web of Science. Thirty studies met the inclusion criteria and were tabulated and critiqued using appropriate appraisal techniques. High risk of injury to healthcare staff was identified relating to bariatric patient handling tasks. High liability and financial risks of organizations were also identified relating to workers' compensation and common law claims by injured staff and medical negligence claims by patients with obesity. Availability of obesity data was identified within clinically captured information, which could be utilized to inform obesity risk management programs. Future research should focus on improving the use and quality of obesity data to better understand obesity risks to healthcare organizations and staff, including accurate identification of obese patient admissions, enhanced ability to measure bariatric patient handling hazards and related staff injuries and improved assessment of bariatric intervention effectiveness.