TY - JOUR AU - Duangnet, Chatree AU - Panyasorn, Jinhatha AU - Phengpinit, Noppadol AU - Jarunai, Warangkana AU - Worachat, Natamon AU - Taweecharoen, Ritthikrai AU - Kunanusont, Chaiyos PY - 2019/09/20 Y2 - 2024/03/29 TI - Rational Classification of Simple Disease Cases in Bangkok Dusit Medical Services Hospitals using Relative Weight and Case Mixed Index JF - The Bangkok Medical Journal JA - BKK Med J VL - 15 IS - 2 SE - Original Article DO - 10.31524/bkkmedj.2019.09.001 UR - https://he02.tci-thaijo.org/index.php/bkkmedj/article/view/222604 SP - 130 AB - <div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p>OBJECTIVES: This study proposes using relative weights (RW) of specific health conditions or diagnoses as a simple tool to differentiate simple from not-simple disease cases.</p><p>MATERIALAND METHODS: Using data from 1,558 records of closed chart review, conducted by Utilization Management and Third-party-payer Services (UM) of Bangkok Dusit Medical Services (BDMS) and a list of simple diseases advised by five health insurance partners, we compared discriminating power of various RW levels. Scenario assessment was conducted to quantify number of cases that could be missed out and turn into risk management (RM) cases.</p><p>RESULT: RW of 0.3 could categorize 22 (71%) of 31 conditions as simple diseases while RW of 0.4 had the power to categorize 27 (87%) and RW of 0.8 could categorize 31 (100%) of the whole list. Scenario assessment showed increasing risk management (RM) cases from 8 cases using RW = 0.3 to 42 cases (5.3 folds) using RW = 0.4 and to 141 cases (17.6 folds) when RW = 0.8 was used. Although greater RW threshold could capture greater proportion of simple diseases, it could result exponentially increase of RM cases. As a result, RW = 0.4 would be the optimum and practical cut-off point to differentiate simple from not-simple diseases. To monitor hospital performance, different levels of “Percentage of simple disease” should be applied due to different complexity (indicated by case mixed index-CMI) of hospitals in BDMS network. We propose “Yellow zones” of 10%-20% for super tertiary care (CMI &gt; 2.0), 40% - 50% for hub tertiary care (CMI 1.00 – 1.99), 60% - 70% for basic tertiary care (CMI 0.50 – 0.99) and 70% - 80% for secondary care (CMI &lt; 0.5) hospitals. Only continuous monitoring is required when performance stays below these yellow zones. However, when the proportion of simple disease is in the yellow zones, hospital management should pay specific attention. If the situation progressed and theproportion is higher than the upper limit of the yellow zone, special interventions of hospital management and insurance partners would be urgently required.</p><p>CONCLUSION: Our data showed that RW of 0.4 was the optimum threshold to differentiate simple from not-simple diseases as it could cover 87% of the current list of simple diseases with minimum number of possible RM cases. Different ranges of proportions of simple diseases are proposed for different complexity of BDMS hospitals according to their case complexity, reflected by case mixed index (CMI). More studies using data from other networks are recommended for broader application of this concept.</p></div></div></div> ER -