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王敬鑫, 崔逢莉, 孟显峰, 杨文怡, 徐英娟, 艾丽梅, 尹新国, 陈萍, 王春平, 盛红旗, 万霞. 再入院比例调整在医保数据计算潍坊市居民脑卒中发病率中应用[J]. 中国公共卫生, 2024, 40(2): 211-217. DOI: 10.11847/zgggws1141555
引用本文: 王敬鑫, 崔逢莉, 孟显峰, 杨文怡, 徐英娟, 艾丽梅, 尹新国, 陈萍, 王春平, 盛红旗, 万霞. 再入院比例调整在医保数据计算潍坊市居民脑卒中发病率中应用[J]. 中国公共卫生, 2024, 40(2): 211-217. DOI: 10.11847/zgggws1141555
WANG Jingxin, CUI Fengli, MENG Xianfeng, YANG Wenyi, XU Yingjuan, AI Limei, YIN Xinguo, CHEN Ping, WANG Chunping, SHENG Hongqi, WAN Xia. Application of readmission ratio adjustment in calculating the incidence rate of stroke in residents of Weifang city: a medical insurance data-based analysis[J]. Chinese Journal of Public Health, 2024, 40(2): 211-217. DOI: 10.11847/zgggws1141555
Citation: WANG Jingxin, CUI Fengli, MENG Xianfeng, YANG Wenyi, XU Yingjuan, AI Limei, YIN Xinguo, CHEN Ping, WANG Chunping, SHENG Hongqi, WAN Xia. Application of readmission ratio adjustment in calculating the incidence rate of stroke in residents of Weifang city: a medical insurance data-based analysis[J]. Chinese Journal of Public Health, 2024, 40(2): 211-217. DOI: 10.11847/zgggws1141555

再入院比例调整在医保数据计算潍坊市居民脑卒中发病率中应用

Application of readmission ratio adjustment in calculating the incidence rate of stroke in residents of Weifang city: a medical insurance data-based analysis

  • 摘要:
    目的 探讨再入院比例调整方法在医保数据计算山东省潍坊市居民脑卒中发病率中的应用,为医保数据库中慢性病首次发病率的估算提供参考依据。
    方法 收集2016年1月1日 — 2020年12月31日潍坊市城乡居民和城镇职工医保信息系统数据,以4年为洗脱期计算2020年潍坊市居民脑卒中发病率,计算分性别、年龄、医保类型的次年至隔3年再入院比例调整系数(Ri),采用再入院比例调整方法计算2016 — 2019年脑卒中发病率,应用Joinpoint模型计算年度变化百分比(APC)分析发病率随年份的变化趋势,并进一步计算标化发病率和不同人群(性别、年龄、医保类型)的发病特征,采用Pearson χ2检验进行组间比较。
    结果 潍坊市居民次年、空隔1年、空隔2年、空隔3年的缺血性卒中和出血性卒中的Ri依次为15.78%和7.52%、6.09%和1.35%、3.89%和0.89%、2.86%和0.83%;经再入院比例调整后,2016 — 2020年分别有71.58%、71.49%、70.09%、70.77%、70.92%的缺血性卒中住院患者和89.39%、89.37%、88.92%、88.92%、90.30%的出血性卒中住院患者为新发病例,缺血性卒中和出血性卒中标化发病率分别为542.41/10万和69.36/10万、579.78/10万和69.78/10万、514.82/10万和66.36/10万、531.96/10万和65.16/10万、557.29/10万和65.55/10万。Joinpoint分析结果显示,2016 — 2020年缺血性卒中发病趋势无显著变化,出血性卒中发病呈下降趋势(APC = – 1.78%,t = – 3.41,P < 0.05)。2016 — 2020年潍坊市男性居民缺血性卒中和出血性卒中标化发病率分别为女性的1.12~1.20倍和1.26~1.41倍;缺血性卒中和出血性卒中发病率均随年龄增长而上升,缺血性卒中在55~59岁出现拐点,上升速度加快,70 ~ 74岁之后变得平缓,出血性卒中无明显拐点;居民医保居民2016 — 2020年缺血性卒中和出血性卒中发病率依次为515.47/10万和69.01/10万、569.41/10万和69.78/10万、562.87/10万和72.96/10万、611.68/10万和73.60/10万、690.49/10万和79.66/10万,职工医保居民2016 — 2020年缺血性卒中和出血性卒中发病率依次为468.55/10万和51.25/10万、519.46/10万和58.93/10万、483.71/10万和57.75/10万、496.65/10万和58.85/10万、492.22/10万和55.25/10万,不同医保类型居民比较,居民医保居民缺血性卒中和出血性卒中各年份发病率均高于职工医保居民(均P < 0.05)。
    结论 再入院比例调整方法可以通过医保数据库估算脑卒中的首次发病率,通过此方法估算出潍坊市居民的脑卒中发病率较高,尤其是缺血性卒中,但随时间变化无上升趋势,男性、老年人和居民医保居民为该地区脑卒中的重点干预对象。

     

    Abstract:
    Objective To explore the application of readmission ratio adjustment method in calculating the incidence rate of stroke among residents in Weifang city, Shandong province for estimating the first incidence rate of chronic diseases based on medical insurance database.
    Methods The data on medical insurance reimbursement of hospitalizations due to ischemic and hemorrhagic stroke from 2016 through 2020 were collected from the Information System of Medical Insurance for urban and rural residents and that for urban employees in Weifang city. The gender-, age-, and medical insurance type-specific readmission rate coefficient (Ri, %) of different clearance periods (1 – 4 years) for the hospitalizations of the stroke inpatients during the period were calculated based on the data collected and then the calculated Ris were adopted to adjust the observed annual incidence rate of ischemic stroke and hemorrhagic stroke among the residents of Weifang city from 2016 to 2020 with the clearance period of 1 to 4 years, respectively. The annual percentage change (APC) was analyzed by using the Joinpoint model to assess changing trend in the adjusted stroke incidence rates over the years. Furthermore, the gender-, age-, and medical insurance type-specific standardized incidence rates were also calculated and compared using Pearson chi-square test.
    Results The overall Ri of clearance periods of 1 – 4 years for ischemic stroke hospitalizations in the city were 15.78%, 6.09%, 3.89%, and 2.86% and those for hemorrhagic stroke were 7.52%, 1.35%, 0.89%, and 0.83%, respectively. After the readmission rate adjustment and for the years from 2016 to 2020, the proportion of newly diagnosed cases among the yearly ischemic stroke inpatients were 71.58%, 71.49%, 70.09%, 70.77%, and 70.92%, and the proportion of newly diagnosed cases of hemorrhagic stroke was 89.39%, 89.37%, 88.92%, 88.92%, and 90.30%; the standardized incidence rates (1/ 100 000) of ischemic stroke were 542.41, 579.78, 514.82, and 531.96 and those of hemorrhagic stroke were 69.36, 69.78, 66.36, 65.16, and 65.55 for the populations in Weifang city, respectively. The Joinpoint analysis results showed that there was no significant change trend in ischemic stroke incidence from 2016 to 2020, but there was a downward trend in the incidence of hemorrhagic stroke (APC = – 1.78%, t = – 3.41, P < 0.05). During the 5-year period in the city, the standardized incidence rates of ischemic stroke and hemorrhagic stroke for male residents were 1.12 – 1.20 times and 1.26 – 1.41 times higher than those for female residents. The incidence rate of both ischemic stroke and hemorrhagic stroke increased with age. The incidence of ischemic stroke showed an accelerated increase at the age of 55 – 59, followed by a slowing down after the age of 70 – 74; while no obvious turning point was observed for the incidence of hemorrhagic stroke. For the residents with medical insurance in the city from 2016 to 2020, the incidence rates (1/ 100 000) of ischemic stroke were 515.47, 569.41, 562.87, 611.68, 690.49, and 515.47 and those of hemorrhagic stroke were 69.01, 69.78, 72.96, 73.6, and 79.66; for the employees with medical insurance, the incidence rates (1/ 100 000) of ischemic stroke were 468.55, 519.46, 483.71, 496.65, and 492.22 and those of hemorrhagic stroke were 51.25, 58.93, 57.75, 58.85, and 55.25/100000, respectively, indicating higher incidence rates of ischemic stroke and hemorrhagic stroke in the residents with medical insurance than those in the employees with medical insurance in all years (all P < 0.05).
    Conclusion The readmission rate adjustment method could be used to estimate the incidence rate of stroke based on the medical insurance database. The analysis with this method reveals a relatively high incidence rate of stroke among the residents in Weifang city during 2016 – 2020, especially for that of ischemic stroke, however, there was no upward trend in the incidence rate over the period; the analysis also indicates that the males, the elderly, and the individuals with the medical insurance for urban and rural residents are key populations for stroke prevention in the city.

     

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