Eggli Yves, Desquins Béatrice, Seker Erol, Halfon Patricia
Institute of Health Economics and Management, Centre Hospitalier Universitaire Vaudois and University of Lausanne (Faculty of Business and Economics and Faculty of Biology and Medicine), Route de Chavannes 31, CH-1015, Lausanne, Switzerland.
BMC Health Serv Res. 2014 Jan 20;14:25. doi: 10.1186/1472-6963-14-25.
Regional rates of hospitalization for ambulatory care sensitive conditions (ACSC) are used to compare the availability and quality of ambulatory care but the risk adjustment for population health status is often minimal. The objectives of the study was to examine the impact of more extensive risk adjustment on regional comparisons and to investigate the relationship between various area-level factors and the properly adjusted rates.
Our study is an observational study based on routine data of 2 million anonymous insured in 26 Swiss cantons followed over one or two years. A binomial negative regression was modeled with increasingly detailed information on health status (age and gender only, inpatient diagnoses, outpatient conditions inferred from dispensed drugs and frequency of physician visits). Hospitalizations for ACSC were identified from principal diagnoses detecting 19 conditions, with an updated list of ICD-10 diagnostic codes. Co-morbidities and surgical procedures were used as exclusion criteria to improve the specificity of the detection of potentially avoidable hospitalizations. The impact of the adjustment approaches was measured by changes in the standardized ratios calculated with and without other data besides age and gender.
25% of cases identified by inpatient main diagnoses were removed by applying exclusion criteria. Cantonal ACSC hospitalizations rates varied from to 1.4 to 8.9 per 1,000 insured, per year. Morbidity inferred from diagnoses and drugs dramatically increased the predictive performance, the greatest effect found for conditions linked to an ACSC. More visits were associated with fewer PAH although very high users were at greater risk and subjects who had not consulted at negligible risk. By maximizing health status adjustment, two thirds of the cantons changed their adjusted ratio by more than 10 percent. Cantonal variations remained substantial but unexplained by supply or demand.
Additional adjustment for health status is required when using ACSC to monitor ambulatory care. Drug-inferred morbidities are a promising approach.
门诊护理敏感型疾病(ACSC)的区域住院率用于比较门诊护理的可及性和质量,但对人群健康状况的风险调整往往很少。本研究的目的是检验更广泛的风险调整对区域比较的影响,并调查各种地区层面因素与经适当调整后的比率之间的关系。
我们的研究是一项基于瑞士26个州200万匿名参保者一到两年常规数据的观察性研究。采用二项负回归模型,纳入关于健康状况的信息越来越详细(仅年龄和性别、住院诊断、从配药推断的门诊疾病以及就诊频率)。通过主要诊断确定19种ACSC疾病的住院情况,并采用更新后的ICD - 10诊断编码列表。将合并症和外科手术作为排除标准,以提高对潜在可避免住院情况检测的特异性。通过比较使用年龄和性别之外的其他数据与不使用这些数据计算出的标准化比率的变化,来衡量调整方法的影响。
通过应用排除标准,住院主要诊断确定的病例中有25%被排除。各州ACSC住院率为每年每1000名参保者1.4至8.9例。从诊断和药物推断出的发病率显著提高了预测性能,对与ACSC相关的疾病影响最大。就诊次数越多,可避免住院情况越少,尽管就诊次数非常多的人风险更高,而未就诊的人风险可忽略不计。通过最大限度地调整健康状况,三分之二的州调整后的比率变化超过10%。各州之间的差异仍然很大,但无法用供给或需求来解释。
在使用ACSC监测门诊护理时,需要对健康状况进行额外调整。通过药物推断发病率是一种很有前景的方法。