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家庭健康访视时长的决定因素:一项多中心前瞻性研究的结果

Determinants of home health visit length: results of a multisite prospective study.

作者信息

Payne S M, Thomas C P, Fitzpatrick T, Abdel-Rahman M, Kayne H L

机构信息

Case Western Reserve University, Cleveland, OH 44109-1998, USA.

出版信息

Med Care. 1998 Oct;36(10):1500-14. doi: 10.1097/00005650-199810000-00008.

Abstract

OBJECTIVES

The authors (1) compare visit length across four categories of skilled nursing home health visits which reflect recent changes in home health casemix-AIDS-related, hospice/terminal (HT), intravenous (IV) therapy, and maternal and child health (MCH)-with general adult medical/surgical (MS) visits and (2) identify factors influencing visit length.

METHODS

The study sites were 12 nonproprietary Massachusetts home health agencies (HHAs). Staff nurses collected data concurrently on a sample of visits they provided between December 1, 1992 and November 30, 1993. The visits were stratified by agency, time of year, and visit category. The authors used analysis of variance to test for significant differences across visit categories in Home Length of Visit (the number of minutes between when the nurse entered and left the home) (HLOV). The authors used multivariate regression analysis to develop models identifying determinants of HLOV and adjusted R2 to measure the explanatory power of partial models.

RESULTS

In univariate analysis, the categories differed significantly from each other in length (P < 0.0001). HT visits were the longest (median visit length = 60, 80, and 59 minutes for HT Only visits, visits in both the HT and AIDS categories (HT/AIDS), and HT/IV visits, respectively). MS visits were the shortest (median = 30 minutes). The remaining categories were intermediate in length (medians = 37 to 50 minutes). Almost half the variability in HLOV was explained by the full multivariate regression model, which includes all independent variables (adjusted R2 = .4486; P < 0.0001). Visit characteristics alone in a partial model explained 18% of the variability in HLOV. Three other variable sub-groups-agency, client characteristics, and nursing workload-each explained about 15% of the variability in HLOV. Nursing activities performed during the visit explained 11%; several of these related to teaching, education, or assessment.

CONCLUSIONS

Accurate reimbursement reflecting casemix differences is important to protect the teaching, education, and assessment functions of nurses; measure nurse productivity and allocate caseloads; maintain access to services for clients with greater needs; and avoid creating economic disincentives to the agencies that serve them. Payers formulating prospective payment systems can adjust per visit reimbursement rates to reflect differences in visit length by category and incorporate functional limitations, clinical instability, and case coordination as classification variables. Developers of home health casemix systems can use factor analysis to improve the robustness of multivariate models and include nursing workload in predicting visit length. Home health agencies measuring productivity and caseload across complex client populations can classify visits into three groups-MS; HT; and AIDS, IV, and MCH-or use the regression results to develop more refined predictors of visit length and nursing caseload.

摘要

目的

作者(1)比较四类熟练护理院健康访视的访视时长,这四类访视反映了家庭健康病例组合的近期变化——与艾滋病相关的、临终关怀/晚期(HT)、静脉注射(IV)治疗以及母婴健康(MCH)——并与一般成人医疗/外科(MS)访视进行比较;(2)确定影响访视时长的因素。

方法

研究地点为马萨诸塞州的12家非盈利性家庭健康机构(HHA)。1992年12月1日至1993年11月30日期间,护士工作人员在其提供的访视样本中同时收集数据。访视按机构、年份和访视类别进行分层。作者使用方差分析来检验不同访视类别在家庭访视时长(护士进入和离开家庭之间的分钟数)(HLOV)方面的显著差异。作者使用多元回归分析来建立模型,以确定HLOV的决定因素,并使用调整后的R²来衡量部分模型的解释力。

结果

在单变量分析中,各类别在时长上存在显著差异(P < 0.0001)。HT访视最长(仅HT访视、HT和艾滋病类别(HT/AIDS)访视以及HT/IV访视的中位访视时长分别为60、80和59分钟)。MS访视最短(中位时长 = 30分钟)。其余类别时长居中(中位数 = 37至50分钟)。完整的多元回归模型解释了HLOV中近一半的变异性,该模型包括所有自变量(调整后的R² = 0.4486;P < 0.0001)。部分模型中仅访视特征就解释了HLOV变异性的18%。其他三个变量子组——机构、客户特征和护理工作量——各自解释了HLOV变异性的约15%。访视期间进行的护理活动解释了11%;其中一些与教学、教育或评估有关。

结论

准确反映病例组合差异的报销对于保护护士的教学、教育和评估功能;衡量护士生产力和分配工作量;维持对有更大需求客户的服务可及性;以及避免对为他们服务的机构产生经济抑制因素很重要。制定前瞻性支付系统的付款人可以调整每次访视的报销率,以反映不同类别访视时长的差异,并将功能限制、临床不稳定和病例协调作为分类变量纳入。家庭健康病例组合系统的开发者可以使用因子分析来提高多元模型的稳健性,并在预测访视时长时纳入护理工作量。衡量复杂客户群体生产力和工作量的家庭健康机构可以将访视分为三组——MS;HT;以及艾滋病、IV和MCH——或者使用回归结果来开发更精确的访视时长和护理工作量预测指标。

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