Factors influencing hospital high length of stay outliers.

BACKGROUND: The study of length of stay (LOS) outliers is important for the management and financing of hospitals. Our aim was to study variables associated with high LOS outliers and their evolution over time. METHODS: We used hospital administrative data from inpatient episodes in public acute care hospitals in the Portuguese National Health Service (NHS), with discharges between years 2000 and 2009, together with some hospital characteristics. The dependent variable, LOS outliers, was calculated for each diagnosis related group (DRG) using a trim point defined for each year by the geometric mean plus two standard deviations. Hospitals were classified on the basis of administrative, economic and teaching characteristics. We also studied the influence of comorbidities and readmissions. Logistic regression models, including a multivariable logistic regression, were used in the analysis. All the logistic regressions were fitted using generalized estimating equations (GEE). RESULTS: In near nine million inpatient episodes analysed we found a proportion of 3.9% high LOS outliers, accounting for 19.2% of total inpatient days. The number of hospital patient discharges increased between years 2000 and 2005 and slightly decreased after that. The proportion of outliers ranged between the lowest value of 3.6% (in years 2001 and 2002) and the highest value of 4.3% in 2009. Teaching hospitals with over 1,000 beds have significantly more outliers than other hospitals, even after adjustment to readmissions and several patient characteristics. CONCLUSIONS: In the last years both average LOS and high LOS outliers are increasing in Portuguese NHS hospitals. As high LOS outliers represent an important proportion in the total inpatient days, this should be seen as an important alert for the management of hospitals and for national health policies. As expected, age, type of admission, and hospital type were significantly associated with high LOS outliers. The proportion of high outliers does not seem to be related to their financial coverage; they should be studied in order to highlight areas for further investigation. The increasing complexity of both hospitals and patients may be the single most important determinant of high LOS outliers and must therefore be taken into account by health managers when considering hospital costs.

The Impact of Electronic Obstetric Records Using the ObsCare Software on Scientific Production.

AIMS: To compare the characteristics of scientific publications performed in hospitals that used with those that didn't use an obstetric electronic health record (EHR). METHODS: This study included two reviews (A and B). Review A was an exploratory analysis of all 100 abstracts presented at the Scientific Meeting of the Portuguese Society of Obstetrics and Maternal-Fetal Medicine, in November 2017. Review B was a systematic review of studies in obstetrics, performed in Portugal and published between 2016-18 and indexed in PubMed. In both reviews, the included papers/abstracts were divided into two groups: from hospitals that used ObsCare® (ObsCare group) and from hospitals without a specific obstetric EHR or that didn't use ObsCare (sObsCare group). RESULTS: In both reviews, the sample size was significantly higher in hospitals from the ObsCare group. In review B, the length of the study period was also significantly longer in ObsCare group; no significant difference was found in review A. CONCLUSION: Publications from hospitals that used an obstetric specific EHR (ObsCare), included a higher number of patients and longer study periods.

Can openEHR Represent the Clinical Concepts of an Obstetric-Specific EHR - ObsCare Software?

ObsCare is an obstetric-specific Electronic Health Record in use in nine Portuguese obstetric departments. Like other EHRs, it faces major challenges related to semantic interoperability and data quality. openEHR is proposed to address those needs. This study aimed to describe a summary representation of Obscare workflow and to validate whether archetypes in the openEHR Clinical Knowledge Manager repository can represent ObsCare clinical concepts. The study included the phases: a) ObsCare form selection; b) Description of the workflow care process; c) Detailed data extraction; and d) CKM models analysis. 379 variables were analyzed: 219 were fully represented in CKM repository; 99 were partially represented and needed archetype modification; and 61 were not represented and need new archetypes. To conclude, our study showed that the openEHR CKM repository requires further enhancements to be able to fully answer to the needs of an obstetric-specific EHR, the ObsCare software.

From ObsCare Software to an OpenEHR Platform: Modelling Obstetric Archetypes.

INTRODUCTION AND AIMS: Electronic health records (EHRs) are important tools to facilitate communication between care providers and to improve clinical research. In obstetrics they became essential. The ObsCare software was created to answer to the need for an EHR with specific obstetric features. The present study aimed to develop openEHR-archetypes capable of representing an ObsCare® EHR form and to create an openEHR-template using the developed archetypes. METHODS: The study was performed in four phases: 1) selection and description of the ObsCare form; 2) Clinical Knowledge Manager (CKM) analysis; 3) modelling of the archetypes; 4) creation and testing of the template. RESULTS: One openEHR-archetype - Newborn summary - was modelled to assemble the following three clinical concepts that were not represented in CKM: hours of life, "Examination of newborn movements" and "Examination of reflexes". Finally, an openEHR-template was built and automatically converted into an EHR by VCIntegrator. CONCLUSIONS: Considering the potential to improve clinical research, we believe that more obstetric-gynecologic clinical statements should be modelled into openEHR.