BackgroundThe 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.MethodsWe 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).ResultsIn 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.ConclusionsIn 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.

Background: Health records are the basis of clinical coding. In Portugal, relevant diagnoses and procedures are abstracted and categorised using an internationally accepted classification system and the resulting codes, together with the administrative data, are then grouped into diagnosis-related groups (DRGs). Hospital reimbursement is partially calculated from the DRGs. Moreover, the administrative database generated with these data is widely used in research and epidemiology, among other purposes. Objective: To explore the perceptions of medical coders (medical doctors) regarding possible problems with health records that may affect the quality of coded data. Method: A qualitative design using four focus groups sessions with 10 medical coders was undertaken between October and November 2017. The convenience sample was obtained from four public hospitals in Portugal. Questions related to problems with the coding process were developed from the literature and authors’ expertise. The focus groups sessions were taped, transcribed and analysed to elicit themes. Results: There are several problems, identified by the focus groups, in health records that influence the coded data: the lack of or unclear documented information; the variability in diagnosis description; “copy & paste”; and the lack of solutions to solve these problems. Conclusion and implications: The use of standards in health records, audits and physician awareness could increase the quality of health records, contributing to improvements in the quality of coded data, and in the fulfilment of its purposes (e.g. more accurate payments and more reliable research).

A retrospective study was performed to investigate seasonal variation in stroke incidence and to evaluate the hypothesis that cold might be a risk factor. Data were obtained from the central registry of the Hospital de S. João, Porto, Portugal, concerning 4048 patients consecutively admitted for cerebrovascular disease during a period of 33 months. Monthly admissions for stroke and its subtypes were related to mean values of ambient temperature using linear correlation. There was a strong inverse correlation between average temperature and total admissions for cerebrovascular disease (r = -0.72, P < 0.00005), intracerebral haemorrhage (r = -0.66, P < 0.00005), ischaemic stroke (r = -0.46, P = 0.007) and transient ischaemic attack (r = -0.41, P = 0.017). These correlations were independent of any seasonal variation in the number of hospital admissions due to all causes. No relation was found between temperature and subarachnoid haemorrhage. The rhythmometric analysis showed the presence of a statistically significant rhythm with an acrophase in the coldest months. These results support the hypothesis of stroke being a chronorisk disease to which cold might represent a triggering factor.

Several methods have been used for the detection of ADRs, but they are difficult to apply at a national level. Spontaneous reporting is widely used but grossly underestimates the frequency of ADRs. The database methodology can be very useful to estimate ADRs frequency and to perform a simple characterization of ADRs nationwide.