Reducing hospital inpatient lengths of stay

Adoption of high technology medical imaging and hospital quality and efficiency: Towards a conceptual framework

Measuring the value of medical imaging is challenging, in part, due to the lack of conceptual frameworks underlying potential mechanisms where value may be assessed. To address this gap, this article proposes a framework that builds on the large body of literature on quality of hospital care and the classic structure-process-outcome paradigm. The framework was also informed by the literature on adoption of technological innovations and introduces 2 distinct though related aspects of imaging technology not previously addressed specifically in the literature on quality of hospital care: adoption (a structural hospital characteristic) and use (an attribute of the process of care). The framework hypothesizes a 2-part causality where adoption is proposed to be a central, linking factor between hospital structural characteristics, market factors, and hospital outcomes (ie, quality and efficiency). The first part indicates that hospital structural characteristics and market factors influence or facilitate the adoption of high technology medical imaging within an institution. The presence of this technology, in turn, is hypothesized to improve the ability of the hospital to deliver high quality and efficient care. The second part describes this ability throughout 3 main mechanisms pointing to the importance of imaging use on patients, to the presence of staff and qualified care providers, and to some elements of organizational capacity capturing an enhanced clinical environment. The framework has the potential to assist empirical investigations of the value of adoption and use of medical imaging, and to advance understanding of the mechanisms that produce quality and efficiency in hospitals.

The Contribution of Ageing to Hospitalisation Days in Hong Kong: A Decomposition Analysis

Background: Ageing has become a serious challenge in Hong Kong and globally. It has serious implications for health expenditure, which accounts for nearly 20% of overall government expenditure. Here we assess the contribution of ageing and related factors to hospitalisation days in Hong Kong. We used hospital discharge data from all publicly funded hospitals in Hong Kong between 2001 and 2012.

Methods: A decomposition method was used to examine the factors that account for the change of total hospitalisation days during the two periods, 2001-2004 and 2004-2012. The five factors include two demographic factors – population size and age-gender composition – and three service components – hospital discharge rate, number of discharge episodes per patient, and average length of stay (LOS) – which are all measured at age-gender group level. In order to assess the health cost burden in the future, we also project the total hospitalisation days up to 2041, for a range of scenarios.

Results: During the decreasing period of hospitalisation days (2001-2004), the reduction of LOS contributed to about 60% of the reduction. For the period of increase (2004-2012), ageing is associated with an increase in total hospitalisation days of 1.03 million, followed by an increase in hospital discharge rates (0.67 million), an increase in the number of discharge episodes per patient (0.62 million), and population growth (0.43 million). The reduction of LOS has greatly offset these increases (-2.19 million days), and has become one of the most significant factors in containing the increasing number of hospitalisation days. Projected increases in total hospitalisation days under different scenarios have highlighted that the contribution of ageing will become even more prominent after 2022.

Conclusion: Hong Kong is facing increasing healthcare burden caused by the rapid increase in demand for inpatient services due to ageing. Better management of inpatient services with the aim of increasing efficiency and reducing LOS, avoidable hospitalisation and readmission, without compromising patient satisfaction and quality of service, are crucial for containing the rapid and enormous increases in total hospitalisation days for Hong Kong. The results would be relevant to many rapidly ageing societies in this region.

Ethnic variations in unplanned readmissions and excess length of hospital stay: a nationwide record-linked cohort study

Background: Studies in the USA have shown ethnic inequalities in quality of hospital care, but in Europe, this has never been analysed. We explored variations in indicators of quality of hospital care by ethnicity in the Netherlands. Methods: We analysed unplanned readmissions and excess length of stay (LOS) across ethnic groups in a large population of hospitalized patients over an 11-year period by linking information from the national hospital discharge register, the Dutch population register and socio-economic data. Data were analysed with stepwise logistic regression. Results: Ethnic differences were most pronounced in older patients: all non-Western ethnic groups > 45 years had an increased risk for excess LOS compared with ethnic Dutch patients, with odds ratios (ORs) (adjusted for case mix) varying from 1.05 [95% confidence intervals (95% CI) 1.02–1.08] for other non-Western patients to 1.14 (95% CI 1.07–1.22) for Moroccan patients. The risk for unplanned readmission in patients >45 years was increased for Turkish (OR 1.24, 95% CI 1.18–1.30) and Surinamese patients (OR 1.11, 95% CI 1.07–1.16). These differences were explained partially, although not substantially, by differences in socio-economic status. Conclusion: We found significant ethnic variations in unplanned readmissions and excess LOS. These differences may be interpretable as shortcomings in the quality of hospital care delivered to ethnic minority patients, but exclusion of alternative explanations (such as differences in patient- and community-level factors, which are outside hospitals’ control) requires further research. To quantify potential ethnic inequities in hospital care in Europe, we need empirical prospective cohort studies with solid quality outcomes such as adverse event rates.

Benchmarking and reducing length of stay in Dutch hospitals

BACKGROUND

To assess the development of and variation in lengths of stay in Dutch hospitals and to determine the potential reduction in hospital days if all Dutch hospitals would have an average length of stay equal to that of benchmark hospitals.

METHODS

The potential reduction was calculated using data obtained from 69 hospitals that participated in the National Medical Registration (LMR). For each hospital, the average length of stay was adjusted for differences in type of admission (clinical or day-care admission) and case mix (age, diagnosis and procedure). We calculated the number of hospital days that theoretically could be saved by (i) counting unnecessary clinical admissions as day cases whenever possible, and (ii) treating all remaining clinical patients with a length of stay equal to the benchmark (15th percentile length of stay hospital).

RESULTS

The average (mean) length of stay in Dutch hospitals decreased from 14 days in 1980 to 7 days in 2006. In 2006 more than 80% of all hospitals reached an average length of stay shorter than the 15th percentile hospital in the year 2000. In 2006 the mean length of stay ranged from 5.1 to 8.7 days. If the average length of stay of the 15th percentile hospital in 2006 is identified as the standard that other hospitals can achieve, a 14% reduction of hospital days can be attained. This percentage varied substantially across medical specialties. Extrapolating the potential reduction of hospital days of the 69 hospitals to all 98 Dutch hospitals yielded a total savings of 1.8 million hospital days (2006). The average length of stay in Dutch hospitals if all hospitals were able to treat their patients as the 15th percentile hospital would be 6 days and the number of day cases would increase by 13%.

CONCLUSION

Hospitals in the Netherlands vary substantially in case mix adjusted length of stay. Benchmarking--using the method presented--shows the potential for efficiency improvement which can be realized by decreasing inputs (e.g. available beds for inpatient care). Future research should focus on the effect of length of stay reduction programs on outputs such as quality of care.

The impact of hospital discharge on inappropriate hospital stay

Appropriate hospital stay should be effective, efficient and tailored to patient needs. Previous studies have found that on average 20 per cent of hospital stay is inappropriate. Within obstetrics, inappropriate hospital stay consists mostly of delays in hospital discharge. The specific goals of this study were to reduce inappropriate hospital stay by fine-tuning patient logistics, increasing efficiency and providing more comfortable surroundings. New policies using strict discharge criteria were implemented. Total inappropriate hospital stay decreased from 13.3 to 7.2 per cent. The delay in discharge procedures halved. P-charts showed a decrease in inappropriate hospital stay, indicating the current process to be stable. Concludes that a significant reduction in inappropriate hospital stay was found following the implementation of innovative hospital discharge policies, indicating greater efficiency and accessibility of hospital services.