Has variation in length of stay in acute hospitals decreased? Analysing trends in the variation in LOS between and within Dutch hospitals

Between-hospital variation in indicators of quality of care: a systematic review

BACKGROUND

Efforts to mitigate unwarranted variation in the quality of care require insight into the 'level' (eg, patient, physician, ward, hospital) at which observed variation exists. This systematic literature review aims to synthesise the results of studies that quantify the extent to which hospitals contribute to variation in quality indicator scores.

METHODS

Embase, Medline, Web of Science, Cochrane and Google Scholar were systematically searched from 2010 to November 2023. We included studies that reported a measure of between-hospital variation in quality indicator scores relative to total variation, typically expressed as a variance partition coefficient (VPC). The results were analysed by disease category and quality indicator type.

RESULTS

In total, 8373 studies were reviewed, of which 44 met the inclusion criteria. Casemix adjusted variation was studied for multiple disease categories using 144 indicators, divided over 5 types: intermediate clinical outcomes (n=81), final clinical outcomes (n=35), processes (n=10), patient-reported experiences (n=15) and patient-reported outcomes (n=3). In addition to an analysis of between-hospital variation, eight studies also reported physician-level variation (n=54 estimates). In general, variation that could be attributed to hospitals was limited (median VPC=3%, IQR=1%-9%). Between-hospital variation was highest for process indicators (17.4%, 10.8%-33.5%) and lowest for final clinical outcomes (1.4%, 0.6%-4.2%) and patient-reported outcomes (1.0%, 0.9%-1.5%). No clear pattern could be identified in the degree of between-hospital variation by disease category. Furthermore, the studies exhibited limited attention to the reliability of observed differences in indicator scores.

CONCLUSION

Hospital-level variation in quality indicator scores is generally small relative to residual variation. However, meaningful variation between hospitals does exist for multiple indicators, especially for care processes which can be directly influenced by hospital policy. Quality improvement strategies are likely to generate more impact if preceded by level-specific and indicator-specific analyses of variation, and when absolute variation is also considered.

PROSPERO REGISTRATION NUMBER

CRD42022315850.

Healthcare Quality Received by Insured Patients in Two Indonesian Regional Public Hospitals

Background: Hospitals are required to improve the quality of health services provided to patients. Purpose: Evaluating and comparing the healthcare quality received by insured patients hospitalized in two Indonesian regional public hospitals. Methods: Secondary data analysis used the 2019 and 2020 Indonesian National Health Insurance e-claim databases of Hospital A and Hospital B. Descriptive and crosstabs analyses were used to determine INA-CBGs diagnoses that were categorized as high volume, high risk, and high cost. Results: The admissions that caused financial loss at the Hospital A were 21.1% in 2019 and 19.8% in 2020, while 30.3% in 2019 and 27.5% at the Hospital B. More than 60% of these admissions were placed in the 3rd class of inpatient wards of the two hospitals. Of these admissions, < 5% at the Hospital A and >5% at the Hospital B were readmitted within 30 days, although more than 90% were previously discharged based on physicians' approval. Conclusions: Inadequate healthcare quality received by insured patients. Hence, an integrated clinical pathways based professional nursing practice model is highly recommended to increase patient outcomes and decrease 30 days hospital readmission rates.

Variation in stroke care at the hospital level: A cross-sectional multicenter study

Introduction

Stroke is one of the leading causes of mortality and disability. Improving patient outcomes can be achieved by improving stroke care and adherence to guidelines. Since wide variation in adherence rates for stroke guidelines still exists, we aimed to describe and compare stroke care variability within Belgian hospitals.

Materials and methods

An observational, multicenter study was performed in 29 Belgian hospitals. We retrospectively collected patient characteristics, quality indicators, and time metrics from the last 30 consecutive patients per hospital, diagnosed with ischemic stroke in 2019 with structured questionnaires. Mean adherence ratios (%) ± SD (minimum – maximum) were calculated.

Results

We analyzed 870 patient records from 29 hospitals. Results showed large inter- and intrahospitals variations in adherence for various indicators. Almost all the patients received brain imaging (99.7%) followed by admission at a stroke unit in 82.9% of patients. Of patients not receiving thrombolysis, 92.5% of patients were started on antithrombotic drugs. Indicators with moderate median adherence but large interhospital variability were glycemia monitoring [82.3 ± 16.7% (26.7–100.0%)], performing clinical neurological examination and documentation of stroke severity [63.1 ± 36.8% (0–100%)], and screening for activities of daily living [51.1 ± 40.3% (0.0–100.0%)]. Other indicators lacked adequate adherence: swallowing function screening [37.0 ± 30.4% (0.0–93.3%)], depression screening [20.2 ± 35.8% (0.0–100%)], and timely body temperature measurement [15.1 ± 17.0% (0.0–60%)].

Conclusion

We identified high adherence to guidelines for some indicators, but lower rates with large interhospital variability for other recommendations also based on robust evidence. Improvement strategies should be implemented to improve the latter.

Variations in LOS and its main determinants overtime at an academic spinal care center from 2006-2019

Objectives

Efforts to safely reduce hospital LOS while maintaining quality outcomes and patient satisfaction are paramount. The primary goal of this study was to assess trends in LOS at a high-volume quaternary care spine center. Secondary goals were to assess trends in factors most associated with prolonged LOS.

Methods

This is a prospective study of all consecutive patients admitted from January 2006 to December 2019. Data included demographics, diagnostic category (degenerative, oncology, deformity, trauma, other), LOS (mean, median, interquartile range, standard deviation, defined as days from admission to discharge), and in-hospital adverse events.

Results

A total of 13,493 patients were included. Overall LOS has not changed over time with an overall median of 6.3 days (p = 0.451). Median LOS significantly increased for patients treated for degenerative pathology from 2.2 days in 2006 to 3.2 days in 2019 (p = 0.019). LOS has not changed for patients treated for deformity (overall median 6.8 days, p = 0.411), oncology (overall median 11.0 days, p = 0.051), or trauma (overall median 11.8 days, p = 0.582). Emergency admissions increased 3.2%/year for degenerative pathologies (p =  < 0.001). Mean age has increased from 48.4 years in 2006 to 58.1 years in 2019 (p =  < 0.001). This trend was observed in the deformity, degenerative and trauma group, not for patients treated for oncological disease. More adverse events were significantly associated with increasing age.

Conclusion

This is the first North American study to comprehensively analyze trends in LOS for spinal surgery overtime in an academic center. Overall, LOS has not changed from 2006–2019. Various factors that influence LOS appear to have balanced each other. It may also be explained by the changing epidemiology of both elective and emergency surgeries. These findings provide opportunities for intervention and improvement, targeted at the geriatric population, to reduce length of hospitalization.

The effectiveness of preoperative education interventions on improving perioperative outcomes of adult patients undergoing cardiac surgery: a systematic review and meta-analysis

BACKGROUND

Cardiac surgeries pose as an emotional experience for patients. Preoperative education is known to positively alter people's perceptions, emotions, and mitigate surgical distress. However, this intervention's effectiveness in improving perioperative outcomes among patients undergoing cardiac surgery lacked rigorous statistical synthesis and remains inconclusive.

AIMS

The aim was to synthesize the effectiveness of preoperative education on improving perioperative outcomes [anxiety, depression, knowledge, pain intensity, pain interference with daily activities, postoperative complications, length of hospitalization, length of intensive care unit (ICU) stay, satisfaction with the intervention and care, and health-related quality of life] among patients undergoing cardiac surgery.

METHODS

This systematic review and meta-analysis conducted a comprehensive search of nine electronic databases (PubMed, EMBASE, Scopus, MEDLINE, CINAHL, Cochrane CENTRAL, Web of Science, PsycINFO, and ERIC) and grey literature for randomized controlled trials examining the preoperative educational interventional effects on patients undergoing cardiac surgery from inception to 31 December 2020. The studies' quality was evaluated using Cochrane Risk-of-Bias Tool 1 (RoB1). Meta-analyses via RevMan 5.4 software synthesized interventional effects.

RESULTS

Twenty-two trials involving 3167 participants were included. Preoperative education had large significant effects on reducing post-intervention preoperative anxiety (P = 0.02), length of ICU stay (P = 0.02), and improving knowledge (P < 0.00001), but small significant effect sizes on lowering postoperative anxiety (P < 0.0001), depression (P = 0.03), and enhancing satisfaction (P = 0.04).

CONCLUSIONS

This review indicates the feasibility of preoperative education in clinical use to enhance health outcomes of patients undergoing cardiac surgery. Future studies need to explore knowledge outcomes in-depth and more innovative technologies in preoperative education delivery.

Models of generalist and specialist care in smaller hospitals in England: a mixed-methods study

Background

The increasing number of older, complex patients who require emergency admission to hospital has prompted calls for better models of medical generalist care, especially for smaller hospitals, whose size constrains resources and staffing.

Objective

To investigate the strengths and weaknesses of the current models of medical generalism used in smaller hospitals from patient, professional and service perspectives.

Methods

The design was a mixed-methods study. Phase 1 was a scoping and mapping exercise to create a typology of models of care, which was then explored further through 11 case studies. Phase 2 created a classification using the Hospital Episode Statistics of acute medical ‘generalist’ and ‘specialist’ work and described differences in workload and explored the links between case mix, typology and length of stay and between case mix and skill mix. Phase 3 analysed the relationships between models of care and patient-level costs. Phase 4 examined the strengths and weaknesses of the models of care through focus groups, a discrete choice experiment and an exploration of the impact of typology on other outcomes.

Results

In total, 50 models of care were explored through 48 interviews. A typology was constructed around generalist versus specialist patterns of consultant working. Twenty-five models were deployed by 48 hospitals, and no more than four hospitals used any one model of care. From the patient perspective, analysis of Hospital Episode Statistics data of 1.9 million care episodes found that the differences in case mix between hospitals were relatively small, with 65–70% of episodes accounted for by 20 case types. The skill mix of hospital staff varied widely; there were no relationships with case mix. Patients exhibited a preference for specialist care in the discrete choice experiment but indicated in focus groups that overall hospital quality was more important. From a service perspective, qualitative work found that models of care were contingent on complex constellations of factors, including staffing, the local hospital environment and policy imperatives. Neither the model of care nor the case mix accounted for variability in the length of stay (no associations were significant at p < 0.05). No significant differences were found in the costs of the models. Professionally, the preferences of doctors for specialist versus generalist work depended on their experiences of providing care and were associated with a healthy organisational culture and a co-operative approach to managing emergency work. Concepts of medical generalism were found to be complex and difficult to define, with theoretical models differing markedly from models in action.

Limitations

Smaller hospitals in multisite trusts were excluded, potentially leading to sample bias. The rapidly changing nature of the models limited the analysis of typology against outcomes.

Conclusions

The case mix of smaller hospitals was dominated by patients with presentations amenable to generalist approaches to care; however, there was no evidence to support any particular pattern of consultant working. Matching hospital staff to better meet local need and the creation of more collaborative working environments appear more likely to improve care in smaller hospitals than changing models.

Future work

The exploration of the relationships between workforce, measures of hospital culture, models of care, costs and outcomes in both smaller and larger hospitals is urgently required to underpin service reforms.

Study registration

This study is registered as Integrated Research Application System project ID 191393.

Funding

This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 9, No. 4. See the NIHR Journals Library website for further project information.

Hospital length of stay variation and comorbidity of mental illness: a retrospective study of five common chronic medical conditions

BACKGROUND

With the increasing burden of mental illness globally, it is becoming common for hospitalised patients with chronic medical conditions to have a comorbidity of mental illness. This combination could prolong length of stay (LOS) of this patient cohort. We conducted an investigation in Tasmania, Australian hospitals to characterise this cohort and assess if co-morbidity of mental illness is a distinguishing factor that generates LOS variation across different chronic medical conditions.

METHODS

The retrospective study analysed 16,898 admissions of patients with a primary diagnosis of one of five chronic medical conditions: lung or colorectal cancer, chronic obstructive pulmonary disease (COPD), type II diabetes, ischaemic heart disease (IHD) and stroke. Data were from July 2010 to June 2015, across four hospitals that collectively cover 95% of public hospital admissions in Tasmania, Australia. Descriptive statistics were used to compare characteristics of patients between the scenarios of with and without co-morbidity of mental illness. We used negative binomial regression models to assess whether co-morbidity of mental illness, along with its sub-types, after adjustment for potential confounding variables, associated with LOS variation in patients of each medical condition. Based on the adjusted LOS variation, we estimated differences in bed days' use between patients with and without comorbidity of mental illness.

RESULTS

Patients with co-morbidity of mental illness were significantly younger in comparison to patients without mental illness. With each medical condition, patients with comorbidity of mental illness had incurred higher bed days' use than for those without mental illness. In cancer and stroke cohorts, co-morbidity of mental illness unfavourably affected the LOS variation by as high as 97% (CI: 49.9%-159%) and 109% (78%-146%), respectively. Though mental and behavioural disorders due to psychoactive substances was a dominant sub-type of mental illness across the medical conditions, it contributed significant unfavourable LOS variation only in the stroke patients i.e. 36.3% (CI: 16.2%-59.9%).

CONCLUSIONS

Mental illness consistently produced unfavourable LOS variation. Upskilling of healthcare teams and greater reporting and analysis of LOS variation for this patient cohort, and the sub-cohorts within it, are necessary to provide improved medical care and achieve system efficiencies.

Effect of Joint Camp on Patient Outcomes Following Total Joint Replacement

Two major cost concerns related to joint replacement surgery are patient length of stay (LOS) and 30-day hospital readmission rates. A quality improvement project was implemented to evaluate the impact of a joint replacement program on patient readmissions and hospital LOS. A total of 1425 patients older than 50 years participated. At the end of the project period, readmission rates decreased from 6.19% to 2.8% and average LOS decreased from 5.87 days to 2.7 days.