Calculating hospital length of stay using the Hospital Episode Statistics; a comparison of methodologies

Indirect effect of the COVID-19 pandemic on hospital mortality in patients with hip fracture: a competing risk survival analysis using linked administrative data

BACKGROUND

Hip fracture is a leading cause of disability and mortality among older people. During the COVID-19 pandemic, orthopaedic care pathways in the National Health Service in England were restructured to manage pressures on hospital capacity. We examined the indirect consequences of the pandemic for hospital mortality among older patients with hip fracture, admitted from care homes or the community.

METHODS

Retrospective analysis of linked care home and hospital inpatient data for patients with hip fracture aged 65 years and over admitted to hospitals in England during the first year of the pandemic (1 March 2020 to 28 February 2021) or during the previous year. We performed survival analysis, adjusting for case mix and COVID-19 infection, and considered live discharge as a competing risk. We present cause-specific hazard ratios (HR_CS) for the effect of admission year on hospital mortality risk.

RESULTS

During the first year of the pandemic, there were 55 648 hip fracture admissions: a 5.2% decrease on the previous year. 9.5% of patients had confirmed or suspected COVID-19. Hospital stays were substantially shorter (p<0.05), and there was a higher daily chance of discharge (HR_CS 1.40, 95% CI 1.38 to 1.41). Overall hip fracture inpatient mortality increased (7.2% in 2020/2021 vs 6.4% in 2019/2020), but patients without concomitant COVID-19 infection had lower mortality rates compared with the year before (5.3%). Admission during the pandemic was associated with a 11% increase in the daily risk of hospital death for patients with hip fracture (HR_CS 1.11, 95% CI 1.05 to 1.16).

CONCLUSIONS

Although COVID-19 infections led to increases in hospital mortality, overall hospital mortality risk for older patients with hip fracture remained largely stable during the first year of the pandemic.

Perioperative Risk Stratification: A Need for an Improved Assessment in Surgery and Anesthesia-A Pilot Study

Background and Objectives: Numerous scoring systems have been introduced into modern medicine. None of the scoring systems assessed both anesthetic and surgical risk of the patient, predict the morbidity, mortality, or the need for postoperative intensive care unit admission. The aim of this study was to compare the anesthetic and surgical scores currently used, for a better evaluation of perioperative risks, morbidity, and mortality. Material and Methods: This is a pilot, prospective, observational study. We enrolled 50 patients scheduled for elective surgery. Anesthetic and surgery risk was assessed using American Society of Anesthesiologists (ASA) scale, Physiological and Operative Severity Score for the enumeration of Mortality and morbidity (P-POSSUM), Acute Physiology and Chronic Health Evaluation (APACHE II), and Surgical APGAR Score (SAS) scores. The real and the estimated length of stay (LOS) were registered. Results: We obtained several statistically significant positive correlations: ASA score–P-POSSUM (p < 0.01, r = 0.465); ASA score–SAS, (p < 0.01, r = −0.446); ASA score–APACHE II, (p < 0.01 r = 0.519); predicted LOS and ASA score (p < 0.01, r = 0.676); predicted LOS and p-POSSUM (p < 0.01, r = 0.433); and predicted LOS and APACHE II (p < 0.01, r = 0.454). A significant negative correlation between predicted LOS, real LOS, ASA class, and SAS (p < 0.05) was observed. We found a statistically significant difference between the predicted and actual LOS (p < 001). Conclusions: Anesthetic, surgical, and severity scores, used together, provide clearer information about mortality, morbidity, and LOS. ASA scale, associated with surgical scores and severity scores, presents a better image of the patient’s progress in the perioperative period. In our study, APACHE II is the best predictor of mortality, followed by P-POSSUM and SAS. P-POSSUM score and ASA scale may be complementary in terms of preoperative physiological factors, providing valuable information for postoperative outcomes.

Mortality after surgery with SARS-CoV-2 infection in England: a population-wide epidemiological study

BACKGROUND

The COVID-19 pandemic has heavily impacted elective and emergency surgery around the world. We aimed to confirm the incidence of perioperative severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and associated mortality after surgery.

METHODS

Analysis of routine electronic health record data from NHS hospitals in England. We extracted data from Hospital Episode Statistics in England describing adult patients undergoing surgery between January 1, 2020 and February 28, 2021. The exposure was SARS-CoV-2 infection defined by International Classification of Diseases (ICD)-10 codes. The primary outcome measure was 90 day in-hospital mortality. Data were analysed using multivariable logistic regression adjusted for age, sex, Charlson Comorbidity Index, Index of Multiple Deprivation, presence of cancer, surgical procedure type and admission acuity. Results are presented as n (%) and odds ratios (OR) with 95% confidence intervals (CI).

RESULTS

We identified 2 666 978 patients undergoing surgery of whom 28 777 (1.1%) had SARS-CoV-2 infection. In total, 26 364 (1.0%) patients died in hospital. SARS-CoV-2 infection was associated with a much greater risk of death (SARS-CoV-2: 6153/28 777 [21.4%] vs no SARS-CoV-2: 20 211/2 638 201 [0.8%]; OR=5.7 [95% CI, 5.5-5.9]; P<0.001). Amongst patients undergoing elective surgery, 2412/1 857 586 (0.1%) had SARS-CoV-2, of whom 172/2412 (7.1%) died, compared with 1414/1 857 586 (0.1%) patients without SARS-CoV-2 (OR=25.8 [95% CI, 21.7-30.9]; P<0.001). Amongst patients undergoing emergency surgery, 22 918/582 292 (3.9%) patients had SARS-CoV-2, of whom 5752/22 918 (25.1%) died, compared with 18 060/559 374 (3.4%) patients without SARS-CoV-2 (OR=5.5 [95% CI, 5.3-5.7]; P<0.001).

CONCLUSIONS

The low incidence of SARS-CoV-2 infection in NHS surgical pathways suggests current infection prevention and control policies are highly effective. However, the high mortality amongst patients with SARS-CoV-2 suggests these precautions cannot be safely relaxed.

Cardiovascular disease recurrence and long-term mortality in a tri-ethnic British cohort

OBJECTIVE

Ethnic differences in cardiovascular disease incidence, but not cardiovascular disease recurrence, are reported. We characterised long-term risk of major adverse cardiovascular event (MACE) and mortality following a non-fatal cardiovascular event in a British cohort of South Asians, African Caribbeans and Europeans.

METHODS

We identified index and recurrent cardiovascular events and mortality between 1988 and 2017 using hospital records and death registry. Using multivariable hazards models, we separately calculated the adjusted HR of MACE and death following index event, adjusting for demographics, vascular and lifestyle risk factors. Using interaction terms, we evaluated if decade of index event modified the association between ethnicity and outcomes.

RESULTS

South Asians were younger at the index event (median age 66 years, n=396) than Europeans (69 years, n=335) and African Caribbeans (70 years, n=70). During 4228 person-years, of the 801 patients, 537 developed MACE and 338 died, with the highest crude rate of MACE in South Asians. On adjustment of baseline factors, compared with the Europeans, the higher risk of MACE (HR 0.97, 95% CI 0.77 to 1.21) and the lower risk of mortality (HR 0.95, 95% CI 0.72 to 1.26) in South Asians was eliminated. African Caribbeans had similar outcomes to Europeans (HR MACE 1.04, 95% CI 0.74 to 1.47; and HR death 1.07, 95% CI 0.70 to 1.64). Long-term survival following an index event improved in South Asians (ptrend 0.02) and African Caribbeans (ptrend 0.07) compared with Europeans.

CONCLUSIONS

Baseline vascular risk factors explained the observed ethnic variation in cardiovascular disease recurrence and long-term mortality, with a relative improvement in survival of minority ethnic groups over time.

General practitioner practice-based pharmacist input to medicines optimisation in the UK: pragmatic, multicenter, randomised, controlled trial

BACKGROUND

Changing demographics across the UK has led to general practitioners (GPs) managing increasing numbers of older patients with multi-morbidity and resultant polypharmacy. Through government led initiatives within the National Health Service, an increasing number of GP practices employ pharmacist support. The purpose of this study is to evaluate the impact of a medicines optimisation intervention, delivered by GP practice-based pharmacists, to patients at risk of medication-related problems (MRPs), on patient outcomes and healthcare costs.

METHODS

A multi-centre, randomised (normal care or pharmacist supplemented care) study in four regions of the UK, involving patients (n = 356) from eight GP practices, with a 6-month follow-up period. Participants were adult patients who were at risk of MRPs.

RESULTS

Median number of MRPs per intervention patient were reduced at the third assessment, i.e. 3 to 0.5 (p < 0.001) in patients who received the full intervention schedule. Medication Appropriateness Index (MAI) scores were reduced (medications more appropriate) for the intervention group, but not for control group patients (8 [4-13] to 5 [0-11] vs 8 [3-13] to 7 [3-12], respectively; p = 0.001). Using the intention-to-treat (ITT) approach, the number of telephone consultations in intervention group patients was reduced and different from the control group (1 [0-3] to 1 [0-2] vs 1 [0-2] to 1 [0-3], p = 0.020). No significant differences between groups were, however, found in unplanned hospital admissions, length of hospital stay, number of A&E attendances or outpatient visits. The mean overall healthcare cost per intervention patient fell from £1041.7 ± 1446.7 to £859.1 ± 1235.2 (p = 0.032). Cost utility analysis showed an incremental cost per patient of - £229.0 (95% CI - 594.6, 128.2) and a mean QALY gained of 0.024 (95% CI - 0.021 to 0.065), i.e. indicative of a health status gain at a reduced cost (2016/2017).

CONCLUSION

The pharmacist service was effective in reducing MRPs, inappropriateness of medications and telephone consultations in general practice in a cost-effective manner.

TRIAL REGISTRATION

ClinicalTrials.Gov, NCT03241498. Registered 7 August 2017-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03241498.

Patient-specific record linkage between emergency department and hospital admission data for a cohort of people who inject drugs: methodological considerations for frequent presenters

Background

People who inject drugs (PWID) have been identified as frequent users of emergency department (ED) and hospital inpatient services. The specific challenges of record linkage in cohorts with numerous administrative health records occurring in close proximity are not well understood. Here, we present a method for patient-specific record linkage of ED and hospital admission data for a cohort of PWID.

Methods

Data from 688 PWID were linked to two state-wide administrative health databases identifying all ED visits and hospital admissions for the cohort between January 2008 and June 2013. We linked patient-specific ED and hospital admissions data, using administrative date-time timestamps and pre-specified linkage criteria, to identify hospital admissions stemming from ED presentations for a given individual. The ability of standalone databases to identify linked ED visits or hospital admissions was examined.

Results

There were 3459 ED visits and 1877 hospital admissions identified during the study period. Thirty-four percent of ED visits were linked to hospital admissions. Most links had hospital admission timestamps in-between or identical to their ED visit timestamps (n = 1035, 87%). Allowing 24-h between ED visits and hospital admissions captured more linked records, but increased manual inspection requirements. In linked records (n = 1190), the ED ‘departure status’ variable correctly reflected subsequent hospital admission in only 68% of cases. The hospital ‘admission type’ variable was non-specific in identifying if a preceding ED visit had occurred.

Conclusions

Linking ED visits with subsequent hospital admissions in PWID requires access to date and time variables for accurate temporal sorting, especially for same-day presentations. Selecting time-windows to capture linked records requires discretion. Researchers risk under-ascertainment of hospital admissions if using ED data alone.

Skill mix and patient outcomes: A multi-country analysis of heart disease and breast cancer patients

Policymakers are becoming aware that increasing the size of the healthcare workforce is no longer the most viable way to address the increasing demand for healthcare. Consequently, a focus of recent healthcare workforce reform has been extending existing roles and creating new roles for health professionals. However, little is known of the influence on outcomes from this variation in labour inputs within hospital production functions. Using a unique combination of primary and administrative data, this paper provides evidence of associations between the composition of care delivery teams and patient outcomes. The primary data enabled the construction of a task component-based measure of skill mix. This novel measure of skill mix has the advantage of capturing how workforce planning can restructure the relative input of nurses or physicians into task components while keeping the overall level of staff fixed. The analysis focuses on specific care pathways and individual hospitals, thus controlling for an under-investigated source of heterogeneity. Additionally, stratifying by country (England, Scotland, and Norway) enabled analysis of skill mix within different health systems. We provide evidence that variations in labour inputs within the breast cancer and heart disease care pathways are associated with both positive and adverse outcomes. The results illustrate the scope for substitution of task components within care pathways as a potential method of healthcare reform.

Developing a standardised approach to the aggregation of inpatient episodes into person-based spells in all specialties and psychiatric specialties

Background

Electronic health record (EHR) data are available for research in all UK nations and cross-nation comparative studies are becoming more common. All UK inpatient EHRs are based around episodes, but episode-based analysis may not sufficiently capture the patient journey. There is no UK-wide method for aggregating episodes into standardised person-based spells. This study identifies two data quality issues affecting the creation of person-based spells, and tests four methods to create these spells, for implementation across all UK nations.

Methods

Welsh inpatient EHRs from 2013 to 2017 were analysed. Phase one described two data quality issues; transfers of care and episode sequencing. Phase two compared four methods for creating person spells. Measures were mean length of stay (LOS, expressed in days) and number of episodes per person spell for each method.

Results

3.5% of total admissions were transfers-in and 3.1% of total discharges were transfers-out. 68.7% of total transfers-in and 48.7% of psychiatric transfers-in had an identifiable preceding transfer-out, and 78.2% of total transfers-out and 59.0% of psychiatric transfers-out had an identifiable subsequent transfer-in. 0.2% of total episodes and 4.0% of psychiatric episodes overlapped with at least one other episode of any specialty.

Method one (no evidence of transfer required; overlapping episodes grouped together) resulted in the longest mean LOS (4.0 days for all specialties; 48.5 days for psychiatric specialties) and the fewest single episode person spells (82.4% of all specialties; 69.7% for psychiatric specialties). Method three (evidence of transfer required; overlapping episodes separated) resulted in the shortest mean LOS (3.7 days for all specialties; 45.8 days for psychiatric specialties) and the most single episode person spells; (86.9% for all specialties; 86.3% for psychiatric specialties).

Conclusions

Transfers-in appear better recorded than transfers-out. Transfer coding is incomplete, particularly for psychiatric specialties. The proportion of episodes that overlap is small but psychiatric episodes are disproportionately affected.

The most successful method for grouping episodes into person spells aggregated overlapping episodes and required no evidence of transfer from admission source/method or discharge destination codes. The least successful method treated overlapping episodes as distinct and required transfer coding. The impact of all four methods was greater for psychiatric specialties.

National trends in emergency readmission rates: a longitudinal analysis of administrative data for England between 2006 and 2016

OBJECTIVE

To assess trends in 30-day emergency readmission rates across England over one decade.

DESIGN

Retrospective study design.

SETTING

150 non-specialist hospital trusts in England.

PARTICIPANTS

23 069 134 patients above 18 years of age who were readmitted following an initial admission (n=62 584 297) between April 2006 and February 2016.

PRIMARY AND SECONDARY OUTCOMES

We examined emergency admissions that occurred within 30 days of discharge from hospital ('emergency readmissions') as a measure of healthcare quality. Presented are overall readmission rates, and disaggregated by the nature of the indexed admission, including whether it was elective or emergency, and by clinical health condition recorded. All rates were risk-adjusted for patient age, gender, ethnicity, socioeconomic status, comorbidities and length of stay.

RESULTS

The average risk-adjusted, 30-day readmission rate increased from 6.56% in 2006/2007 to 6.76% (P<0.01) in 2012/2013, followed by a small decrease to 6.64% (P<0.01) in 2015/2016. Emergency readmissions for patients discharged following elective procedures decreased by 0.13% (P<0.05), whereas those following emergency admission increased by 1.27% (P<0.001). Readmission rates for hip or knee replacements decreased (-1.29%; P<0.001); for acute myocardial infarction (-0.04%; P<0.49), stroke (+0.62%; P<0.05), chronic obstructive pulmonary disease (+0.41%; P<0.05) and heart failure (+0.15%; P<0.05) remained stable; and for pneumonia (+2.72%; P<0.001), diabetes (+7.09%; P<0.001), cholecystectomy (+1.86%; P<0.001) and hysterectomy (+2.54%; P<0.001) increased.

CONCLUSIONS

Overall, emergency readmission rates in England remained relatively stable across the observation period, with trends of slight increases contained post 2012/2013. However, there were large variations in trends across clinical areas, with some experiencing marked increases in readmission rates. This highlights the need to better understand variations in outcomes across clinical subgroups to allow for targeted interventions that will ensure highest standards of care provided for all patients.