Resource utilisation, length of hospital stay, and pattern of investigation during acute medical hospital admission

Perioperative cardiac investigations for chest pain after parathyroidectomy rarely yield a cardiac diagnosis

Background:

The incidence of adverse perioperative cardiac complications after parathyroidectomy has not been well described. This study aimed to evaluate the incidence of perioperative chest pain and cardiac complications after parathyroidectomy and to evaluate risk factors that may identify patients who are more likely to benefit from a cardiac workup.

Methods:

We performed a retrospective study of all patients undergoing parathyroidectomy for primary hyperparathyroidism by a single endocrine surgeon at a tertiary endocrine centre between 2011 and 2018. Patient demographics, clinicopathologic variables, operative and postoperative details (reported chest pain, performance of a cardiac workup and new postoperative cardiac diagnosis) were reviewed. Patients with chest pain were compared to those without chest pain using the Fisher exact test and Student t test.

Results:

Fourteen of 295 patients (4.7%) reported chest pain in the immediate postoperative period. Most patients were investigated with a 12-lead electrocardiogram and troponin (n = 12/14), yet none were diagnosed with a cardiac event. When comparing patients with and without chest pain, there was no significant difference in age, gender, body mass index, presence of cardiovascular risk factors, American Society of Anesthesiologists score or length of surgery.

Conclusion:

Postoperative chest pain after parathyroidectomy is not an uncommon event and leads to a cardiac workup in most cases; however, the risk of significant postoperative cardiac events is minimal. In the “choosing wisely” era, one should evaluate each patient’s pretest probability of such events and avoid extensive workup in low-risk patients to avoid unnecessary costs to the health care system.

Is It Time to Be More Explicit About the Purpose of a Hospital Admission?

PURPOSE

Patient care suffers when teaching teams fail to achieve a shared understanding of problems to be addressed during a hospital admission. In academic contexts where attending physicians take turns supervising, practice variability may contribute to undermining this shared understanding. Exploring variability around what constitutes the purpose of the hospital admission was the focus of this study.

METHOD

Constructivist grounded theory was used to inform data collection and analysis of this two-phase study, conducted in London and Hamilton, Ontario, Canada, in 2012. In phase 1, interviews with 24 attending physicians from 2 academic health centers were conducted. Phase 2 involved analyzing 18 audio-recorded admission case review discussions in relation to the emergent theory from phase 1. Participants for phase 2 were 7 different attendings, 7 medical students, and 5 junior residents.

RESULTS

Three dominant perspectives around the purpose of an admission were identified. The most focused perspective characterized the purpose as making patients ready for discharge. By contrast, the most comprehensive perspective characterized admission as an opportunity to identify ways to improve overall patient health status. The third perspective was in-between-treating acute issues while monitoring pertinent chronic conditions. All attendings expressed a sense of discharge pressure but responded with different strategies. Attendings rarely explicitly discussed their perspectives as part of case review.

CONCLUSIONS

These extremes of practice and lack of overt dialogue are concerning. Potential effects include mixed messages to trainees and missed opportunities for dialogue and debate around what can and should be achieved during a hospital admission.

Pre- and intra-operative predictors of postoperative hospital length of stay in patients undergoing radical prostatectomy for prostate cancer in China: a retrospective observational study

Background

Hospital length of stay (LOS) has recently been receiving increasing attention as a marker of medical resource consumption. Identifying predictors of longer LOS can better equip doctors to counsel patients and facilitate more efficient patient flow and utilization of medical resources. The objective of this study was to identify pre- and intra-operative risk factors for postoperative hospital LOS in patients who had undergone radical prostatectomy in China.

Methods

We retrospectively analyzed data of 793 eligible patients with prostate cancer who had undergone radical prostatectomy in our institution between January 2011 and March 2016. Relevant preoperative variables, including patient characteristics, medical comorbidities, prostate cancer disease-specific variables, urinary tract symptoms, preoperative laboratory values, and intraoperative variables including operation type, operation duration, and blood loss, were analyzed. The outcome was postoperative length of stay which was calculated as the time from the date of operation to the date of discharge. Multiple linear regression analysis was used to identify predictors of this outcome.

Results

The mean postoperative LOS was 11.7 days (±4.6 days) and the median 10 days (range, 5–46 days). According to univariate and multivariate analysis, operation type (open or laparoscopic), blood loss, Gleason score (≥8) and preoperative laboratory values of white blood count (WBC) were found to be the main explanatory predictors of postoperative LOS of patients with prostate cancer in our institution. Additionally, open surgery was the strongest significant predictor of longer LOS according to the standardized coefficients in this model.

Conclusions

Our findings indicate that significant predictors of longer postoperative LOS in patients who have undergone radical prostatectomy in China include both preoperative variables of Gleason score, WBC and intraoperative variables of operation type (open or laparoscopic), blood loss. To shorten hospital LOS in patients with prostate cancer and optimize utilization of Chinese medical resources, efforts should be made to improve the intraoperative process and reduce the prevalence of preoperative risk factors.

Patient length of stay and mortality prediction: A survey

Over the past few years, there has been increased interest in data mining and machine learning methods to improve hospital performance, in particular hospitals want to improve their intensive care unit statistics by reducing the number of patients dying inside the intensive care unit. Research has focused on prediction of measurable outcomes, including risk of complications, mortality and length of hospital stay. The length of stay is an important metric both for healthcare providers and patients, influenced by numerous factors. In particular, the length of stay in critical care is of great significance, both to patient experience and the cost of care, and is influenced by factors specific to the highly complex environment of the intensive care unit. The length of stay is often used as a surrogate for other outcomes, where those outcomes cannot be measured; for example as a surrogate for hospital or intensive care unit mortality. The length of stay is also a parameter, which has been used to identify the severity of illnesses and healthcare resource utilisation. This paper examines a range of length of stay and mortality prediction applications in acute medicine and the critical care unit. It also focuses on the methods of analysing length of stay and mortality prediction. Moreover, the paper provides a classification and evaluation for the analytical methods of the length of stay and mortality prediction associated with a grouping of relevant research papers published in the years 1984 to 2016 related to the domain of survival analysis. In addition, the paper highlights some of the gaps and challenges of the domain.

Social deprivation, population dependency ratio and an extended hospital episode - Insights from acute medicine

BACKGROUND

Patients from deprived backgrounds have a higher in-patient mortality following an emergency medical admission; this study aimed to investigate the extent to which Deprivation status and the population Dependency Ratio influenced extended hospital episodes.

METHODS

All Emergency Medical admissions (75,018 episodes of 41,728 patients) over 12 years (2002-2013) categorized by quintile of Deprivation Index and Population Dependency Rates (proportion of non-working/working) were evaluated against length of stay (LOS). Patients with an Extended LOS (ELOS), >30 days, were investigated, by Deprivation status, Illness Severity and Co-morbidity status. Univariate and multi-variable risk estimates (Odds Rates or Incidence Rate Ratios) were calculated, using truncated Poisson regression.

RESULTS

Hospital episodes with ELOS had a frequency of 11.5%; their median LOS (IQR) was 55.0 (38.8, 97.6) days utilizing 57.6% of all bed days by all 75,018 emergency medical admissions. The Deprivation Index independently predicted the rate of such ELOS admissions; these increased approximately five-fold (rate/1000 population) over the Deprivation Quintiles with model adjusted predicted admission rates of for Q1 0.93 (95% CI: 0.86, 0.99), Q22.63 (95% CI: 2.55, 2.71), Q3 3.84 (95% CI: 3.77, 3.91), Q4 3.42 (95% CI: 3.37, 3.48) and Q5 4.38 (95% CI: 4.22, 4.54). Similarly the Population Dependency Ratio Quintiles (dependent to working structure of the population by small area units) independently predicted extended LOS admissions.

CONCLUSION

The admission of patients with an ELOS is strongly influenced by the Deprivation status and the population Dependency Ratio of the catchment area. These factors interact, with both high deprivation and Dependency cohorts having a major influence on the numbers of emergency medical admission patients with an extended hospital episode.

Enhanced clinical pharmacy service targeting tools: risk-predictive algorithms

RATIONALE, AIMS AND OBJECTIVES

This study aimed to determine the value of using a mix of clinical pharmacy data and routine hospital admission spell data in the development of predictive algorithms. Exploration of risk factors in hospitalized patients, together with the targeting strategies devised, will enable the prioritization of clinical pharmacy services to optimize patient outcomes.

METHODS

Predictive algorithms were developed using a number of detailed steps using a 75% sample of integrated medicines management (IMM) patients, and validated using the remaining 25%. IMM patients receive targeted clinical pharmacy input throughout their hospital stay. The algorithms were applied to the validation sample, and predicted risk probability was generated for each patient from the coefficients. Risk threshold for the algorithms were determined by identifying the cut-off points of risk scores at which the algorithm would have the highest discriminative performance. Clinical pharmacy staffing levels were obtained from the pharmacy department staffing database.

RESULTS

Numbers of previous emergency admissions and admission medicines together with age-adjusted co-morbidity and diuretic receipt formed a 12-month post-discharge and/or readmission risk algorithm. Age-adjusted co-morbidity proved to be the best index to predict mortality. Increased numbers of clinical pharmacy staff at ward level was correlated with a reduction in risk-adjusted mortality index (RAMI).

CONCLUSIONS

Algorithms created were valid in predicting risk of in-hospital and post-discharge mortality and risk of hospital readmission 3, 6 and 12 months post-discharge. The provision of ward-based clinical pharmacy services is a key component to reducing RAMI and enabling the full benefits of pharmacy input to patient care to be realized.

Falls in hospital increase length of stay regardless of degree of harm

RATIONALE, AIMS AND OBJECTIVES

Acute inpatient falls are common and serious adverse events that lead to injury, prolonged hospitalization and increased cost of care. To determine the difference in total acute hospital care length of stay (LOS) for patients with and without an in-hospital fall (IHF), regardless of degree of harm.

METHODS

This was a retrospective observational study at a 728-bed acute care teaching hospital. We used propensity scores to match 292 patients with 330 controls by case mix group, sex, Resource Intensity Weights and week of admission. We used two administrative databases: hospital fall incident reporting system and Discharge Abstract Database. We reviewed all IHF incidents for patients 18 years and older, admitted to inpatient acute care hospital units/programs between 1 November 2009 and 31 August 2011.

RESULTS

The average LOS for IHF cases was 37.2 days [median 26.5 days; interquartile range (IQR) 14, 54] and 25.7 days (median 13 days; IQR 5, 33) for matched control patients. Survival analysis results indicated that patients who did not have an IHF were 2.4 times (95% CI 2.1, 2.7; P < 0.001) more likely to be discharged earlier from acute care than patients who had an IHF.

CONCLUSIONS

Experiencing either an injurious or a non-injurious fall during an acute care hospitalization was associated with prolonged LOS.

Use of data mining techniques to determine and predict length of stay of cardiac patients

Objectives

Predicting the length of stay (LOS) of patients in a hospital is important in providing them with better services and higher satisfaction, as well as helping the hospital management plan and managing hospital resources as meticulously as possible. We propose applying data mining techniques to extract useful knowledge and draw an accurate model to predict the LOS of heart patients.

Methods

Data were collected from patients with coronary artery disease (CAD). The patient records of 4,948 patients who had suffered CAD were included in the analysis. The techniques used are classification with three algorithms, namely, decision tree, support vector machines (SVM), and artificial neural network (ANN). LOS is the target variable, and 36 input variables are used for prediction. A confusion matrix was obtained to calculate sensitivity, specificity, and accuracy.

Results

The overall accuracy of SVM was 96.4% in the training set. Most single patients (64.3%) had an LOS ≤5 days, whereas 41.2% of married patients had an LOS >10 days. Moreover, the study showed that comorbidity states, such as lung disorders and hemorrhage with drug consumption have an impact on long LOS. The presence of comorbidities, an ejection fraction <2, being a current smoker, and having social security type insurance in coronary artery patients led to longer LOS than other subjects.

Conclusions

All three algorithms are able to predict LOS with various degrees of accuracy. The findings demonstrated that the SVM was the best fit. There was a significant tendency for LOS to be longer in patients with lung or respiratory disorders and high blood pressure.

Impact of teaching intensity and academic status on medical resource utilization by teaching hospitals in Japan

Teaching hospitals require excess medical resources to maintain high-quality care and medical education. To evaluate the appropriateness of such surplus costs, we examined the impact of teaching intensity defined as activities for postgraduate training, and academic status as functions of medical research and undergraduate teaching on medical resource utilization. Administrative data for 47,397 discharges from 40 academic and 12 non-academic teaching hospitals in Japan were collected. Hospitals were classified into three groups according to intern/resident-to-bed (IRB) ratio. Resource utilization of medical services was estimated using fee-for-service charge schedules and normalized with case mix grouping. 15-24% more resource utilization for laboratory examinations, radiological imaging, and medications were observed in hospitals with higher IRB ratios. With multivariate adjustment for case mix and academic status, higher IRB ratios were associated with 10-15% more use of radiological imaging, injections, and medications; up to 5% shorter hospital stays; and not with total resource utilization. Conversely, academic status was associated with 21-33% more laboratory examinations, radiological imaging, and medications; 13% longer hospital stays; and 10% more total resource utilization. While differences in medical resource utilization by teaching intensity may not be associated with indirect educational costs, those by academic status may be. Therefore, academic hospitals may need efficiency improvement and financial compensation.

Patients' length of stay in women hospital and its associated clinical and non-clinical factors, tehran, iran

BACKGROUND

Length of Stay (LOS) is an appropriate hospital indicator to evaluate hospital resource utilization rate, efficiency, and quality of services delivered. In this survey, we aimed to study hospital LOS and determine its association with clinical and non-clinical factors in Women Hospital in Tehran.

METHODS

In this cross-sectional study, we reviewed all 3421 charts of patients admitted in Oncology, Surgery and Obstetrics units in 2008. We used a data collection sheet and conducted interviews to collect the following data: distance from living area, medical insurance coverage types, admission and discharge months, days and times, inpatient units, final diagnoses and the number of diagnostic tests.

RESULTS

The overall median of the LOS in the studied hospital was 50.8 hours. The medians were 48.5, 54.4, and 94.2 hours in the Obstetrics, Surgical and Oncology units, respectively. Results showed that the associated factors with the LOS were patient admissions on Thursdays, admitting by residents, the number of performed diagnostic tests (p<0.001), suffering from neoplastic diseases (p=0.005) and spouse jobs.

CONCLUSION

Among the associated factors, policy makers and managers can only change the admission days and the number of diagnostic tests to decrease the LOS. Further researches are needed to find other factors associated with LOS.

Difference in resource utilization between patients with acute and chronic heart failure from Japanese administrative database

BACKGROUND

Many studies have reported economic evaluation of evolving agents or therapies for patients with heart failure (HF). However, little is known whether the disease progression category (acute or chronic HF) would be considered as a risk adjustment in health service research.

OBJECTIVES

This study profiles the difference in resource use or medical care for acute versus chronic HF.

METHODS

This study analyzed 17,912 HF patients treated in 62 academic hospitals and 351 community hospitals. Study variables included demographic variables, comorbid status, physical activity or disease progression at admission, procedures and laboratory tests, type and dose of heart-related medications, length of stay (LOS), and total charges (TC; 1 US$= 100 yen) for acute and chronic HF. The independent contributions of disease progression categories on LOS and TC were identified using multivariate analysis.

RESULTS

We identified 9813 chronic and 8099 acute HF patients. Median LOS was 18 days for both chronic and acute HF, whereas TC was US$5731 and US$6447, respectively. Regression analysis revealed that acute HF was associated with a slightly greater TC, whereas performance of procedures was the most prominent factor. As NYHA class was the next most influential factor, class 3 or 4 resulted in longer LOS or greater TC, than did class 1.

CONCLUSIONS

This study suggests that acute HF increased resource use slightly, whereas use of some practices indicated in critical care was affected more by the procedures performed. Disease progression category should remain an indicator for appropriateness of medical care.

Short stay emergency admissions to a West Midlands NHS Trust: a longitudinal descriptive study, 2002 2005

OBJECTIVES

To describe changes and characteristics in emergency admissions to a West Midlands National Health Service Trust, 2002-2005, with a focus on short stay emergency admissions.

METHODS

A longitudinal descriptive study using retrospective analysis of routine admissions data. Admissions were categorised as short (0/1 day) or long (>or=2 days) and examined separately using a General Linear Model. Factors favouring short stays as opposed to long stays were examined using multivariable logistic regression.

RESULTS

There were 151 478 emergency admissions to the Trust between 1 April 2002 and 31 December 2005, of which 2910 (1.92%) had no discharge date recorded. Adjusted means showed a 7.76% increase in emergency admissions in winter months (October-January) and a 14.50% increase across the study period. Increases were greater in short stay (34.03%) than long stay emergency admissions (8.38%). Odds of short stays in admitted patients increased by 25%. Higher odds of short stays were also associated with younger age, winter month and medical admitting specialty (p<0.001).

CONCLUSIONS

Increases in emergency admissions were greater in short stay than long stay cases. Reasons for this may be both appropriate (increased use of clinical protocols and falling average length of stay) and detrimental (pressure to meet 4 h emergency department target, changing primary care provision). Further research is needed before generalising findings to other Trusts.

Emergency care in the first 48 hours

“Acute physicians” herald the new specialty of acute medicine

Pounds of Cure: Chart Weight as a Measure of Service Intensity

Intensity of hospital services is often estimated by length of stay (LOS). Increasing demands for documentation in the medical record suggested to us an alternate method: weighing the chart. In a retrospective study, we compared LOS and chart weight as predictors of actual hospital costs at a community teaching hospital. We reviewed a sample of 123 patients randomly chosen from the medical service and stratified by phase of the academic year. Both least-squares regression and a multiple sampling/validating technique were used to derive mean cost per ounce of chart and per day of stay. Costs estimated from weight were within 7% and from LOS within 14% of measured actual costs among patients not used to derive the formulae. We conclude that the intensity of paper documentation closely reflects actual costs; the same may be true of bytes or key-strokes for electronic records.