Palliative care inpatients in Switzerland (2012-2021): characteristics, in-hospital mortality and avoidable admissions.

OBJECTIVES: Palliative patients generally prefer to be cared for and die at home. Overly aggressive treatments place additional strain on already burdened patients and healthcare services, contributing to decreased quality of life and increased healthcare costs. This study characterises palliative inpatients, quantifies in-hospital mortality and potentially avoidable hospitalisations. METHODS: We conducted a multicentre retrospective analysis using the national inpatient cohort. The extracted data encompassed all inpatients for palliative care spanning the years 2012-2021. The dataset comprised information on demographics, diagnoses, comorbidities, treatments and clinical outcomes. Content experts reviewed a list of treatments for which no hospitalisation was required. RESULTS: 120 396 hospitalisation records indicated palliative patients. Almost half were women (n=59 297, 49%). Most patients were ≥65 years old. 66% had an oncologic primary diagnosis. The majority were admitted from home (82 443; 69%). The patients stayed a median of 12 days (6-20). All treatments for 25 188 patients (21%) could have been performed at home. In-hospital deaths ended 64 739 stays (54%); of note, 10% (n=6357/64 739) of in-hospital deaths occurred within 24 hours. CONCLUSIONS: In this nationwide study of palliative inpatients, two-thirds were 65 years old and older. Regarding the performed treatments alone, a fifth of these hospitalisations can be considered as avoidable. More than half of the patients died during their hospital stay, and 1 in 10 of those within 24 hours.

Developing indicators for medication-related readmissions based on a Delphi consensus study.

BACKGROUND: Medication-related readmissions challenge healthcare systems by burdening patients, increasing costs and straining resources. However, to date, there has been no consensus study on indicators for medication-related readmissions. OBJECTIVES: This Delphi study aimed to develop a consensus-based set of indicators for detecting patients at risk of medication-related readmission. METHODS: An expert panel of clinical pharmacists, physicians and nursing experts participated in a two-round Delphi study. In round 1, 31 indicators taken from the literature were rated for relevance on a scale from 1 to 9, with a median rating of 7 or higher suggesting relevance. The RAND/UCLA method was used to determine consensus. In round 2, indicators lacking consensus were re-rated together with a series of new indicators generated by the experts. Additional details were sought for some indicators. The main outcomes were the relevance of, consensus on, and completeness of the proposed indicators for identifying risks of 30-day medication-related readmission. RESULTS: Thirty-eight experts participated in round 1. Consensus was found for all the indicators, with 25 included and 6 excluded. Thirty-four experts participated in round 2. Consensus was found for all 5 newly suggested indicators, and 4 were included. The expert panel prioritized the following indicators: (1) insufficient communication between different healthcare providers, (2) polypharmacy (≥7 medications), (3) low rates of medication adherence (twice-weekly mistakes or missing administration), (4) complex medication regimens (≥3 doses, ≥2 dosage forms and ≥2 administration routes per day), and (5) multimorbidity (≥3 chronic conditions). The final set comprised 29 indicators. CONCLUSIONS: The indicator set developed for flagging potential medication-related readmissions could guide priorities for clinical pharmacy services at hospital discharge, improving patient outcomes and resource use. A validation study of these indicators is planned.

Evolution of disability pension after renal transplantation: methods and results of a database linkage study of the Swiss Transplant Cohort Study and Swiss Disability Insurance.

AIMS: In Switzerland, certain patients with disabilities and reduced working ability are entitled to a disability pension granted by the Swiss Federal Social Insurance Office (FSIO). The aim was to assess the evolution of disability pension and work capacity after kidney transplantation and thereby pilot the procedures linking FSIO data with Swiss Transplant Cohort Study (STCS) data. METHODS: The current study pilot tested the record linkage of FSIO data with data from the STCS in a single-centre, observational setting. Patients were requested to consent to the use of their Swiss social security number (SSSN) for the purpose of record linkage. A privacy preserving trust centre approach was implemented with blinded statistical analysis. RESULTS: Between May 2008 and December 2015, 282 working-age renal transplant recipients of the University Hospital of Basel transplant centre were eligible for inclusion and 136 (48%, median age 48 years) consented to the use of their social security number and record linkage. The FSIO datasets of all patients were successfully retrieved and linked to STCS data in the trust centre and were numerically analysable. Yearly FSIO allowance data were available for the entire study duration. Fifty-five patients (40%) were registered as disability insurance recipients (DIR). In the entire population, the proportion of working patients slightly decreased from 76% to 72% between the pre-transplant and the post-transplant period. This was due to the lower proportion of patients working after transplantation in DIR compared with non-recipients (non-DIR) (DIR: 60% before vs 44% after; non-DIR: 83% before vs 88% after). In the DIR group, the proportion of patients not working increased from 36% to 49%, whereas in non-DIR the proportion changed only marginally (14% to 12%). The average disability insurance allowance was CHF 1172 per month. It changed from CHF 1135 before transplantation to CHF 1209 after transplantation (p = 0.59). CONCLUSIONS: In the Swiss healthcare and social insurance system, record linkage studies combining clinical datasets with data from FSIO are feasible but associated with great efforts and resource needs. The lack of changes in disability allowances after kidney transplantation should be further investigated in the nationwide setting.

A comparison of general and disease-specific machine learning models for the prediction of unplanned hospital readmissions.

Unplanned hospital readmissions are a burden to patients and increase healthcare costs. A wide variety of machine learning (ML) models have been suggested to predict unplanned hospital readmissions. These ML models were often specifically trained on patient populations with certain diseases. However, it is unclear whether these specialized ML models-trained on patient subpopulations with certain diseases or defined by other clinical characteristics-are more accurate than a general ML model trained on an unrestricted hospital cohort. In this study based on an electronic health record cohort of consecutive inpatient cases of a single tertiary care center, we demonstrate that accurate prediction of hospital readmissions may be obtained by general, disease-independent, ML models. This general approach may substantially decrease the cost of development and deployment of respective ML models in daily clinical routine, as all predictions are obtained by the use of a single model.

Bayesian networks to identify potential high-risk multimorbidity and intervention clusters in inpatients: an explorative data mining study.

AIMS OF THE STUDY: Based on large sets of routine hospital data from inpatient cases, we aimed to explore multimorbidity and intervention clusters showing high risks for in-hospital mortality and unplanned readmissions using data-driven analytical methods. METHODS: We performed an explorative, historical cohort study of consecutive inpatient cases at a tertiary care centre with an integrated platform for routine healthcare data in Switzerland. From January 2012 through to December 2017, all inpatients aged ≥18 years at hospital admission were eligible for study inclusion. We predefined all-cause in-hospital death and unplanned hospital readmission as co-primary outcomes. In a first step, we explored and visualised multimorbidity and intervention clusters using mutual information analysis. In a subsequent step, we trained multi-layer Bayesian networks to identify clusters associated with in-hospital death and/or unplanned hospital readmission. RESULTS: Among 190,837 inpatient cases, 7994 unique diagnoses and 6639 interventions were routinely recorded during the six-year study period. Based on the mutual information analysis, we identified 32 multimorbidity clusters and 24 intervention clusters – of which several were directly related to in-hospital mortality and/or unplanned readmission in the subsequent Bayesian network analysis. CONCLUSIONS: Bayesian network analysis may be used as a tool to mine large healthcare databases in order to explore intervention targets for quality improvement programmes. However, the resulting associations should be substantiated in consecutive investigations using specific causal models. (Trial registration no EKNZ 2016-02128.).

Medical diagnoses showed low relatedness in an explorative mutual information analysis of 190,837 inpatient cases.

OBJECTIVES: We aimed to quantify the shared information between medical diagnoses of an adult inpatient population to explore both multimorbidity patterns and vice versa the unrelatedness of medical diagnoses. STUDY DESIGN AND SETTING: This was a cross-sectional study, performed at a tertiary care center in Switzerland. Diagnoses were routinely coded using the International Classification of Diseases, 10th revision. RESULTS: Among 190,837 inpatient cases, 7,994 unique diagnoses were coded. There were 31.9 million possible diagnosis pairs; the respective mutual information scores in diagnosis pairs were low (range, 10-7 to 0.237). There were 148 pairs of diagnoses with a mutual information score higher than 0.01, which formed several clinically plausible disease clusters; 27.2% of cases did not have a diagnosis that belonged to one of the morbidity clusters. CONCLUSION: In an explorative analysis, we observed a high unrelatedness of diagnoses in a tertiary-care inpatient population. This finding indicates that although multimorbidity patterns can be observed, inpatient cases frequently have further, unrelated diagnoses, which share little information with specific other diagnoses. Therefore, management of multimorbid patients should be individualized and may not be generalized based on a few multimorbidity patterns or clusters.

Costs versus earnings in colon surgery and coronary artery bypass grafting under a prospective payment system: Sufficient financial incentives to reduce surgical site infections?

Based on a surgical site infection (SSI) cohort at an academic center, we showed a median potentially preventable loss per non-SSI case of $17,916 in colon surgery and of $34,741 in coronary artery bypass grafting.

Secondary use of routine data in hospitals: description of a scalable analytical platform based on a business intelligence system.

We describe a scalable platform for research-oriented analyses of routine data in hospitals, which evolved from a state-of-the-art business intelligence architecture for enterprise resource planning. This platform involves an in-memory database management system for data modeling and analytics and a high-performance cluster for more computing-intensive analytical tasks. Setting up platforms for research-oriented analyses is a highly dynamic, time-consuming, and costly process. In some health care institutions, effective research platforms may be derived from existing business intelligence systems.

Direct Costs of a Contact Isolation Day: A Prospective Cost Analysis at a Swiss University Hospital.

We prospectively evaluated direct costs of contact precautions using on-site observation. Additional mean costs per patient day were calculated for extra materials used, increased workload, and one-off isolation activities. The cost of contact precautions was $158.90 (95% confidence interval, $124.90‒$192.80) per patient day. Infect Control Hosp Epidemiol 2018;39:101-103.

MELD score as a predictor of mortality, length of hospital stay, and disease burden: A single-center retrospective study in 39,323 inpatients.

The laboratory-based model for end-stage liver disease (MELD) score reflects the function of the kidney, liver, and extrinsic coagulation pathway and might be used as a general prognostic tool for the assessment of patients. We therefore aimed to investigate a potential association of the MELD score with mortality, length of hospital stay (LOS), and disease burden in a general patient population.We performed a retrospective observational study at a tertiary referral center. From January 2012 through December 2013, all consecutive inpatients aged 18 years were eligible for the study; patients with missing MELD parameters on hospital admission and/or treatments influencing the international normalized ratio, that is, novel oral anticoagulants and vitamin K antagonists, were excluded. The MELD score on hospital admission was calculated retrospectively. The primary outcome measure was in-hospital all-cause mortality; secondary outcome measures were LOS and the number of comorbidities.A total of 39,323 inpatients were included in the final analysis. On admission, MELD scores of 15 to 19, 20 to 29, and ≥30 points (reference <15 points) showed increased hazard ratios (HRs) for in-hospital mortality in uni- and multivariable analysis with an adjusted HR of 2.52 (95% confidence interval [CI], 1.81-3.49; P < .001), 2.70 (95% CI, 1.89-3.84; P < .001), and 8.00 (95% CI, 3.91-16.39; P < .001), respectively. Increased MELD scores of 15 to 19, 20 to 29, and ≥30 points were positively associated with LOS and the number of comorbidities in uni- and multivariable analysis.In our study population consisting of adult inpatients, the MELD score on hospital admission was significantly associated with mortality, LOS, and the number of comorbidities. We suggest to prospectively validate the MELD score in inpatients as part of clinical decision support systems.

Iron homeostasis in inflammation: a single centre prospective observational study in medical inpatients.

AIMS OF THE STUDY: We aimed to assess a potential association of iron status with mortality and morbidity of inpatients with systemic inflammation. METHODS: This was a single centre prospective observational study. From April 2014 to October 2014, all consecutive medical inpatients aged >=18 years with a C-reactive protein value >5 mg/l on hospital admission were eligible for the study. We excluded pregnant women and patients with terminal renal insufficiency or past allogeneic stem cell transplantation. For all patients, a complete set of serum iron parameters was obtained on hospital admission. In the final analysis, the in-hospital all-cause mortality and several morbidity measures (length of stay, number of secondary diagnoses and Charlson Comorbidity Index) were compared between four distinct iron status groups: patients having iron deficiency anaemia, iron deficiency without anaemia, anaemia without iron deficiency, and normal iron status. Iron deficiency was quantifies as the serum transferrin receptor / ferritin index, with a cut-off level of 1.5. RESULTS: A total of 438 patients were included in the final analysis. Patients with iron deficiency had a higher in-hospital mortality than patients with iron deficiency anaemia, anaemia without iron deficiency, or normal iron status (6% vs 1%, 5%, and 1%, respectively; p = 0.042). Patients with iron deficiency anaemia had a higher number of secondary diagnoses (mean 8.4; standard deviation 4.2) and a higher Charlson Comorbidity Index (mean 1.8; standard deviation 1.9) than patients with iron deficiency, anaemia without iron deficiency, or normal iron status (p <0.001 and p <0.001, respectively). The median length of stay did not differ significantly between the iron status groups (p = 0.080). CONCLUSIONS: In our study population, iron status was significantly associated with mortality and morbidity. Further studies are required to assess the pathophysiological and clinical effects of an altered iron metabolism and iron substitution therapies in inflammation.

The Model for End-stage Liver Disease (MELD) as a predictor of short-term mortality in Staphylococcus aureus bloodstream infection: A single-centre observational study.

BACKGROUND: Automated laboratory-based prediction models may support clinical decisions in Staphylococcus aureus bloodstream infections (BSIs), which carry a particularly high mortality. Small studies indicated that the laboratory-based Model for End-stage Liver Disease (MELD) score is a risk factor for mortality in critically ill patients with infections. For S. aureus BSIs, we therefore aimed to assess a potential association of the MELD score with mortality. METHODS: In this single-centre observational study, all consecutive patients with a first episode of methicillin-susceptible S. aureus BSI occurring between 2001 and 2013 were eligible. Relevant patient data were retrieved from our prospective in-house BSI database. We assessed the association of the MELD score at day of BSI onset (range ± two days) with 30-day all-cause mortality using uni- and multivariable logistic regression analysis. RESULTS: 561 patients were included in the final analysis. The MELD score at BSI onset was associated with 30-day mortality in S. aureus BSIs (odds ratio per 1-point increase, 1.06; 95% confidence interval, 1.03‒1.09; P < 0.001). After adjustment for relevant patient and infection characteristics, an increased MELD score remained a predictor of 30-day mortality (adjusted odds ratio per 1-point increase, 1.05; 95% confidence interval, 1.01‒1.08; P = 0.005). CONCLUSIONS: In our study population, the MELD score at BSI onset was an independent predictor of mortality in S. aureus BSIs. We therefore suggest to prospectively validate the MELD score as part of clinical decision support systems in inpatients with suspected or confirmed BSI.

Head-to-head comparison of length of stay, patients' outcome and satisfaction in Switzerland before and after SwissDRG-Implementation in 2012 in 2012: an observational study in two tertiary university centers.

BACKGROUND: On 1 January 2012 Swiss Diagnosis Related Groups (DRG), a new uniform payment system for in-patients was introduced in Switzerland with the intention to replace a "cost-based" with a "case-based" reimbursement system to increase efficiency. With the introduction of the new payment system we aim to answer questions raised regarding length of stay as well as patients' outcome and satisfaction. METHODS: This is a prospective, two-centre observational cohort study with data from University Hospital Basel and the Cantonal Hospital Aarau, Switzerland, from January to June 2011 and 2012, respectively. Consecutive in-patients with the main diagnosis of either community-acquired pneumonia, exacerbation of COPD, acute heart failure or hip fracture were included. A questionnaire survey was sent out after discharge investigating changes before and after SwissDRG implementation. Our primary endpoint was LOS. RESULTS: Of 1,983 eligible patients 841 returned the questionnaire and were included into the analysis (429 in 2011, 412 in 2012). The median age was 76.7 years (50.8% male). Patients in the two years were well balanced in regard to main diagnoses and co-morbidities. Mean LOS in the overall patient population was 10.0 days and comparable between the 2011 cohort and the 2012 cohort (9.7 vs 10.3; p = 0.43). Overall satisfaction with care changed only slightly after introduction of SwissDRG and remained high (89.0% vs 87.8%; p = 0.429). DISCUSSION: Investigating the influence of the implementation of SwissDRG in 2012 regarding LOS patients' outcome and satisfaction, we found no significant changes. However, we observed some noteworthy trends, which should be monitored closely.

Diagnosis and treatment of iron deficiency in medical inpatients at a Swiss tertiary university referral hospital: a retrospective observational cohort study of clinical practice.

BACKGROUND: Iron deficiency anaemia is a common disease with a prevalence of up to 19.2% in populations at risk. However, the prevalence of iron deficiency (ID) in hospitalised patients is not well known. The aims of this retrospective, observational cohort study were to evaluate the current diagnostic procedures for, and treatment of, ID as well as to estimate the prevalence of undiagnosed ID in hospitalised patients at the division of internal medicine in a Swiss tertiary university referral centre. METHODS: Within a study period of 6 months, data from all patients hospitalised at the division of internal medicine were analysed for the presence of anaemia (defined as haemoglobin levels for males <130 g/l and for females <120 g/l) and ID (ferritin <15 µg/l or ferritin <50 µg/l and transferrin saturation <20%). RESULTS: A total of 2,781 hospitalisation cases were analysed (2,251 unique patients, male 55.5%, mean age 66.4 years). In 2,267 cases (81.5%) results of a red blood cell count were available. In 329 cases (14.5%) iron parameters (IP) were determined and 45 (13.7%) cases / unique patients with ID were detected. Among the remaining 1,938 cases without IP determination, statistical estimation predicted 103 (56-329) undiagnosed ID cases. In ID patients, the most prevalent diagnosis was heart failure (24.4%). Of these patients, 72.7% had haemorrhage-facilitating drugs on hospital admission or discharge. CONCLUSION: Iron deficiency is common in internal medicine and up to two-thirds of cases may not be diagnosed. Every seventh patient who had iron parameters analysed was iron deficient and two-thirds of patients with ID were treated with intravenous iron.

Head-to-head comparison of fee-for-service and diagnosis related groups in two tertiary referral hospitals in Switzerland: an observational study.

BACKGROUND: Reimbursement for inpatients in Switzerland differed among states until 2012. Some hospitals used diagnosis related groups (DRG) and others used fee-for-service (FFS). We compared length of hospital stay (LOS), patient satisfaction and quality of life between the two systems before a nation-wide implementation of DRG. METHODS: In a prospective, two-centre observational cohort study, we identified all patients with a main diagnosis of either community-acquired pneumonia, exacerbation of chronic pulmonary obstructive disease, acute heart failure or hip fracture from January to June 2011 and performed a systematic questionnaire survey 2-4 months after hospital discharge. RESULTS: Of 1,093 inpatients, 450 were included. Mean age was 71.1 (±SD 19.5) years (48% male). Patients in the FFS hospital were older (mean age 74.8 vs. 65.2 years; p <0.001) and suffered from more co-morbidities. Mean LOS was 9 days and shorter in the all-patient DRG (AP-DRG) hospital (unadjusted mean 8.2 vs. 9.5 days, p = 0.04). After multivariate adjustment, no significant difference in LOS was found (p = 0.24). More patients from the FFS hospital were re-hospitalised for any reason (35% vs. 17.5%; p = 0.01), re-admitted to acute-care institutions (11.7% vs. 5.2%; p = 0.014), not satisfied with the discharge process (15.3% vs. 9.7%; p = 0.02), showed problems with self-care (93.8% vs. 88%; p = 0.03) and usual activities (79.3% vs. 76%; p = 0.02). DISCUSSION: This study suggested that the AP-DRG hospital showed higher patient satisfaction regarding discharge, lower re-hospitalisation rates and shorter LOS partly explained by a lower burden of co-morbidities and disease severity. This study needs validation in a larger cohort of patients and at multiple time points.

[Not Available]. / Zufallsbefunde - Grundsätzliche Abklärungsschritte, Erlös unter Swiss DRG und ethische Überlegungen am Beispiel des Nebennieren-Inzidentaloms.

Adrenal incidentalomas (AI) are defined as neoplasias of the adrenal of =/> 1 cm diameter randomly diagnosed in radiographic imaging such as computed tomography (CT) or magnetic resonance imaging (MRI). In literature, their prevalence ranges from 0.81 % to 6 % depending on the cohort and age of patients analyzed. - Computing the revenues under Swiss DRG 1.0 the randomness of AIs does not exert any influence; rather AIs are billed as benign, malign or adrenal tumors with unknown dignity. Revenue is computed using the appropriate ICD-10-GM code leading to its DRG group in combination with the diagnostic and therapeutic procedures involved. We present 48 cases of patients with adrenal neoplasms, their coding and range of revenue. - From the ethical perspective the randomness of the diagnosis needs above all professional communication between the treating physician and the patient. The field of random findings in radiographic imaging is well known and broadly discussed in radiologic research of the central nervous system.

Use of hepatotoxic drugs in chronic liver disease.

Cirrhosis and chronic liver disease are common illnesses that cause high mortality and require treatment. Medication use in these patients may be challenging because of idiosyncratic or dose-dependent drug toxicity. Therefore, drug choice and drug dose adaptations play an important role. The objective of this clinical review is to discuss the literature about and challenges in drug use in patients with chronic liver disease. To make good decisions regarding drug choice and dose adjustments in these patients, well-defined clinical information about diagnoses and laboratory results (creatinine, international normalized ratio, bilirubin, and serologies) as well as in some instances, pathological findings like liver biopsies are needed. In a second step, these data should be organized in electronically supported clinical decision systems, which can then assist providers in making choices about medication selection and dosage. In summary, although substantial research has been done in the field of drug use in patients with liver dysfunction, a great deal also remains to be learned. Although many of these patients can now be identified, it is still very difficult to assess their individual level of hepatic function. The degree of risk associated with drug use and how best to use medications in these patients represents an important area for further study. In the future, pharmacogenomics and electronic linking of clinical data may well prove helpful for making decisions about optimal drug choices in this complex group of patients.