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.

An overview of reviews and synthesis across 440 studies examines the importance of hospital readmission predictors across various patient populations.

OBJECTIVES: The scientific literature contains an abundance of prediction models for hospital readmissions. However, no review has yet synthesized their predictors across various patient populations. Therefore, our aim was to examine predictors of hospital readmissions across 13 patient populations. STUDY DESIGN AND SETTING: An overview of systematic reviews was combined with a meta-analytical approach. Two thousand five hundred four different predictors were categorized using common ontologies to pool and examine their odds ratios and frequencies of use in prediction models across and within different patient populations. RESULTS: Twenty-eight systematic reviews with 440 primary studies were included. Numerous predictors related to prior use of healthcare services (odds ratio; 95% confidence interval: 1.64; 1.42-1.89), diagnoses (1.41; 1.31-1.51), health status (1.35; 1.20-1.52), medications (1.28; 1.13-1.44), administrative information about the index hospitalization (1.23; 1.14-1.33), clinical procedures (1.20; 1.07-1.35), laboratory results (1.18; 1.11-1.25), demographic information (1.10; 1.06-1.14), and socioeconomic status (1.07; 1.02-1.11) were analyzed. Diagnoses were frequently used (in 37.38%) and displayed large effect sizes across all populations. Prior use of healthcare services showed the largest effect sizes but were seldomly used (in 2.57%), whereas demographic information (in 13.18%) was frequently used but displayed small effect sizes. CONCLUSION: Diagnoses and patients' prior use of healthcare services showed large effects both across and within different populations. These results can serve as a foundation for future prediction modeling.

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.

[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.

The costs of adverse drug events in community hospitals.

BACKGROUND: Adverse drug events (ADEs) occur often in hospitals, causing high morbidity and a longer length of stay (LOS), and are costly. However, most studies on the impact of ADEs have been conducted in tertiary referral centers, which are systematically different than community hospitals, where the bulk of care is delivered, and most available data about ADE costs in any setting are dated. Costs in community settings are generally lower than in academic hospitals, and the costs of ADEs might be as well. To assess the additional costs and LOS associated with patients with ADEs, a multicenter retrospective cohort study was conducted in six community hospitals with 100 to 300 beds in Massachusetts during a 20-month observation period (January 2005-August 2006). METHODS: A random sample of 2,100 patients (350 patients per study site) was drawn from a pool of 109,641 patients treated within the 20-month observation period. Unadjusted and adjusted cost of ADEs as well as LOS were calculated. RESULTS: ADEs were associated with an increased adjusted cost of $3,420 and an adjusted increase in length of stay (LOS) of 3.15 days. For preventable ADEs, the respective figures were +$3,511 and +3.37 days. The severity of the ADE was also associated with higher costs--the costs were +$2,852 for significant ADEs (LOS +2.77 days), +$3,650 for serious ADEs (LOS +3.47 days), and +$8,116 for life-threatening ADEs (LOS +5.54 days, all p < .001). CONCLUSIONS: ADEs in community hospitals cost more than $3,000 dollars on average and an average increase of LOS of 3.1 days--increments that were similar to previous estimates from academic institutions. The LOS increase was actually greater. A number of approaches, including computerized provider order entry and bar coding, have the potential to improve medication safety.

Essential steps in the development, implementation, evaluation and quality assurance of the written part of the Swiss federal licensing examination for human medicine.

Purpose: This report describes the essential steps in the development, implementation, evaluation and quality assurance of the written part of the Swiss Federal Licensing Examination for Human Medicine (FLE) and the insights gained since its introduction in 2011. Methods: Based on existing scientific evidence, international expertise, and experience gained from previous examinations, the FLE is developed by experts from all five medical faculties in Switzerland with the support of the Institute for Medical Education and is held simultaneously at five locations. The exam organisers document and review every examination held and continuously optimise the processes; they have summarised the results in this report. Results: The essential steps comprise the development, revision and translation of questions; construction of the exam and production of materials; candidate preparation; implementation and analysis. The quality assurance measures consist of guideline coherence in the development of the questions and implementation of the exam, revision processes, construction of the exam based on the national blueprint, multiphase review of the translations and exam material, and statistical analysis of the exam and the comments from candidates. The intensive collaboration, especially on the part of representatives from all the participating faculties and a central coordination unit, which provides methodological support throughout and oversees the analysis of the exam, has proven successful. Successfully completed examinations and reliable results in the eleven examinations so far implemented represent the outcomes of the quality assurance measures. Significant insights in recent years are the importance of appreciating the work of those involved and the central organisation of exam development, thus ensuring the long-term success of the process. Conclusion: Common guidelines and workshops, quality assurance measures accompanied by the continuous improvement of all processes, and appreciation of everyone involved, are essential to carrying out such an examination at a high-quality level in the long term.

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.

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.

Adverse drug event rates in six community hospitals and the potential impact of computerized physician order entry for prevention.

CONTEXT: Medications represent a major cause of harm and are costly for hospitalized patients, but more is known about these issues in large academic hospitals than in smaller hospitals. OBJECTIVE: To assess the incidence of adverse drug events (ADEs) in six community hospitals. DESIGN: Multicenter, retrospective cohort study. SETTING: Six Massachusetts community hospitals with 100 to 300 beds. PATIENTS: From 109,641 adult patients hospitalized from January 2005 through August 2006, a random sample of 1,200 patients was drawn, 200 per site. MAIN OUTCOME MEASURES: ADEs and preventable ADEs. METHODS: Presence of an ADE was evaluated using an adaptation of a trigger instrument developed by the Institute for Health Care Improvement. Independent reviewers classified events by preventability, severity, and potential for preventability by computerized physician order entry (CPOE). RESULTS: A total of 180 ADEs occurred in 141 patients (rate, 15.0/100 admissions). Overall, 75% were preventable. ADEs were rated as serious in 49.4% and life threatening in 11.7%. Patients with ADEs were older (mean age, 74.6 years, p < 0.001), more often female (60.3%, p = 0.61), and more often Caucasian (96.5%, p < 0.001) than patients without ADEs. Of the preventable ADEs, 81.5% were judged potentially preventable by CPOE. CONCLUSIONS: The incidence of ADEs in these community hospital admissions was high, and most ADEs were preventable, mostly through CPOE. These data suggest that CPOE may be beneficial in this setting.

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.).

Occurrence of adverse, often preventable, events in community hospitals involving nephrotoxic drugs or those excreted by the kidney.

Medication errors in patients with reduced creatinine clearance are harmful and costly; however, most studies have been conducted in large academic hospitals. As there are few studies regarding this issue in smaller community hospitals, we conducted a multicenter, retrospective cohort study in six community hospitals (100 to 300 beds) to assess the incidence and severity of adverse drug events (ADEs) in patients with reduced creatinine clearance. A chart review was performed on adult patients hospitalized during a 20-month study period with serum creatinine over 1.5 mg/dl who were exposed to drugs that are nephrotoxic or cleared by the kidney. Among 109,641 patients, 17,614 had reduced creatinine clearance, and in a random sample of 900 of these patients, there were 498 potential ADEs and 90 ADEs. Among these ADEs, 91% were preventable, 51% were serious, 44% were significant, and 4.5% were life threatening. Of the potential ADEs, 54% were serious, 44% were significant, 1.6% were life threatening, and 96.6% were not intercepted. All 82 preventable events could have been intercepted by renal dose checking. Our study shows that ADEs were common in patients with impaired kidney function in community hospitals, and many appear potentially preventable with renal dose checking.

Outcomes of early switching from intravenous to oral antibiotics on medical wards.

OBJECTIVES: To evaluate outcomes following implementation of a checklist with criteria for switching from intravenous (iv) to oral antibiotics on unselected patients on two general medical wards. METHODS: During a 12 month intervention study, a printed checklist of criteria for switching on the third day of iv treatment was placed in the medical charts. The decision to switch was left to the discretion of the attending physician. Outcome parameters of a 4 month control phase before intervention were compared with the equivalent 4 month period during the intervention phase to control for seasonal confounding (before-after study; April to July of 2006 and 2007, respectively): 250 episodes (215 patients) during the intervention period were compared with the control group of 176 episodes (162 patients). The main outcome measure was the duration of iv therapy. Additionally, safety, adherence to the checklist, reasons against switching patients and antibiotic cost were analysed during the whole year of the intervention (n = 698 episodes). RESULTS: In 38% (246/646) of episodes of continued iv antibiotic therapy, patients met all criteria for switching to oral antibiotics on the third day, and 151/246 (61.4%) were switched. The number of days of iv antibiotic treatment were reduced by 19% (95% confidence interval 9%-29%, P = 0.001; 6.0-5.0 days in median) with no increase in complications. The main reasons against switching were persisting fever (41%, n = 187) and absence of clinical improvement (41%, n = 185). CONCLUSIONS: On general medical wards, a checklist with bedside criteria for switching to oral antibiotics can shorten the duration of iv therapy without any negative effect on treatment outcome. The criteria were successfully applied to all patients on the wards, independently of the indication (empirical or directed treatment), the type of (presumed) infection, the underlying disease or the group of antibiotics being used.

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.

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.

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.

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.

Individualising drug dispensaries in a university hospital.

BACKGROUND: In hospitals and other healthcare institutions drugs are routinely stored in designated satellite areas on the wards. Often ad hoc decisions are made by clinicians and nurses regarding drug type and quantity to be stored. As a result the number of different drugs and drug packages in storage tends to increase, which may lead to inefficient drug handling and become a potential risk factor in the medication control process. Based on an extended analysis of drug inventories on three different wards it was hypothesized that a ward-individualised formulary (WIF) can halve the number of different drugs and drug packages in a drug dispensary and hence reduce bound capital, money lost through expired drugs, and facilitate safer drug handling. The interdisciplinary intervention described here took place on three 40-bed wards in a 700-bed university hospital housing patients in general internal medicine, haematology, nephrology and oncology. METHODS: A WIF was defined by including all drugs from the hospital formulary ordered at least three times in the past six months. A pharmacist, a nurse and a clinician reviewed the inclusion list of drugs and clinicians were strongly encouraged to prescribe drugs primarily from the WIF. Drugs excluded from the WIF were removed from the drug dispensaries and the number of included drug packages stored in the remote dispensaries was reduced according to their order history. Drug inventory on the wards was monitored from February 2004 to April 2006. RESULTS: The initial drug dispensary inventories on wards A, B and C consisted of 2031, 1667 and 1536 packages with 943, 897 and 831 different drugs valued at h 83 931, h 44 590 and h 57 285. respectively. After adjusting the drug dispensaries according to the WIF drug dispensary inventories on wards A, B and C consisted of 808 (-60%), 600 (-64%) and 485 (-68%) packages with 415 (-56%), 334 (-63%) and 376 (-55%) different drugs valued euro 28 012 (-67%), euro 10 381 (-77%) an euro 17 898 (-69%). The overall reductions the number of packages, the different drugs and the drug value were comparable (>50%) and remained low during the entire observation time (A: 18 months, B: 13 months, C: 8 months). CONCLUSION: Rearranging dispensaries by individualizing the drug inventory according to the needs of the ward by introducing a WIF is a valuable means to significantly (>50%) reduce [1] the number of drug packages, [2] the number of different drugs stored and [3] the capital bound drugs. The positive effects of the WIF are supported by the interdisciplinary interaction of the different professional groups involved in the medication process. The leaner drug dispensaries offer optimal basic conditions for introducing new IT-based systems to further increase the safety of the medication process.

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.