Hospital financing of ischaemic stroke: determinants of funding and usefulness of DRG subcategories based on severity of illness

Background

Several Western and Arab countries, as well as over 30 States in the US are using the “All-Patient Refined Diagnosis-Related Groups” (APR-DRGs) with four severity-of-illness (SOI) subcategories as a model for hospital funding. The aim of this study is to verify whether this is an adequate model for funding stroke hospital admissions, and to explore which risk factors and complications may influence the amount of funding.

Methods

A bottom-up analysis of 2496 ischaemic stroke admissions in Belgium compares detailed in-hospital resource use (including length of stay, imaging, lab tests, visits and drugs) per SOI category and calculates total hospitalisation costs. A second analysis examines the relationship between the type and location of the index stroke, medical risk factors, patient characteristics, comorbidities and in-hospital complications on the one hand, and the funding level received by the hospital on the other hand. This dataset included 2513 hospitalisations reporting on 35,195 secondary diagnosis codes, all medically coded with the International Classification of Disease (ICD-9).

Results

Total costs per admission increased by SOI (€3710–€16,735), with severe patients costing proportionally more in bed days (86%), and milder patients costing more in medical imaging (24%). In all resource categories (bed days, medications, visits and imaging and laboratory tests), the absolute utilisation rate was higher among severe patients, but also showed more variability.

SOI 1–2 was associated with vague, non-specific stroke-related ICD-9 codes as primary diagnosis (71–81% of hospitalisations). 24% hospitalisations had, in addition to the primary diagnosis, other stroke-related codes as secondary diagnoses. Presence of lung infections, intracranial bleeding, severe kidney disease, and do-not-resuscitate status were each associated with extreme SOI (p < 0.0001).

Conclusions

APR-DRG with SOI subclassification is a useful funding model as it clusters stroke patients in homogenous groups in terms of resource use. The data on medical care utilisation can be used with unit costs from other countries with similar healthcare set-ups to 1) assess stroke-related hospital funding versus actual costs; 2) inform economic models on stroke prevention and treatment. The data on diagnosis codes can be used to 3) understand which factors influence hospital funding; 4) raise awareness about medical coding practices.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3134-6) contains supplementary material, which is available to authorized users.

Incidence of Torsade de Pointes in a tertiary hospital population

BACKGROUND

Multiple risk factors play a role in the development of QTc-prolongation and Torsade de Pointes (TdP). Cases of TdP are underreported and data on the incidence of TdP is scarce. The aim of this study was to investigate the incidence of TdP in a Belgian university hospital and describe the characteristics of TdP-cases using a risk score.

METHODS

All cases from 2011 till 2013 coded with the ICD-9 code 427.1 in the University Hospitals of Leuven were selected. The medical files were reviewed and demographical, medical, medication and electrocardiographic data were collected. We focused on TdP-cases that were probably caused by the acquired long QT-syndrome. The RISQ-PATH score was used to quantify the risk in these cases (≥10 points as high risk for QTc-prolongation/TdP).

RESULTS

Over three years, 41 TdP-cases were identified of which 19 cases were secondary to the acquired long QT-syndrome (52.6% females, mean age of 74±12years). This corresponds with an incidence of 0.16‰/year in a hospital population. Most of the patients (N=17) were treated with at least one QTc-prolonging drug (most frequently amiodarone, sotalol and furosemide) of whom 12 patients with ≥1 QTc-prolonging drug of list 1 of CredibleMeds. Fifteen patients had an electrocardiogram in a 24-hours interval before the TdP with a prolonged QTc-interval (≥450/470ms). All the patients had a RISQ-PATH score≥10.

CONCLUSIONS

Although the incidence of 0.16‰/year might seem low, this means that approximately 173 possibly lethal TdP-cases can be expected in Belgian hospitals each year. All TdP-cases were associated with a high RISQ-PATH score.

Do we need authorized orphan drugs when compounded medications are available?

WHAT IS KNOWN AND OBJECTIVE

Orphan drugs are used to diagnose, prevent or treat a rare disease. This Commentary aims to present a number of case studies questioning the need for designating compounded medications with a long history of effective use, which is well-supported by published clinical evidence.

COMMENT

Prior to the market introduction of orphan drugs, medication compounding was done in our hospital pharmacy for several rare diseases. Examples include amifampridine for the treatment of Lambert-Eaton myasthenic syndrome (Firdapse(®)), ibuprofen for the treatment of neonatal patent ductus arteriosus (Pedea(®)) and zinc acetate for the treatment of Wilson's disease (Wilzin(®)). Several 'non-orphan' pharmaceutical products, used off-label for the treatment of rare diseases, that became orphan medicinal products include Hydrea(®) for the treatment of sickle-cell syndrome (Siklos(®)) and Viagra(®) for the treatment of pulmonary arterial hypertension (Revatio(®)).

WHAT IS NEW AND CONCLUSION

In our opinion, as indicated by our examples, a better balance should be struck between the development of orphan drugs along the recently established regulatory pathways and the pragmatic use of pharmacy-compounded products and evidence-based off-label use of already available commercial products. Societal needs would be best met by focusing orphan drug development on rare diseases for which there is a high unmet medical need.

Interpretative reporting and alarming based on laboratory data

The utilisation of laboratory services for patient diagnosis and management involves many steps with both clinical and laboratory components. The clinical components include the decision to order a test, interpretation of the test results and actions taken on the basis of the results. The laboratory components on the other hand include receipt of the request, specimen collection, preparation and analysis, result entry, test result validation and verification and reporting of the results. In this paper, which is part of the OpenLabs project, we concentrate on the post-analytical applications which include interpretation and reporting of the laboratory results to the users in primary care and in high dependency care units. The final objective of the work described is to develop generic modules which can be integrated both with an Open laboratory information system architecture and existing laboratory information processing environment.

Computer aided interpretation of acid-base disorders

This paper describes an expert system for the interpretation of acid-base disorders. The target users are residents in training in internal medicine, anaesthesia and intensive care medicine. The program is written in PROLOG and runs on a SUN 3/160 minicomputer. Evaluation of a learning set (N = 202) and a test set (N = 194) has proved that the system's accuracy is acceptable. As a result, the program has recently been put in routine clinical practice.

Computer aided phenotyping of dyslipoproteinemia

An expert system was developed in order to obtain uniform and fast phenotyping and reporting of dyslipoproteinemia. PROLOG is used as knowledge representation formalism. The program is in daily use on an IBM PC AT, in the Laboratory of Clinical chemistry of the University Hospitals in Leuven. Evaluation has proved the system to be reliable and useful for the interpretation of lipoprotein disorders. Indeed accuracy figures of 98.4% and 95.2% were obtained in the learning (N = 315) and test set (N = 126) respectively.